Representing personal web information using a topic-oriented interface

ABSTRACT

Nowadays, Web activities have become daily practice for people. It is therefore essential to organize and present this continuously increasing Web information in a more usable manner. In this paper, we developed a novel approach to reorganize personal Web information as a topic-oriented interface. In our approach, we proposed to utilize anchor, title and URL information to represent content information for the browsed Web pages rather than the content body. Furthermore, we explored three methods to organize personal Web information: 1) top-down statistical clustering; 2) salience phrase based clustering; and 3) support vector machine (SVM) based classification. Finally, we conducted a usability study to verify the effectiveness of our proposed solution. The experimental results demonstrated that users could visit the pages that have been browsed previously more easily with our approach than existing solutions.

REFERENCES

• 1: Foner L. A multi-agent referral system for matchmaking. Proc. of the 1st Int. Conf. on the Practical Applications of Agents and Multi Agent Systems, London, UK, 1996.
• 2: Thorsten Joachims, Text Categorization with Suport Vector Machines: Learning with Many Relevant Features, Proceedings of the 10th European Conference on Machine Learning, p.137-142, April 21-23, 1998
• 3: Natasa Milic-Frayling , Rachel Jones , Kerry Rodden , Gavin Smyth , Alan Blackwell , Ralph Sommerer, Smartback: supporting users in back navigation, Proceedings of the 13th international conference on World Wide Web, May 17-20, 2004, New York, NY, USA [doi>10.1145/988672.988682]
• 4: Westerveld T., Kraaij W., and Hiemstra D. Retrieving Web pages using content, links, urls and anchors. In Text REtrieval Conference (TREC-10), pages 663--672, 2001.
• 5: Hua-Jun Zeng , Qi-Cai He , Zheng Chen , Wei-Ying Ma , Jinwen Ma, Learning to cluster web search results, Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval, July 25-29, 2004, Sheffield, United Kingdom [doi>10.1145/1008992.1009030]

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.4 INFORMATION SYSTEMS APPLICATIONS
      H.4.3 Communications Applications
          Subjects: Information browsers

General Terms:
Design, Human Factors

Keywords:
clustering, personal web information, topic classfication, user information mining, user interface