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Proceedings of the 2009 International Conference on Intelligent User Interfaces

Fullname:International Conference on Intelligent User Interfaces
Editors:Cristina Conati; Mathias Bauer; Dan Weld; Nuria Oliver
Location:Sanibel Island, Florida
Dates:2009-Feb-08 to 2009-Feb-11
Publisher:ACM
Standard No:ISBN: 1-60558-168-2, 978-1-60558-168-2; ACM Order no: 608090; ACM DL: Table of Contents hcibib: IUI09
Papers:74
Pages:504
Links:Conference Home Page
  1. Keynote talks
  2. Summarization
  3. Recommendations
  4. Intelligent web systems
  5. Information & knowledge management
  6. Demonstration based interfaces
  7. Novel input & output
  8. Mobile interaction
  9. Intelligent assistants
  10. Visualization & designer tools
  11. Short papers
  12. Demonstrations
  13. Workshops

Keynote talks

Invited talk: image recognition for intelligent interfaces BIBAKFull-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 BIBAKFull-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 BIBAKFull-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

Summarization

User-oriented document summarization through vision-based eye-tracking BIBAKFull-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 BIBAKFull-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 BIBAKFull-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 BIBAKFull-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

Recommendations

Tagsplanations: explaining recommendations using tags BIBAKFull-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 BIBAKFull-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 BIBAKFull-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 BIBAKFull-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

Intelligent web systems

Learning to recognize valuable tags BIBAKFull-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 BIBAKFull-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 BIBAKFull-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

Information & knowledge management

Detecting and correcting user activity switches: algorithms and interfaces BIBAKFull-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 BIBAKFull-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 BIBAKFull-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 BIBAKFull-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

Demonstration based interfaces

What were you thinking?: filling in missing dataflow through inference in learning from demonstration BIBAKFull-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 BIBAKFull-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 BIBAKFull-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 BIBAKFull-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

Novel input & output

Simplified facial animation control utilizing novel input devices: a comparative study BIBAKFull-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 BIBAKFull-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 BIBAKFull-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 BIBAKFull-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

Mobile interaction

Parakeet: a continuous speech recognition system for mobile touch-screen devices BIBAKFull-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 BIBAKFull-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 BIBAKFull-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 BIBAKFull-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

Intelligent assistants

Discovering frequent work procedures from resource connections BIBAKFull-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 BIBAKFull-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 BIBAKFull-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 BIBAKFull-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

Visualization & designer tools

Behavior-driven visualization recommendation BIBAKFull-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 BIBAKFull-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 BIBAKFull-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 BIBAKFull-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

Short papers

A bayesian reinforcement learning approach for customizing human-robot interfaces BIBAKFull-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 BIBAKFull-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 BIBAKFull-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 BIBAKFull-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 BIBAKFull-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 BIBAKFull-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 BIBAKFull-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 BIBAKFull-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 BIBAKFull-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 BIBAKFull-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 BIBAKFull-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 BIBAKFull-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 BIBAKFull-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 BIBAKFull-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 BIBAKFull-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 BIBAKFull-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 BIBAKFull-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 BIBAKFull-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 BIBAKFull-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 BIBAKFull-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 BIBAKFull-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

Demonstrations

Fully automatic user interface generation from discourse models BIBAKFull-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 BIBAKFull-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 BIBAKFull-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 BIBAKFull-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 BIBAKFull-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 BIBAKFull-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 BIBAKFull-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 BIBAKFull-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

Workshops

CSIUI 2009: story understanding and generation for aware and interactive interface design BIBAKFull-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) BIBAKFull-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 BIBAKFull-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 BIBAKFull-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) BIBAKFull-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 BIBAKFull-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 BIBAKFull-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