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Confluence: enhancing contextual desktop search

Published:23 July 2007Publication History

ABSTRACT

We present Confluence, an enhancement to a desktop file search tool called Confluence which extracts conceptual relationships between files by their temporal access patterns in the file system. A limitation of a purely file-based approach is that as file operations are increasingly abstracted by applications, their correlation to a user's activity weakens and thereby reduces the applicability of their temporal patterns. To deal with this problem, we augment the file event stream with a stream of window focus events from the UI layer. We present 3 algorithms that analyze this new stream, extracting the user's task information which informs the existing Confluence algorithms. We present results and conclusions from a preliminary user study on Confluence.

References

  1. S. Dumais, E. Cutrell, J. Cadiz, G. Jancke, R. Sarin, and D. C. Robbins. Stuff I've seen: a system for personal information retrieval and re-use. In Proc. of SIGIR '03, pages 72--79, New York, NY, USA, 2003. ACM Press. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. D. Karger, K. Bakshi, D. Huynh, D. Quan, and V. Sinha. Haystack: A General Purpose Information Management Tool for End Users of Semistructured Data. In CIDR '05, pages 13--26, 2005.Google ScholarGoogle Scholar
  3. C. A. N. Soules and G. R. Ganger. Connections: using context to enhance file search. In Proc. of SOSP '05, pages 119--132, New York, NY, USA, 2005. ACM Press. Google ScholarGoogle ScholarDigital LibraryDigital Library

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    • Published in

      cover image ACM Conferences
      SIGIR '07: Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
      July 2007
      946 pages
      ISBN:9781595935977
      DOI:10.1145/1277741

      Copyright © 2007 ACM

      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 23 July 2007

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      Overall Acceptance Rate792of3,983submissions,20%

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