An Academic Information Retrieval System Based on Multiagent Framework

In real-life searches in information, a set of information retrieved by a query influences user’s knowledge. Usually this influence inspires the user with new ideas and new conception of the query. As a result, the search in information is iterated while the user’s query is continually shifting in part or whole. This sort of search is called an “evolving search,” and it performs an important role also in academic information retrieval. To support the utilization of digital academic information, this paper proposes a novel system for academic information retrieval. In the proposed system, which is based on a multiagent framework, each piece of academic information is structured as an agent and provided with autonomy. Consequently, since a search is iterated by academic information itself, part of an evolving search is entrusted to the system, and the user’s load to retrieve academic information can be reduced effectively.