A Collaborative Filtering System of Information on the Internet

Authors:
DongSeop Lee;HyungIl Choi
Affiliations:
-;-
Venue:
ICCS '02 Proceedings of the International Conference on Computational Science-Part III
Year:
2002

Citing 2
Cited 1

NN-driven fuzzy reasoning

International Journal of Approximate Reasoning
An algorithmic framework for performing collaborative filtering

Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval

AdROSA-Adaptive personalization of web advertising

Information Sciences: an International Journal

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Abstract

In this paper we describe a collaborative filtering system for automatically recommending high-quality information to users with similar interests on arbitrarily narrow information domains. It asks a user to rate a gauge set of items. It then evaluates the user's ratings and suggests a recommendation set of items. We interpret the process of evaluation as an inference mechanism that maps a gauge set to a recommendation set. We accomplish the mapping with FAM (Fuzzy Associative Memory). We implemented the suggested system in a Web server and tested its performance in the domain of retrieval of technical papers, especially in the field of information technologies. The experimental results show that it may provide reliable recommendations.