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David Leake

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Personal Homepage:
http://www.cs.indiana.edu/~leake
Current place of employment:
Indiana University

David B. Leake is a Full Professor and the Director of Graduate Studies for the Computer Science Department at Indiana University. He is also a member of the university's Cognitive Science Program faculty and the faculty of the Human-Computer Interaction Program of the School of Informatics. His research interests include intelligent user interfaces, case-based reasoning, explanation, knowledge management, and introspective reasoning. He has published over 100 research publications. He is the author of Evaluating Explanations: A Content Theory (Erlbaum, 1992), co-editor of Goal-Driven Learning (MIT Press/Bradford Books, 1995), and editor of Case-Based Reasoning: Experiences, Lessons, and Future Directions (AAAI Press, 1996). He Chaired the Seventh International Conference on Intellint User Interfaces (IUI-03) and is the Editor of AI Magazine. - July 2005

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Publications by David Leake (bibliography)

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» 2002 «

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Gil, Yolanda and Leake, David (eds.) International Conference on Intelligent User Interfaces 2002 January 13-16, 2002, San Francisco, California, USA.

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Bauer, Travis and Leake, David (2002): Exploiting information access patterns for context-based retrieval. In: Gil, Yolanda and Leake, David (eds.) International Conference on Intelligent User Interfaces 2002 January 13-16, 2002, San Francisco, California, USA. pp. 176-177. Available online

In order for intelligent interfaces to provide proactive assistance, they must customize their behavior based on the user's task context. Existing systems often assess context based on a single snapshot of the user's current activities (e. g., examining the content of the document that the user is currently consulting). However, an accurate picture of the user's context may depend not only on this local information, but also on information about the user's behavior over time. This paper discusses work on a recommender system, Calvin, which learns to identify broader contexts by relating documents that tend to be accessed together. Calvin's text analysis algorithm, WordSieve, develops term vector descriptions of these contexts in real time, without needing to accumulate comprehensive statistics about an entire corpus. Calvin uses these descriptions (1) to index documents to suggest them in similar future contexts and (2) to formulate contextbased queries for search engines. Results of initial experiments are encouraging for the approach's improved ability to associate documents with the research tasks in which they were consulted, compared to methods using only local information. This paper sketches the project goals, the current implementation of the system, and plans for its continued development and evaluation.

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Leake, David, Birnbaum, Larry, Hammond, Kristian J., Marlow, Cameron and Yang, Hao (2001): An Integrated Interface for Proactive, Experience-Based Design Support. In: International Conference on Intelligent User Interfaces 2001 January 14-17, 2001, Sanata Fe, New Mexico, USA. pp. 101-108. Available online

Many case-based reasoning systems have been developed to aid designers by providing them with libraries of prior design experiences. Traditionally, these systems are implemented as stand-alone "external memories" for the designer to query manually. This paper presents a contrasting approach that integrates proactive case retrieval into the designer's normal task processes, automatically tailoring information selection and presentation emphasis to fit changing designer needs and attention flow. The paper presents a set of principles for this integrated intelligent design support and describes their application in the Stamping Advisor, a system to support design feasibility analysis for sheet metal automotive parts. The Stamping Advisor interface proactively provides designers with relevant information to support feasibility analysis, automatically prepares their information products, and unobtrusively gathers the information needed to generate new cases to improve the quality of future support.

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Leake, David and Scherle, Ryan (2001): Towards Context-Based Search Engine Selection. In: International Conference on Intelligent User Interfaces 2001 January 14-17, 2001, Sanata Fe, New Mexico, USA. pp. 109-112. Available online

A well-known problem for web search is targeting search on information that satisfies users' information needs. User queries tend to be short, and hence often ambiguous, which can lead to inappropriate results from general-purpose search engines. This has led to a number of methods for narrowing queries by adding information. This paper presents an alternative approach that aims to improve query results by using knowledge of a user's current activities to select search engines relevant to their information needs, exploiting the proliferation of high-quality special-purpose search services. The paper introduces the PRISM source selection system and describes its approach. It then describes two initial experiments testing the system's methods.

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Changes to this page (author)

25 Feb 2010: Enabled abstracts to be shown on David Leake's author page.
28 Apr 2003: Added the author to the bibliography

Publication statistics

Publication period:2001-2002
Publication count:4
Number of co-authors:7



Productive colleagues

David Leake's 3 most productive colleagues in number of publications:

Kristian J. Hammond:31
Larry Birnbaum:16
Yolanda Gil:14


Collaboration count

Number of publications with 3 favourite co-authors:

Hao Yang:1
Ryan Scherle:1
Cameron Marlow:1

 

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Mar 20

Computer programs emerge as the outcome of complex human processes of cognition, communication and negotiation, which serve to establish the meaningful embedding of the computer system in its intended use context.

-- Floyd, 1992, p. 24

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