Identification of ambiguous queries in web search

Information Processing and Management

Volumn 45, Issue 2, 2009, Pages 216-229

  Song, Ruihua ^a,b   Luo, Zhenxiao ^c   Nie, Jian Yun ^d   Yu, Yong ^a   Hon, Hsiao Wuen ^b  

^a SHANGHAI JIAO TONG UNIVERSITY   (China)

^b MICROSOFT RESEARCH ASIA   (China)

^c FUDAN UNIVERSITY   (China)

^d UNIVERSITÉ DE MONTRÉAL   (Canada)

Author keywords

Ambiguous query; Broad topics; Query classification; Query taxonomy

Indexed keywords

INFORMATION RETRIEVAL; SEARCH ENGINES; TAXONOMIES;

AMBIGUOUS QUERY; BROAD TOPICS; QUERY CLASSIFICATION; QUERY TAXONOMY; WEB SEARCHES;

WORLD WIDE WEB;

EID: 60549101677     PISSN: 03064573     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ipm.2008.09.005     Document Type: Article

References (34)

1. Broder, A. (2002). A taxonomy of web search. In Proceedings of the 25th ACM conference on research in information retrieval (SIGIR) forum (Vol. 36, no. 2).
2. Carmel, D., Yom-Tov, E., Darlow, A., & Pelleg, D. (2006). What makes a query difficult? In Proceedings of the 29th ACM conference on research in information retrieval (SIGIR).
3. Chen, H., & Karger, D. R. (2006). Less is more: Probabilistic models for retrieving fewer relevant documents. In Proceedings of the 29th ACM conference on research in information retrieval (SIGIR).
4. Chirita, P.-A., Nejdl, W., Paiu, R., & Kohlschütter, C. (2005). Using ODP metadata to personalize search. In Proceedings of the 28th ACM conference on research in information retrieval (SIGIR).
5. Cohen J. A coefficient of agreement for nominal scales. Educational and Psychological Measurement 20 1 (1960) 37-46
6. Cronen-Townsend, S., Zhou, Y., & Croft, W. B. (2002). Predicting query performance. In Proceedings of the 25th ACM conference on research in information retrieval (SIGIR) (pp. 299-306).
7. Dai, H. K., Nie, Z., Wang, L., Zhao, L., Wen, J.-R., & Li, Y. (2006). Detecting Online commercial intention (OCI). In Proceedings of the 15th international world wide web conference.
8. Evans, D. A., Shanahan, J. G., & Sheftel, V. (2002). Topic structure modeling. In Proceedings of the 25th ACM conference on research in information retrieval (SIGIR) (pp. 417-418).
9. Fleiss J.L. Measuring nominal scale agreement among many raters. Psychological Bulletin 76 5 (1971) 378-382
10. Fleiss J.L., and Cohen J. The equivalence of weighted kappa and the intraclass correlation coefficient as measures of reliability. Educational and Psychological Measurement 33 (1973) 613-619
11. Harman, D., & Buckley, C. (2004). The NRRC reliable information access (RIA) workshop. In Proceedings of the 27th ACM conference on research in information retrieval (SIGIR). (pp. 528-529).
12. Haveliwala, T. (2002). Topic-sensitive pagerank. In Proceedings of the 11th international world wide web conference. Honolulu, Hawaii.
13. Hearst, M. A., & Pedersen, J. O. (1996). Reexamining the cluster hypothesis: Scatter/gather on retrieval results. In Proceedings of the 19th ACM conference on research in information retrieval.
14. Kang, I.-H., & Kim, G. (2003). Query type classification for Web document retrieval. In Proceedings of the 26th ACM conference on research in information retrieval (SIGIR).
15. Lawrie, D., & Croft, W. B. (2000). Discovering and comparing topic hierarchies. In Proceedings of RIAO 2000 conference (pp. 314-330).
16. Lee, U., Liu, Z., & Cho, J. (2005). Automatic identification of user goals in web search. In Proceedings of the 14th international world wide web conference.
17. Leouski, A. V., & Croft, W. B. (1996). An evaluation of techniques for clustering search results. Technical report IR-76, University of Massachusetts, Amherst.
18. Li Y., Zhang Z., and Dai H.K. KDD CUP-2005 report: Facing a great challenge. SIGKDD Explorations 7 2 (2005) 91-99
19. Lin J. Divergence measures based on the Shannon entropy. IEEE Transactions on Information Theory 37 1 (1991) 145-151
20. MacQueen, J. B. (1967). Some methods for classification and analysis of multivariate observations, In Proceedings of the fifth Berkeley symposium on mathematical statistics and probability (Vol. 1, pp. 281-297). Berkeley, University of California Press.
21. Mihalcea, R., & Pedersen, T. (2005). Advances in word sense disambiguation. In Tutorial at the 20th national conference on artificial intelligence.
22. Mothe, J., & Tanguy, L. (2005). Linguistic features to predict query difficulty. In Proceedings of the 28th ACM conference on research in information retrieval (SIGIR) workshop on predicting query difficulty - Methods and applications.
23. Page, L., Brin, S., Motwani, R., & Winograd, T. (1998). The pagerank citation ranking: Brining order to the web. Technical report, Stanford Digital Library Technologies Project.
24. Platt J.C. Fast training of support vector machines using sequential minimal optimization. In: Schölkopf B., Burges C.J., and Smola A.J. (Eds). Advanced in kernel methods - Support vector learning (1998), MIT Press
25. Rose, D. E., & Levinson, D. (2004). Understanding user goals in web search. In Proceedings of the 13th international world wide web conference.
26. Sanderson, M., & Croft, W. B. (1999). Deriving concept hierarchies from text. In Proceedings of the 22nd ACM conference on research in information retrieval (SIGIR) (pp. 206-213).
27. Shen D., Pan R., Sun J.-T., Pan J.J., Wu K., Yin J., and Yang Q. Q2c@ust: Our winning solution to query classification in KDDCUP 2005. SIGKDD Explorations 7 2 (2005) 100-110
28. Song, R., Wen, J.-R., Shi, S., Xin, G., Liu, T.-Y., Qin, T., et al. (2004). Microsoft research asia at web track and terabyte track of TREC 2004. In Proceedings of text retrieval conference 2004.
29. Sugiyama, K., Hatano, K., & Yoshikawa, M. (2004). Adaptive Web search based on user profile constructed without any effort from users. In Proceedings of the 13th international world wide web conference.
30. Vapnik V. Principles of risk minimization for learning theory. In: Lippman D.S., Moody J.E., and Touretzky D.S. (Eds). Advances in neural information processing systems Vol. 3 (1992), Morgan Kaufmann 831-838
31. Yang Y. An evaluation of statistical approaches to text categorization. Journal of Information Retrieval 1 1/2 (1999) 67-88
32. Yom-Tov, E., Fine, S., Carmel, D., & Darlow, A. (2005). Learning to estimate query difficulty: Including applications to missing content detection and distributed information retrieval. In Proceedings of the 28th ACM conference on research in information retrieval (SIGIR) (pp. 512-519).
33. Zeng, H.-J., He, Q.-C., Chen, Z., Ma, W.-Y., & Ma, J. (2004). Learning to cluster web search results. In Proceedings of the 27th ACM conference on research in information retrieval (SIGIR). (pp. 210-217).
34. Zhai, C., Cohen, W. W., & Lafferty, J. (2003). Beyond independent relevance: Methods and evaluation metrics for subtopic retrieval. In Proceedings of the 26th ACM conference on research in information retrieval (SIGIR) (pp. 10-17).