Leveraging web services discovery with customizable hybrid matching

27Citations
Citations of this article
14Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Improving web service discovery constitutes a vital step for making a reality the Service Oriented Computing (SOC) vision of dynamic service selection, composition and deployment. Matching allows for comparing user requests with descriptions of available service implementations, and sits at the heart of the service discovery process. This paper firstly evaluates the efficacy of several key similarity metrics for matching syntactic, semantic and structural information from service interface descriptions, using a uniform corpus of web services. Secondly, it experiments with a hybrid style of matching that allows for blending various matching approaches and makes them configurable to cater service discovery given domain-specific constraints and requirements. © 2006 Springer-Verlag.

References Powered by Scopus

Similarity Search for Web Services

633Citations
N/AReaders
Get full text

Evaluating evaluation measure stability

434Citations
N/AReaders
Get full text

Structural and semantic matching for assessing web-service similarity

140Citations
N/AReaders
Get full text

Cited by Powered by Scopus

Improving Web service descriptions for effective service discovery

64Citations
N/AReaders
Get full text

Web service discovery based on goal-oriented query expansion

63Citations
N/AReaders
Get full text

Research review: A survey of approaches to Web Service discovery in service-oriented architectures

53Citations
N/AReaders
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Kokash, N., Van Den Heuvel, W. J., & D’Andrea, V. (2006). Leveraging web services discovery with customizable hybrid matching. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4294 LNCS, pp. 522–528). https://doi.org/10.1007/11948148_50

Readers over time

‘09‘10‘11‘12‘13‘17‘2102468

Readers' Seniority

Tooltip

PhD / Post grad / Masters / Doc 10

77%

Professor / Associate Prof. 2

15%

Researcher 1

8%

Readers' Discipline

Tooltip

Computer Science 12

92%

Business, Management and Accounting 1

8%

Save time finding and organizing research with Mendeley

Sign up for free
0