Facets extraction-based approach for query recommendation using data mining approach

  • Authors

    • A. V. Zadgaonkar assistant professor, rcoem, cse dept
    • A. J. Agrawal
    • S. Aote
    2018-01-30
    https://doi.org/10.14419/ijet.v7i1.8944
  • Facets, Information Retrieval, Query Recommendation

  • Search engines are popularly utilized for extracting desired information from World Wide Web by users.  Efficiency of these search engines are dependent on how fast search results can be retrieved and whether these results reflects the desired info or not. For a particular query, vast amount of relevant information is scattered across the multiple web pages. Search engines generate multiple web links as a output. It has been a jigsaw puzzle for users to identify and select relevant links to extract further desired information. To address this issue, we are proposing an approach for Query Recommendation for getting relevant search results from web using facet mining techniques. Facets are the semantically related words for a query which defines its multiple aspects. We are extracting these aspects of a query from Wikipedia pages which is considered to be a trustworthy resource on the web. Our proposed system uses various text processing techniques to refine the results using lexical resource like WorldNet. In this paper we are discussing our approach and its implementation and results obtained. In the paper , Discussion on future research direction is included to conclude.

  • References

    1. [1] B. Wei, J. Liu, Q. Zheng, W. Zhang, X. Fu, B. Feng, A survey of faceted search, J. Web Eng. 12 (1–2) (2013) 041–064.

      [2] Zhicheng Dou, Member, IEEE, Zhengbao Jiang, Sha Hu, Ji-Rong Wen, and Ruihua Song, Automatically Mining Facets for Queries from Their Search Results," IEEE Transactions on knowledge and data engineering, pp. 385-397, 2016.

      [3] Sheetal Sonwane1, Nilam Patil2 Survey on Query Facets Mining Approaches, International Journal of Science and Research (IJSR) ISSN (Online): 2319-7064 , Volume 6 Issue 1, January 2017. www.ijsr.net.

      [4] E. Stoica, M.A. Hearst, M. Richardson, Automating creation of hierarchical faceted metadata structures, in: Human Language Technology Conference of the North American Chapter of the Association for Computational Linguistics, Rochester, NY, 2007, pp. 244–251.

      [5] W. Dakka, P.G. Ipeirotis, Automatic extraction of useful facet hierarchies from text databases, in: 2008 IEEE 24th International Conference on Data Engineering, Cancun, Mexico, 2008, pp. 466–475.

      [6] B. Wei, J. Liu, J. Ma, Q. Zheng, W. Zhang, B. Feng, DFT-extractor: a system to extract domain-specific faceted taxonomies from Wikipedia, in: Proceedings of the 22nd International Conference on World Wide Web companion, Rio de Janeiro, Brazil, 2013, pp. 277–280.

      [7] Bifan Wei, Jun Liu , Qinghua Zheng , Wei Zhang , Chenchen Wang, Bei Wu, DF-Miner: Domain-specific facet mining by leveraging the hyperlink structure of Wikipedia, Available online 13 January 2015, Knowledge-Based Systems 77 (2015) 80–91.

      [8] Q.Mei, X. Shen, C. Zhai, Automatic labeling of multinomial topic models, in: 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Jose, California, USA, 2007, pp. 490–499.

      [9] S.B. Roy, H.D. Wang, U. Nambiar, G. Das, M. Mohania, DynaCet: building dynamic faceted search systems over databases, in: 2009 IEEE 25th International Conference on Data Engineering, Shanghai, China, 2009, pp. 1463–1466.

      [10] W. Kong and J. Allan, “Extracting query facets from search results,†in Proc. 36th Int. ACM SIGIR Conf. Res. Develop. Inf. Retrieval, 2013, pp.93–102

      [11] J. Pound, S. Paparizos, P. Tsaparas, Facet discovery for structured web search: a query-log mining approach, in: 2011 ACM SIGMOD International Conference on Management of Data, Athens, Greece, 2011, pp. 169–180.

      [12] O. Ben-Yitzhak, N. Golbandi, N. Har’El, R. Lempel, A. Neumann, S. Ofek-Koifman, D. Sheinwald, E. Shekita, B. Sznajder, and S.Yogev, “Beyond basic faceted search,†in Proc. Int. Conf. Web Search Data Mining, 2008, pp. 33–44.

  • Downloads

  • How to Cite

    Zadgaonkar, A. V., Agrawal, A. J., & Aote, S. (2018). Facets extraction-based approach for query recommendation using data mining approach. International Journal of Engineering & Technology, 7(1), 121-125. https://doi.org/10.14419/ijet.v7i1.8944