Mining web query hierarchies from clickthrough data

Proceedings of the National Conference on Artificial Intelligence

Volumn 1, Issue , 2007, Pages 341-346

  Shen, Dou ^a   Qin, Min ^b   Chen, Weizhu ^c   Yang, Qiang ^a   Chen, Zheng ^c  

^a HONG KONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Hong Kong)

^b XI'AN JIAOTONG UNIVERSITY   (China)

^c MICROSOFT RESEARCH ASIA   (China)

Author keywords

[No Author keywords available]

Indexed keywords

HIERARCHICAL SYSTEMS; QUERY LANGUAGES; SEARCH ENGINES; USER INTERFACES; WEB SERVICES; WEBSITES;

AUTOMATIC ACQUISITION; CLICKTHROUGH DATA; MINING WEB QUERY HIERARCHIES; WEB QUERY;

ARTIFICIAL INTELLIGENCE;

EID: 36348989659     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (20)

1. Beeferman, D., and Berger, A. 2000. Agglomerative clustering of a search engine query log. In KDD '00, 407-416.
2. Bloehdorn, S., and Hotho, A. 2004. Text classification by boosting weak learners based on terms and concepts. In ICDM '04, 331-334.
3. Bloehdorn, S.; Cimiano, P.; and Hotho, A. March 9-11, 2005. Learning ontologies to improve text clustering and classification. In GfKl '05, 334-341.
4. Buitelaar, P.; Cimiano, P.; and Magnini, B., eds. 2005. Ontology Learning from Text: Methods, Evaluation and Applications, volume 123 of Frontiers in Artificial Intelligence and Applications Series. Amsterdam: IOS Press.
5. Buitelaar, P.; Olejnik, D.; and Sintek, M. 2004. A protégé plug-in for ontology extraction from text based on linguistic analysis. In ESWS '04.
6. Cimiano, P.; Hotho, A.; and Staab, S. 2005, Learning concept hierarchies from text corpora using formal concept analysis, Journal of Artificial Intelligence Research (JAIR) 24:305-339.
7. Fotzo, H. N., and Gallinari, P. 2004. Learning «generalization/ specialization» relations between concepts c application for automatically building thematic document hierarchies. In RIAO '04.
8. Gravano, L.; Hatzivassiloglou, V.; and Lichtenstein, R. 2003. Categorizing web queries according to geographical locality. In CIKM '03, 325-333.
9. Harris, Z. 1968. Mathematical Structures of Language. New York: Interscience Publishers John Wiley & Sons.
10. Hearst, M. A. 1992. Automatic acquisition of hyponyms from large text corpora. In ACL '92, 539-545. Morristown, NJ, USA: Association for Computational Linguistics.
11. Kang, I.-H., and Kim, G. 2003. Query type classification for web document retrieval. In SIGIR '03, 64-71.
12. Lee, U.; Liu, Z.; and Cho, J. 2005. Automatic identification of user goals in web search. In WWW '05, 391-400.
13. Manning, C. D.; Raghavan, P.; and Schüze, H. 2007. Introduction to Information Retrieval. Cambridge University Press.
14. Miller, G.; Beckwith, R.; Fellbaum, C.; Gross, D.; and Miller, K. 1990. Introduction to wordnet: an on-line lexical database. International Journal of Lexicography 3(4):23-244.
15. Paşca, M., and Durme, B. V. 2007. What you seek is what you get: Extraction of class attributes from query logs. In IJCAI '07, 2832-2837.
16. Pu, H.-T.; Chuang, S.-L.; and Yang, C. 2002. Subject categorization of query terms for exploring web users' search interests. J. Am. Soc. Inf. Sci. Technol. 53(8):617-630.
17. Sanderson, M., and Croft, B. 1999. Deriving concept hierarchies from text. In SIGIR '99, 206-213.
18. Shen, D.; Pan, R.; Sun, J.-T.; Pan, J. J.; Wu, K.; Yin, J.; and Yang, Q. 2006. Query enrichment for web-query classification. ACM Trans. Inf. Syst. 24(3):320-352.
19. Voorhees, E. M. 1994. Query expansion using lexical-semantic relations. In SIGIR '94, 61-69.
20. Wen, J.-R.; Nie, J.-Y.; and Zhang, H.-J. 2001. Query clustering using content words and user feedback. In SIGIR '01, 442-443.