| Invited talk: image recognition for intelligent interfaces | | BIBAK | Full-Text | 1-2 | |
| Trevor Darrell | |||
| When interaction concerns the physical world, interfaces should do their
best to search for information using direct observation. Image-based interfaces
have been tried in the past, but generally required artificial barcode tags to
be affixed to each viewed object or surface. Recent advances in computer vision
and content-based image retrieval have enabled fast and robust indexing from
images of individual objects -- CD covers, book jackets, magazine
advertisements, etc. -- even on relatively low-power platforms such as
camera-equipped mobile phones. I'll review the relevant algorithms and design
of such systems, and discuss what types of image recognition interfaces are
feasible in the near term. I'll describe very recent work on multimodal
question answering interfaces, which combine image and text query matching with
human-in-the-loop interaction. I'll close with a discussion of the anticipated
future progress on category-level visual recognition, and what classes of
interfaces it may enable. Keywords: computer vision, object recognition, user interfaces | |||
| Sensonomy: intelligence penetrating into the real space | | BIBAK | Full-Text | 3-4 | |
| Jun Rekimoto | |||
| Recent commoditization of mobile digital devices and networking brought us
to use them as a very large-scale sensing platform. We call this possibility
"Sensonmoy", which is an integration of collective intelligence (also known as
"folksonomy") and pervasive sensing. As many users own mobile devices with
sensing facilities, a collection of sensing data from these devices becomes
quite important, and integration of them can be used in a very different
manner. Such feature could be a new way to create intelligent systems and
interfaces. In this talk, I am going to discuss a possibility of connecting a
large number of simple devices to produce intelligent interactions. As a
realistic example of them, I will introduce a city-scale indoor and outdoor
positioning system that we have developed, and how its database can be evolved
by using the idea of Sensonomy. I would also like to discuss computer-augmented
memory and lifelong computing based on our platform. Keywords: lifelong computing, location aware computing, sensonomy | |||
| User-focused database management | | BIBAK | Full-Text | 5-6 | |
| Alon Y. Halevy | |||
| This talk describes two projects whose over goal is to make database
management systems usable by a wider audience. Dataspaces aim to eliminate the
upfront effort involved in creating a database. Data management for
collaboration attempts to shift the focus of data management to supporting
users in their natural environments and workflow. Keywords: collaboration systems, database management, dataspaces, user interfaces | |||
| User-oriented document summarization through vision-based eye-tracking | | BIBAK | Full-Text | 7-16 | |
| Songhua Xu; Hao Jiang; Francis C. M. Lau | |||
| We propose a new document summarization algorithm which is personalized. The
key idea is to rely on the attention (reading) time of individual users spent
on single words in a document as the essential clue. The prediction of user
attention over every word in a document is based on the user's attention during
his previous reads, which is acquired via a vision-based commodity eye-tracking
mechanism. Once the user's attentions over a small collection of words are
known, our algorithm can predict the user's attention over every word in the
document through word semantics analysis. Our algorithm then summarizes the
document according to user attention on every individual word in the document.
With our algorithm, we have developed a document summarization prototype
system. Experiment results produced by our algorithm are compared with the ones
manually summarized by users as well as by commercial summarization software,
which clearly demonstrates the advantages of our new algorithm for
user-oriented document summarization. Keywords: commodity eye-tracking, implicit user feedback, personalized discourse
abstract, user attention, user-oriented document summarization | |||
| Improving meeting summarization by focusing on user needs: a task-oriented evaluation | | BIBAK | Full-Text | 17-26 | |
| Pei-Yun Hsueh; Johanna D. Moore | |||
| Advances in multimedia technologies have enabled the creation of huge
archives of audio-video recordings of meetings, and there is burgeoning
interest in developing meeting browsers to help users better leverage these
archives. A recent study has shown that extractive summaries provide a more
efficient way of navigating meeting content than simply reading through the
transcript and using the audio-video record, or navigating via keyword search
(Murray, 2007). The extractive summary technique identifies informative
dialogue acts to generate general purpose summaries. These summaries can still
be lengthy. Recently, we have developed a decision-focused summarization system
that presents only 1-2% of the recordings related to decision making. In this
paper, we describe a task-based evaluation in which we compare the
decision-focused summaries to the general purpose summaries. Our results
indicate that the more focused summaries help users perform the decision
debriefing task more effectively and improve perceived efficiency. In addition,
this study also investigates the effect of automatic summaries and
transcription on task effectiveness, report quality, and users' perceptions of
task success. Keywords: automatic summarization, meeting browser, multimedia information retrieval,
task-oriented evaluation, user study | |||
| Rich interfaces for reading news on the web | | BIBAK | Full-Text | 27-36 | |
| Earl J. Wagner; Jiahui Liu; Larry Birnbaum; Kenneth D. Forbus | |||
| Using content-specific models to guide information retrieval and extraction
can provide richer interfaces to end-users for both understanding the context
of news events and navigating related news articles. In this paper we discuss a
system, Brussell, that uses semantic models to organize retrieval and
extraction results, generating both storylines explaining how news event
situations unfold and also biographical sketches of the situation participants.
We generalize these models to introduce a new category of knowledge
representation, an explanatory structure, that can scale up to include
information from hundreds of documents, yet still provide model-based UI
support to end-users. An informal survey of business news suggests the broad
prevalence of news event situations indicating Brussell's potential utility,
while an evaluation quantifies its performance in finding kidnapping
situations. Keywords: explanatory structures | |||
| Have a say over what you see: evaluating interactive compression techniques | | BIBAK | Full-Text | 37-46 | |
| Simon Tucker; Steve Whittaker | |||
| We all encounter many documents on a daily basis that we do not have time to
process in their entirety. Nevertheless, we lack good tools to rapidly skim and
identify key information from within such documents. This paper develops and
evaluates Interactive Compression (IC) techniques that allow users to
dynamically configure the amount of information they view in a document, e.g.
by automatically removing unimportant information from view (Excision) or by
making important information more salient (Highlighting). We explore IC
techniques in the context of meeting transcripts that are typically
unstructured -- making it difficult to isolate relevant regions and extract key
information. We demonstrate the superiority of IC compared with an unmodified
text control. In contrast to traditional summaries, our results show extensive
use of interactive, as opposed to fixed compression level, summarization. They
also show the value of word- as opposed to utterance-based compression. There
are also trade-offs between different IC designs. Excision allows users to scan
documents faster than Highlighting but at the expense of overlooking relevant
sections of the document. Keywords: gist, interactive compression, meetings, reading, scanning, summary | |||
| Tagsplanations: explaining recommendations using tags | | BIBAK | Full-Text | 47-56 | |
| Jesse Vig; Shilad Sen; John Riedl | |||
| While recommender systems tell users what items they might like,
explanations of recommendations reveal why they might like them. Explanations
provide many benefits, from improving user satisfaction to helping users make
better decisions. This paper introduces tagsplanations, which are explanations
based on community tags. Tagsplanations have two key components: tag relevance,
the degree to which a tag describes an item, and tag preference, the user's
sentiment toward a tag. We develop novel algorithms for estimating tag
relevance and tag preference, and we conduct a user study exploring the roles
of tag relevance and tag preference in promoting effective tagsplanations. We
also examine which types of tags are most useful for tagsplanations. Keywords: explanations, recommender systems, tagging | |||
| A low-order markov model integrating long-distance histories for collaborative recommender systems | | BIBAK | Full-Text | 57-66 | |
| Geoffray Bonnin; Armelle Brun; Anne Boyer | |||
| Recommender systems provide users with pertinent resources according to
their context and their profiles, by applying statistical and knowledge
discovery techniques. This paper describes a new approach of generating
suitable recommendations based on the active user's navigation stream, by
considering long and short-distance resources in the history with a tractable
model.
