An Innovative Method for Concluding User Search Intention Using Feedback Session

Authors(1) :-Vipul D. Punjabi

With the advent of computers, it became possible to store large amounts of information and finding useful information from such collections became a necessity of today’s world. For a broad-topic and ambiguous query, different users may have different search goals. The inference and analysis of user search goals can be very useful in improving search engine relevance and user experience. Hence, in this paper we have tried to improve the efficiency of the search engine by combining inferring user search goal with feedback sessions. Initially, we composed a framework to implement different user search goals for an ambiguous query with the help of clustering the proposed feedback sessions. The user needs are reflected efficiently through the feedback sessions built by the user click-through logs. Second, to represent better feedback sessions for clustering we generate the pseudo document. Finally, we proposed a new criterion “Classified Average Precision (CAP) to evaluate the performance of inferring user search goals. Therefore, when users submit their queries, the search engine can return the results that are categorized into different groups according to user search goals online. Thus, users can find what they want conveniently

Authors and Affiliations

Vipul D. Punjabi
Department of Computer Engineering, R. C. Patel Institute of Technology, Shirpur, Maharashtra, India

Query logs, clicked un-clicked, pseudo-document, clustering, feedback session, Classified Average Precision (CAP).

  1. R. Jones and K.L. Klinkner, "Beyond the Session Timeout: Automatic Hierarchical Segmentation of Search Topics in Query Logs," Proc. 17th ACM Conf. Information and Knowledge Management (CIKM ’08), pp. 699-708, 2008.
  2. D. Beeferman and A. Berger, "Agglomerative Clustering of a Search Engine Query Log," Proc. Sixth ACM SIGKDD Int’l Conf. Knowledge Discovery and Data Mining (SIGKDD ’00), pp. 407-416, 2000.
  3. H. Chen and S. Dumais, "Bringing Order to the Web: Automatically Categorizing Search Results," Proc. SIGCHI Conf. Human Factors in Computing Systems (SIGCHI ’00), pp. 145-152, 2000.
  4. T. Joachims, "Optimizing Search Engines Using Clickthrough Data," Proc. Eighth ACM SIGKDD Int’l Conf. Knowledge Discovery and Data Mining (SIGKDD ’02), pp. 133-142, 2002.
  5. R. Baeza-Yates and B. Ribeiro-Neto, Modern Information Retrieval. ACM Press, 1999.
  6. H. Cao, D. Jiang, J. Pei, Q. He, Z. Liao, E. Chen, and H. Li, "Context-Aware Query Suggestion by Mining Click-Through," Proc. 14th ACM SIGKDD Int’l Conf. Knowledge Discovery and Data Mining (SIGKDD ’08), pp. 875-883, 2008.

Publication Details

Published in : Volume 1 | Issue 2 | March-April 2015
Date of Publication : 2015-04-25
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 429-432
Manuscript Number : IJSRSET1522138
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

Vipul D. Punjabi, " An Innovative Method for Concluding User Search Intention Using Feedback Session, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 1, Issue 2, pp.429-432, March-April-2015.
Journal URL : http://ijsrset.com/IJSRSET1522138

Follow Us

Contact Us