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Authors: Erdem S. Ilhan ; Gokay B. Akkus and Ayse B. Bener

Affiliation: Bogazici University, Turkey

ISBN: 978-989-8111-10-4

ISSN: 2184-4895

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 matchmaking 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. (More)

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Paper citation in several formats:
S. Ilhan E.; B. Akkus G.; B. Bener A. and (2007). IMPROVED SERVICE RANKING AND SCORING: SEMANTIC ADVANCED MATCHMAKER (SAM).In Proceedings of the Second International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE, ISBN 978-989-8111-10-4, pages 95-102. DOI: 10.5220/0002586700950102

@conference{enase07,
author={Erdem {S. Ilhan} and Gokay {B. Akkus} and Ayse {B. Bener}},
title={IMPROVED SERVICE RANKING AND SCORING: SEMANTIC ADVANCED MATCHMAKER (SAM)},
booktitle={Proceedings of the Second International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE,},
year={2007},
pages={95-102},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002586700950102},
isbn={978-989-8111-10-4},
}

TY - CONF

JO - Proceedings of the Second International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE,
TI - IMPROVED SERVICE RANKING AND SCORING: SEMANTIC ADVANCED MATCHMAKER (SAM)
SN - 978-989-8111-10-4
AU - S. Ilhan, E.
AU - B. Akkus, G.
AU - B. Bener, A.
PY - 2007
SP - 95
EP - 102
DO - 10.5220/0002586700950102

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