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<journal-id journal-id-type="publisher">global-journal-of-computer-science-and-technology-d-neural-ai</journal-id>
<journal-title-group>
<journal-title>Global Journal of Computer Science and Technology - D: Neural &amp; AI</journal-title>
</journal-title-group>
<issn publication-format="print">0975-4350</issn>
<issn publication-format="electronic">0975-4172</issn>
<publisher><publisher-name>Global Journals Publishing Group Incorporated</publisher-name></publisher>
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<article-id pub-id-type="publisher-id">73517</article-id>
<title-group>
<article-title>Assessing the Quality of a Software Service at the Time of Project Development by Identifying its Reputation</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author"><name><surname>Ch</surname><given-names>Dr. Panchamukesh</given-names></name><xref ref-type="aff" rid="aff1" />
</contrib>
<contrib contrib-type="author"><name><surname>B</surname><given-names>Venkateswarlu</given-names></name></contrib>
</contrib-group>
<aff id="aff1">INDIA, Avanthi Institute of Engineering &amp; Technology</aff>
<pub-date publication-format="electronic" date-type="pub" iso-8601-date="2011-09-29">
<day>29</day>
<month>09</month>
<year>2011</year>
</pub-date>
<volume>11</volume>
<issue>18</issue>
<fpage>31</fpage>
<lpage>36</lpage>
<abstract><p>At the time of integration of the software while developing a project the reputation and the quality of execution is tough to identify and which is very risky. As the software industry is introduced with a new type of service delivery model known as SaaS(Software as a service),the problem has increased a lot . Existing system be inclined to rely on rating from customer to experiences of past service which may create major issues in terms of subjectivity and rating unfairness. Few previous works have been considered quality and reputation for selection of services bur none have done service rating process through automation. We proposed an automated quality and reputation framework for rating and selecting a service. In this paper the management of risk has been formulated in context of development of the project using third party software service components and credibility is calculated by a measured reputation system.</p></abstract>
<kwd-group kwd-group-type="author-generated">
<kwd>Reputation</kwd>
<kwd>Service Vendor</kwd>
<kwd>Automation</kwd>
<kwd>SaaS</kwd>
<kwd>Service rating.</kwd>
</kwd-group>
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<title>Full Text</title>
<p>At the time of integration of the software while developing a project the reputation and the quality of execution is tough to identify and which is very risky. As the software industry is introduced with a new type of service delivery model known as SaaS(Software as a service),the problem has increased a lot . Existing system be inclined to rely on rating from customer to experiences of past service which may create major issues in terms of subjectivity and rating unfairness. Few previous works have been considered quality and reputation for selection of services bur none have done service rating process through automation. We proposed an automated quality and reputation framework for rating and selecting a service. In this paper the management of risk has been formulated in context of development of the project using third party software service components and credibility is calculated by a measured reputation system.</p>
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