Fuzzy cognitive agents for personalized recommendation

There is an increasing need for various Web-service, e-commerce and e-business sites to provide personalized recommendations to on-line customers. This paper proposes a new type of personalized recommendation agents called fuzzy cognitive agents. Fuzzy cognitive agents are designed to give personalized suggestions based on the user´s current personal preferences, other user´s common preferences, and an expert´s domain knowledge. Fuzzy cognitive agents are able to represent knowledge via extended fuzzy cognitive maps, learn users´ preferences from most recent cases, and help customers make inferences and decisions through numeric computation instead of symbolic and logic deduction. A case study is included to illustrate how personalized recommendations are made by fuzzy cognitive agents in e-commerce sites. The case study demonstrates that the fuzzy cognitive agent is both flexible and effective in supporting e-commerce applications.