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Using annotations in enterprise search

Published: 23 May 2006 Publication History

Abstract

A major difference between corporate intranets and the Internet is that in intranets the barrier for users to create web pages is much higher. This limits the amount and quality of anchor text, one of the major factors used by Internet search engines, making intranet search more difficult. The social phenomenon at play also means that spam is relatively rare. Both on the Internet and in intranets, users are often willing to cooperate with the search engine in improving the search experience. These characteristics naturally lead to considering using user feedback to improve search quality in intranets. In this paper we show how a particular form of feedback, namely user annotations, can be used to improve the quality of intranet search. An annotation is a short description of the contents of a web page, which can be considered a substitute for anchor text. We propose two ways to obtain user annotations, using explicit and implicit feedback, and show how they can be integrated into a search engine. Preliminary experiments on the IBM intranet demonstrate that using annotations improves the search quality.

References

[1]
Anchor text optimization. www.seo-gold.com/tutorial/anchor-text-optimization.html
[2]
Google enterprise solutions. http://www.google.com/enterprise/http://www.google.com/enterprise/.
[3]
IBM OmniFind solution for enterprise search. http://www-306.ibm.com/software/data/integration/db2ii/editions_womnifind.html
[4]
NCSA mosaic: Annotations overview. http://archive.ncsa.uiuc.edu/SDG/Software/XMosaic/Annotations/overview.html
[5]
Panoptic enterprise search engine. http://www.panopticsearch.comhttp://www.panopticsearch.com.
[6]
StumbleUpon. http://www.stumbleupon.comhttp://www.stumbleupon.com.
[7]
Verity enterprise search solution. http://www.verity.com/products/search/enterprise_web_search/index.html
[8]
Yahoo! MyWeb 2.0 BETA. http://myweb2.search.yahoo.com/
[9]
Sergey Brin and Lawrence Page. The anatomy of a large-scale hypertextual web search engine. In Proc. Proc. 7th World Wide Web Conference, Brisbane, Australia, 1998, pages 107--117, 1998.
[10]
Vannevar Bush. As we may think. In The Atlantic Monthly, July 1945.
[11]
Junghoo Cho and Sourashis Roy. Impact of search engines on page popularity. In Proc. 13th World Wide Web Conference, pages 20--29, May 2004.
[12]
Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein. Introduction to Algorithms. The MIT Press, Cambridge, MA, 2003.
[13]
Laurent Denoue and Laurence Vignollet. New ways of using web annotations. In Proc. 9th World Wide Web Conference, Amsterdam, 2000.
[14]
Nadav Eiron and Kevin S. McCurley. Analysis of anchor text for web search. In Proc. 26th ACM Conference on Research and Development in Information Retrieval, pages 459--460, 2003.
[15]
Ronald Fagin, Ravi Kumar, Kevin S. McCurley, Jasmine Novak, D. Sivakumar, John A. Tomlin, and David P. Williamson. Searching the workplace web. In Proc. 12th World Wide Web Conference, Budapest, Hungary, 2003.
[16]
Susan Feldman and Chris Sherman. The high cost of not finding information. In IDC Technical Report 29127, 2003.
[17]
Marcus Fontoura, Eugene J. Shekita, Jason Y. Zien, Sridhar Rajagopalan, and Andreas Neumann. High performance index build algorithms for intranet search engines. In VLDB, pages 1158--1169, 2004.
[18]
David Hawking. Challenges in enterprise search. In Fifteenth Australian Database Conference, Dunedin, NZ, 2004.
[19]
Thorsten Joachims. Optimizing search engines using clickthrough data. In Proc. 8th ACM Conference on Knowledge Discovery and Data Mining, Alberta, Canada, 2002.
[20]
Thorsten Joachims, Dayne Freitag, and Tom Mitchell. Webwatcher: A tour guide for the world wide web. In Proc. International Joint Conference on Artificial Intelligence, Nagoya, Japan, 1997.
[21]
Thorsten Joachims, Laura Granka, Bing Pang, Helene Hembrooke, and Geri Gay. Accurately interpreting clickthrough data as implicit feedback. In Proc. 28th ACM Conference on Research and Development in Information Retrieval, Salvador, Brazil, 2005.
[22]
Charles Kemp and Kotagiri Ramamohanarao. Long-time learning for web search engines. In Proc. 6th European Conference on Principles and Practice of Knowledge Discovery in Databases, Helsinki, Finland, 2002.
[23]
Hannes Marais and Krishna Bharat. Supporting cooperative and personal surfing with a desktop assistant. In 10th annual ACM symposium on User Interface Software and Technology, Banff, Alberta, Canada, 1997.
[24]
Lawrence Page, Sergey Brin, Rajeev Motwani, and Terry Winograd. The PageRank citation ranking: Bringing order to the web. Technical report, Stanford Digital Library Technologies Project, 1998. Paper SIDL-WP-1999-0120 (version of 11/11/1999).
[25]
Filip Radlinski and Thorsten Joachims. Query chains: Learning to rank from implicit feedback. In Proc. 11th ACM Conference on Knowledge Discovery and Data Mining, Chicago, IL, USA, 2005.
[26]
Robert Sedgewick. Algorithms in C++. Addison-Wesley Publishing Company, Boston, MA, 1998.
[27]
Venu Vasudevan and Mark Palmer. On web annotations: Promises and pitfalls of current web infrastructure. In 32nd Hawaii International Conference on Systems Sciences, Maui, Hawaii, 1999.
[28]
Vishwa Vinay, Ken Wood, Natasa Milic-Frayling, and Ingemar J. Cox. Comparing relevance feedback algorithms for web search. In Proc. 14th World Wide Web Conference, Chiba, Japan, 2005.
[29]
I. Witten, A. Moffat, and T. Bell. Managing Gigabytes. Morgan Kaufmann, 1999.

