A multi-agent personalized ontology profile based query refinement approach for information retrieval
Qian Gao, Young Im Cho · 2013
This paper proposes a multi-agent query refinement approach to comprehensively track the users' behaviors. Based on the approach, this paper creates the personalized ontology profile, with which it refines and expands the users' initial query. We use four agents in our entire system. First, we use Client Agent to verify user identities by creating a union user account and to monitor whether a device is ready to run a personalized ontology profile creation task; then we use a Personalized Ontology Profile Agent to create a personalized ontology profile which not only can consider the Knowledge structure but also consider the users' behavior. Finally, we use a three level-strategy to expand the query automatically, and send back the retrieval results to the user. Based on the users' feedback, we reformulate the expanded query. We compare our method with the conceptual retrieval method as well as WordNet-based expansion, and we prove that our method has better average precision ratio.