A Personal Agent for Bookmark Classification
The World Wide Web has become a source of enormous amount of information. Most web browsers feature bookmarking facilities as a means to harness the vast web space. Users record the URLs of the sites for future visits with bookmarks, but the organization and maintenance of the bookmark file cost users time and cognitive work. A personal agent is an automated program to which users can delegate often tedious or sophisticated tasks. We implemented a learning agent called BClassifier using Naive Bayesian learning method and present the findings in this paper.
KeywordsPersonal Agent User Profile Local Machine Future Visit Sophisticated Task
Unable to display preview. Download preview PDF.
- 1.Bradshaw Jeffrey M., Software Agent. AAAI Press/The MIT Press. (1995).Google Scholar
- 2.Chen, L. and K. Sycara, “WebMate: A personal agent for browsing and searching,” Proc. 2nd Int. Conf. on Autonomous Agents and Multi-Agent Systems, (1998) 132–139.Google Scholar
- 4.Lim, Yoon-Taik and Choong-Wha Yoon, “An Evolving Algorithm Based on Cross Validation.” Proc of 1999 Fall Conference, Korean Information Processing Society, Vol. 6, No. 1. (1999)Google Scholar
- 5.McCallum, A. and K. Nigam, “A Comparison of Event Models for Naïve Bayes Text Classification”, AAAI-98 Workshop on Learning for Text Categorization, (1998).Google Scholar
- 6.Mladenic, Dunja and Marko Grobelnik, “Feature selection for classification based on text hierarchy”. In Conference on Automated Learning and Discovery, Proc. of CONALD_98, (1998).Google Scholar
- 7.Mladenic, D., “Personal WebWatcher: Design and Implementation.” Technical Report IJS-DP-7472, School of Computer Science, Carnegie-Mellon University, Pittsburgh, USA, (1996).Google Scholar
- 8.Mitchell, Tom M., Machine Learning, McGraw-Hill, (1997).Google Scholar
- 10.Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach. Prentice Hall, (1995).Google Scholar
- 11.Zhang, Byoung-Tak, “Learning Agents”, Communications of Korea Information Science Society, Vol. 18, No. 5, (2000) 26–35.Google Scholar