Cited By

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  • (2018)Enterprise Search: A New Dimension in Information Retrieval2018 3rd International Conference for Convergence in Technology (I2CT)10.1109/I2CT.2018.8529602(1-6)Online publication date: Apr-2018
  • (2018)Social SearchSocial Information Access10.1007/978-3-319-90092-6_7(213-276)Online publication date: 3-May-2018
  • (2016)Social networks and information retrieval, how are they converging? A survey, a taxonomy and an analysis of social information retrieval approaches and platformsInformation Systems10.1016/j.is.2015.07.00856:C(1-18)Online publication date: 1-Mar-2016
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    cover image ACM Conferences
    WWW '06: Proceedings of the 15th international conference on World Wide Web
    May 2006
    1102 pages
    ISBN:1595933239
    DOI:10.1145/1135777
    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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    Publication History

    Published: 23 May 2006

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    Author Tags

    1. anchortext
    2. community ranking
    3. enterprise search

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    View all
    • (2018)Enterprise Search: A New Dimension in Information Retrieval2018 3rd International Conference for Convergence in Technology (I2CT)10.1109/I2CT.2018.8529602(1-6)Online publication date: Apr-2018
    • (2018)Social SearchSocial Information Access10.1007/978-3-319-90092-6_7(213-276)Online publication date: 3-May-2018
    • (2016)Social networks and information retrieval, how are they converging? A survey, a taxonomy and an analysis of social information retrieval approaches and platformsInformation Systems10.1016/j.is.2015.07.00856:C(1-18)Online publication date: 1-Mar-2016
    • (2014)Personalized tag recommendation based on generalized rulesACM Transactions on Intelligent Systems and Technology10.1145/2542182.25421945:1(1-22)Online publication date: 3-Jan-2014
    • (2014)Standing on the schemas of giantsProceedings of the 17th ACM conference on Computer supported cooperative work & social computing10.1145/2531602.2531644(999-1010)Online publication date: 15-Feb-2014
    • (2014)Improved Corporate Search Engine for the National (Australian) Spatial Information Management System: Case StudyINCOSE International Symposium10.1002/j.2334-5837.2009.tb01037.x19:1(1591-1608)Online publication date: 4-Nov-2014
    • (2014)4.1.1 A Case Study of the Effects of Platform Software Selection on Information System Maintenance Cost ‐ An Example of Enterprise Search System Establishment ‐INCOSE International Symposium10.1002/j.2334-5837.2009.tb00970.x19:1(593-606)Online publication date: 4-Nov-2014
    • (2013)LAICOSProceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining10.1145/2487575.2487705(1446-1449)Online publication date: 11-Aug-2013
    • (2013)SopraProceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval10.1145/2484028.2484131(861-864)Online publication date: 28-Jul-2013
    • (2013)Using social annotations to enhance document representation for personalized searchProceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval10.1145/2484028.2484130(1049-1052)Online publication date: 28-Jul-2013
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