An ontological Proxy Agent with prediction, CBR, and RBR techniques for fast query processing

This paper proposed a three-tier Proxy Agent working as a mediator between the users and the backend process of a FAQ system. The first tier makes use of an improved sequential patterns mining technique to propose effective query prediction and cache services. The second tier employs an ontology-supported case-based reasoning technique to propose adapted query solutions and tune itself by retaining and updating highly-satisfied cases identified by the user. Finally, the third tier utilizes an ontology-supported rule-based reasoning to generate possible solutions for the user. Our experiments show around 79.1% of the user queries can be answered by Proxy Agent, leaving about 20.9% of the queries for the backend Answerer Agent to take care, which can effectively alleviate the overloading problem usually associated with a backend server.