Knowledge-based information retrieval: The IKF project

Abstract

The Internet has become the leading information delivery medium in our days, yet it represents a huge, heterogeneous and distributed network from the point of view of information retrieval. Numerous software systems have appeared in the past years to support the automated information retrieval processes, applying useful information and knowledge retrieval techniques. Nevertheless, the core services of these systems do not provide real knowledge representation methods. The aim of our research is to design and develop a complete information and knowledge management system that applies integrated state-of-the-art knowledge intensive techniques. The research is part of the IKF project at the Department of Measurement and Information Systems of the Budapest University of Technology and Economics (BUTE) aims to analyze, design and implement a new intelligent knowledge-warehousing environment, allowing advanced knowledge management and decision support. The development is targeted towards specific financial application domain. This paper intends to provide a short review of knowledge-based information retrieval and extraction, and knowledge presentation technologies through the brief discussion of the project and the realized application. First, we present the architecture and the main features of the complete knowledge-based retrieval system. Then we focus on two major subjects: the document retrieval and information extraction system as well as the ontology-based knowledge management services. We also introduce some related topics briefly, such as structured information extraction with web wrappers, XML, and conceptualization with ontologies. Besides theory, we show some experimental results of the realized software systems.