A Context-based Semantically Enhanced Information Retrieval Model

This paper approaches the use of both context and semantic information in the information retrieval process with the goal of developing context-based semantically enhanced infirmation retrieval systems. To achieve our objective we have identified, defined and formalized three distinct types of context information relevant for an information retrieval system: knowledge context information, user context information and constraint context information. The context information is represented in an information system interpretable way by mapping it onto our RAP context model elements. The proposed infirmation retrieval model is tested using the arhiNet system, our integrated information retrieval system for archive content, based on semantic enhancements.