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Context-Based Recommendation Approach for Measurement and Evaluation Projects

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DOI: 10.4236/jsea.2010.312128    5,551 Downloads   9,921 Views   Citations


Data, information and knowledge are recognized as useful assets for analysis, recommendation and decision making at any business level of an organization. Providing the right information for decision making considering different user-requirements, projects and situations is, however, a difficult issue. A frequently-neglected challenge is to cope with the influence of contextual issues affecting the success of outcomes and decisions. Particularly, when conducting quality evaluations in software organizations, it is of paramount importance to identify beforehand the contextual issues affecting outcomes and interpretations for measurement and evaluation projects. Therefore, the relevant context information should be clearly identified, specified and recorded for performing more robust analysis and recommendations. In this work, a domain-independent context model and a mechanism to integrate it to any application domain is presented. The context model is built upon a measurement and evaluation framework enabling quantification and semantic capabilities. The context model is then integrated in the mentioned framework itself to enable recommendations in meas- urement and evaluation projects.

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The authors declare no conflicts of interest.

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H. Molina, L. Olsina and G. Rossi, "Context-Based Recommendation Approach for Measurement and Evaluation Projects," Journal of Software Engineering and Applications, Vol. 3 No. 12, 2010, pp. 1089-1106. doi: 10.4236/jsea.2010.312128.


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