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An interactive, smart notepad for context-sensitive information seeking
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International Conference on Intelligent User Interfaces archive
Proceedings of the 13th international conference on Intelligent user interfaces table of contents
Sanibel Island, Florida, USA
SESSION: Information & knowledge management table of contents
Pages 127-136  
Year of Publication: 2009
ISBN:978-1-60558-168-2
Authors
Jie Lu  IBM T.J. Watson Research Center, Hawthorne, NY, USA
Michelle X. Zhou  IBM China Research Lab, Beijing, China
Sponsors
SIGCHI: ACM Special Interest Group on Computer-Human Interaction
ACM: Association for Computing Machinery
SIGART: ACM Special Interest Group on Artificial Intelligence
Publisher
ACM  New York, NY, USA
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ABSTRACT

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.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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J. Budzik and K. Hammond. Watson: Anticipating and contextualizing information needs. In of AAIS' 99 pages 727--740.
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M. Speretta. Personalizing search based on user search histories. In CIKM '04.
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E. Voorhees and H. Tang. Overview of the TREC 2005 question answering track. In TREC '05.
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Collaborative Colleagues:
Jie Lu: colleagues
Michelle X. Zhou: colleagues