The Skipping Based Recommender we propose uses Markov models inspired from the ones used in language modeling while integrating skipping techniques to handle noise during navigation. Weighting schemes are also used to alleviate the importance of distant resources. This recommender has also the characteristic to be anytime. It has been tested on a browsing dataset extracted from Intranet logs provided by a French bank. Results show that the use of exponential decay weighting schemes when taking into account non contiguous resources to compute recommendations enhances the accuracy. Moreover, the skipping variant we propose provides a high accuracy while being less complex than state of the art variants. Keywords: markov models, recommender systems, skipping, weighting schemes | |||
| Discovery-oriented collaborative filtering for improving user satisfaction | | BIBAK | Full-Text | 67-76 | |
| Yoshinori Hijikata; Takuya Shimizu; Shogo Nishida | |||
| Many recommender systems employed in commercial web sites use collaborative
filtering. The main goal of traditional collaborative filtering techniques is
improvement of the accuracy of recommendation. Nevertheless, such techniques
present the problem that they include many items that the user already knows.
These recommendations appear to be good when we consider accuracy alone. On the
other hand, when we consider users' satisfaction, they are not necessarily good
because of the lack of discovery. In our work, we infer items that a user does
not know by calculating the similarity of users or items based on information
about what items users already know. We seek to recommend items that the user
would probably like and does not know by combining the above method and the
most popular method of collaborative filtering. Keywords: collaborative filtering, discovery ratio, novelty, profile of acquaintance | |||
| Do you know?: recommending people to invite into your social network | | BIBAK | Full-Text | 77-86 | |
| Ido Guy; Inbal Ronen; Eric Wilcox | |||
| In this paper we describe a novel UI and system for providing users with
recommendations of people to invite into their explicit enterprise social
network. The recommendations are based on aggregated information collected from
various sources across the organization and are displayed in a widget, which is
part of a popular enhanced employee directory. Recommended people are presented
one by one, with detailed reasoning as for why they were recommended. Usage
results are presented for a period of four months that indicate an extremely
significant impact on the number of connections created in the system.
Responses in the organization's blogging system, a survey with over 200
participants, and a set of interviews we conducted shed more light on the way
the widget is used and implications of the design choices made. Keywords: people recommendations, recommender systems, sns, social networks | |||
| Learning to recognize valuable tags | | BIBAK | Full-Text | 87-96 | |
| Shilad Sen; Jesse Vig; John Riedl | |||
| Many websites use tags as a mechanism for improving item metadata through
collective user effort. Users of tagging systems often apply far more tags to
an item than a system can display. These tags can range in quality from tags
that capture a key facet of an item, to those that are subjective, irrelevant,
or misleading. In this paper we explore tag selection algorithms that choose
the tags that sites display. Based on 225,000 ratings and survey responses, we
conduct offline analyses of 21 tag selection algorithms. We select the three
best performing algorithms from our offline analysis, and deploy them live on
the MovieLens website to 5,695 users for three months. Based on our results, we
offer tagging system designers advice about tag selection algorithms. Keywords: moderation, tagging, user interfaces | |||
| End-user programming of mashups with vegemite | | BIBAK | Full-Text | 97-106 | |
| James Lin; Jeffrey Wong; Jeffrey Nichols; Allen Cypher; Tessa A. Lau | |||
| Mashups are an increasingly popular way to integrate data from multiple web
sites to fit a particular need, but it often requires substantial technical
expertise to create them. To lower the barrier for creating mashups, we have
extended the CoScripter web automation tool with a spreadsheet-like environment
called Vegemite. Our system uses direct-manipulation and
programming-by-demonstration techniques to automatically populate tables with
information collected from various web sites. A particular strength of our
approach is its ability to augment a data set with new values computed by a web
site, such as determining the driving distance from a particular location to
each of the addresses in a data set. An informal user study suggests that
Vegemite may enable a wider class of users to address their information needs. Keywords: automation, data integration, end-user programming, mashup, programming by
demonstration, web | |||
| Context-based page unit recommendation for web-based sensemaking tasks | | BIBAK | Full-Text | 107-116 | |
| Wen-Huang Cheng; David Gotz | |||
| Sensemaking tasks require that users gather and comprehend information from
many sources to answer complex questions. Such tasks are common and include,
for example, researching vacation destinations or performing market analysis.
In this paper, we present an algorithm and interface which provides
context-based page unit recommendation to assist in connection discovery during
sensemaking tasks. We exploit the natural note-taking activity common to
sensemaking behavior as the basis for a task-specific context model. Our
algorithm then dynamically analyzes each web page visited by a user to
determine which page units are most relevant to the user's task. We present the
details of our recommendation algorithm, describe the user interface, and
present the results of a user study which show the effectiveness of our
approach. Keywords: recommendation, search, sensemaking, www | |||
| Detecting and correcting user activity switches: algorithms and interfaces | | BIBAK | Full-Text | 117-126 | |
| Jianqiang Shen; Jed Irvine; Xinlong Bao; Michael Goodman; Stephen Kolibaba; Anh Tran; Fredric Carl; Brenton Kirschner; Simone Stumpf; Thomas G. Dietterich | |||
| The TaskTracer system allows knowledge workers to define a set of activities
that characterize their desktop work. It then associates with each user-defined
activity the set of resources that the user accesses when performing that
activity. In order to correctly associate resources with activities and provide
useful activity-related services to the user, the system needs to know the
current activity of the user at all times. It is often convenient for the user
to explicitly declare which activity he/she is working on. But frequently the
user forgets to do this. TaskTracer applies machine learning methods to detect
undeclared activity switches and predict the correct activity of the user. This
paper presents TaskPredictor2, a complete redesign of the activity predictor in
TaskTracer and its notification user interface. TaskPredictor2 applies a novel
online learning algorithm that is able to incorporate a richer set of features
than our previous predictors. We prove an error bound for the algorithm and
present experimental results that show improved accuracy and a 180-fold speedup
on real user data. The user interface supports negotiated interruption and
makes it easy for the user to correct both the predicted time of the task
switch and the predicted activity. Keywords: activity recognition, online learning, resource management | |||
| An interactive, smart notepad for context-sensitive information seeking | | BIBAK | Full-Text | 127-136 | |
| Jie Lu; Michelle X. Zhou | |||
| We are building an interactive, smart notepad system where users enter brief
notes to drive a dynamic information-seeking process. In this paper, we focus
on describing our work from two aspects: 1) dynamic interpretation of user
notes in context to infer a user's information needs, and 2) automatic
generation of data queries to satisfy the inferred user needs. Compared to
existing information systems, our work offers three unique contributions.
First, our system allows users to focus on what to retrieve instead of how,
since users can use brief notes to express their information needs without
worrying about specific retrieval details. Second, users can use notes to
efficiently request multiple pieces of information at once instead of issuing
one query at a time. Third, users can easily update any part of their notes to
obtain new or updated information. Whenever a user's notes are modified, our
system automatically detects and evaluates all affected note sections to
retrieve new or updated information. Our preliminary evaluation shows the
promise of this work. Keywords: automatic query formulation, context-sensitive information seeking,
note-driven information retrieval | |||
| An interface for targeted collection of common sense knowledge using a mixture model | | BIBAK | Full-Text | 137-146 | |
| Robert Speer; Jayant Krishnamurthy; Catherine Havasi; Dustin Smith; Henry Lieberman; Kenneth Arnold | |||
| We present a game-based interface for acquiring common sense knowledge. In
addition to being interactive and entertaining, our interface guides the
knowledge acquisition process to learn about the most salient characteristics
of a particular concept. We use statistical classification methods to discover
the most informative characteristics in the Open Mind Common Sense knowledge
base, and use these characteristics to play a game of 20 Questions with the
user. Our interface also allows users to enter knowledge more quickly than a
more traditional knowledge-acquisition interface. An evaluation showed that
users enjoyed the game and that it increased the speed of knowledge
acquisition. Keywords: common sense reasoning, hierarchical bayes model, human computation,
knowledge acquisition | |||
| Passages through time: chronicling users' information interaction history by recording when and what they read | | BIBAK | Full-Text | 147-156 | |
| Karl Gyllstrom | |||
| The Passages system enhances information management by maintaining a
detailed chronicle of all the text the user ever reads or edits, and making
this chronicle available for rich temporal queries about the user's information
workspace. Passages enables queries like, "which papers and web pages did I
read when writing the 'related work' section of this paper?", and, "which of
the emails in this folder have I skimmed, but not yet read in detail?" As time
and interaction history are important attributes in users' recall of their
personal information, effectively supporting them creates useful possibilities
for information retrieval. We present methods to collect and make sense of the
large volume of text with which the user interacts. We show through user
evaluation the accuracy of Passages in building interaction history, and
illustrate its capacity to both improve existing retrieval systems and enable
novel ways to characterize document activity across time. Keywords: context, information retrieval, time-machine computing | |||
| What were you thinking?: filling in missing dataflow through inference in learning from demonstration | | BIBAK | Full-Text | 157-166 | |
| Melinda T. Gervasio; Janet L. Murdock | |||
| Recent years have seen a resurgence of interest in programming by
demonstration. As end users have become increasingly sophisticated, computer
and artificial intelligence technology has also matured, making it feasible for
end users to teach long, complex procedures. This paper addresses the problem
of learning from demonstrations involving unobservable (e.g., mental) actions.
