Document ontology based personalized filtering system (poster session)

Authors:
Kyung-Sam Choi;Chi-Hoon Lee;Phill-Kyu Rhee
Affiliations:
IM Laboratory, In Ha Univ. Incheon, Korea;IM Laboratory, In Ha Univ. Incheon, Korea;IM Laboratory, In Ha Univ. Incheon, Korea
Venue:
MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
Year:
2000

Citing 2
Cited 3

Learning Probabilistic Relational Models

IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Syskill & webert: Identifying interesting web sites

AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1

MEMPHIS: a mobile agent-based system for enabling acquisition of multilingual content and providing flexible format internet premium services

Journal of Systems Architecture: the EUROMICRO Journal
Construction of Ontology-Based User Model for Web Personalization

UM '07 Proceedings of the 11th international conference on User Modeling
A knowledge-based model using ontologies for personalized web information gathering

Web Intelligence and Agent Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

We propose the use of the personalized ontology model to improve the effectiveness of web documents filtering process. One important feature of this model is that by constructing the user specific ontology, web documents can be classified by using the user oriented meta data that reflects the user's view about the documents concept. Another is that by applying the user model to searching the classified documents, we achieved the effective document search performance. To find the user's preference, Bayesian Learner accepts user's interests flow as an input and writes output to users profile. Based on those user profiles, user specific ontologies are constructed to provide efficient search environment.