Automatic text processing: the transformation, analysis, and retrieval of information by computer
Automatic text processing: the transformation, analysis, and retrieval of information by computer
The cost structure of sensemaking
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ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
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ACM Transactions on Computer-Human Interaction (TOCHI)
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CHI '05 Extended Abstracts on Human Factors in Computing Systems
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WWW '05 Special interest tracks and posters of the 14th international conference on World Wide Web
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Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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The ScratchPad: sensemaking support for the web
Proceedings of the 16th international conference on World Wide Web
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Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
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Remedy: supporting consumer-centered medication information search
Proceedings of the 7th International Conference on Pervasive Computing Technologies for Healthcare
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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.