Intelligent query agent for structural document databases

Abstract

Querying a database for document retrieval is often a process close to querying an answering expert system. In this work, we apply the expert system techniques to the intelligent query agent establishment and regard the structural document database as the expertise which can be the objective of the knowledge acquisition. A new knowledge representation, named Structural Documents (SDs), is proposed to be the base of our model, and a transformation process from the raw data to the format of a database is applied. Based on the SDs, more suitable results could be inferenced rapidly by inference engine, and the flow of inference is also described. For implementation, an intelligent Chinese information retrieval system for personnel regulations by integrating knowledge-based and full-text searching techniques is proposed. In our experiments, the structural information of the documents can be acquired from the database using the knowledge extraction module. By observing the operating process of users, we found the query process of users are simplified.