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Understanding temporal query dynamics

Kulkarni, Anagha, Teevan, Jaime, Svore, Krysta M., Dumais, Susan T.·2011·Proceedings of the fourth ACM international conference on Web search and data mining

Abstract

Web search is strongly influenced by time. The queries people issue change over time, with some queries occasionally spiking in popularity (e.g., earthquake) and others remaining relatively constant (e.g., youtube). The documents indexed by the search engine also change, with some documents always being about a particular query (e.g., the Wikipedia page on earthquakes is about the query earthquake) and others being about the query only at a particular point in time (e.g., the New York Times is only about earthquakes following a major seismic activity). The relationship between documents and queries can also change as people's intent changes (e.g., people sought different content for the query earthquake before the Haitian earthquake than they did after). In this paper, we explore how queries, their associated documents, and the query intent change over the course of 10 weeks by analyzing query log data, a daily Web crawl, and periodic human relevance judgments. We identify several interesting features by which changes to query popularity can be classified, and show that presence of these features, when accompanied by changes in result content, can be a good indicator of change in query intent.

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Research works printed but not linked: 28

  1. 10.1145/1498759.1498837 · DOI
  2. 10.1145/1518701.1518909 · DOI
  3. 10.1145/1242572.1242595 · DOI
  4. 10.5555/1699648.1699650 · DOI
  5. 10.1145/1148170.1148273 · DOI · Paper page
  6. 10.1145/1008992.1009048 · DOI
  7. Beyer , H. and Holtzblatt , K . Contextual Design: Defining Customer-Centered Systems . Academic Press , 1998 . Beyer, H. and Holtzblatt, K. Contextual Design: Defining Customer-Centered Systems. Academic Press, 1998.
  8. 10.1145/1060745.1060752 · DOI
  9. 10.1145/1066157.1066220 · DOI · Paper page
  10. 10.1145/1458082.1458320 · DOI
  11. 10.1145/1498759.1498825 · DOI
  12. 10.1145/1008992.1008998 · DOI
  13. 10.1145/1718487.1718490 · DOI
  14. 10.1145/1242572.1242651 · DOI
  15. 10.1002/asi.v61:7 · DOI
  16. 10.1145/1718487.1718489 · DOI · Paper page
  17. 10.1145/775152.775246 · DOI · Paper page
  18. 10.1038/nature07634 · DOI · Paper page
  19. 10.1145/1247715.1247720 · DOI · Paper page
  20. 10.1145/775047.775061 · DOI
  21. Kleinberg , J. Temporal dynamics of on-line information systems . In Data Stream Management: Processing High-Speed Data . Springer , 2006 . Kleinberg, J. Temporal dynamics of on-line information systems. In Data Stream Management: Processing High-Speed Data. Springer, 2006.
  22. 10.1145/956863.956951 · DOI · Paper page
  23. 10.1145/988672.988674 · DOI
  24. 10.1145/1367497.1367557 · DOI
  25. 10.1145/1390334.1390364 · DOI
  26. 10.1145/1007568.1007586 · DOI
  27. 10.1002/asi.10262 · DOI
  28. 10.5555/1620853.1620899 · DOI

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Metadata

Authors
Kulkarni, A., Teevan, J., Svore, K. M., & Dumais, S. T.
Affiliations
  • Carnegie Mellon University, Pittsburgh, PA, USA
  • Microsoft Research, Redmond, WA, USA
Venue
Proceedings of the fourth ACM international conference on Web search and data mining
Publisher
ACM
Published
2011-02-09
Pages
167-176
Cited by
94
References
0

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