We explore the use of knowledge base inference to complete missing dataflow and
investigate the approach in the context of the CALO cognitive personal desktop
assistant. We experiment with the Pathfinder utility, which efficiently finds
all the relationships between any two objects in the CALO knowledge base.
Pathfinder often returns too many paths to present to the user and its default
shortest path heuristic sometimes fails to identify the correct path. We
develop a set of filtering techniques for narrowing down the results returned
by Pathfinder and present experimental results showing that these techniques
effectively reduce the alternative paths to a small, meaningful set suitable
for presentation to a user. Keywords: end-user programming, knowledge-base inference, programming by
demonstration, programming by example, task learning | |||
| Learning to generalize for complex selection tasks | | BIBAK | Full-Text | 167-176 | |
| Alan Ritter; Sumit Basu | |||
| Selection tasks are common in modern computer interfaces: we are often
required to select a set of files, emails, data entries, and the like. File and
data browsers have sorting and block selection facilities to make these tasks
easier, but for complex selections there is little to aid the user without
writing complex search queries. We propose an interactive machine learning
solution to this problem called "smart selection," in which the user selects
and deselects items as inputs to a selection classifier which attempts at each
step to correctly generalize to the user's target state. Furthermore, we take
advantage of our data on how users perform selection tasks over many sessions,
and use it to train a label regressor that models their generalization
behavior: we call this process learning to generalize. We then combine the
user's explicit labels as well the label regressor outputs in the selection
classifier to predict the user's desired selections. We show that the selection
classifier alone takes dramatically fewer mouse clicks than the standard file
browser, and when used in conjunction with the label regressor, the predictions
of the classifier are significantly more accurate with respect to the target
selection state. Keywords: file selection, interactive selection, learning by example, learning to
generalize, learning user models, meta-learning, programming by demonstration,
transfer learning, user modeling | |||
| Trailblazer: enabling blind users to blaze trails through the web | | BIBAK | Full-Text | 177-186 | |
| Jeffrey P. Bigham; Tessa Lau; Jeffrey Nichols | |||
| For blind web users, completing tasks on the web can be frustrating. Each
step can require a time-consuming linear search of the current web page to find
the needed interactive element or piece of information. Existing interactive
help systems and the playback components of some programming-by-demonstration
tools identify the needed elements of a page as they guide the user through
predefined tasks, obviating the need for a linear search on each step. We
introduce TrailBlazer, a system that provides an accessible, non-visual
interface to guide blind users through existing how-to knowledge. A formative
study indicated that participants saw the value of TrailBlazer but wanted to
use it for tasks and web sites for which no existing script was available. To
address this, TrailBlazer offers suggestion-based help created on-the-fly from
a short, user-provided task description and an existing repository of how-to
knowledge. In an evaluation on 15 tasks, the correct prediction was contained
within the top 5 suggestions 75.9% of the time. Keywords: blind users, non-visual interfaces, programming-by-demonstration,
suggestions, web accessibility | |||
| Fixing the program my computer learned: barriers for end users, challenges for the machine | | BIBAK | Full-Text | 187-196 | |
| Todd Kulesza; Weng-Keen Wong; Simone Stumpf; Stephen Perona; Rachel White; Margaret M. Burnett; Ian Oberst; Andrew J. Ko | |||
| The results of a machine learning from user behavior can be thought of as a
program, and like all programs, it may need to be debugged. Providing ways for
the user to debug it matters, because without the ability to fix errors users
may find that the learned program's errors are too damaging for them to be able
to trust such programs. We present a new approach to enable end users to debug
a learned program. We then use an early prototype of our new approach to
conduct a formative study to determine where and when debugging issues arise,
both in general and also separately for males and females. The results suggest
opportunities to make machine-learned programs more effective tools. Keywords: debugging, end-user programming, machine learning | |||
| Simplified facial animation control utilizing novel input devices: a comparative study | | BIBAK | Full-Text | 197-206 | |
| Nikolaus Bee; Bernhard Falk; Elisabeth André | |||
| Editing facial expressions of virtual characters is quite a complex task.
The face is made up of many muscles, which are partly activated concurrently.
Virtual faces with human expressiveness are usually designed with a limited
amount of facial regulators. Such regulators are derived from the facial muscle
parts that are concurrently activated. Common tools for editing such facial
expressions use slider-based interfaces where only a single input at a time is
possible. Novel input devices, such as gamepads or data gloves, which allow
parallel editing, could not only speed up editing, but also simplify the
composition of new facial expressions. We created a virtual face with 23 facial
controls and connected it with a slider-based GUI, a gamepad, and a data glove.
We first conducted a survey with professional graphics designers to find out
how the latter two new input devices would be received in a commercial context.
A second comparative study with 17 subjects was conducted to analyze the
performance and quality of these two new input devices using subjective and
objective measurements. Keywords: data glove, facial expression, gamepad, input device, virtual avatar | |||
| Automatic design of a control interface for a synthetic face | | BIBAK | Full-Text | 207-216 | |
| Nicolas Stoiber; Renaud Seguier; Gaspard Breton | |||
| Getting synthetic faces to display natural facial expressions is essential
to enhance the interaction between human users and virtual characters. Yet
traditional facial control techniques provide precise but complex sets of
control parameters, which are not adapted for non-expert users. In this
article, we present a system that generates a simple, 2-Dimensional interface
that offers an efficient control over the facial expressions of any synthetic
character. The interface generation process relies on the analysis of the
deformation of a real human face. The principal geometrical and textural
variation patterns of the real face are detected and automatically reorganized
onto a low-dimensional space. This control space can then be easily adapted to
pilot the deformations of synthetic faces. The resulting virtual character
control interface makes it easy to produce varied emotional facial expressions,
both extreme and subtle. In addition, the continuous nature of the interface
allows the production of coherent temporal sequences of facial animation. Keywords: aam, avatar, facial animation, traveling salesman problem, user interface,
virtual character | |||
| Positive effects of redundant descriptions in an interactive semantic speech interface | | BIBAK | Full-Text | 217-226 | |
| Lane Schwartz; Luan Nguyen; Andrew Exley; William Schuler | |||
| Spoken language interfaces based on interactive semantic language models
allow probabilities for hypothesized words to be conditioned on the semantic
interpretation of these words in the context of some interfaced application
environment. This conditioning may allow users to avoid recognition errors in
an intuitive way, by adding extra, possibly redundant description. This paper
evaluates the effect on error reduction of redundant descriptions in an
interactive semantic language model. In order to evaluate the effect in natural
use, the model is run on rich domains, supporting references to sets of
individuals (instead of just individuals themselves) arranged in multiple
continuous dimensions (a 2-D floorplan scene). Results of these experiments
suggest that an interactive semantic language model allows users to achieve
significantly higher recognition accuracy by providing additional redundant
spoken description. Keywords: interactive semantics, semantics, speech recognition, spoken language
interfaces | |||
| Data-driven exploration of musical chord sequences | | BIBAK | Full-Text | 227-236 | |
| Eric Nichols; Dan Morris; Sumit Basu | |||
| We present data-driven methods for supporting musical creativity by
capturing the statistics of a musical database. Specifically, we introduce a
system that supports users in exploring the high-dimensional space of musical
chord sequences by parameterizing the variation among chord sequences in
popular music. We provide a novel user interface that exposes these learned
parameters as control axes, and we propose two automatic approaches for
defining these axes. One approach is based on a novel clustering procedure, the
other on principal components analysis. A user study compares our approaches
for defining control axes both to each other and to an approach based on
manually-assigned genre labels. Results show that our automatic methods for
defining control axes provide a subjectively better user experience than axes
based on manual genre labeling. Keywords: chords, clustering, creativity, genre, hmms, music, pca, transition matrix | |||
| Parakeet: a continuous speech recognition system for mobile touch-screen devices | | BIBAK | Full-Text | 237-246 | |
| Keith Vertanen; Per Ola Kristensson | |||
| We present Parakeet, a system for continuous speech recognition on mobile
touch-screen devices. The design of Parakeet was guided by computational
experiments and validated by a user study. Participants had an average text
entry rate of 18 words-per-minute (WPM) while seated indoors and 13 WPM while
walking outdoors. In an expert pilot study, we found that speech recognition
has the potential to be a highly competitive mobile text entry method,
particularly in an actual mobile setting where users are walking around while
entering text. Keywords: continuous speech recognition, error correction, mobile text entry,
predictive keyboard, speech input, text input, touch-screen interface, word
confusion network | |||
| Understanding the intent behind mobile information needs | | BIBAK | Full-Text | 247-256 | |
| Karen Church; Barry Smyth | |||
| Mobile phones are becoming increasingly popular as a means of information
access while on-the-go. Mobile users are likely to be interested in locating
different types of content. However, the mobile space presents a number of key
challenges, many of which go beyond issues with device characteristics such as
screen-size and input capabilities. In particular, changing contexts such as
location, time, activity and social interactions are likely to impact on the
types of information needs that arise. In order to offer personalized,
effective mobile services we need to understand mobile users in more detail.
