| Intelligent User Interfaces: An Introduction | | BIBAK | PDF | 3-4 | |
| Mark Maybury | |||
| Intelligent user interfaces promise to improve the interaction for all.
Drawing upon material from the recently completed Readings in Intelligent User
Interfaces (IUI) (Maybury and Wahlster, 1998), this tutorial will define terms,
outline the history, describe key subfields, and exemplify and demonstrate
intelligent user interfaces in action. Keywords: Intelligent user interfaces, Intelligent multimedia interpretation and
generation, User and discourse modelling, Agent-based interfaces, Model-based
interfaces | |||
| Designing and Evaluating Intelligent User Interfaces | | BIBAK | PDF | 5-6 | |
| Kristina Höök | |||
| Intelligent user interfaces have been proposed as a means to overcome some
of the problems that direct-manipulation interfaces cannot handle, such as:
information overflow problems; providing help on how to use complex systems; or
real-time cognitive overload problems. Intelligent user interfaces are also
being proposed as a means to make systems individualised or personalised,
thereby increasing the systems flexibility and appeal.
But in order for intelligent user interface to gain ground and be of real use to their users, more attention has to be given to usability issues. In this tutorial we shall discuss methods for design and evaluation of intelligent user interfaces from a usability perspective. Keywords: Intelligent user interfaces, Usability, Design methods, Evaluation | |||
| Intelligent Interface Agents | | BIB | PDF | 7 | |
| Henry Lieberman | |||
| Agent-Based Multimedia Interaction for Virtual Web Pages | | BIB | PDF | 11 | |
| Wolfgang Wahlster | |||
| Collapsible User Interfaces for Information Retrieval Agents | | BIBAK | PDF | 15-22 | |
| Martin Frank; Pedro Szekely | |||
| This paper presents an architecture for information retrieval agents in
which each agent declaratively describes its domain, input, output, and user
interface. A mediating piece of software can then assemble software agents for
a given information retrieval task, and produce a single, unified user
interface for that task from the individual agents' descriptions. Keywords: Software agents, Information retrieval, Model-based user interfaces,
Graphical user interfaces, Human-computer interaction | |||
| Multi-Agent Learning Approach to WWW Information Retrieval using Neural Network | | BIBAK | PDF | 23-30 | |
| Yong S. Choi; Suk I. Yoo | |||
| In this paper, we propose a multi-agent learning approach to information
retrieval on the World Wide Web where each agent collaboratively learns its
environment from user's relevance feedback using a neural network mechanism.
Our approach makes it possible to discover information sources that will give
the desired information, and retrieve that information efficiently and
effectively. First, we present a framework for our multi-agent learning
approach and introduce a training procedure for capturing knowledge about
user's interests and preferences in the information retrieval domain.
Secondly, we mathematically analyze the performance of our approach. Finally,
to show the utility of our approach, we present the experimental results of our
approach and compare them to those obtained. Keywords: Agent, Learning, Information retrieval, World Wide Web, Relevance feedback,
Neural network, Search service | |||
| IBOTS: Agent Control Through the User Interface | | BIBAK | PDF | 31-37 | |
| Luke S. Zettlemoyer; Robert St. Amant; Martin S. Dulberg | |||
| This paper describes an ibot, a specialized software agent that exists in
the environment of the user interface. Such an agent interacts with
applications through the same medium as a human user. Its sensors process
screen contents and mouse/keyboard events to monitor the user's actions and the
responses of the environment, while its effecters can generate such events for
its own contributions to the interaction. We describe the architecture of our
agent and * its algorithms for image processing, event management, and state
representation. We illustrate the use of the agent with a small feasibility
study in the area of software logging; results are promising for future
progress. Keywords: Agents, Intelligent assistants, User interface | |||
| Butterfly: A Conversation-Finding Agent for Internet Relay Chat | | BIBAK | PDF | 39-41 | |
| Neil W. Van Dyke; Henry Lieberman; Pattie Maes | |||
| The Internet enables groups of people throughout the world to interact to
discuss issues, get assistance, learn, and socialize. However, when there are
thousands of loosely defined groups in which a user could potentially
participate, the problem becomes finding the groups of most interest. In this
paper we focus on the domain of Internet Relay Chat real-time text messaging,
and describe a "social butterfly" agent called Butterfly that samples available
conversational groups and recommends ones of interest. We discuss Butterfly's
motivation, usage, real-world design constraints, implementation, and results.
