A Web Document Personalization User Model and System

In this paper, we present PVA, an adaptive personal view information agent system to track, learn and manage user interests in the Internet documents. PVA consists of three parts: proxy, personal view constructor and personal view maintainer. Proxy logs user’s activities and extracts user interests without user intervention. Personal view constructor mines user interests and maps them to a class hierarchy (i.e. personal view). Personal view maintainer synchronizes user interests and personal view periodically. When user interests change, PVA, not only the contents but also the structure of user profile, is modified to adapt the changes. Experimental results show that modulating the structure of user profile does increase the accuracy of personalization systems.

[1]  Jan-Ming Ho,et al.  ACIRD: Intelligent Internet Document Organization and Retrieval , 2002, IEEE Trans. Knowl. Data Eng..

[2]  Susan Brewer,et al.  Information storage and retrieval , 1959, ACM '59.

[3]  Alexander Pretschner,et al.  Personalization on the Web , 1999 .

[4]  Filippo Menczer,et al.  Artificial Life Applied to Adaptive Information Agents , 1995 .

[5]  Gerard Salton,et al.  Automatic Text Processing: The Transformation, Analysis, and Retrieval of Information by Computer , 1989 .

[6]  Alexander Pretschner,et al.  Ontology based personalized search , 1999, Proceedings 11th International Conference on Tools with Artificial Intelligence.

[7]  Jude W. Shavlik,et al.  Learning users' interests by unobtrusively observing their normal behavior , 2000, IUI '00.

[8]  Michael J. Pazzani,et al.  A personal news agent that talks, learns and explains , 1999, AGENTS '99.

[9]  Thomas G. Dietterich.  What is machine learning? , 2020, Archives of Disease in Childhood.

[10]  Keiichiro Hoashi,et al.  Document filtering method using non-relevant information profile , 2000, SIGIR '00.

[11]  Vipin Kumar,et al.  WebACE: a Web agent for document categorization and exploration , 1998, AGENTS '98.

[12]  John Yen,et al.  An adaptive algorithm for learning changes in user interests , 1999, CIKM '99.

[13]  Chi-Sheng Shih,et al.  Extracting classification knowledge of Internet documents with mining term associations: a semantic approach , 1998, SIGIR '98.

[14]  Dunja Mladenic,et al.  Machine learning used by Personal WebWatcher , 1999 .

[15]  Katia P. Sycara,et al.  WebMate: a personal agent for browsing and searching , 1998, AGENTS '98.