Thus we carried out a four-week diary study of mobile information needs,
looking in particular at the goal/intent behind mobile information needs, the
topics users are interested in and the impact of mobile contexts such as
location and time on user needs. Keywords: context, diary study, information needs, intent, mobile | |||
| Searching large indexes on tiny devices: optimizing binary search with character pinning | | BIBAK | Full-Text | 257-266 | |
| Guy Shani; Christopher Meek; Tim Paek; Bo Thiesson; Gina Danielle Venolia | |||
| The small physical size of mobile devices imposes dramatic restrictions on
the user interface (UI). With the ever increasing capacity of these devices as
well as access to large online stores it becomes increasingly important to help
the user select a particular item efficiently. Thus, we propose binary search
with character pinning, where users can constrain their search to match
selected prefix characters while making simple binary decisions about the
position of their intended item in the lexicographic order. The underlying
index for our method is based on a ternary search tree that is optimal under
certain user-oriented constraints. To better scale to larger indexes, we
analyze several heuristics that rapidly construct good trees. A user study
demonstrates that our method helps users conduct rapid searches, using less
keystrokes, compared to other methods. Keywords: binary search, optimal binary search tree | |||
| Subobject detection through spatial relationships on mobile phones | | BIBAK | Full-Text | 267-276 | |
| Benjamin Brombach; Erich Bruns; Oliver Bimber | |||
| We present a novel image classification technique for detecting multiple
objects (called subobjects) in a single image. In addition to image
classifiers, we apply spatial relationships among the subobjects to verify and
to predict the locations of detected and undetected subobjects, respectively.
By continuously refining the spatial relationships throughout the detection
process, even locations of completely occluded exhibits can be determined. This
approach is applied in the context of PhoneGuide, an adaptive museum guidance
system for camera-equipped mobile phones.
Laboratory tests as well as a field experiment reveal recognition rates and performance improvements when compared to related approaches. Keywords: image classification, mobile computing, museum guidance application, spatial
relationships, subobject detection | |||
| Discovering frequent work procedures from resource connections | | BIBAK | Full-Text | 277-286 | |
| Jianqiang Shen; Erin Fitzhenry; Thomas G. Dietterich | |||
| Intelligent desktop assistants could provide more help for users if they
could learn models of the users' workflows. However, discovering desktop
workflows is difficult because they unfold over extended periods of time (days
or weeks) and they are interleaved with many other workflows because of user
multi-tasking. This paper describes an approach to discovering desktop
workflows based on rich instrumentation of information flow actions such as
copy/paste, SaveAs, file copy, attach file to email message, and save
attachment. These actions allow us to construct a graph whose nodes are files,
email messages, and web pages and whose edges are these information flow
actions. A class of workflows that we call work procedures can be discovered by
applying graph mining algorithms to find frequent subgraphs. This paper
describes an algorithm for mining frequent closed connected subgraphs and then
describes the results of applying this method to data collected from a group of
real users. Keywords: automated assistance, data mining, intelligent interfaces, provenance,
resource management, workflow | |||
| A probabilistic mental model for estimating disruption | | BIBAK | Full-Text | 287-296 | |
| Bowen Hui; Grant Partridge; Craig Boutilier | |||
| Adaptive software systems are intended to modify their appearance,
performance or functionality to the needs and preferences of different users. A
key bottleneck in building effective adaptive systems is accounting for the
cost of disruption to a user's mental model of the application caused by the
system's adaptive behaviour. In this work, we propose a probabilistic approach
to modeling the cost of disruption. This allows an adaptive system to tradeoff
disruption cost with expected savings (or other benefits) induced by a
potential adaptation in a principled, decision-theoretic fashion. We conducted
two experiments with 48 participants to learn model parameters in an adaptive
menu selection environment. We demonstrate the utility of our approach in
simulation and usability studies. Usability results with 8 participants suggest
that our approach is competitive with other adaptive menus w.r.t. task
performance, while providing the ability to reduce disruption and adapt to user
preferences. Keywords: decision-theoretic systems, disruption, probabilistic mental model, user
modeling | |||
| Intelligently creating and recommending reusable reformatting rules | | BIBAK | Full-Text | 297-306 | |
| Christopher Scaffidi; Brad Myers; Mary Shaw | |||
| When users combine data from multiple sources into a spreadsheet or dataset,
the result is often a mishmash of different formats, since phone numbers,
dates, course numbers and other string-like kinds of data can each be written
in many different formats. Although spreadsheets provide features for
reformatting numbers and a few specific kinds of string data, they do not
provide any support for the wide range of other kinds of string data
encountered by users. We describe a user interface where a user can describe
the formats of each kind of data. We provide an algorithm that uses these
formats to automatically generate reformatting rules that transform strings
from one format to another. In effect, our system enables users to create a
small expert system called a "tope" that can recognize and reformat instances
of one kind of data. Later, as the user is working with a spreadsheet, our
system recommends appropriate topes for validating and reformatting the data.
