An Intelligent Recommender System for Web Resource Discovery and Selection

The Web is now evolving from information sharing to resource provision-ing as the emerging Web services and Grid technologies are widely ac-cepted and practiced. Soon the Web will be populated with abundant re-sources that can be accessed, shared and reused, which will inevitably lead to resource overflow. This chapter introduces a semantic-enabled, knowl-edge-based intelligent recommender system for Web resource discovery, selection and effective use. The system is based on a novel hybrid ap-proach, which draws on the functionality of Semantic Web Services to rep-resent, expose and discover available resources, and exploits domain knowledge to guide resource selection and use. We propose an integrated system architecture and describe the underpinning semantic- and knowl-edge-based recommending mechanisms. A number of technologies and tools are developed, and further applied to a real world application – the UK e-Science GEODISE project, to demonstrate the system’s applicability and benefits