Volume -I , Issue -XI, June 2015

ANDROID MOBILE SEARCH ENGINE WITH USER PERSONALIZATION

Author(s) :

Soni Kamuni , Suhas Raut

Abstract

The primary problem in mobile search is that the interactions among the users and search engines are limited by the small screen of the mobile devices. To give more relevant results to the users, search engines must able to create a user’s profile, including interests and personalizing the search results according to the user profiles. The proposed personalized mobile search engine is an innovative approach to personalize search query and corresponding search results. The Proposed system takes the help of Google’s GPS service to detect user location and location-content mining concept to personalize the search query as per query type. And also uses the user profile and user interest to modify the user query close to user personal approach to find anything on the internet. Proposed system uses Google, yahoo and Bing search engine’s API’s to search out the personalized query which returns search results.

Keywords

mobile search engine, personalization, privacy setting, click through data.

References
  1. K. Leung, D. Lee, W. Lee,” Personalized Web Search with Location Preferences”, ICDE Conference 2010, 978-1-4244-5446-4/10/@ 2010 IEEE.
  2. W. Ng, L. Deng, and D. L. Lee, “Mining user preference using spy voting for Search engine personalization” ACM Trans.Internet Technology, vol. 7, no. 4, article 19, 2007.
  3. S. Yokoji, “Kokono Search: A Location Based Search Engine,” Proc.Int’l Conf. World Wide Web (WWW), 2001.
  4. B. Liu, W.S. Lee, P.S.Yu, and X. Li, “Partially Supervised Classification of Tex Documents,” Proc. Int’l Conf. Machine Learning (ICML), 2002.
  5. E. Agichtein, E. Brill, S. Dumais, and R. Ragno, “Learning User Interaction Models for
  6. Predicting Web Search Result Preferences,” Proc. Ann. Int’l ACM SIGIR Conf. Research and Development in Information Retrieval (SIGIR), 2006.
  7. Q. Gan, J. Attenberg, A. Markowetz, and T. Suel, “Analysis of Geographic Queries in a Search Engine Log,” Proc. First Int’l Workshop Location and the Web (Loc Web), 2008.
  8. T. Joachim’s, “Optimizing Search Engines Using Click through Data,” Proc.ACM SIGKDD Int’l Conf. Knowledge Discovery and Data Mining, 2002.
  9. C.E. Shannon, “Prediction and Entropy of Printed English,” Bell Systems Technical J., vol. 30, pp. 50-64, 1951.
How to Cite this Paper? [APA Style]
Soni Kamuni , Suhas Raut, (2015), ANDROID MOBILE SEARCH ENGINE WITH USER PERSONALIZATION, Industrial Science Journal, http://industrialscience.org/Article.aspx?aid=72&vid=11, (June, 2015)
Full Text in PDF

Full Article in PDF Format

Comment on this article...!!!

 
 
 
Previous Comments...
No previous comments.

Archive

Alert Me...!!!

When new article publish, article link will mail to your mail...

Enter Your Name :
Enter Your Email ID :

For Authors

For Readers