Browse > Article
http://dx.doi.org/10.5391/JKIIS.2005.15.4.443

Design & Evaluation of an Intelligent Model for Extracting the Web User' Preference  

Kim, Kwang-Nam (국방대학교 전산정보학과)
Yoon, Hee-Byung (국방대학교 전산정보학과)
Kim, Hwa-Soo (아주대학교 정보통신대학교)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.15, no.4, 2005 , pp. 443-450 More about this Journal
Abstract
In this paper, we propose an intelligent model lot extraction of the web user's preference and present the results of evaluation. For this purpose, we analyze shortcomings of current information retrieval engine being used and reflect preference weights on learner. As it doesn't depend on frequency of each word but intelligently learns patterns of user behavior, the mechanism Provides the appropriate set of results about user's questions. Then, we propose the concept of preference trend and its considerations and present an algorithm for extracting preference with examples. Also, we design an intelligent model for extraction of behavior patterns and propose HTML index and process of intelligent learning for preference decision. Finally, we validate the proposed model by comparing estimated results(after applying the Preference) of document ranking measurement.
Keywords
Preference Weight; Information Retrieval Engine; Intelligent Model; Behavior Pattern;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Catherine Stones and Stephen Sobol, 'DMASC : A Tool For Visualizing User Paths THrough A Web Site,' 13th International Workshop on Database and Expert Systems Applications, pp.389-393, 2002
2 R. Cooley, B.Mobasher, and J.Srivastava, 'Web Mining : Information and Pattern Discovery on the World Wide Web,' 9th IEEE International Conference on Tools with Artificial Intelligent, 1997
3 Juan Velásquez, Hiroshi Yasuda and Terumasa Aoki, 'Combining the Web Content and Usage mining to Understand the Visitor behavior in a Web Site,' 3rd IEEE International Conference on Data Mining, pp.669-672. 2003
4 Kibum Kim, John M. Carroll and Mary Beth Rosson, 'An Empirical Study of Web Personalization Assistants : Supporting End- Users in Web Information Systems,' IEEE 2002 Symposia on Human Centric Computing Languages and Environments, pp.60-62, 2002
5 Osmar R. Zaïane, Man Xin and Jiawei Han, 'Discovering Web Access Patterns and Trends by Applying OLAP and Data Mining Technology on Web Logs,' Research and Technology Advances in Digital Libraries, IEEE International Forum, pp.19-29, 1998
6 Doru Tanasa and Brigitte Trousse, 'Advanced Data Preprocessing for Intersites Web Usage Mining,' IEEE Intelligent Systems, vol.19, Issue 2, pp.59-65, 2004   DOI
7 L. Catledge and J. Pitkow, 'Characterizing Browsing Behaviors on the World Wide Web,' Computer Networks and ISDN Systems, vol. 27, no. 6, 1995
8 Kwangnam Kim, Heebyung Yoon, Hwa-Soo Kim 'Design and Implementation of XML-based Indexing Algorithm Using Depth-First and Shortest Distance Between Nodes,' 31th KISS spring conference, vol. 31, no. 1, p.547-549, 2004
9 Feng Guozhen, Cheng Xueqi, Bai Shuo, 'SAInSE : An Intelligent Search Engine Based on WWW Structure Analysis,' 15th International Parallel and Distributed Processing Symposium, pp.1734- 1740, 2001
10 Kun_Lung Lu, Charu C. Aggarwal and Philip S. Yu, 'Personalization with Dynamic Profiler,' 3rd International workshop on Advanced Issues of E-Commerce and Web-Based Information Sytems(WECWIS), pp.12-20, 2001
11 George T. Wang, 'Web Search With Personalization and Knowledge,' IEEE 4th International Symposium on Multimedia Software Engineering, 2002
12 Jaideep Srivastava, Robert Cooley, Musund Deshpande, Pang-Ning Tan 'Web Usage Mining : Discovery and Applications of Usage Patterns from Web Data,' Exploration ACM SIGKDD, 2000
13 Yew-Kwong Woon, Wee-Keong Ng, Xiang Li and Web-Feng Lu, 'Efficient Web Log Mining for Product Development,' Internaltional Conference on Cyberworlds, pp.294-301, 2003