Finally, we introduce work in progress on a multi-agent approach that has grown
out of our experience with Butterfly. Keywords: Agents, Internet, Conversation, Information filtering | |||
| Bridging Science and Applications | | BIBAK | PDF | 45-46 | |
| Jude Shavlik; Lawrence Birnbaum; William Swartout; Eric Horvitz; Barbara Hayes-Roth | |||
| The members of this panel will discuss their experiences and lessons learned
transferring research on intelligent user interfaces to the "marketplace."
They will also discuss the influence applications-oriented work should have on
defining basic research issues. Panelists are from leading industrial and
academic institutions. They will address questions such as the following:
1. Which basic research issues in intelligent user interfaces are most relevant
to their work? 2. Which intelligent-interfaces technique proved most useful in their projects? 3. Which intelligent-interfaces technique least met what was expected of it when their projects began? 4. What "major breakthrough" in intelligent-interfaces research would have the largest impact on their current and future projects? 5. Which basic research topic appears to be most over emphasized, in terms of its expected practical impact? 6. Which basic research topic appears to be most under emphasized, in terms of its expected practical impact? 7. How important is it that users are aware of the "true" level of intelligence of their interfaces? Did users expect too much or too little of the intelligent interfaces, especially compared to their expectations for traditional interfaces? 8. In hindsight, how should they have restructured their initial expectations about the role of automated intelligence in the development of advanced user interfaces? Keywords: Technology transfer, Intelligent interfaces, Commercialization | |||
| Documentation Know-How Sharing by Automatic Process Tracking | | BIBAK | PDF | 49-56 | |
| Kenji Satoh; Akitoshi Okumura | |||
| Some groupware products support office jobs by providing cooperative
functions such as workflow management. However, they cannot support
documentation jobs because the jobs need individual creativity which is
difficult to share. This paper proposes a 'Know-how Sharing Agent' which
allows individual creativity used for documentation jobs to be shared. The
Know-how Sharing Agent supports document creation by preparing the most
exemplary document and its documentation operations. The documentation
operations were also saved by the agent automatically when the document was
created. This type of agent thus promotes documentation activities by sharing
the know-how needed for documentation. Keywords: Know-how, Documentation support, Document sharing, Citation | |||
| Collecting User Access Patterns for Building User Profiles and Collaborative Filtering | | BIBAK | PDF | 57-64 | |
| Ahmad M. Ahmad Wasfi | |||
| The paper proposes a new learning mechanism to extract user preferences
transparently for a World Wide Web recommender system. The general idea is
that we use the entropy of the page being accessed to determine its
interestingness based on its occurrence probability following a sequence of
pages accessed by the user. The probability distribution of the pages is
obtained by collecting the access patterns of users navigating on the Web. A
finite context-model is used to represent the usage information. Based on our
proposed model, we have developed an autonomous agent, named ProfBuilder, that
works as an online recommender system for a Web site. ProfBuilder uses the
usage information as a base for content-based and collaborative filtering. Keywords: Autonomous agent, Classical information theory, Finite context-model,
Content-based filtering, Collaborative filtering | |||
| Let's Browse: A Collaborative Web Browsing Agent | | BIBAK | PDF | 65-68 | |
| Henry Lieberman; Neil W. Van Dyke; Adriana S. Vivacqua | |||
| Web browsing, like most of today's desktop applications, is usually a
solitary activity. Other forms of media, such as watching television, are
often done by groups of people, such as families or friends. What would it be
