Advertisement

National Academy Science Letters

, Volume 42, Issue 2, pp 105–108 | Cite as

An Efficient Hybrid User Profile Based Web Search Personalization Through Semantic Crawler

  • Jaytrilok ChoudharyEmail author
  • Deepak Singh Tomar
  • Dhirendra Pratap Singh
Short Communication
  • 38 Downloads

Abstract

The World Wide Web has a collection of trillions of web pages and these web pages are increasing day by day. Web pages available on the Web change frequently and these changes are sometimes unnoticeable by the end user. The exponential growth of web documents on the Internet makes it difficult to find out which are the most relevant web documents for a particular end user on a given search query and user spends a lot of time to get relevant information. The proposed web search personalization system successfully identifies preferences of the end user and constructs an efficient user profile for every end user. It utilizes the built web page repository by retrieving web search results and personalizes them according to user preferences. It is also capable to handle ambiguous queries. The proposed system increases the search accuracy by 37.6% over existing agent based personalization system.

Keywords

Personalization Web search Re-rank Semantic crawler 

References

  1. 1.
    Pretschner A, Gauch S (199) Ontology based personalized search. In: Proceedings of the 11th IEEE international conference on tools with artificial intelligence, pp 391–398Google Scholar
  2. 2.
    Shen X, Tan B, Zhai C (2005) Implicit user modeling for personalized search. In: Proceedings of the ACM international conference information and knowledge management, pp 824–831Google Scholar
  3. 3.
    Sieg A, Mobasher B, Burke R (2007) Web search personalization with ontological user profiles. In: Proceedings of the ACM international conference information and knowledge managementGoogle Scholar
  4. 4.
    Matthijs N, Radlinski F (2011) Personalizing web search using long-term browsing history. In: Proceedings of the ACM conference on web search and data mining, pp 25–34Google Scholar
  5. 5.
    Bennett PN, White RW, Chu W et al (2012) Modeling the impact of short-term and long-term behavior on search personalization. In: Proceedings of the 35th international ACM SIGIR conference on research and development in information retrieval, pp 185–194Google Scholar
  6. 6.
    Dhanalakshmi D, Kousalya R, Saravanan V (2012) Time based web user personalization and search. Int J Comput Appl 46(23):11–17Google Scholar
  7. 7.
    Moawad IF, Talha H, Hosny E, Hashim M (2012) Agent-based web search personalization approach using dynamic user profile. Egypt Inf J 13:191–198CrossRefGoogle Scholar
  8. 8.
    Choudhary J, Roy D (2013) Priority based semantic web crawling. Int J Comput Appl 81(15):10–13Google Scholar

Copyright information

© The National Academy of Sciences, India 2018

Authors and Affiliations

  • Jaytrilok Choudhary
    • 1
    Email author
  • Deepak Singh Tomar
    • 1
  • Dhirendra Pratap Singh
    • 1
  1. 1.Department of CSEMANITBhopalIndia

Personalised recommendations