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Editor-in-chief
Dr. Lin Huang
Metropolitan State University of Denver, USA
It's my honor to take on the position of editor in chief of IJMLC. We encourage authors to submit papers concerning any branch of machine learning and computing.
IJMLC 2013 Vol.3(3): 279-283 ISSN: 2010-3700
DOI: 10.7763/IJMLC.2013.V3.320

Service Identification in SMEs: Appropriate Elements and Methods

Ali Taei Zadeh, Shahnorbanun Sahranb, and Muriati Mukhtar
Abstract—Implementing SOA in big enterprises are subjected to serious challenges such as a lack of comprehensive service governance road map and appropriate service identification method however the overall number of successes in service oriented solutions is increasing. Small medium enterprises (SME) on the other hand have specific challenges and problems that is peculiar to their nature. They have encountered serious problems in service modeling. Lack of researches in Service Identification is one of the first problem that an SME encounters when starting a SOA migration. Although a number of service identification methods have been proposed but they did not consider the SME challenges in those methods. Also the majority of those methods only considered the management point of view without considering a deep technical view. To fill this gap, this paper review existing service identification methods and proposes an improved method for identification of services based on SMEs specification and challenges.

Index Terms—Service identification method, SME, SOA, criteria.

A. T. Zadeh is with the UKM university, FTSM, Bangi 43000, Malaysia (e-mail: alitaee@gmail.com). S. Sahranb and M. Mukhtar are with the Department of Industrial Computing, UKM university, FTSM, Bangi 43000, Malaysia (e-mail:shah@ftsm.ukm.my, mm@ftsm.ukm.my).

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Cite:Ali Taei Zadeh, Shahnorbanun Sahranb, and Muriati Mukhtar, "Service Identification in SMEs: Appropriate Elements and Methods," International Journal of Machine Learning and Computing vol.3, no. 3, pp. 279-283, 2013.

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