like to do collaborative Web browsing? Could the computer provide assistance
to group browsing by trying to help find mutual interests among the
participants? Let's Browse is an experiment in building an agent to assist a
group of people in browsing, by suggesting new material likely to be of common
interest. It is built as an extension to the single-user Web browsing agent
Letizia. Let's Browse features automatic detection of the presence of users,
automated "channel surfing" browsing, and dynamic display of the user profiles
and explanation of recommendations. Keywords: Browsing, Collaboration, Agents, User profiles | |||
| Generating Mixed-Initiative Hypertexts: A Reactive Approach | | BIBAK | PDF | 71-78 | |
| Berardina De Carolis | |||
| Interaction with an adaptive hypertext can be seen as a form of
"goal-oriented" dialogue, where the user asks for information through a set of
predefined queries and the system answers ensuring that the global
communicative goal of the information process is achieved through a sequence of
dialogue sections (hypermedia nodes). The system establishes what to say to
the user at every turn of the dialogue based on the user model settings and on
the interaction history. Planning on demand the information content of a
hypertext node that responds to a particular link selection in a particular
context requires a "reactive" approach; this differs from common hypertext
planning in that it applies local adjustment criteria to an overall plan and,
in mixed-initiative situations, tries to tit together the system's and the
user's points of view. Keywords: Dynamic hypertext generation, Mixed-initiative interaction, Automated
presentation of information | |||
| Making Systems Sensitive to the User's Time and Working Memory Constraints | | BIBAK | PDF | 79-86 | |
| Anthony Jameson; Ralph Schafer; Thomas Weis; Andre Berthold; Thomas Weyrath | |||
| Recent advances in user modeling technology have brought within reach the
goal of having systems adapt to temporary limitations of the user's available
time and working memory capacity. We first summarize empirical research by
ourselves and others that sheds light on the causes and consequences of these
(continually changing) resource limitations. We then present a
decision-theoretic approach that allows a system to assess a user's resource
limitations and to adapt its behavior accordingly. This approach is
illustrated with reference to the performance of the prototype assistance
system READY. Keywords: Adaptive systems, User modeling, Bayesian networks, Time pressure, Working
memory, Natural language | |||
| Adapting to User Preferences in Crisis Response | | BIBAK | PDF | 87-90 | |
| Wayne Iba; Melinda Gervasio | |||
| The domain of crisis planning and scheduling taxes human response managers
due to high levels of urgency and uncertainty. Such applications require
assistant technologies (in contrast to automation technologies) and provide
special challenges for interface design. We present INCA, the INteractive
Crisis Assistant, that helps users develop effective crisis response plans and
schedules in a timely manner. INCA also adapts to the individual users by
anticipating their preferred responses to a given crisis and their intended
repairs to a candidate response. We evaluate our system in HAZMAT, a synthetic
domain involving hazardous material incidents. The results show that INCA
provides effective support for the timely generation of effective responses and
tailors itself to individual users. Keywords: Adaptive interfaces, Collaborative scheduling, User modeling | |||
| IUI and Agents for the New Millennium | | BIBAK | PDF | 93-94 | |
| Henry Lieberman; Jeffrey M. Bradshaw; Yolanda Gil; Ted Selker | |||
| Advocates of intelligent user interfaces are used to fighting an uphill
battle against more conventional approaches. Skeptics have been reluctant to
accept intelligent tutoring systems, adaptive user interfaces, machine
learning, predictive user models, anthropomorphic interaction, etc. as part of
everyday interfaces because they have been suspicious of the feasibility of
such techniques and fearful of the risk of possible mistakes.