With a recall of over 80% for a query time of under 1 second, this algorithm is
accurate enough and fast enough to make useful recommendations in an
interactive setting. A laboratory experiment shows that compared to manual
typing, users can reformat sample spreadsheet data more than twice as fast by
creating and using topes. Keywords: consistent data format, end-user programming, spreadsheets | |||
| Intelligent wheelchair (IW) interface using face and mouth recognition | | BIBAK | Full-Text | 307-314 | |
| Jin Sun Ju; Yunhee Shin; Eun Yi Kim | |||
| between the user and the wheelchair. To facilitate a wide variety of user
abilities, the proposed system uses face inclination and mouth-shape
information as user's intention, where the direction of an IW is determined by
the inclination of the user's face, while proceeding and stopping are
determined by the shape of the user's mouth. This mechanism requires minimal
motion, thereby making the system more comfortable and adaptable for the
severely disabled. Furthermore, to fully guarantee user's safety, the 10
range-sensors are used to detect obstacles in environment and avoid them. To
assess the effectiveness of the proposed IW, it was tested with 34 users and
the results show that it can provide a user unable to drive a standard joystick
with friendly and convenient system. Keywords: adaboost, facial feature recognition, intelligent interface, intelligent
wheelchair, k-means clustering, vision based interface | |||
| Behavior-driven visualization recommendation | | BIBAK | Full-Text | 315-324 | |
| David Gotz; Zhen Wen | |||
| We present a novel approach to visualization recommendation that monitors
user behavior for implicit signals of user intent to provide more effective
recommendation. This is in contrast to previous approaches which are either
insensitive to user intent or require explicit, user specified task
information. Our approach, called Behavior-Driven Visualization Recommendation
(BDVR), consists of two distinct phases: (1) pattern detection, and (2)
visualization recommendation. In the first phase, user behavior is analyzed
dynamically to find semantically meaningful interaction patterns using a
library of pattern definitions developed through observations of real-world
visual analytic activity. In the second phase, our BDVR algorithm uses the
detected patterns to infer a user's intended visual task. It then automatically
suggests alternative visualizations that support the inferred visual task more
directly than the user's current visualization. We present the details of BDVR
and describe its implementation within our lab's prototype visual analysis
system. We also present study results that demonstrate that our approach
shortens task completion time and reduces error rates when compared to
behavior-agnostic recommendation. Keywords: information visualization, intelligent visualization, user behavior
modeling, visualization recommendation | |||
| A multimedia interface for facilitating comparisons of opinions | | BIBAK | Full-Text | 325-334 | |
| Giuseppe Carenini; Lucas Rizoli | |||
| Written opinion on products and other entities can be important to consumers
and researchers, but expensive and difficult to analyze. We present a
multimedia interface designed to facilitate the analysis of opinions on
multiple entities, which could be beneficial to many individuals and
organizations. It integrates an information visualization and an intelligent
system that selects notable comparisons in the data and summarizes them in
text. This system applies a set of statistics for comparing opinions across
entities. We conducted a study of our interface with 36 subjects. Subjects
liked the visualization overall and our system's selections overlapped with
those of subjects more than did the selections of baseline systems. Given the
choice, subjects often changed their selections to be more consistent with
those of our system. This suggests that system selections were valuable to
them. Keywords: automatic summarization, evaluative text, information visualization, opinion
mining, user study | |||
| Modality effects on cognitive load and performance in high-load information presentation | | BIBAK | Full-Text | 335-344 | |
| Yujia Cao; Mariët Theune; Anton Nijholt | |||
| In this study, we argue that modality planning in multimodal presentation
systems needs to consider the modality characteristics at not only the
presentational level but also the cognitive level, especially in a situation
where the information load is high and the user task is time-critical. As a
first step towards automatic cognitive-aware modality planning, we integrated
the effect of different modalities on cognitive load and performance, using a
high-load information presentation scenario. Mainly based on modality-related
psychology theories, we selected five modality conditions (text, image,
text+image, text+speech, and text+sound) and made hypotheses about their
effects on cognitive load. Modality effects were evaluated by two cognitive
load measurements and two performance measurements. Results confirmed most of
the predicted modality effects, and showed that these effects become
significant when the information load and the task demand are high. The
findings of this study suggest that it is highly necessary to encode
modality-related principles of human cognition into the modality planning
procedure for systems that support high-load human-computer interaction. Keywords: cognitive load, heart rate variability, high-load information presentation,
modality effect, performance | |||
| UI Fin: a process-oriented interface design tool | | BIBAK | Full-Text | 345-354 | |
| Angel Puerta; Martin Hu | |||
| Even though over the years a multitude of user interface design tools have
been created, designers in practice find themselves limited to a small set of
realistic options. These options include interface builders that are attached
to development environments, or general-purpose tools such as Microsoft Visio.
We claim that the inability of many user interface tools to find their way into
a designer's toolbox is due in great part to their failure to support the
process of designing a user interface. In this paper, we introduce UI Fin, a
user interface design tool that: (a) fits within and supports a common process
for user interface design, (b) enables user-centered, as opposed to
widget-centered, screen design, (c) provides decision-support for designers,
and (d) bridges the transitions between the multiple actors in the design and
engineering of a user interface. UI Fin has been used in real-world interface
design projects and it appears to improve the efficiency of the design process,
to enable multiple types of users to create design artifacts, and to present a
relatively low barrier for novice users to become productive with the tool. Keywords: knowledge-based interface design tools, model-based interface design,
user-interface description languages, user-interface tools | |||
| A bayesian reinforcement learning approach for customizing human-robot interfaces | | BIBAK | Full-Text | 355-360 | |
| Amin Atrash; Joelle Pineau | |||
| Personal robots are becoming increasingly prevalent, which raises a number
of interesting issues regarding the design and customization of interfaces to
such platforms. The particular problem addressed by this paper is the use of
learning methods to improve the quality and effectiveness of human-machine
interaction onboard a robotic wheelchair. In support of this, we present a
method for learning and adapting probabilistic models with the aid of a human
operator. We use a Bayesian reinforcement learning framework, that allows us to
mix learning and execution, as well as take advantage of prior information
about the world. We address the problems of learning, handling a partially
observable environment, and limiting the number of action requests. We
demonstrate empirical feasibility of our approach on an interface for an
autonomous wheelchair. Keywords: activity & plan recognition, intelligent assistants, intelligent interfaces
for ubiquitous computing | |||
| Collaborative translation by monolinguals with machine translators | | BIBAK | Full-Text | 361-366 | |
| Daisuke Morita; Toru Ishida | |||
| In this paper, we present the concept for collaborative translation, where
two non-bilingual people who use different languages collaborate to perform the
task of translation using machine translation (MT) services, whose quality is
imperfect in many cases. The key idea of this model is that one person, who
handles the source language (source language side) and another person, who
handles the target language (target language side), play different roles: the
target language side modifies the translated sentence to improve its fluency,
and the source language side evaluates its adequacy. We demonstrated the
effectiveness and the practicality of this model in a tangible way. Keywords: computer-mediated communication, intercultural collaboration, machine
translation | |||
| A comparative user study on rating vs. personality quiz based preference elicitation methods | | BIBAK | Full-Text | 367-372 | |
| Rong Hu; Pearl Pu | |||
| We conducted a user study evaluating two preference elicitation approaches
based on ratings and personality quizzes respectively. Three criteria were used
in this comparative study: perceived accuracy, user effort and user loyalty.
Results from our study show that the perceived accuracy in two systems is not
significantly different. However, users expended significantly less effort,
both perceived cognitive effort and actual task time, to complete the
preference profile establishing process in the personality quiz-based system
than in the rating-based system. Additionally, users expressed stronger
intention to reuse the personality quiz-based system and introduce it to their
friends. After using these two systems, 53% of users preferred the personality
quiz-based system vs. 13% of users preferred the rating-based system, since
most users thought the former is easier to use. Keywords: personality quiz, preference elicitation, rating-based, recommender systems,
user study | |||
| Context restoration in multi-tasking dialogue | | BIBAK | Full-Text | 373-378 | |
| Fan Yang; Peter A. Heeman | |||
| In this paper we conduct an exploratory experiment on context restoration in
multi-tasking dialogue and report our preliminary findings. We examine a corpus
of human-human dialogues, in which pairs of conversants, using speech, work on
an ongoing task while occasionally completing real-time tasks. We investigate
whether the conversants, when returning to the ongoing task, make any effort to
restore the context. First, we identify two types of actions, utterance
restatement and information review, as possible restorations. Second, from a
statistical analysis, we find that these actions are used more often when
returning to the ongoing task, and hence seem to play a role in context
restoration. Our findings will help to build a foundation for future speech
interfaces that support multi-tasking dialogue. Keywords: context restoration, multi-tasking dialogue | |||
| Crafting an environment for collaborative reasoning | | BIBAK | Full-Text | 379-382 | |
| Susanne C. Hupfer; Steven I. Ross; Jamie C. Rasmussen; James E. Christensen; Stephen E. Levy; Daniel M. Gruen; John F. Patterson | |||
| We motivate the need for new environments for collaborative reasoning and
describe the foundations of our approach, namely collaboration, semantics, and
adaptability. We describe the CRAFT collaborative reasoning interface and
infrastructure that we are developing to explore this approach. Keywords: collaborative reasoning environment, collective intelligence,
computer-supported cooperative work, intelligent interface, ontology,
semantics, sensemaking | |||
| Designing user interface adaptation rules with T: XML | | BIBAK | Full-Text | 383-388 | |
| Víctor López-Jaquero; Francisco Montero; Fernando Real | |||
| The specification of model adaptation and generation rules is a topic of
great interest for the user interface development community, since there are
more and more approaches supporting the model-based approach. The
ubiquitousness in interaction and the different user profiles are not the only
challenges when designing interactive systems. Furthermore, the context of use
evolves over time. In this situation, there is a strong need to provide a set
of adaptation rules to make the user interface evolve according to the context
of use evolution. This paper contributes a metamodel for the definition of
adaptation rules in a systematic approach, pursuing engineer adaptation.
