Recommendations for selection process automation in systematic reviews
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Recommendations for selection process automation in systematic reviews

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This is a report providing recommendations for the selection process automation in systematic reviews. It is completed as part of an exam for the course "Empirical methods in Software Engineering".......

This is a report providing recommendations for the selection process automation in systematic reviews. It is completed as part of an exam for the course "Empirical methods in Software Engineering". Presented by Faisal Razzak.

The recommendations are based on the previous work described in "Linked Data approach for selection process automation in Systematic Reviews"

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  • 1. Report for the course “EmpiricalMethods in Software Engineering”. Faisal Razzak (faisal.razzak@polito.it)
  • 2.  What is Systematic Review? My Goal. Recommendations. Report for the course “Empirical Methods in Software Engineering”. -- Faisal Razzak
  • 3.  Literature review to answer a set of research questions. Pre-defined protocol for selecting and categorizing primary sources of literature. Objective evaluation of findings. Reducing subjectivity bias. Report for the course “Empirical Methods in Software Engineering”. -- Faisal Razzak
  • 4. 1. Identification of research2. Selection of studies3. Study Quality assessment4. Data extraction and Monitoring progress.5. Data synthesis. Report for the course “Empirical Methods in Software Engineering”. -- Faisal Razzak
  • 5.  Tomassetti et al. [2] proposed to semi- automate the selection process of studies (Step 2), to reduce manual work needed and the resulting subjectivity bias. This informal report provides recommendations to improve the work presented in [2]. [Note] The recommendations are based on reviewing the relevant paper and no development and testing have been performed. Report for the course “Empirical Methods in Software Engineering”. -- Faisal Razzak
  • 6.  To construct the bag of words model (M) from the initial set of sources (I0), ‘Related Work or Literature Review’ sections should be considered. These sections already provide the related papers discussing similar topics and their relevant titles, abstract and introduction should be used to construct M. Report for the course “Empirical Methods in Software Engineering”. -- Faisal Razzak
  • 7.  Moreover, many papers these days use ‘keywords’ to describe the content of the paper. It is not perfect but inclusion of some keywords from I0 might be helpful for model M. Bibbase [5] is also an important resource to extract paper information. Report for the course “Empirical Methods in Software Engineering”. -- Faisal Razzak
  • 8.  Each paper (wi) in I0 is processed to extract key phrases (K). Each key phrase (ki ε K) is linked to corresponding Dbpedia resource (if available). Besides Dbpedia, using resources like WordNet [8], MultiwordNet [7] or their Linked Data representations, i.e., GeoWordNet [4], WordNet [6] might be better. Report for the course “Empirical Methods in Software Engineering”. -- Faisal Razzak
  • 9.  These word databases provide a much better resource for getting the description of the concept and its possible equivalent concepts (key phrases). Moreover, if the operation has to be restricted to Linked Data, use of Sindice API [3] can ensure to search relevant concepts on Linked Data Cloud. Report for the course “Empirical Methods in Software Engineering”. -- Faisal Razzak
  • 10.  In current version, the bag of words contain words from all the statements of a resource. It might be better to find common property among such resources and only use it to construct key phrases. Report for the course “Empirical Methods in Software Engineering”. -- Faisal Razzak
  • 11. 1. B.Kitchenham, Procedures for performing systematic reviews. Technical Report, 2004.2. Tomassetti F., Rizzo G., Vetro A., Ardito L., Torchiano M., Morisio M. (2011) Linked Data approach for selection process automation in Systematic Reviews. In: 15th Annual Conference on Evaluation & Assessment in Software Engineering (EASE 2011), Durham City (UK), 11/04/2011-12/04/2011. pp. 31-353. http://sindice.com/4. http://geowordnet.semanticmatching.org/5. http://bibbase.org/6. http://www.w3.org/TR/wordnet-rdf/7. http://multiwordnet.fbk.eu/english/home.php8. http://wordnet.princeton.edu/ Report for the course “Empirical Methods in Software Engineering”. -- Faisal Razzak
  • 12. Faisal Razzak (Faisal.razzak@polito.it)