Context-based page unit recommendation for web-basedsensemaking tasks

ABSTRACT

Sensemaking tasks require users to perform complex research behaviors to gather and comprehend information from many sources. Such tasks are common and include, for example, researching vacation destinations or deciding how to invest. In this paper, we present an algorithm and interface that 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. Each web page visited by a user is dynamically analyzed to determine the most relevant content fragments which are then recommended to the user. Our initial evaluations indicate that our approach improves user performance.

REFERENCES

• 1: Sergey Brin , Lawrence Page, The anatomy of a large-scale hypertextual Web search engine, Proceedings of the seventh international conference on World Wide Web 7, p.107-117, April 1998, Brisbane, Australia
• 2: David Gotz, The ScratchPad: sensemaking support for the web, Proceedings of the 16th international conference on World Wide Web, May 08-12, 2007, Banff, Alberta, Canada [doi>10.1145/1242572.1242834]
• 3: Ard W. Lazonder , Harm J. A. Biemans , Iwan G. J. H. Wopereis, Differences between novice and experienced users in searching information on the World Wide Web, Journal of the American Society for Information Science, v.51 n.6, p.576-581, April 2000 [doi>10.1002/(SICI)1097-4571(2000)51:6<576::AID-ASI9>3.0.CO;2-7]
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INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.3 Information Search and Retrieval
          Subjects: Relevance feedback

Additional Classification:
  H. Information Systems
  H.4 INFORMATION SYSTEMS APPLICATIONS
      H.4.3 Communications Applications
          Subjects: Information browsers

General Terms:
Algorithms, Design, Human Factors

Keywords:
recommendation, search, sensemaking, www