Moreover, a tool called T:XML is presented that supports the specification of
adaptation rules using a visual notation that greatly simplifies the process of
designing adaptation for model-based user interface environments. Keywords: t:xml tool, user interface adaptation, user interface development
environment | |||
| From geek to sleek: integrating task learning tools to support end users in real-world applications | | BIBAK | Full-Text | 389-394 | |
| Aaron Spaulding; Jim Blythe; Will Haines; Melinda Gervasio | |||
| Numerous techniques exist to help users automate repetitive tasks; however,
none of these methods fully support end-user creation, use, and modification of
the learned tasks. We present an integrated task learning system (ITL) that
learns executable procedures based on user demonstration and instruction,
constituting a first step toward a broader solution for procedure management.
We discuss our deployment of ITL into a collaborative command-and-control
system. In this complex domain, ITL's performance with end users doing real
tasks indicates that providing multiple, integrated learning techniques both
extends functionality and improves user experience. Our experience in
integrating this system also provides key insights for future designs of
domain-independent task learning systems, specifically in supporting users'
ability to understand and edit lengthy procedures. Keywords: end user programming, interaction design, programming by demonstration,
reasoning about actions, task learning | |||
| Generating pictorial-based representation of mental images for video monitoring | | BIBAK | Full-Text | 395-400 | |
| Chuan-Heng Hsiao; Wei-Chia Huang; Kuan-Wen Chen; Li-Wei Chang; Yi-Ping Hung | |||
| Multi-camera systems have been widely used in many video surveillance
applications. When an event happens and is monitored across multiple cameras,
it is easy for an expert to generate the corresponding spatial representation
to comprehend the series of event. However, it is not trivial for users new to
the environment. With support from psychological evidences, we propose an
approach to mimic generating pictorial-based representation of mental images
when a target is moving across the views of cameras. First we conduct a
ball-rolling experiment to compare this approach with others. The empirical
results demonstrate that the performance of users with this approach is
significantly better than others. We suggest that it is because this approach
is better for users to preserve spatial representation of the environment while
transiting views between cameras. Then we propose a framework to realize this
approach. The demonstrations in different situations indicate the validity of
such framework. Keywords: intelligent visualization, mental images, surveillance, user study | |||
| Hand gesture recognition and virtual game control based on 3D accelerometer and EMG sensors | | BIBAK | Full-Text | 401-406 | |
| Xu Zhang; Xiang Chen; Wen-hui Wang; Ji-hai Yang; Vuokko Lantz; Kong-qiao Wang | |||
| This paper describes a novel hand gesture recognition system that utilizes
both multi-channel surface electromyogram (EMG) sensors and 3D accelerometer
(ACC) to realize user-friendly interaction between human and computers. Signal
segments of meaningful gestures are determined from the continuous EMG signal
inputs. Multi-stream Hidden Markov Models consisting of EMG and ACC streams are
utilized as decision fusion method to recognize hand gestures. This paper also
presents a virtual Rubik's Cube game that is controlled by the hand gestures
and is used for evaluating the performance of our hand gesture recognition
system. For a set of 18 kinds of gestures, each trained with 10 repetitions,
the average recognition accuracy was about 91.7% in real application. The
proposed method facilitates intelligent and natural control based on gesture
interaction. Keywords: accelerometer, electromyogram, gesture recognition, human computer
interaction | |||
| Handling conditional preferences in recommender systems | | BIBAK | Full-Text | 407-412 | |
| Zhiyong Yu; Zhiwen Yu; Xingshe Zhou; Yuichi Nakamura | |||
| In this paper, we propose an approach to handle conditional preferences in
recommender systems. A quantitative conditional preference model based on
domain knowledge is introduced. The inheritance property in concept trees and
bipolar property in preference statements are adopted when interpreting
conditional preference rules. Group preferences are merged from personal
preferences with consideration of manipulability. A graphical user interface is
developed for visualization of domain knowledge, conditional preference rules,
personal and group preferences. Keywords: conditional preference, recommender system | |||
| Illuminac: simultaneous naming and configuration for workspace lighting control | | BIBAK | Full-Text | 413-418 | |
| Ana Ramírez Chang; John Canny | |||
| We explore natural and calm interfaces for configuring ubiquitous computing
environments. A natural interface should enable the user to name a desired
configuration and have the system enact that configuration. Users should be
able to use familiar names for configurations without learning, which implies
the mapping from names to configurations is many-to-one. Instead of users
learning the environment's command language, the system simultaneously learns
common configurations and infers the keywords that are most salient to them. We
call this the SNAC problem (Simultaneous Naming and Configuration). As a case
study, we design a speech interface for workspace lighting control on a large
array of individually-controllable lights. We present an approach to the SNAC
problem and demonstrate its applicability through an evaluation of our system,
Illuminac. Keywords: environment control, natural speech interfaces, non-negative matrix
factorization | |||
| MediaGLOW: organizing photos in a graph-based workspace | | BIBAK | Full-Text | 419-424 | |
| Andreas Girgensohn; Frank Shipman; Lynn Wilcox; Thea Turner; Matthew Cooper | |||
| We designed an interactive visual workspace, MediaGLOW, that supports users
in organizing personal and shared photo collections. The system interactively
places photos with a spring layout algorithm using similarity measures based on
visual, temporal, and geographic features. These similarity measures are also
used for the retrieval of additional photos. Unlike traditional spring-based
algorithms, our approach provides users with several means to adapt the layout
to their tasks. Users can group photos in stacks that in turn attract
neighborhoods of similar photos. Neighborhoods partition the workspace by
severing connections outside the neighborhood. By placing photos into the same
stack, users can express a desired organization that the system can use to
learn a neighborhood-specific combination of distances. Keywords: photo organization, photo retrieval, photo sharing | |||
| Multi-touch interaction for robot control | | BIBAK | Full-Text | 425-428 | |
| Mark Micire; Jill L. Drury; Brenden Keyes; Holly A. Yanco | |||
| Recent developments in multi-touch technologies have exposed fertile ground
for research in enriched human-robot interaction. Although multi-touch
technologies have been used for virtual 3D applications, to the authors'
knowledge, ours is the first study to explore the use of a multi-touch table
with a physical robot agent. This baseline study explores the control of a
single agent with a multi-touch table using an adapted, previously studied,
joystick-based interface. We performed a detailed analysis of users'
interaction styles with two complex functions of the multi-touch interface and
isolated mismatches between user expectations and interaction functionality. Keywords: human-robot interaction, interaction styles, multi-touch interaction | |||
| Musicsim: integrating audio analysis and user feedback in an interactive music browsing ui | | BIBAK | Full-Text | 429-434 | |
| Ya-Xi Chen; Andreas Butz | |||
| In music information retrieval (MIR), there are two main research
directions, which are based either on a folder hierarchy and metadata, or on
the actual acoustic content. We believe that both content-based and
hierarchy-based retrieval have their respective strengths for browsing and
organizing music collections, and that the integration of content analysis
techniques in metadata-based media UIs can lead to more powerful UIs. In this
paper we present a prototype, in which audio analysis techniques and user
feedback are integrated into an interactive UI for browsing and organizing
large music collections. We also provide visual assistance to support
non-visual perception of music. We discussed our system with test users and
received encouragement as well as valuable suggestions for future re-search. Keywords: audio analysis, music browser, music information retrieval, playlist
generation, user feedback | |||
| Predictive text input in a mobile shopping assistant: methods and interface design | | BIBAK | Full-Text | 435-438 | |
| Petteri Nurmi; Andreas Forsblom; Patrik Floréen; Peter Peltonen; Petri Saarikko | |||
| The fundamental nature of grocery shopping makes it an interesting domain
for intelligent mobile assistants. Even though the central role of shopping
lists is widely recognized, relatively little attention has been paid to
facilitating shopping list creation and management. In this paper we introduce
a predictive text input technique that is based on association rules and item
frequencies. We also describe an interface design for integrating the
predictive text input with a web-based mobile shopping assistant. In a user
study we compared two interfaces, one with text input support and one without.
