Classifying search queries using the Web as a source of knowledge

ACM Transactions on the Web

Volumn 3, Issue 2, 2009, Pages

  Gabrilovich, Evgeniy ^a   Broder, Andrei ^a   Fontoura, Marcus ^b   Joshi, Amruta ^c   Josifovski, Vanja ^a   Riedel, Lance ^a   Zhang, Tong ^d  

^a YAHOO RESEARCH   (United States)

^b PONTIFICAL CATHOLIC UNIVERSITY OF RIO DE JANEIRO   (Brazil)

^c Department of Civil and Environmental Engineering   (United States)

^d RUTGERS UNIVERSITY   (United States)

Author keywords

Pseudo relevance feedback; Query classification; Web search

Indexed keywords

CLASSIFICATION ACCURACY; EMPIRICAL EVALUATIONS; MACHINE-LEARNING; ONLINE ADS; PSEUDO RELEVANCE FEEDBACK; QUERY CLASS; QUERY CLASSIFICATION; REAL TIME; SEARCH QUERIES; USER EXPERIENCE; WEB SEARCH; WEB SEARCH ENGINES; WEB SEARCHES;

FEEDBACK; IMAGE RETRIEVAL; SEARCH ENGINES;

WORLD WIDE WEB;

EID: 70349742467     PISSN: 15591131     EISSN: 1559114X     Source Type: Journal    
DOI: 10.1145/1513876.1513877     Document Type: Conference Paper

References (38)

