Collaborative and evolutionary ontology development & its application in IM system for enhanced presence

Abstract

This research contributes to the field of ontology-based semantic matching techniques and also to the field of Instant Messaging (IM) based enhanced presence. It aims to achieve a mutually beneficial development of two fields through interactions in their use of data and their functionality. With respect to semantic matching this research has developed a collaborative and self-evolutionary approach based on user involvement in order to overcome disadvantages of traditional ontology-based approaches. At the same time, enhanced semantic matching algorithms were also explored and developed to achieve better performance when searching and querying through the ontology. In order to realize this automatic, dynamic and collaborative approach, a Jabber-based IM system was built to support its development with specific data and to evaluate its performance. In the prototype of the system, Computer Science area is selected to be the domain of the ontology in order to demonstrate the practicability of the new approach. With respect to enhanced presence an efficient semantic-based contacts search engine which can feature context-based search ranking is provided to support academic researchers. It is especially designed to help new academic researchers to find potential contacts who share a common research interest. It enriches the IM system’s presence information, and helps the user to pick the most suitable contacts and conveniently organize meetings or co-operating with others. Consequently, this research improves the efficiency of users’ academic researching, and extends users’ relationship radius during their academic research careers. The contributions are particularly highlighted by the comprehensive support during the academic user’s self-educational process.