Enhancing the Quality of Recommendations through Expert and Trusted Agents

In multi-agent recommender systems, agents are able to generate recommendations according to the preferences of the customer. However, in some domains, specific knowledge is required in order to compose a recommendation and this knowledge may be not available for the agent. In these cases, agents need to communicate with other agents in the community searching for the specific information to complete the recommendation. This paper presents a multi-agent recommender system based on trust and expert agents. It aims at improving the quality of the information exchanged among agents because communication will occur primarily with trusted sources in the hope to decrease the communication load. Also, agents become experts in specific types of recommendation. The approach was validate in the tourism domain by means of recommendations of travel packages and experiments were performed to illustrate the impact of using trust assignment in the quality of the recommendations generated by expert agents. Results corroborate the intuition that expert agents that use a trust mechanism are able to increase the quality of recommendation provided.

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