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A Comprehensive Survey on Query Expansion Techniques, their Issues and Challenges

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Neha Kathuria, Kanika Mittal, Anusha Chhabra

Neha Kathuria, Kanika Mittal and Anusha Chhabra. A Comprehensive Survey on Query Expansion Techniques, their Issues and Challenges. International Journal of Computer Applications 168(12):17-20, June 2017. BibTeX

	author = {Neha Kathuria and Kanika Mittal and Anusha Chhabra},
	title = {A Comprehensive Survey on Query Expansion Techniques, their Issues and Challenges},
	journal = {International Journal of Computer Applications},
	issue_date = {June 2017},
	volume = {168},
	number = {12},
	month = {Jun},
	year = {2017},
	issn = {0975-8887},
	pages = {17-20},
	numpages = {4},
	url = {},
	doi = {10.5120/ijca2017914424},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


In order to improve the retrieval performance, the process of Query expansion is performed on the original user’s query in order to reformulate the user’s query. The basis of these query expansion techniques is to expand the query by adding the terms, which are in close proximity to the original query terms. Various query expansion techniques do not consider the context of the terms present in the user’s query which can result in low precision and recall due to the ambiguity and vagueness of terms present in the query. Through this paper, a comprehensive survey is presented to study the various query expansion techniques proposed in literature by researchers and the various keyholes in the current scenario.