Our results indicate that, even though shopping list entries are typically
short, our technique makes text input significantly faster, decreases typing
error rates and increases overall user satisfaction. Keywords: adaptive, recommendations, usability, user interface | |||
| Pulling strings from a tangle: visualizing a personal music listening history | | BIBAK | Full-Text | 439-444 | |
| Dominikus Baur; Andreas Butz | |||
| The history of songs, to which a person has listened, is a very personal
piece of information. It is a rich data set that comes as a byproduct of the
use of digital music players and can be obtained without interfering with the
user.
In this paper, we present three visualizations for this data set and a mechanism for generating new playlists from the user's own listening history, based on a navigation metaphor. First, temporal proximity is interpreted as a simple similarity measure to lay out the entire history on a two-dimensional plane. Closed listening sessions are then used to make chronological relations visible. The generated playlists mimic the user's previous listening behavior, and the visualizations make the automatic choices understandable, as they share visual properties with the history. In this sense, our visualizations provide a visual vocabulary for listening behaviors and bring scrutability to automatic playlist generation. Keywords: listening history, navigation metaphor, playlist creation, visualization | |||
| A scientific workflow construction command line | | BIBAK | Full-Text | 445-450 | |
| Paul T. Groth; Yolanda Gil | |||
| Workflows have emerged as a common tool for scientists to express their
computational analyses. While there are a multitude of visual data flow editors
for workflow construction, to date there are none that support the input of
workflows using natural language. This work presents the design of a hybrid
system that combines natural language input through a command line with a
visual editor. Keywords: command line, natural language, scientific workflows | |||
| Skipping spare information in multimodal inputs during multimodal input fusion | | BIBAK | Full-Text | 451-456 | |
| Yong Sun; Yu Shi; Fang Chen; Vera Chung | |||
| In a multimodal interface, a user can use multiple modalities, such as
speech, gesture, and eye gaze etc., to communicate with a system. As a critical
component in a multimodal interface, multimodal input fusion explores the ways
to effectively interpret the combined semantic interpretation of user's
multimodal inputs. Although multimodal inputs may contain spare information,
few multimodal input fusion approaches have tackled how to deal with spare
information in multimodal inputs. This paper proposes a novel multimodal input
fusion approach to flexibly skip spare information in multimodal inputs and
derive semantic interpretation of them. The evaluation about the proposed
approach confirms that the approach makes human-computer interaction more
natural and smooth. Keywords: processing of multimodal input, spare information in multimodal input | |||
| Structuring and manipulating hand-drawn concept maps | | BIBAK | Full-Text | 457-462 | |
| Yingying Jiang; Feng Tian; Xugang Wang; Xiaolong Zhang; Guozhong Dai; Hongan Wang | |||
| Concept maps are an important tool to knowledge organization,
representation, and sharing. Most current concept map tools do not provide full
support for hand-drawn concept map creation and manipulation, largely due to
the lack of methods to recognize hand-drawn concept maps. This paper proposes a
structure recognition method. Our algorithm can extract node blocks and link
blocks of a hand-drawn concept map by combining dynamic programming and graph
partitioning and then build a concept-map structure by relating extracted nodes
and links. We also introduce structure-based intelligent manipulation technique
of hand-drawn concept maps. Evaluation shows that our method has high structure
recognition accuracy in real time, and the intelligent manipulation technique
is efficient and effective. Keywords: dynamic programming, graph partition, hand-drawn concept map, structure
recognition | |||
| Using salience to segment desktop activity into projects | | BIBAK | Full-Text | 463-468 | |
| Daniel Lowd; Nicholas Kushmerick | |||
| Knowledge workers must manage large numbers of simultaneous, ongoing
projects that collectively involve huge numbers of resources (documents,
emails, web pages, calendar items, etc). An activity database that captures the
relationships among projects, resources, and time can drive a variety of tools
that save time and increase productivity. To maximize net time savings, we
would prefer to build such a database automatically, or with as little user
effort as possible. In this paper, we present several sets of features and
algorithms for predicting the project associated with each action a user
performs on the desktop. Key to our methods is salience, the notion that more
recent activity is more informative. By developing novel features that
represent salience, we were able to learn models that outperform both a simple
benchmark and an expert system tuned specifically for this task on real-world
data from five users. Keywords: activity recognition, information workers, interruption recovery, logistic
regression, machine learning, time tracking | |||
| You can play that again: exploring social redundancy to derive highlight regions in videos | | BIBAK | Full-Text | 469-474 | |
| Jose San Pedro; Vaiva Kalnikaite; Steve Whittaker | |||
| Identifying highlights in multimedia content such as video and audio is
currently a very difficult technical problem. We present and evaluate a novel
algorithm that identifies highlights by combining content analysis with Web 2.0
data mining techniques. We exploit the fact that popular content tends to be
redundantly uploaded onto community sharing sites. Our "social summarization"
technique first identifies overlaps in uploaded scenes and then uses the upload
frequency of each video scene to compute that scene's importance in the
complete video. Our user evaluation shows the reliability of the technique:
scenes automatically selected by our method are agreed by experts to be the
most relevant. Keywords: community, social network, summarization, video content analysis | |||
| Fully automatic user interface generation from discourse models | | BIBAK | Full-Text | 475-476 | |
| Jüergen Falb; Sevan Kavaldjian; Roman Popp; David Raneburger; Edin Arnautovic; Hermann Kaindl | |||
| Automatic generation of user interfaces (UIs) has made some progress, but it
still faces many challenges, especially when starting from high-level models.
We developed an approach and a supporting tool for modeling discourses, from
which the tool can generate WIMP (window, icon, menu, pointer) UIs
automatically. This involves several complex steps, most of which we have been
able to implement using model-driven transformations. When given specific
target platform specifications, UIs for a variety of devices such as PCs,
mobile phones and PDAs can be generated automatically. Keywords: interaction design, model-driven ui generation | |||
| Interactive multimodal transcription of text images using a web-based demo system | | BIBAK | Full-Text | 477-478 | |
| Verónica Romero; Luis A. Leiva; Alejandro H. Toselli; Enrique Vidal | |||
| This document introduces a web based demo of an interactive framework for
transcription of handwritten text, where the user feedback is provided by means
of pen strokes on a touchscreen. Here, the automatic handwriting text
recognition system and the user both cooperate to generate the final
transcription. Keywords: handwritten recognition, hci, interactive framework, web | |||
| IVEA: toward a personalized visual interface for exploring text collections | | BIBAK | Full-Text | 479-480 | |
| Vinh Tuan Thai; Siegfried Handschuh | |||
| In this paper we present IVEA, a personalized visual interface which enables
users to explore text collections from different perspectives and levels of
detail. This work explores the use of a personal ontology, which encapsulates
users' entities of interest, as an anchor for the exploration process. This, in
effect, simplifies the comprehension of visual representation of text
collections by helping users to focus on aspects that they are particularly
concerned with. Keywords: text collections, visual exploration | |||
| A meta user interface to control multimodal interaction in smart environments | | BIBAK | Full-Text | 481-482 | |
| Dirk Roscher; Marco Blumendorf; Sahin Albayrak | |||
| Smart environments bring together multiple users, (interaction) resources
and services. This creates complex and unpredictable interactive computing
environments that are hard to understand. Users thus have difficulties to build
up their mental model of such interactive systems. To address this issue users
need possibilities to evaluate the state of these systems and to adapt them
according to their needs. In this work we present our implementation of the
functionalities to evaluate and control multimodal interaction in smart
environments, which is accessible for users through a meta user interface. Keywords: human-computer interaction, meta user interfaces, model-based user
interfaces, multimodal interaction, smart environments | |||
| Parakeet: a demonstration of speech recognition on a mobile touch-screen device | | BIBAK | Full-Text | 483-484 | |
| Keith Vertanen; Per Ola Kristensson | |||
| We demonstrate Parakeet -- a continuous speech recognition system for mobile
touch-screen devices. Parakeet's interface is designed to make correcting
errors easy on a handheld device while on the move. Users correct errors using
a touch-screen to either select alternative words from a word confusion network
or by typing on a predictive software keyboard. Our interface design was guided
by computational experiments. We conducted a user study to validate our design.