The good news is that we seem to be making progress in gaining acceptance. Past IUI conferences abound with examples of intelligent interface experiments that clearly demonstrate their feasibility. Limited examples of intelligent interfaces are actually starting to make their ways into commercial products. There is considerable evidence that opposition is softening. However, we're not out of the woods yet. Many of the early examples of commercial IUI and agent software are positioned as "add-ons" to the more familiar direct-manipulation interfaces, rather than playing a central role. We haven't yet reached the point where a new application is simply assumed, as a matter of course, to require all the representation, reasoning and learning features that IUI attendees advocate. But suppose we do? Suppose intelligence becomes such an integral part of the interface in the 21st century that we couldn't imagine applications without it? How will our software environment and the software industry change as a result? Will knowledge bases, inference engines, and learning algorithms become as much a part of the operating system as windows and menus? Will the idea of an "application", as a standalone, shrink-wrapped single-purpose interface, disappear? Once the interface is intelligent, is there any point to having present-day concepts like "files" or "directories"? Will all interfaces become personalized to the extent that there won't be any more "generic" interfaces that remain the same across millions of users? Will all information sources be interactive and customized, obsoleting paper books and linear movies? Will that lead to a loss of shared context among users? How will different intelligent user interfaces interoperate and co-operate? What, if anything, will be the next step beyond IUIs and agents? The panel will ask participants to speculate on how the widespread acceptance of intelligent user interfaces that we expect for the next millennium will transform our computing environments. Keywords: Agents, Intelligent interfaces, Personalization | |||
| Collaborative, Spoken-Language Interface Agents | | BIBA | PDF | 97 | |
| Candace L. Sidner; Daniel M. Coffman | |||
| First, the day of the GUI is drawing to a close. Second, many visionaries
have argued that the new user interface will be a direct and delegate
interface. But that's wrong.
The coming interface is one in which the user collaborates with the computer. The computer understands what the user is doing, can take part in those activities and is able to respond conversationally to the user's activities. This requires an interface that not only understands the user's individual utterances but also can participate in a conversation. Because conversations are fundamentally about the purposes for which people participate in the conversation, this new interface will also require that the machine understand and model purposes behind conversation. During this talk we will demonstrate new interfaces, some with speech, that participate with users in collaborations about doing email. We will use these demonstrations to illustrate how conversation and tasks can play a role in user interfaces. We will also demonstrate instances where spoken conversational interaction is more efficient than GUI interaction. | |||
| Mixing Scripted Interaction with Task-Oriented Language Processing in a Conversational Interface | | BIBAK | PDF | 101-103 | |
| Gene Ball | |||
| Natural conversational interaction with computers will require systems that
can successfully process unconstrained spoken input. Within the domain of its
competency, such a system must be able to process an utterance in a "deep"
fashion, extracting the detailed information necessary to carry out a useful
task. When users stray outside the supported domain, the system must still be
able to respond to a "broad" range of plausible inputs to maintain basic
conversational competency. This paper reports on an effort to combine simple
pattern matching techniques which can provide broad coverage with deep
processing based on robust natural language template matching. Keywords: Conversational interfaces, Dialogue, Scripting, Speech recognition | |||
| A Robust Selection System using Real-Time Multi-Modal User-Agent Interactions | | BIBAK | PDF | 105-108 | |
| Katsumi Tanaka | |||
| This paper presents a real-time object selection system which can deal with
gaze and speech inputs that include uncertainty. Although much research has
focused on integration of multi-modal information, most of it assumes that each
input is accurately symbolized in advance. In addition, real-time interaction
with the user is an important and desirable feature which most systems have
overlooked. Unlike those systems, our system is intended to satisfy these two
