Semantic Matchmaking with Expressive Preference Representation

Grafting semantic technologies into electronic commerce brings new opportunities for the application of knowledge representation techniques originally devised for isolated and standalone knowledge bases. In this talk, I focus on matchmaking, a basic discovery method for commerce opportunities. Surfing the Internet for a used car, a new personal computer, or a room to share can be a tedious and time-consuming activity. I show how such tasks can be partially automated by providing agents with expressive languages for stating their preferences, and employing reasoning services that perform semantic matching between buyers' wants and sellers' offerings.

The result of such a matchmaking process is an ordered list of promising matches, coupled with logical explanations of the matchmaking result. In this way the user is supported in the discovery phase as opportunities are ranked based on their semantic similarity with respect to specified preferences.

Azzurra Ragone received the Master of Science degree with honors in Management Engineering from Politecnico di Bari in 2004. She is currently pursuing her PhD degree in Information Engineering at Politecnico di Bari, Italy. Her research interests are in the area of automatic Web services discovery and composition and automated knowledge-based matchmaking and negotiation in electronic commerce.

She coauthored the paper "concept Covering for Automated Building Blocks Selection based on Business Processes Semantics" that received the best paper award at theJoint 8th IEEE Conference on E-Commerce Technology (CEC' 06) and 3rd IEEE Conference on Enterprise Computing, E-Commerce and E-Services (EEE' 06). She is currently visiting scholar at the AI Laboratory of the University of Michigan.