Journal Title : International Journal of Modern Trends in Engineering and Science
Author’s Name : A.Shanmugam, Mr.P.Sundaramoorthy, Dr.S.Karthik
Volume 01 Issue o5 Year 2014
ISSN no: 2348-3121
Page no: 240-243
Abstract—In the existing system, a major problem is that the interactions between the users and search engines are limited by the small form factors of the mobile devices. Mobile user gives smaller queries, so more ambiguous queries occurs compared to their counterparts. In this model, users searches either by specifying area (specified area) (or) user’s location, server send the information to the user’s PC ,where ontology is applied. PC user displays all the relevant keywords to the user’s mobile, so user selects the exact requirement. Ranking occurs and finally information is produced exactly mapped to the mobile users. In the modification, UDD apply the algorithm to eliminate duplication of records which Helps to minimize the number of URL listed to the user.
Keywords—Mobile search, Ontology, UDD Algorithm, Personalized search.
 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).
 E. Agichtein, E. Brill, S. Dumais, and R. Ragno, “Learning User Interaction Models for Predicting Web Search Result Preferences,” Proc. Ann. Int’l ACM SIGIR Conf. Research and Development in Information Retrieval (SIGIR), (2006).
 Y.-Y. Chen, T. Suel, and A. Markowetz, “Efficient Query Processing in Geographic Web Search Engines,” Proc. Int’l ACM SIGIR Conf. Research and Development in Information Retrieval (SIGIR), (2006).
 K.W. Church, W. Gale, P. Hanks, and D. Hindle, “Using Statistics in Lexical Analysis,” Lexical Acquisition: Exploiting On-Line Resources to Build a Lexicon, Psychology Press, (1991).
 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 (LocWeb), (2008).
 T. Joachims, “Optimizing Search Engines Using Clickthrough Data,” Proc. ACM SIGKDD Int’l Conf. Knowledge Discovery and Data Mining, (2002).
 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).
 H. Li, Z. Li, W.-C. Lee, and D.L. Lee, “A Probabilistic Topic-Based Ranking Framework for Location-Sensitive Domain Information Retrieval,” Proc. Int’l ACM SIGIR Conf. Research and Development in Information Retrieval (SIGIR), (2009).
 R. Baeza-Yates and B. Ribeiro-Neto. Modern Information Retrieval. Addison-Wesley-Longman, Harlow, UK, May (1999).
 B. Bartell, G. Cottrell, and R. Belew. Automatic combination of multiple ranked retrieval systems. In Annual ACM SIGIR Conf. on Research and Development in Information Retrieval (SIGIR), (1994).
 D. Beeferman and A. Berger. Agglomerative clustering of a search engine query log. In ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), (2000).
 B. E. Boser, I. M. Guyon, and V. N. Vapnik. A traininig algorithm for optimal margin classifiers. In D. Haussler, editor, Proceedings of the 5th Annual ACM Workshop on Computational Learning Theory, pages 144–152, (1992).