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Context-based page unit recommendation for web-based sensemaking tasks
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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: Intelligent web systems table of contents
Pages 107-116  
Year of Publication: 2009
ISBN:978-1-60558-168-2
Authors
Wen-Huang Cheng  National Taiwan University, Taipei, Taiwan Roc
David Gotz  IBM T.J. Watson Research Center, Hawthorne, NY, USA
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

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.


REFERENCES

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Collaborative Colleagues:
Wen-Huang Cheng: colleagues
David Gotz: colleagues