Leveraging temporal dynamics of document content in relevance ranking

ABSTRACT

Many web documents are dynamic, with content changing in varying amounts at varying frequencies. However, current document search algorithms have a static view of the document content, with only a single version of the document in the index at any point in time. In this paper, we present the first published analysis of using the temporal dynamics of document content to improve relevance ranking. We show that there is a strong relationship between the amount and frequency of content change and relevance. We develop a novel probabilistic document ranking algorithm that allows differential weighting of terms based on their temporal characteristics. By leveraging such content dynamics we show significant performance improvements for navigational queries.

References

1. E. Adar, M. Dontcheva, J. Fogarty, and D.S. Weld. Zoetrope: Interacting with the ephemeral web. In UIST '08: Proceedings of the 21st Annual ACM Symposium on User Interface Software and Technology, pages 239--248, New York, NY, USA, 2008. ACM.
2. E. Adar, J. Teevan, and S.T. Dumais. Resonance on the web: Web dynamics and revisitation patterns. In CHI '09: Proceedings of the 27th International Conference on Human Factors in Computing Systems, pages 1381--1390, New York, NY, USA, 2009. ACM.
3. E. Adar, J. Teevan, S.T. Dumais, and J.L. Elsas. The web changes everything: Understanding the dynamics of web content. In WSDM '09: Proceedings of the Second ACM International Conference on Web Search and Data Mining, pages 282--291, New York, NY, USA, 2009. ACM.
4. O. Alonso and M. Gertz. Clustering of search results using temporal attributes. In SIGIR '06: Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 597--598, New York, NY, USA, 2006. ACM.
5. P. Anick and R. Flynn. Versioning a full-text information retrieval system. In SIGIR '92: Proceedings of the 15th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 98--111, New York, NY, USA, 1992. ACM.
6. K. Berberich, S. Bedathur, T. Neumann, and G. Weikum. A time machine for text search. In SIGIR '07: Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 519--526, New York, NY, USA, 2007. ACM.
7. A.Z. Broder, S.C. Glassman, M.S. Manasse, and G. Zweig. Syntactic clustering of the web. Computer Networks and ISDN Systems, 29(8-13):1157--1166, 1997.
8. J. Cho, S. Roy, and R.E. Adams. Page quality: In search of an unbiased web ranking. In SIGMOD '05: Proceedings of the 2005 ACM SIGMOD International Conference on Management of Data, pages 551--562, New York, NY, USA, 2005. ACM.
9. F. Diaz and R. Jones. Using temporal profiles of queries for precision prediction. In SIGIR '04: Proceedings of the 27th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 18--24, New York, NY, USA, 2004. ACM.
10. D. Fetterly, M. Manasse, M. Najork, and J. Wiener. A large-scale study of the evolution of web pages. In WWW '03: Proceedings of the 12th International Conference on World Wide Web, pages 669--678, New York, NY, USA, 2003. ACM.
11. M. Herscovici, R. Lempel, and S. Yogev. Efficient indexing of versioned document sequences. Lecture Notes in Computer Science, 4425:76--87, 2007.
12. K. Järvelin and J. Kekäläinen. Cumulated gain-based evaluation of ir techniques. ACM Transactions on Information Systems (TOIS), 20(4):422--446, 2002.
13. A. Jatowt, Y. Kawai, and K. Tanaka. Visualizing historical content of web pages. In WWW '08: Proceeding of the 17th International Conference on World Wide Web, pages 1221--1222, New York, NY, USA, 2008. ACM.
14. R. Jones and F. Diaz. Temporal profiles of queries. ACM Transactions on Information Systems (TOIS), 25(3):14, 2007.
15. U. Lee, Z. Liu, and J. Cho. Automatic identification of user goals in web search. In WWW '05: Proceedings of the 14th International Conference on World Wide Web, pages 391-400, New York, NY, USA, 2005. ACM.
16. X. Li and W.B. Croft. Time-based language models. In CIKM '03: Proceedings of the Twelfth International Conference on Information and Knowledge Management, pages 469--475, New York, NY, USA, 2003. ACM.
17. A. Ntoulas, J. Cho, and C. Olston. What's new on the web?: The evolution of the web from a search engine perspective. In WWW '04: Proceedings of the 13th International Conference on World Wide Web, pages 1--12, New York, NY, USA, 2004. ACM.
18. P. Ogilvie and J. Callan. Combining document representations for known-item search. In SIGIR '03: Proceedings of the 26th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 143--150, New York, NY, USA, 2003. ACM.
19. C. Olston and S. Pandey. Recrawl scheduling based on information longevity. In WWW '08: Proceeding of the 17th International Conference on World Wide Web, pages 437--446, New York, NY, USA, 2008. ACM.
20. C. Zhai and J. Lafferty. A study of smoothing methods for language models applied to information retrieval. ACM Transactions on Information Systems (TOIS), 22(2):179--214, 2004.
21. R. Zhang, Y. Chang, Z. Zheng, D. Metzler, and J.-y. Nie. Search result re-ranking by feedback control adjustment for time-sensitive query. In NAACL '09: Proceedings of the 2009 Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Short Papers, pages 165--168, Morristown, NJ, USA, 2009. Association for Computational Linguistics.

Index Terms

• Information systems

  • Information retrieval

    • Retrieval models and ranking