SUITOR: an attentive information system
@inproceedings{Maglio2000SUITORAA, title={SUITOR: an attentive information system}, author={Paul P. Maglio and Rob Barrett and Christopher S. Campbell and Ted Selker}, booktitle={IUI '00}, year={2000} }
Attentive systems pay attention to what users do so that they can attend to what users need. Such systems track user behavior, model user interests, and anticipate user desires and actions. Because the general class of attentive systems is broad — ranging from human butlers to web sites that profile users — we have focused specifically on attentive information systems, which observe user actions with information resources, model user information states, and suggest information that might be…
Figures from this paper
127 Citations
Gaze and Speech in Attentive User Interfaces
- Computer ScienceICMI
- 2000
Based on users' verbal data and eye-gaze patterns, the results suggest people naturally address individual devices rather than theOffice of the future, where information is accessed on displays via verbal commands.
User Goals and Attention Costs Attuning Notification Design to
- Computer Science
- 2003
This work believes dissatisfaction results from incorrect estimates of the user’s task prioritization during design time, and information is introduced at inappropriate times and with unsuitable presentation choices.
Attentive user interfaces: the surveillance and sousveillance of gaze-aware objects
- Computer Science
- 2008
The authors present a framework for augmenting user attention through attentive user interfaces and propose 5 key properties of attentive systems: to sense attention, reason about attention, regulate interactions, communicate attention and augment attention.
Gaze Based Learning and Access for Search Engine
- Computer Science
- 2015
This work is proposing a system that monitors user activities as he browses through the web and tries to capture user’s interest through implicit feedback technique, to enhance user experience and reduce the gulf of evaluation.
Adaptive interfaces and agents
- Art
- 2002
As its title suggests, this chapter covers a broad range of interactive systems. But they all have one idea in common: that it can be worthwhile for a system to learn something about each individual…
Beyond Similarity
- Computer Science
- 2000
This work proposes techniques that bring modest amounts of task-specific knowledge to bear in order to perform lexical transformations on the queries these systems perform, thereby ensuring they retrieve not similar documents, but documents that are relevant and useful in purposeful and interesting ways.
Designing for augmented attention: Towards a framework for attentive user interfaces
- Computer ScienceComput. Hum. Behav.
- 2006
Implicit feedback for inferring user preference: a bibliography
- Computer ScienceSIGF
- 2003
Traditional relevance feedback methods require that users explicitly give feedback by specifying keywords, selecting and marking documents, or answering questions about their interests, which can be difficult to collect the necessary data and the effectiveness of explicit techniques can be limited.
Conversing with the user based on eye-gaze patterns
- Computer ScienceCHI
- 2005
It is demonstrated that eye-gaze could play an important role in managing future multimodal human-computer dialogues.
References
SHOWING 1-10 OF 50 REFERENCES
How to personalize the Web
- Computer ScienceCHI
- 1997
Web Browser Intelligence (WBI, pronounced “WEB-ee”) is an implemented system that organizes agents on a user’s workstation to observe user actions, proactively offer assistance, modify web documents, and perform new functions.
Letizia: An Agent That Assists Web Browsing
- Computer ScienceIJCAI
- 1995
Letizia is a user interface agent that assists a user browsing the World Wide Web by automates a browsing strategy consisting of a best-first search augmented by heuristics inferring user interest from browsing behavior.
COACH: a teaching agent that learns
- Computer ScienceCACM
- 1994
The adaptive teaching scenario works to keep this type of programmer oricntcd by providing context-sensitive help and user examples.
The Lumière Project: Bayesian User Modeling for Inferring the Goals and Needs of Software Users
- Computer ScienceUAI
- 1998
This work reviews work on Bayesian user models that can be employed to infer a user's needs by considering a users' background, actions, and queries and proposes an overall architecture for an intelligent user interface.
Inferring Informational Goals from Free-Text Queries: A Bayesian Approach
- Computer ScienceUAI
- 1998
A Bayesian approach to modeling the relationship between words in a user's query for assistance and the informational goals of the user is described and several extensions that center on integrating additional distinctions and structure about language usage and user goals into the Bayesian models are described.
Building user and expert models by long-term observation of application usage
- Computer Science
- 1999
A new type of user model and a new kind of expert model are described and it is shown how these models can be used to individualize the selection of instructional topics.
Remembrance Agent: A continuously running automated information retrieval system
- Computer Science, Biology
- 1996
The Remembrance Agent is a program which augments human memory by displaying a list of documents which might be relevant to the user’s current context by allowing a user to pursue or ignore the RA's suggestions as desired.
A gaze-responsive self-disclosing display
- Computer ScienceCHI '90
- 1990
An information display system is described which uses eye-tracking to monitor user looking about its graphics screen. The system analyzes the user's patterns of eye movements and fixations in…
Autonomous interface agents
- Computer ScienceCHI
- 1997
This work explores some design principles for autonomous interface agents, and illustrates these principles with a description of Letizia, an autonomous interface agent that makes real-time suggestions for Web pages that a user might be interested in browsing.