  1. A. Roshdi and A. Roohparvar, “Review: Information Retrieval Techniques and Applications”, International Journal of Computer Networks and Communications Security Vol. 3, No. 9, pp. 373–377, 2015.
  2. R. Sagayam, S.Srinivasan and S. Roshni, “A Survey of Text Mining: Retrieval, Extraction and Indexing Techniques”, International Journal of Computational Engineering Research (, Vol.2, 2012.
  3. R.Kosala and H. Blockeel, “Web Mining Research: A Survey”, ACM Sigkdd Explorations Newsletter-, 2000.
  4. A. Kankaria, ”Query Expansion techniques”, Indian Institute of Technology Bombay, Mumbai, CSI Journal of Computing,  Vol. 1,  No. 2, 2012.
  5. R. Mihalcea and D. Moldovan, “Semantic Indexing using WordNet Senses”, Proceedings of the ACL-workshop on recent advances in natural language processing and information retrieval: 38th Annual Meeting of the Association for Computational, Vol.11, pp. 35-45, 2000.
  6. L.A.Zadeh, “Fuzzy Sets”, Information and Control, Vol.8.3, pp. 338-353, 1965.
  7. A.Jain, K.Mittal, S. Sabharwal, “Information Retrieval in Fuzzy Logic Framework: A Survey”, ICNICT, 2012.
  8. N.O.Rubens, “The Application of Fuzzy Logic to the Construction of the ranking Function of Information Retrieval Systems”, Computer Modelling and New Technologies, Vol.10, No.1, pp. 20-27, 2006.
  9. Abdelmgeid Amin Aly, “Using a Query Expansion Technique to improve document retrieval”, International Journal Information Technologies and Knowledge, Vol.2, 343, 2008.
  10. O.Hoeber, XD Yang and Y Yao, “Conceptual Query Expansion”, International Atlantic Web Intelligence Conference, pp. 190-196, 2005.
  11. M.Peng, Q.Lin, Ye Tian, M.Yang, Y.Xiao and B.Ni , “Query expansion based on Conceptual Word Cluster Space Graph”, Information Science and Service Science(NISS), 5th International Conference on New Trends, Vol.1, pp. 128-133, 2011.
  12. A.Jain, K.Mittal, S. Sabharwal, “Conceptual weighing Query Expansion on user profiles”, National Conference on Communication Technologies & its impact on Next Generation Computing CTNGC Proceedings published by International Journal of Computer Applications (IJCA), 2012.
  13. G.Akrivas, M. Wallace, G. Andreou, G.Stamou and S. Kollias, “Context-Sensitive Semantic Query Expansion”, Artificial Intelligence Systems (ICAIS) IEEE International Conference, pp. 109-114, 2002.
  14. Kang, J.W., H.K., Ko, M.C., Jeon, H.S., and Nam, “A Term Cluster Query Expansion Model Based on Classification Information in Natural Language Information Retrieval”, Aritifical Intelligence and Computational Intelligence(AICI), IEEE, International Conference, Vol.2, pp. 172-176, 2010.
  15. C.H.Chang and CC Hsu, “Integrating query expansion and conceptual relevance feedback for personalized Web information retrieval”, Computer Networks and ISDN Systems, pp. 621-623, 1998.
  16. GJ Hahm, MY Yi, JH Lee and HW Suh, “A Personalized Query Expansion Approach for Engineering document retrieval”, Advanced Engineering Informatics 28 (4), pp. 344–359, 2014.
  17. P.Karisani, M.Rahgozar and F.Oroumchian,” A Query term re-weighting approach using document similarity” Information Processing and Management,Vol.52, pp. 478-489, 2016.
  18. D. K. Tayal, S. Sabharwal, A.Jain and K.Mittal, “Intelligent Query Expansion for the Queries including Numerical Terms”, Proceedings of International Journal of Computer Applications (IJCA), pp. 35-39, 2012.
  19. HC Lin, LH Wang and SM Chen, “Query Expansion for Document Retrieval by Mining Additional Query Terms”, Information and Management Sciences, 19(1), pp. 17-30, 2008.
  20. A.Hust, S.Klink, M. Junker and A. Dengel, “Query Expansion for Web Information Retrieval”, GI Jahrestagung, pp. 176-182, 2002.
  21. J Zhang, B Deng and X Li, “Concept Based Query Expansion Using WordNet”, Proceedings of the 2009 International e-Conference on Advanced Science and Technology IEEE Computer Society Washington, DC, USA, pp. 52-55, 2009.
  22. K. Mittal and A. Jain, ”A graph Based Query Expansion using Semantic Similarity and OWA Operator” , ICTACT Journal on Soft Computing, Vol.5 pp. 896-904, 2015.
  23. A. Jain, K. Mittal and D. K. Tayal, “Automatically incorporating context meaning for query expansion using graph connectivity measures”, Progress in Artificial Intelligence, Vol.2, pp. 129–139, 2014.
  24. R.Navigli and M. Lapata, “An Experimental Study of Graph Connectivity for Unsupervised Word Sense Disambiguation”, IEEE transactions on pattern analysis and machine intelligence, VOL. 32, NO.4, pp. 678-692, 2010.
  25. M.Barathi and S.Valli, “Ontology Based Query Expansion Using Word Sense Disambiguation”, (IJCSIS) International Journal of Computer Science and Information Security, Vol.7, No. 2, 2010.
  26. D.Parapar, Á. Barreiro and D.E. Losada, “Query Expansion Using WordNet with a Logical Model of Information Retrieval”, IADIS AC, pp.487-494, 2005.
  27. J. Singh and A.Sharan , “ A new Fuzzy Logic based Q.E. Model for efficient IR using Relevance Feedback Approach”, Neural Computing and Applications, pp. 1-24, 2016.
  28. Y.Gupta, A.Saini and A.K. Saxena, “A new Fuzzy Logic Based Ranking Function for efficient IR System” Expert Systems with Applications, 42(3), Vol.42, pp. 1223–1234, 2015.
  29. J. Ropero, A. Gomez, A. Carrasco, C. Leon and J. Luque , “Term Weighting for Information Retrieval Using Fuzzy Logic”, 2012.
  30. M.J. Martin-Bautista, D. Sanchez, J. C. Martinez, J.M. Serrano and M.A Vila, “Mining web documents to find additional query terms using fuzzy association rules”, Fuzzy Sets and Systems,148(1), pp.85-104, 2004.
  31. H.M Lee, S.K Lin and CW. Huang, “Interactive Query Expansion Based on Fuzzy Association Thesaurus for Web Information Retrieval”, Fuzzy Systems, 10th IEEE International Conference on Vol.2, pp. 724-727, 2001.


Query Expansion, Natural Language Processing, Information Retrieval, Fuzzy Logic