requirements. In our system, target objects are modeled by agents which react
to user's action in real-time. The agent's reactions are based on integration
of multi-modal inputs. We use gaze input which enables real-time detection of
focus-of-attention but has low accuracy, whereas speech input has high accuracy
but non-real-time feature. Highly accurate selection with robustness is
achieved by complementary effect through probabilistic integration of these two
modalities. Our first experiment shows that it is possible to select target
object successfully in most cases, even if either of the modalities includes
great uncertainty. Keywords: Multi-modal interface, Uncertainty, Real-time interaction, Gaze, Speech,
Agent model | |||
| User Acceptance of an Intelligent User Interface: A Rotorcraft Pilot's Associate Example | | BIBAK | PDF | 109-116 | |
| Christopher A. Miller; Matthew D. Hannen | |||
| The U.S. Army's Rotorcraft Pilot's Associate (RPA) program is developing an
advanced, intelligent "associate" system for flight demonstration in a future
attack/scout helicopter. A significant RPA component is the intelligent user
interface known as the Cockpit Information Manager (CIM). This paper describes
the high level architecture of the CIM, with emphasis on its pilot-perceptible
behaviors: Crew Intent Estimation, Page Selection, Symbol Selection/Declutter,
Intelligent Window Location, Automated Pan and Zoom, and Task Allocation. We
then present the subjective results of recent full mission simulation studies
using the CIM to illustrate pilots' attitudes toward these behaviors and their
perceived effectiveness. Keywords: Cockpit information management, Rotorcraft Pilot's Associate, Associate
Systems, Page selection, Symbol selection/declutter, Automated task allocation,
Pan & zoom, Window location, Intent estimation | |||
| Intelligent Multi-Shot Visualization Interfaces for Dynamic 3D Worlds | | BIBAK | PDF | 119-126 | |
| William H. Bares; James C. Lester | |||
| In next-generation virtual 3D simulation, training, and entertainment
environments, intelligent visualization interfaces must respond to
user-specified viewing requests so users can follow salient points of the
action and monitor the relative locations of objects. Users should be able to
indicate which object(s) to view, how each should be viewed, cinematic style
and pace, and how to respond when a single satisfactory view is not possible.
When constraints fail, weak constraints can be relaxed or multi-shot solutions
can be displayed in sequence or as composite shots with simultaneous viewports.
To address these issues, we have developed CONSTRAINTCAM, a real-time camera
visualization interface for dynamic 3D worlds. It has been studied in an
interactive testbed in which users can issue viewing goals to monitor multiple
autonomous characters navigating through a virtual cityscape. CONSTRAINTCAM's
real-time performance in this testbed is encouraging. Keywords: Intelligent 3D visualization, Adaptive and customizable user interfaces | |||
| Integrating Organizational Memory and Performance Support | | BIBAK | PDF | 127-134 | |
| Christopher Johnson; Larry Birnbaum; Ray Bareiss; Tom Hinrichs | |||
| We describe an approach to building integrated performance support systems
by using model-based task tracking to link performance support tools to
video-based organizational memory systems, enabling contextually appropriate
help and advice as well as proactive critiquing. Keywords: Intelligent performance support, Task models, Organizational memory,
Hypermedia | |||
| Planning and User Interface Affordances | | BIBAK | PDF | 135-142 | |
| Robert St. Amant | |||
| This paper takes a first step toward formalizing the concept of affordance
in user interfaces. Using a simple example of an AI planning domain, we show
how different types of affordance can be described in terms of the costs
associated with plan execution. We identify a number of similarities between
executing plans and interacting with a graphical user interface, and argue that
affordances for planning environments apply equally well to user interface
environments. We support our argument with examples of common user interface
mechanisms, described in affordance terms. Keywords: Planning, Affordances | |||
| Programming by Demonstration: An Inductive Learning Formulation | | BIBAK | PDF | 145-152 | |
| Tessa A. Lau; Daniel S. Weld | |||
| Although Programming by Demonstration (PBD) has the potential to improve the
productivity of unsophisticated users, previous PBD systems have used brittle,
heuristic, domain-specific approaches to execution-trace generalization. In
this paper we define two application-independent methods for performing
generalization that are based on well-understood machine learning technology.
