Mobile Search Engine Personalization Enhanced with Recommendation System with an Impact of Affect Analysis

Authors

  • Raja Arulmozhi Keerthana. R  Department of Information Technology Velammal Institute of Technology, Anna University, Chennai, Tamilnadu, India
  • Sruthi. R  Department of Information Technology Velammal Institute of Technology, Anna University, Chennai, Tamilnadu, India
  • Yamini. R  Department of Information Technology Velammal Institute of Technology, Anna University, Chennai, Tamilnadu, India

Keywords:

Personalization, ontology, rank adaptation.

Abstract

As the amount of web information grows rapidly, we propose a personalized search engine with an affect analysis. In this paper, we propose a new web search personalization which recommends the user with the additional information about the content they searched. It gives the user knowledge about the content which they never knew. The user preferences are organized in ontology based, multifacet user profiles, which are used to adapt a personalized ranking function for rank adaptation of future results. To recommend the users with additional information we have to analyse the other user's click through data. Based on the client - server model, we also present a detailed architecture and design for implementation of personalized mobile search engine with an impact of affect analysis. We prototype PMSE on the google android platform. Experimental results show that PMSE significantly improves the precision comparing to the baseline.

References

  1. S. Cronen-Townsend and W.B. Croft, “Quantifying Query Ambiguity”, Proceedings of the Conference on Human Language Technology, San Diego, 2002, 94–98.
  2. R Song, Z.X. Luo, J.R. Wen, and H.W. Hon, “Identifying Ambiguous Queries in Web Search”, The International World World Wide Web Conference, Banff, Canada, May 8-12, 2007,112-116
  3. Anand S.S. And Mobasher B.: Intelligent Techniques for Web Personalization. ITWP 2003, pp.1-36, 2005.
  4. E. Agichtein, E. Brill, and S. Dumais, “Improving Web Search Ranking by Incorporating User Behavior, Information,” Proc. 29th Ann. Int’l ACM SIGIR Conf. Research and Development in Information Retrieval (SIGIR), 2006, pp.19-26
  5. T. Joachims, “Optimizing Search Engines Using Click through Data,” Proc. ACM SIGKDD Int’l Conf. Knowledge Discovery and Data Mining, 2002, pp. 133-142
  6. K.W.-T. Leung, D.L. Lee, and W.-C. Lee, “Personalized Web Search with Location Preferences,” Proc. IEEE Int’l Conf. Data Mining (ICDE), 2010, pp. 248-256.         
  7. Kenneth Wai-Ting Leung, Dik Lun Lee, Wilfred Ng and Hing Yuet Fung,” A Framework for Personalizing Web Search with Concept BasedUserProfiles”ACMTransactionsonInternet technologies, Vol.2.N o.3.Article.A.Sep-01
  8. K. W. -T. Leung, W.Ng, and D.L.Lee, “Personalized Concept-Based Clustering of Search Engine Queries,” IEEE Trans. Knowledge and Data Eng., vol. 20, no. 11, pp. 1505-1518, Nov. 2008.
  9. Snigdha Gupta, Saral Jain, Mohammed chose, Komal Kapoor,” Personalization of web search result based on user profile” First International Conference on Emerging Trends in Engineering and Technology. pp 1115-1119.
  10.  Keenoy, K. And Levene M. Personalization of Web Search, School of Computer Science and Information Systems, Birkbeck, University of London,2009.
  11. Y. Xu, K. Wang, B. Zhang, and Z. Chen, “Privacy-Enhancing Personalized Web Search,” Proc. Int’l Conf. World Wide Web (WWW), 2007.
  12. K.W-T Leung, Dik Lun Lee, and Wang- Chien Lee, ”Personalized Mobile Search Engine” IEEE Trans. Knowledge and Data Eng., April. 2013, vol. 25, no. 4, pp. 452-464.
  13. Varun mishra , Premnarayan Arya, Manish Dixit ,” Improving Mobile Search through Location Based Context and Personalization”, 2012 International Conference on Communication Systems and Network Technologies, pp 392-395.
  14. Zhen HE, Yongchun HE, Yanquan ZHOU, Cong WANG and Chunxiao Fan,”Research on personalized information service on mobile networks based on mining user's interest” 2006 IEEE International Conference on Industrial Informatics, pp 1052-1056.
  15. B. Liu,M.Hu, and J. Cheng,“Opinion observer: Analyzing and comparing opinions on the web,”in Proceedings of WWW, 2005,article 10,pp.235-356.
  16. J. Teevan, M.R. Morris, and S. Bush, “Discovering and Using Groups to Improve Personalized Search,” Proc. ACM Int’l Conf. Web Search and Data Mining (WSDM), 2009, pp. 124-139
  17. Yu,H.,and Hatzivassiloglou, V. 2003. Towards answering opinion questions: Separating facts from opinions and identifying the polarity of opinion sentences. EMNLP’03,pp 138-142
  18. Pang, B., Lee, L., and Vaithyanathan, S., 2002. Thumbs up? Sentiment Classification Using Machine Learning Techniques. EMNLP’2002,pp 234-253

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Published

2015-04-11

Issue

Section

Research Articles

How to Cite

[1]
Raja Arulmozhi Keerthana. R, Sruthi. R, Yamini. R, " Mobile Search Engine Personalization Enhanced with Recommendation System with an Impact of Affect Analysis, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 1, Issue 2, pp.386-390, March-April-2015.