Multi-term Web Query Expansion Using WordNet

  • Zhiguo Gong
  • Chan Wa Cheang
  • Leong Hou U
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4080)


In this paper, we propose a method for multi-term query expansions based on WordNet. In our approach, Hypernym/Hyponymy and Synonym relations in WordNet is used as the basic expansion rules. Then we use WordNet Lexical Chains and WordNet semantic similarity to assign terms in the same query into different groups with respect to their semantic similarities. For each group, we expand the highest terms in the WordNet hierarchies with Hypernym and Synonym, the lowest terms with Hyponym and Synonym, and all other terms with only Synonym. Furthermore, we use collection related term semantic network to remove the low-frequency and unusual words in the expansions. And our experiment reveals that our solution for query expansion can improve the query performance dramatically.


Semantic Similarity Average Precision Retrieval Performance Similarity Threshold Query Expansion 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Pedersem, T., Patwardhan, S., Michelizzi, J.: WordNet::Similarity – Measuring the Relatedness of Concept. In: Proc. of Fifth Annual Meeting of the North American Chapter of the ACL (NACCL 2004), Boston, MA (2004)Google Scholar
  2. 2.
  3. 3.
    Budanitsky, A., Hirst, G.: Semantic distance in WordNet: An experimental, application-oriented evaluation of five measures. In: NAACL Workshop on WordNet and Other Lexical Resources (2001)Google Scholar
  4. 4.
    Jiang, J.J., Conrath, D.W.: Semantic Similarity Based on Corpus Statistics and Lexical Taxonomy. In: The Proceedings of ROCLING X, Taiwan (1997)Google Scholar
  5. 5.
    Gong, Z., Cheang, C.W., U, L.H.: Web Query Expansion by WordNet. In: Andersen, K.V., Debenham, J., Wagner, R. (eds.) DEXA 2005. LNCS, vol. 3588, pp. 166–175. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  6. 6.
    Miller, G.A., Beckwith, R., Felbaum, C., Gross, D., Miller, K.: Introduction to WordNet: An On-line Lexicala Database, Revised Version (1993)Google Scholar
  7. 7.
    Gong, Z., U, L.H., Cheang, C.W.: An Implementation of Web Image Search Engines. In: Chen, Z., Chen, H., Miao, Q., Fu, Y., Fox, E., Lim, E.-p. (eds.) ICADL 2004. LNCS, vol. 3334, pp. 355–367. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  8. 8.
    Baeza-Yates, R., Ribeiro-Neto, B.: Modern Information Retrieval. Addison-Wesley, Reading (1999)Google Scholar
  9. 9.
    Sriari, R.K., Zhang, Z., Rao, A.: Intelligent indexing and semantic retrieval of multimodal documents. Information Retrieval 2(2), 1–37 (2000)Google Scholar
  10. 10.
    Cui, H., Wen, J.-R., Nie, J.-Y., Ma, W.-Y.: Query Expansion by Mining User Logs. IEEE Transactions on Knowledge and Data Engineering 15(4), 829–839 (2003)CrossRefGoogle Scholar
  11. 11.
    Gong, Z., U, L.H., Cheang, C.W.: Text-Based Semantic Extractions of Web Images. Knowledge and Information Systems: An International Journal, Springer (to appear)Google Scholar
  12. 12.
    Agrawaland, R., Srikant, R.: Fast Algorithms for Mining Association Rules. In: Proc. 20th Int’l. Conf. Very Large Data Bases (VLDB) (September 1994)Google Scholar
  13. 13.
    Voorhees, E.M.: Query Expansion using Lexical-Semantic Relations. In: Proceedings of the 17th ACM-SIGIR Conference, pp. 61–69 (1994)Google Scholar
  14. 14.
    Smeaton, A.F., Berrut, C.: Thresholding postings lists, query expansion by word-worddistance and POS tagging of Spanish text. In: Proceedings of the 4th Text Retrieval Conference (1996)Google Scholar
  15. 15.
    Kwon, O.-W., Kim, M.-C., Choi, K.-S.: Query Expansion Using Domain-Adapted Thesaurus in an Extended Boolean Model. In: Proceedings of ACM CIKM 1994, pp. 140–146 (1994)Google Scholar
  16. 16.
    Qiu, Y., Frei, H.P.: Concept Based Query Expansion. In: Proceedings of ACM-SIGIR 1993, pp. 160–169 (1993)Google Scholar
  17. 17.
    Xu, J., Croft, W.B.: Improving the Effectiveness of Information Retrieval with Local Context Analysis. ACM Transactions on Information Systems 18(1), 79–112 (2000)CrossRefGoogle Scholar
  18. 18.
    Bai, J., Song, D., Bruza, P., Nie, J.-y., Cao, G.: Query Expansion Using Term Relationships in Language Models for Information Retrieval. In: Proceedings of ACM CIKM 2005, pp. 688–695 (2005)Google Scholar
  19. 19.
    Billerbeck, B., Scholer, F., Williams, H.E., Zobel, J.: Query Expansion Using Associated Queries. In: Proceedings of ACM CIKM 2003, pp. 2–9 (2003)Google Scholar
  20. 20.
    Chen, Z., Liu, S., Liu, W., Pu, A., Ma, W.: Building a Web Thesaurus from Web Link Structure. In: Proceedings of ACM SIGIR 2003, pp. 48–55 (2003)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Zhiguo Gong
    • 1
  • Chan Wa Cheang
    • 1
  • Leong Hou U
    • 1
  1. 1.Faculty of Science and TechnologyUniversity of MacauMacaoPRC

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