Skip to main content

Concept Based Personalized Search and Collaborative Search Using Modified HITS Algorithm

  • Conference paper
  • 2631 Accesses

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8284))

Abstract

Keyword based search is commonly used by popular search engines. The major problem with this kind of search is that we do not get user intended results for the search. In addition, every user gets the same set of results for the same query whereas, their interests may be different. In order to tackle this, we go in for personalized web search and collaborative web search. We find out the user interest and accordingly display only pages that are relevant to their interest and not relevant blindly only to their query. This paper, describes a novel approach for storing the personalized user concepts and proposes a modification to the HITS algorithm based on user interested concepts. This paper also describes how to extend the concept based personalized search to concept based collaborative search. In addition we propose a new methodology to form dynamic groups in the case of collaborative search.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Delgado, J., Ishii, N., Ura, T.: Content-based collaborative information filtering: Actively learning to classify and recommend documents. In: Klusch, M., Weiss, G. (eds.) CIA 1998. LNCS (LNAI), vol. 1435, pp. 206–215. Springer, Heidelberg (1998)

    Google Scholar 

  2. Hu, J., Chan, P.K.: Personalized Web Search by Using Learned User Profiles in Re-ranking. In: Proceedings of Web KDD, Workshop on Web Mining and Web Usage Analysis (2008)

    Google Scholar 

  3. Pérez, J.D.J., Calderón, M.L., González, C.N.: Towards an Information Filtering System in the Web Integrating Collaborative and Content Based Techniques. In: IEEE Proceedings of the First Latin American Web (2003)

    Google Scholar 

  4. Kleinberg, J.: Authoritative Sources in a Hyperlinked Environment. In: Proceedings of the ACM-SIAM Symposium on Discrete Algorithms (1997)

    Google Scholar 

  5. Mittal, N., Nayak, R., Govil, M.C., Jain, K.C.: A Hybrid Approach of Personalized Web Information Retrieval. In: IEEE International Conference on Web Intelligence and Intelligent Agent Technology (2010)

    Google Scholar 

  6. Palleti, P., Karnick, H., Mitra, P.: PersonalizedWeb Search using Probabilistic Query Expansion. In: International Conferences on Web Intelligenceand Intelligent Agent Technology - Workshops (2007)

    Google Scholar 

  7. Roma, Y., Shtykh, Q.J.: Integrating Search and Sharing: User-Centric Collaborative Information Seeking. In: Eigth IEEE/ACIS International Conference on Computer and Information Science (2009)

    Google Scholar 

  8. Sendhilkumar, S., Geetha, T.V.: User Representation in Personalized Web Search using Interest Vectors. In: International Journal of Recent Trends in Engineering (2009)

    Google Scholar 

  9. Gauch, S., Speretta, M., Chandramouli, A., Micarelli, A.: User Profiles for Personalized Information Access. Artificial Intelligence Publisher: Springer (2007)

    Google Scholar 

  10. Umamaheswari, E., Geetha, T.V., Parthasarathi, R., Karky, M.: A Multilevel UNL Concept based Searching and Ranking. In: WEBIST (2011)

    Google Scholar 

  11. UNL- http://www.undl.org

  12. Shu-hong, Y., Fu-liang, W.: Study on Personalized Search Engine Based on Files. In: IEEE International Conference on Internet Technology and Applications (2010)

    Google Scholar 

  13. Zeng, J., H.-J., Li, H., Niu, C., Chen, Z.: Demographic prediction based on user’s browsing behaviour. In: Proceedings of the 16th International Conference on World Wide Web, pp. 151–160 (2007)

    Google Scholar 

  14. Shi, X.: An intelligent knowledge-based recommendation system. Intelligent information processing II, 431-435 (2005)

    Google Scholar 

  15. Jeon, H., Kim, T., Choi, J.: Adaptive User Profiling for Personalized Information Retrieval. In: Third International Conference on Convergence and Hybrid Information Technology (2008)

    Google Scholar 

  16. Miller, J.C., Rae, G., Schaefer, F., Ward, L.A., Lofaro, T., Faraha, A.: Modifications of Kleinberg’s HITS algorithm using matrix exponentiation and web log records. In: Proceedings of the 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 444–445 (2001)

    Google Scholar 

  17. Jayanthi, J., Jayakumar, K.S.: An Integrated Page Ranking Algorithm for Personalized Web Search. International Journal of Computer Applications 12 (2011)

    Google Scholar 

  18. Gauch, S., Chaffee, J., Pretschner, A.: Ontology-based personalized search and browsing. Web Intelligence and Agent Systems: An International Journal, 219–234 (2003)

    Google Scholar 

  19. Sendhilkumar, S., Geetha, T.V.: Concept based Personalized Web Search. Advances in Semantic Computing 2, 79–102 (2010)

    Google Scholar 

  20. Daoud, M., Tamine-Lechani, L., Boughanem, M.: Using A Concept-based User Context For Search Personalization. In: Proceedings of the World Congress on Engineering, vol. I (2008)

    Google Scholar 

  21. Leung, K.W.-T., Lee, D.L., Ng, W., Fung, H.Y.: A Framework for Personalizing Web Search with Concept-Based User Profiles. ACM Transactions on Internet Technology 2(3) (2001)

    Google Scholar 

  22. Prabaharan, S., Wahidabanu, R.S.D.: Ontological Approach for Effective Generation of Concept Based User Profiles to Personalize Search Results. Journal of Computer Science, 205–215 (2012)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer International Publishing Switzerland

About this paper

Cite this paper

Pavai, G., Umamaheswari, E., Geetha, T.V. (2013). Concept Based Personalized Search and Collaborative Search Using Modified HITS Algorithm. In: Prasath, R., Kathirvalavakumar, T. (eds) Mining Intelligence and Knowledge Exploration. Lecture Notes in Computer Science(), vol 8284. Springer, Cham. https://doi.org/10.1007/978-3-319-03844-5_64

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-03844-5_64

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-03843-8

  • Online ISBN: 978-3-319-03844-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics