Behavior-based web page evaluation

ABSTRACT

This paper describes our efforts to factor in a user's browsing behavior to automatically evaluate web pages that the user shows interest in, based on user browsing behaviors while browsing. To evaluate a webpage automatically, we have developed a client-side logging tool: the GINIS Framework. We do not focus just on clicking, scrolling, navigation, or duration of visit alone, but we propose integrating these patterns of interaction to recognize and evaluate a user's response to a given web page.

REFERENCES

• 1: Lara D. Catledge , James E. Pitkow, Characterizing browsing strategies in the World-Wide Web, Computer Networks and ISDN Systems, v.27 n.6, p.1065-1073, April 1995
• 2: Masahiro Morita , Yoichi Shinoda, Information filtering based on user behavior analysis and best match text retrieval, Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval, p.272-281, July 03-06, 1994, Dublin, Ireland
• 3: R. Cooley, Pang-Ning Tan, and Jaideep Srivastava. Discovery of interesting usage patterns from web data. Technical Report TR 99-022, University of Minnesota, 1999.
• 4: Tjen-Sien Lim , Wei-Yin Loh , Yu-Shan Shih, A Comparison of Prediction Accuracy, Complexity, and Training Time of Thirty-Three Old and New Classification Algorithms, Machine Learning, v.40 n.3, p.203-228, Sept. 2000 [doi>10.1023/A:1007608224229 ]

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.1 MODELS AND PRINCIPLES
      H.1.2 User/Machine Systems
          Subjects: Human factors

Additional Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.3 Information Search and Retrieval
          Subjects: Information filtering

General Terms:
Design, Human Factors, Theory

Keywords:
automatic profiling, information extraction, web browsing behavior, web usage mining, web-human interaction