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Rants: a framework for rank editing and sharing in web search

Published: 26 April 2010 Publication History

Abstract

With a Wiki-like search interface, users can edit ranks of search results and share the edits with the rest of the world. This is an effective way of personalization, as well as a practice of mass collaboration that allows users to vote for ranking and improve search performance. Currently, there are several ongoing experimentation efforts from the industry, e.g., SearchWiki by Google and U Rank by Microsoft. Beyond that, there is little published research on this new search paradigm. In this paper, we make an effort to establish a framework for rank editing and sharing in the context of web search, where we identify fundamental issues and propose principled solutions. Comparing to existing systems, for rank editing, our framework allows users to specify not only relative, but also absolute preferences. For edit sharing, our framework provides enhanced flexibility, allowing users to select arbitrarily aggregated views. In addition, edits can be shared among similar queries. We present a prototype system Rants, that implements the framework and provides search services through the Google web search API.

References

[1]
Eurekster Swiki. http://www.eurekster.com.
[2]
Google Personalized Search. http://googleblog.blogspot.com/2007/02/personally-speaking.html.
[3]
Google SearchWiki. http://googleblog.blogspot.com/2008/11/searchwiki-make-search-your-own.html.
[4]
Google Social Search. http://googleblog.blogspot.com/2009/10/introducing-google-social-search-i.html.
[5]
Google Web Search API. http://code.google.com/.
[6]
Microsoft U Rank. http://research.microsoft.com/en-us/projects/urank/.
[7]
Rants. http://dmlab.cs.txstate.edu/rants.
[8]
Yahoo! Personalized Search. http://myweb.yahoo.com/.
[9]
W. Kruskal. Ordinal measures of association. Journal of the American Statistical Association, 53(284):814--861, 1958.

Cited By

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  • (2020)Personalization in text information retrievalJournal of the Association for Information Science and Technology10.1002/asi.2423471:3(349-369)Online publication date: 28-Jan-2020
  • (2011)A framework for personalized and collaborative clustering of search resultsProceedings of the 20th ACM international conference on Information and knowledge management10.1145/2063576.2063662(573-582)Online publication date: 24-Oct-2011

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    cover image ACM Other conferences
    WWW '10: Proceedings of the 19th international conference on World wide web
    April 2010
    1407 pages
    ISBN:9781605587998
    DOI:10.1145/1772690

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 26 April 2010

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    Author Tags

    1. edit sharing
    2. mass collaboration
    3. personalization
    4. rank editing
    5. search interface
    6. social search

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    WWW '10
    WWW '10: The 19th International World Wide Web Conference
    April 26 - 30, 2010
    North Carolina, Raleigh, USA

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    Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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    View all
    • (2020)Personalization in text information retrievalJournal of the Association for Information Science and Technology10.1002/asi.2423471:3(349-369)Online publication date: 28-Jan-2020
    • (2011)A framework for personalized and collaborative clustering of search resultsProceedings of the 20th ACM international conference on Information and knowledge management10.1145/2063576.2063662(573-582)Online publication date: 24-Oct-2011

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