1. BEITZEL, S., JENSEN, E., CHOWDHURY, A., GROSSMAN,D., and FRIEDER, O. 2004. Hourly analysis of a very large topically categorized web query log. In Proceedings of the 27th Annual International
2. BEITZEL, S., JENSEN, E., FRIEDER,0., GROSSMAN, D., LEWIS, D., CHOWDHURY, A., AND KOLCZ, A. 2005a. Automatic web query classification using labeled and unlabeled training data. In Proceedings of the ACM Conference on Research and Development in Information Retrieval (SIGIR). ACM Press, 581-582.
3. BEITZEL, S., JENSEN, E., FRIEDER, O., LEWIS, D., CHOWDHURY, A., AND KOLCZ, A. 2005b. Improving automatic query classification via semi-supervised learning. In Proceedings of the 5th IEEE International Conference on Data Mining. IEEE Computer society.
4. BEITZEL, S. M., JENSEN,E.C., LEWIS,D.D., CHOWDHURY, A., AND FRIEDER, O. 2007. Automatic classification of web queries using very large unlabeled query logs. ACM Trans. Inform. Syst. 25, 1-29.
5. Broder, A., Ciccolo, P., Fontoura, M., Gabrilovich, E., Josifovski,V., and Riedel, L. 2008. Search advertising using Web relevance feedback. In Proceedings of the Conference on Information andKnowledge Management (CIKM).
6. BRODER, A., CICCOLO, P., GABRILOVICH, E., JOSIFOVSKI, V., METZLER, D., RIEDEL, L., AND YUAN, J. 2009. Online expansion of rare queries for sponsored search. In Proceedings of the 18th International World Wide Web Conference.
7. BRODER, A., FONTOURA, M., GABRILOVICH, E., JOSHI, A., JOSIFOVSKI,V., AND ZHANG, T. 2007. Robust classification of rare queries using web knowledge. In Proceedings of the 30th ACM International Conference on Research and Development in Information Retrieval. ACM Press
8. DUDA,R. AND HART, P. 1973. Pattern Classification and Scene Analysis. John Wiley and Sons, New York, NY.
9. EFTHIMIADIS,E. AND BIRON, P. 1994. UCLA-Okapi at TREC-2: Query expansion experiments. In Proceedings of the Text REtrieval Conference (TREC-2). National institute of standards and Technology (NIST).
10. GABRILOVICH,E. AND MARKOVITCH, S. 2007. Harnessing the expertise of 70,000 human editors: Knowledge-based feature generation for text categorization. J. Mach. Learn. Res. 8, 2297-2345.
11. Gates, S. C., Teiken,W., and Cheng, K.-S. F. 2005. Taxonomies by the numbers: building high- performance taxonomies. In Proceedings of the 14th ACM International Conference on Information and Knowledge Management (CIKM). ACM Press, 568-577.
12. GRAVANO, L., HATZIVASSILOGLOU,V., AND LICHTENSTEIN, R. 2003. Categorizing web queries according to geographical locality. in Proceedings of the 12th International Conference on Information and Knowledge Management (CIKM). ACM Press, 325-333.
13. HAN,E. AND KARYPIS, G. 2000. Centroid-based document classification: Analysis and experimental results. in Proceedings of the 4th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD). springer-verlag.
14. JARVELIN,K. AND KEKALAINEN, J. 2000. IR evaluation methods for retrieving highly relevant documents. in Proceedings of the ACM Conference and Research and Development in Information Retrieval (SIGIR). ACM Press.
15. JOACHIMS, T. 1998. Text categorization with support vector machines: Learning with many relevant features. In Proceedings of the European Conference on Machine Learning (ECML). 137-142.
16. KARDKOVACS, Z., TIKK,D., AND BANSAGHI, Z. 2005. The ferrety algorithm for the KDD Cup 2005 problem. In SIGKDD Explorations. Vol.7. ACM, 111-116.
17. KOWALCZYK, P., ZUKERMAN, I., AND NIEMANN, M. 2004. Analyzing the effect of query class on document retrieval performance. In Proceedings of the Australian Conference on Artificial Intelligence. springer, 550-561.
18. LI, Y., ZHENG, Z., AND DAI, H. 2005. KDD CUP-2005 report: Facing a great challenge. In SIGKDD Explorations. Vol.7. ACM, 91-99.
19. LU, Y., PENG, F., LI, X., AND AHMED, N. 2006. Coupling feature selection and machine learning methods for navigational query identification. In Proceedings of the 15th ACM International Conference on Information and Knowledge Management (CIKM). ACM Press, 682-689.
20. MANNING,C.D., RAGHAVAN,P., AND SCHUETZE, H. 2008. Introduction to Information Retrieval. Cambridge university Press.
21. MCCALLUM,A. AND NIGAM, K. 1998. A comparison of event models for naive Bayes text classification. In AAAI/ICML Workshop on Learning for Text Categorization. 41-48.
22. MITRA, M., SINGHAL, A., AND BUCKLEY, C. 1998. Improving automatic query expansion. In Proceedings of the 21st ACM International Conference on Research and Development in Information Retrieval (SIGIR). ACM Press, 206-214.
23. MORAN,M. AND HUNT, B. 2005. Search Engine Marketing, Inc.: Driving Search Traffic to Your Company's Web Site. Prentice Hall, Upper Saddle River, NJ.
24. ROBERTSON, S., WALKER, S., JONES, S., HANCOCK-BEAULIEU, M., AND GATFORD, M. 1995. Okapi at TREC-3. In Proceedings of the Text REtrieval Conference (TREC-3). NIST, Gaithersburg.
25. MD. ROCCHIO, J. 1971. Relevance feedback in information retrieval. In The SMART Retrieval System: Experiments in Automatic Document Processing. Prentice Hall, Englewood Cliffs, NJ, 313-323.
26. SAHAMI, M., MITTAL, V., BALUJA,S., AND ROWLEY, H. 2004. The happy searcher: Challenges in web information retrieval. In Proceedings of the 8th Pacific Rim International Conference on Artificial Intelligence. Springer-Verlag.
27. SALTON,G. AND BUCKLEY, C. 1988. Term weighting approaches in automatic text retrieval. Inform. Proc. Manag. 24, 5, 513-523.
28. Salton,G. and Buckley, C. 1990. Improving retrieval performance by relevance feedback. J. Am. Soc. Inform. Sci. 41, 4, 288-297.
29. Santner,T. and Duffy, D. 1989. The Statistical Analysis of Discrete Data. Springer-Verlag.
30. Sebastiani, F. 2002. Machine learning in automated text categorization. ACM Comput. Surv. 34, 1, 1-47.
31. SHEN, D., PAN, R., SUN, J., PAN, J., WU, K., YIN,J., AND YANG, Q. 2005. Q2C@UST: Our winning solution to query classification in KDDCUP 2005. In SIGKDD Explorations. Vol.7. ACM, Chicago, IL, USA, 100-110.
32. SHEN, D., PAN, R., SUN, J., PAN, J., WU, K., YIN,J., AND YANG, Q. 2006a. Query enrichment for web-query classification. ACM Trans. Info. Syst. 24, 320-352.
33. SHEN, D., SUN, J., YANG,Q., AND CHEN, Z. 2006b. Building bridges for web query classification. In Proceedings of the ACM International Conference on Research and Development in Information Retrieval (SIGIR). ACM Press, 131-138.
34. VOGEL, D., BICKEL, S., HAIDER, P., SCHIMPFKY, R., SIEMEN, P., BRIDGES,S., AND SCHEFFER, T. 2005. Classifying search engine queries using the web as background knowledge. In SIGKDD Explorations. Vol.7. ACM, 117-122.
35. VOORHEES, E. 1994. Query expansion using lexical-semantic relations. In Proceedings of the 17th ACM International Conference on Research and Development in Information Retrieval (SIGIR). Springer-Verlag, 61-69.
36. XU,J. AND CROFT, W. B. 2000. Improving the effectiveness of information retrieval with local context analysis. ACM Trans. Inform. Sys. 18, 1, 79-112.
37. YANG, Y. 1999. An evaluation of statistical approaches to text categorization. Inform. Retriev. J. 1, 69-90.
38. ZHANG,T. AND OLES, F. J. 2001. Text categorization based on regularized linear classification methods. Inform. Retriev. 4, 5-31.