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A Hybrid Query Recommendation Technique in Information Retrieval

  • Neelanshi WadhwaEmail author
  • Rajesh Kumar Pateriya
  • Sonika Shrivastava
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 958)

Abstract

As the amount of information available online is enormous, search engines continue to be the best tools to find relevant and required information in the least amount of time. However, with this growth of internet, the number of pages indexed in search engines is also increasing rapidly. The major concern at present is no more having enough information or not; it is rather having too much information which is in numerous different formats, languages and without any measure of precision. Therefore, it is essential to devise techniques that can benefit the process of extracting useful information suitable for users’ demands. Several mechanisms have been developed and some methods have been enhanced by researchers from all over the world to generate better or more relevant query that can be provided as suggestion to the user for enriched Information Retrieval. The objective of this paper is to summarize and analyze the various techniques adopted to optimize the Web Search process to support the user. The existing strategies developed in this scenario are also compared using standard IR metrics to evaluate the relevance of results.

Keywords

Query recommendation Query logs Information retrieval 

References

  1. 1.
    Song, W., Liang, J.Z., Cao, X.L., Park, S.C.: An effective query recommendation approach using semantic strategies for intelligent information retrieval. Expert Syst. Appl. 41, 366–372 (2014)CrossRefGoogle Scholar
  2. 2.
    Liu, Y., Miao, J., Zhang, M., Ma, S., Ru, L.: How do users describe their information need: query recommendation based on snippet click model. Expert Syst. Appl. 38, 13847–13856 (2011)Google Scholar
  3. 3.
    Bordogna, G., Campi, A., Psaila, G., Ronchi, S.: Disambiguated query suggestions and personalized content-similarity and novelty ranking of clustered results to optimize web searches. Inf. Process. Manag. 48, 419–437 (2012)CrossRefGoogle Scholar
  4. 4.
    Zahera, H.M., El Haddy, G.F., Keshk, A.E.: Optimizing Search Engine Result using an Intelligent Model (2012)Google Scholar
  5. 5.
    Baeza-Yates, R., Hurtado, C., Mendoza, M.: Query Recommendation Using Query Logs in Search Engines. In: Lindner, W., Mesiti, M., Türker, C., Tzitzikas, Y., Vakali, A.I. (eds.) Current Trends in Database Technology - EDBT 2004 Workshops. LNCS, vol. 3268, pp. 588–596. Springer, Heidelberg (2004).  https://doi.org/10.1007/978-3-540-30192-9_58CrossRefGoogle Scholar
  6. 6.
    He, Q.: Web query recommendation via sequential query prediction. In: IEEE International Conference on Data Engineering, 1084–4627/09 (2009)Google Scholar
  7. 7.
    Nguyen, T.T.S., Lu, H.Y., Lu, J.: Web-page recommendation based on web usage and domain knowledge. IEEE Trans. Knowl. Data Eng. 26(10), 2574–2587 (2014)CrossRefGoogle Scholar
  8. 8.
    Zhu, X., Guo, J., Cheng, X., Lan, Y.: More than relevance: high utility query recommendation by mining users’ search behaviors, In: CIKM 2012, 29 October–2 November 2012, Maui, HI, USA (2012)Google Scholar
  9. 9.
    Habibia, M., Mahdabib, P., Popescu-Belis, A.: Question answering in conversations: query refinement using contextual and semantic information. Data Knowl. Eng. 106, 38–51 (2016)CrossRefGoogle Scholar
  10. 10.
    Shanna, A.K., Aggarwal, N., Duhan, N., Gupta, R.: Web search result optimization by mining the search engine query logs. In: International Conference on Methods and Models in Computer Science (2010)Google Scholar
  11. 11.
    Anagnostopoulos, A., Becchetti, L., Castillo, C., Gionis, A.: An optimization framework for query recommendation. In: WSDM, pp. 161–170 (2010)Google Scholar
  12. 12.
    Beeferman, D., Berger, A.: Agglomerative clustering of a search engine query log. In: SIGKDD, pp. 407–416 (2000)Google Scholar
  13. 13.
    Yadav, U., Duhan, N., Kaushik, B.: Relevant page retrieval and query recommendation using semantic analysis of queries. Int. J. Sci. Eng. Res. 4(7), 694 (2013)Google Scholar
  14. 14.
    Deepak, G., Priyadarshini, J.S., Hareesh Babu, M.S.: A differential semantic algorithm for query relevant web page recommendation. In: IEEE International Conference on Advances in Computer Applications (ICACA) (2016)Google Scholar
  15. 15.
    Sahu, S.K., Mahapatra, D.P., Balabantaray, R.C.: Analytical study on intelligent information retrieval system using semantic network. In: ICCCA (2016)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Neelanshi Wadhwa
    • 1
    Email author
  • Rajesh Kumar Pateriya
    • 1
  • Sonika Shrivastava
    • 1
  1. 1.Department of Computer Science and EngineeringMaulana Azad National Institute of TechnologyBhopalIndia

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