We found novices entered text at 18 WPM while seated indoors and 13 WPM while
walking outdoors. Keywords: error correction, mobile continuous speech recognition, speech input,
touch-screen interface, word confusion network | |||
| Prime III: an innovative electronic voting interface | | BIBAK | Full-Text | 485-486 | |
| Shaneé Dawkins; Tony Sullivan; Greg Rogers; E. Vincent, II Cross; Lauren Hamilton; Juan E. Gilbert | |||
| Voting technology today has not addressed the issues that disabled voters
are confronted with at the polls. Because approximately 17% of the voting
population is disabled, their issues should be handled with a solution geared
towards their needs. Disabled voters need to be able to cast their vote without
the assistance of others. The Prime III multimodal voting system [2] addresses
these issues. This demonstration will illustrate the use of the Prime III
system, a virtual reality (VR) version (Prime V), and a similar version created
using a voice user interface (VUI). Keywords: e-voting, multimodal user interaction, universal access | |||
| Serious processing for frivolous purpose: a chatbot using web-mining supported affect analysis and pun generation | | BIBAK | Full-Text | 487-488 | |
| Rafal Rzepka; Wenhan Shi; Michal Ptaszynski; Pawel Dybala; Shinsuke Higuchi; Kenji Araki | |||
| By our demonstration we want to introduce our achievements in combining
different purpose algorithms to build a chatbot which is able to keep a
conversation on any topic. It uses snippets of Internet search results to stay
within a context, Nakamura's Emotion Dictionary to detect an emotional load
existence and categorization of a textual utterance and a causal consequences
retrieval algorithm when emotive features are not found. It is also able to
detect a possibility to make a pun by analyzing the input sentence and create
one if timing is adequate. Keywords: affect analysis, chatbot, pun generation, web-mining | |||
| Tribal taste: mobile multiagent recommender system | | BIBAK | Full-Text | 489-490 | |
| Magnus Jändel; Mehdi Elahi | |||
| We demonstrate a system for filtering media streams according to the
collective taste of a leader-less informal clan of users. Applications on
mobile devices receive streams of content items that are assessed by local
software agents. The agents learn the collective preferences of the tribe by
forming a distributed multi-agent society that shares data on the behavior of
all users. The underlying artificial intelligence is based on support vector
machines that cooperate by broadcasting new support vectors. The demo shows
micro-blog readers on cell phones running support vector machine agents with
text kernels and communicating over IP Multimedia System networks. Keywords: ip multimedia subsystem, mobile application, multiagent, recommender system,
support vector machine | |||
| CSIUI 2009: story understanding and generation for aware and interactive interface design | | BIBAK | Full-Text | 491-492 | |
| Catherine Havasi; Henry Lieberman; Erik T. Mueller | |||
| In order to be helpful to people, the intelligent interfaces of the future
will have to acquire, represent, and infer simple knowledge about everyday life
and activities. While much work in AI has represented this knowledge at the
word, sentence, and logical assertion level, we see a growing need to
understand it at a larger granularity, that of stories.
The workshop, like its predecessors, had the goal of bringing together researchers in common sense reasoning with researchers in intelligent interfaces. Each year our workshop has a different focus in addition to these two areas and this year's workshop focused on the acquisition, understanding and creation of stories. Keywords: common sense reasoning, events, intelligent user interfaces, knowledge
collection, story understanding | |||
| Multimodal interfaces for automotive applications (MIAA) | | BIBAK | Full-Text | 493-494 | |
| Christian Müller; Gerald Friedland | |||
| This paper summarizes the main objectives of the IUI workshop W2 on
multimodal interfaces for automotive applications. Keywords: automotive applications, human-machine-interaction, multimodal interfaces | |||
| IUI'09 workshop summary: human interaction with intelligent & networked systems | | BIBAK | Full-Text | 495-496 | |
| Peter Johnson; Christopher Paul Middup; Rachid Hourizi; Mark Maybury | |||
| This workshop brings together a community of researchers and practitioners
to identify and develop the research agenda needed to enhance human interaction
with increasingly powerful and independent intelligent systems e.g. sensors
networks, autonomous systems, agents and robotic systems. These systems have
applications in many domains including health, transport, environment,
emergency situations and defense. Aspects of these systems give rise to
properties found in loose federations, collaborations and dynamic coalitions.
The research questions include awareness, joint working, decision-making,
intentionality, coordination, task-allocation, and planning. The workshop
brings together researchers from different disciplines to discuss and develop
research and to provide a focus for interdisciplinary research in this area. Keywords: agents, autonomous systems, awareness, collaboration, coordination,
decision-making, intelligent systems, planning, robotic systems, sensor
networks | |||
| Users' preferences regarding intelligent user interfaces: differences among users and changes over time | | BIBAK | Full-Text | 497-498 | |
| Anthony Jameson; Silvia Gabrielli; Antti Oulasvirta | |||
| The goal of this full-day workshop is to arrive at a synthesis of knowledge
that will help people who work with intelligent user interfaces to predict and
explain how users' attitudes and behavior toward aspects of such systems (a)
differ from one user to the next and (b) change over time. Keywords: individual differences, longitudinal studies, user preferences | |||
| Visual interfaces to the social and the semantic web (VISSW 2009) | | BIBAK | Full-Text | 499-500 | |
| Siegfried Handschuh; Tom Heath; VinhTuan Thai | |||
| Recent developments in the Social and Semantic Web fields have resulted in
large amounts of data created, published and consumed by users of the Web. The
ability to easily integrate such vast amounts of data raises significant and
exciting research challenges, not least of which how to provide effective
access to and navigation across heterogeneous data sources. The IUI2009
workshop on Visual Interfaces to the Social and the Semantic Web aims to bring
together researchers and practitioners from different fields to discuss the
latest research results and challenges in designing, implementing, and
evaluating intelligent interfaces supporting access, navigation and publishing
of different types of contents on the Social and Semantic Web. This paper
outlines the context of the workshop and provides an overview of the research
to be presented at the event. Keywords: semantic web, social web, visual interfaces | |||
| IUI'09 workshop summary: sketch recognition | | BIBAK | Full-Text | 501-502 | |
| Tracy Anne Hammond | |||
| This paper describes the IUI'09 workshop on Sketch Recognition. Keywords: cad, document processing, pen input computing, sketch recognition, sketch
understanding, sketching | |||
| Fourth international workshop on model driven development of advanced user interfaces | | BIBAK | Full-Text | 503-504 | |
| Gerrit Meixner; Daniel Görlich; Kai Breiner; Heinrich Hußmann; Andreas Pleuß; Stefan Sauer; Jan Van den Bergh | |||
| Model Driven Development (MDD) is an important paradigm in Software
Engineering. In MDD, applications are specified systematically using abstract,
platform independent models. The models are then transformed into executable
code for different platforms and target devices. Model-driven techniques become
ever more prominent in any kind of application, such as multimedia and Web,
ubiquitous and automotive applications. Keywords: hci, mbuid, mdd, task model | |||