TGENVS uses version-space generalization, and TGENFOIL is based on the FOIL
inductive logic programming algorithm. We analyze each method both
theoretically and empirically, arguing that TGENVS has lower sample complexity,
but TGENFOIL can learn a much more interesting class of programs. Keywords: Programming by demonstration, Machine learning, Inductive logic programming,
Version spaces | |||
| InfoBeams -- Configuration of Personalized Information Assistants | | BIBAK | PDF | 153-156 | |
| Mathias Bauer; Dietmar Dengler | |||
| With the enormous amount of data contained in the WWW, one of the crucial
tasks a user has to face is the identification and aggregation of relevant
pieces of information to satisfy her current information needs. This paper
presents an approach to the system-supported configuration of individualized
information services. The programming-by-demonstration approach pursued by the
InfoBeans releases the user from learning a programming language or dealing
with technical subtleties. The first version of this system will be released
this fall. Keywords: Information assistants, Wrapper induction, Programming by demonstration,
Information integration | |||
| An Instructable, Adaptive Interface for Discovering and Monitoring Information on the World-Wide Web | | BIBAK | PDF | 157-160 | |
| Jude Shavlik; Susan Calcari; Tina Eliassi-Rad; Jack Solock | |||
| We are creating a customizable, intelligent interface to the World-Wide Web
that assists a user in locating specific, current, and relevant information.
The Wisconsin Adaptive Web Assistant (WAWA) is capable of accepting
instructions regarding what type of information that users are seeking and how
to go about looking for it. WAWA compiles these instructions into neural
networks, which means that the system's behavior can be modified via training
examples. Users can create these training examples by rating pages retrieved
by WAWA, but more importantly the system uses techniques from reinforcement
learning to internally create its own examples (users can also later provide
additional instructions). WAWA uses these neural networks to guide its
autonomous navigation of the Web, thereby producing an interface to the Web
that users periodically instruct and which in the background searches the Web
for relevant information, including periodically revisiting pages that change
regularly. Keywords: Intelligent Web interfaces, Instructable software agents, Machine learning,
Neural networks, Information retrieval | |||
| Developing Adaptable Hypermedia | | BIBAK | PDF | 163-170 | |
| Fabio Paterno; Cristiano Mancini | |||
| In this paper we discuss the design and implementation of hypermedia able to
adapt to different types of usage. Our work is based on a method whose main
elements are: a strong user involvement, the identification of different types
of users, and the application of task models to support the design and
development of hypermedia. Different task models are associated with different
types of users. We show examples of the approach proposed taken from a case
study where museum information is considered. Keywords: Task models, Model-based design, Hypermedia, Adaptable user interfaces,
Museum applications | |||
| Towards a General Computational Framework for Model-Based Interface Development Systems | | BIBAK | PDF | 171-178 | |
| Angel Puerta; Jacob Eisenstein | |||
| Model-based interface development systems have not been able to progress
beyond producing narrowly focused interface designs of restricted
applicability. We identify a level-of-abstraction mismatch in interface
models, which we call the mapping problem, as the cause of the limitations in
the usefulness of model-based systems. We propose a general computational
framework for solving the mapping problem in model-based systems. We show an
implementation of the framework within the MOBI-D (Model-Based Interface
Designer) interface development environment. The MOBI-D approach to solving
the mapping problem enables for the first time with model-based technology the
design of a wide variety of types of user interfaces. Keywords: Model-based interface development, Interface models, Knowledge-based user
interface design, User interface development tools | |||
| Anticipating User's Needs: Redeeming Big Brother in the Information Age | | BIB | PDF | 181-182 | |
| Kristian J. Hammond | |||
| ConCall: Edited and Adaptive Information Filtering | | BIB | PDF | 185 | |
| Annika Wærn; Mark Tierney; Asa Rudsstrom; Jarmo Laaksolahti | |||
| Adaptive Support: The Intelligent Tour Guide | | BIBAK | PDF | 186 | |
| Marc Rossel | |||
| This paper presents the Intelligent Tour Guide realized in an Adaptive
Multimedia Presentation System which is called AMPreS [1]. It supports an
individual learning process by establishing user-tailored guided tours in
real-time. Furthermore, different kinds of tours are developed to meet
different users' needs. Keywords: Adaptive navigation support, User models, Guided tours | |||
| Evaluating Adaptive Navigation Support | | BIBAK | PDF | 187 | |
| Kristina Höök; Martin Svensson | |||
| "Lost in hyperspace" is a feeling that is familiar to almost anyone using a
computer. After a few actions, we do not know where we are, how we got there,
or what our original goal was. Adaptive navigation systems has been proposed
as a means to aid users in finding their way through information spaces.
