Inference of recommendation information on the internet using improved FAM

摘要

This paper proposes a collaborative filtering system using Improved Fuzzy Associative Memory (IFAM) which re-adjusts the connection weights between the nodes of FAM using error back propagation and simplifies the fuzzy rules. The proposed technique automatically recommends 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 rates and suggests a recommendation set of items. The proposed system is implemented 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.