Authors:
Erdem S. Ilhan
;
Gokay B. Akkus
and
Ayse B. Bener
Affiliation:
Bogazici University, Turkey
Keyword(s):
Matchmaking, semantic similarity, scoring, ranking, OWL-S, bi-partite graph, scoring, semantic distance.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
e-Business
;
Enterprise Information Systems
;
Enterprise Software Technologies
;
Global Communication Information Systems and Services
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Knowledge Engineering
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Knowledge-Based Systems Applications
;
Software Engineering
;
Symbolic Systems
;
Telecommunications
;
Web and Mobile Business Systems and Services
;
Web Technologies and Web Services
Abstract:
In recent years Semantic Web has drawn a lot of attention in order to solve the problem of automatic discovery and processing of web services. Although there are different efforts and frameworks for semantic annotation and discovery of web services, they mostly classify the discovered web services as set-based. Improvement in matching process could be gained by the use of ontological information in a useful form. The goal of this research is to propose a more accurate discovery method using the ontological distance information defined and ranked by users. In this paper, we focus on one of the most challenging tasks in service discovery: matchmaking process. We use an efficient matchmaking algorithm based on bi-partite graphs. Our proposed algorithm uses attribute ranking through weight assignment. Our experiment results show that bi-partite matchmaking has advantages over other approaches in the literature for parameter pairing problem. We present value added approaches in matchmakin
g such as property-level matching, semantic distance information and WordNet scoring. The value added approaches provide better scoring scheme and allows similarity to be captured resulting in ranking of services according to their relatedness.
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