Several systems have been designed that adapts the navigation to users'
knowledge (e.g 11), to users' preferences and goals (9), to users' tasks (8),
or to users' spatial ability (1,6). The hope is that if user characteristics
are considered the cognitive workload can be reduced, or users' learning may be
improved, etc., but will they? Keywords: Adaptive, Navigation, Evaluation, Hypermedia | |||
| STARzoom -- An Interactive Visual Database Interface | | BIBAK | PDF | 188 | |
| Per Bruno; Viktor Ehrenberg; Lars Erik Holmquist | |||
| STARzoom is a visualisation of a semantic hierarchical database utilising
the hypemym structure from WordNet. It is also the search tool for that same
database with which the user interacts in trying to visually chisel out a
search query. Keywords: Information retrieval, WordNet, Hypernyms, Semantic clustering, Visual
information seeking | |||
| Visual Querying and Explanation of Recommendations from Collaborative Filtering Systems | | BIBA | PDF | 189 | |
| Junichi Tatemura | |||
| Collaborative filtering is a technique that makes use of knowledge from other users to find useful information by computing similarity of the users based on their rating patterns [2]. Although this technique can deal with a user's subjective "taste" for data such as movies and music, one of its problems is that a user's taste is diverse and changing; the filter might fit only a portion of the user's taste or fail to satisfy her or his temporary needs. We claim that the system should explain how filtered items match the user's taste and give users control so that they can explore the information space to find what they want. We have developed a visual interface of a collaborative filtering system that supports querying and explanation of recommendations. | |||
| Stack Search -- A Graphical Search Model | | BIBAK | PDF | 190 | |
| Ted Skolnick | |||
| Most text-searching user interfaces (UIs) are made of standard UI components
arranged in text-based forms. This approach to searching has some shortcomings.
Text based UIs can be difficult to understand, seem unpredictable or lack the
control needed to find information quickly. Stack Search is a graphical search
tool created at The Wall Street Journal Interactive Edition that provides a
different model of searching. It gives feedback that allows users to see the
affects of their actions as well as the control needed to precisely isolate
information. Keywords: Search, Boolean, Stack, Paper, News, Graphical, Model, Keyword, Wall Street
Journal Interactive Edition (WSJIE) | |||
| Opportunistic Exploration of Large Consumer Product Spaces | | BIBAK | PDF | 191 | |
| Doug Bryan; Anatole Gershman | |||
| We have identified a user behavior called opportunistic exploration that is
significantly different than both browsing and searching. A novel visual
metaphor for opportunistic exploration, an aquarium, is presented. In an
aquarium users may explore a corpus at any level of granularity. The aquarium
automatically controls granularity based on the history of operations performed
by a user. We will demonstrate the metaphor on a collection of 12,000 consumer
products. Keywords: Information retrieval, Visual navigation, Visual metaphor, Browsing,
Searching | |||
| A Software Agent for Performance Improvement of Existing Information Retrieval Systems | | BIBAK | PDF | 192 | |
| Bernard J. Jansen | |||
| This paper describes a software agent developed specifically for integration
with existing information retrieval interfaces and search engines. The
software agent assists the user with query reformulation. The agent assistance
is based on characteristics of the user population, user actions during the
search process, information from retrieved documents, and historical
information from past queries. With minor modification, the software agent can
be integrated with a variety of interfaces and search engines. Keywords: Software agents, Information retrieval, Adaptive interfaces, Interface
agents, Software integration | |||
| Multilingual "Worldtrek" for Authoring and Comprehension | | BIBAK | PDF | 193 | |
| Marie-Luce Picard; Eric Boudaillier | |||
| WORLDTREK offers an interactive graphical visualization of multilingual
terminologies within authoring systems and comprehension assistance tools. It
will be customized for browsing of dependencies in data-mining applications. Keywords: Graph, Semantic networks, tcl/tk, Hypertextual navigation | |||
| WordView: Understanding Words in Context | | BIBAK | PDF | 194 | |
| Lorraine Normore; Mark Bendig; Carol Jean Godby | |||
| WordView is a tool that shows how words are used in naturally occurring
phrases to support the intelligent parsing of such phrases. It embodies an
easy to understand graphic summary and a user-controllable inspection facility. Keywords: Information retrieval, Information visualization, Natural language
processing, Compound nominals | |||
| PESCE: A Visual Generator for Software Understanding | | BIBAK | PDF | 195 | |
| Rogelio Adobbati; W. Lewis Johnson; Stacy Marsella | |||
| We present a short overview of PESCE, a system that addresses the problem of
automatically generating consistent visual explanations of software. Keywords: Software visualization, Knowledge-based user interfaces, Presentation
generation | |||
| Visual Presentation Agents for 3D Environments | | BIBAK | PDF | 196 | |
| Volker Paelke | |||
| We describe a platform independent system that provides reusable visual
presentation techniques for use in highly interactive 3D environments like 3D
interfaces. Keywords: Visual presentation techniques, 3D user interfaces, Interactive 3D
animation, Agents, 3D illustrations | |||
| A High-Level "Tasking" Interface for Uninhabited Combat Air Vehicles | | BIB | PDF | 197 | |
| Christopher A. Miller; Michael Pelican; Robert Goldman | |||
| Mobile Communication and Interaction in Context | | BIBA | PDF | 198 | |
| Jo Herstad; Do Van Thanh; Jan Arild Audestad | |||
| Current mobile communication solutions leave out information about the context in which the communication takes place. Context is, however, a key factor for the success of interpersonal communication. The contextual communication system described in this paper enhances existing mobile multimedia communication systems by introducing a feedback loop to convey contextual information. This information can be used either by the communication system or the addressee to select the most appropriate communication media, or to adjust and optimize the interaction mechanisms. Our claim is that to make useful, functional and powerful new tools for supporting human-human communication and interaction at a distance, the context has to be considered in the design of communication and information solutions. | |||
| A Contextual Analysis of Referring Gestures | | BIB | PDF | 199 | |
| Frederic Wolff; Laurent Romary | |||
| The Optimization Assistant -- Helping Engineers Explore Designs through Collaboration | | BIBAK | PDF | 200 | |
| Ted Long | |||
| In this paper, we discuss an intelligent assistant that was placed into
Engineous Software's iSIGHT product. It helps mechanical engineers design
optimization plans for discovering optimal product designs. It was determined
that an intelligent assistant was a better solution than providing data filters
or a wizard. Keywords: Intelligent assistant, Advisor, Collaboration | |||
| StoryMat: A Play Space with Narrative Memories | | BIBAK | PDF | 201 | |
| Kimiko Ryokai; Justine Cassell | |||
| In this paper, we present the design and the prototype of a
work-in-progress, StoryMat: a soft intelligent play mat that records and
recalls children's storytelling activities. Keywords: Storytelling, Recording and recalling stories, Soft interface | |||
| Programming Constraint System by Demonstration | | BIBAK | PDF | 202 | |
| Takashi Hattori | |||
| The executable constraint system aims to maintain the integrity of
structures that users create during an edit session. When the users modify a
part of the structures, other parts are modified accordingly, based on
instructions given by the users. The instructions are presented by
demonstration, and form a constraint that is satisfied when the current state
is its fixed point. The users can dynamically control a set of executable
constraints to be satisfied. Keywords: Constraints, Programming by demonstration, End user programming | |||