Towards evidence-based ontology for supporting systematic literature review
Towards evidence-based ontology for supporting systematic literature review
- Author(s): Yueming Sun ; Ye Yang ; He Zhang ; Wen Zhang ; Qing Wang
- DOI: 10.1049/ic.2012.0022
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- Author(s): Yueming Sun ; Ye Yang ; He Zhang ; Wen Zhang ; Qing Wang Source: 16th International Conference on Evaluation & Assessment in Software Engineering (EASE 2012), 2012 p. 171 – 175
- Conference: 16th International Conference on Evaluation & Assessment in Software Engineering (EASE 2012)
- DOI: 10.1049/ic.2012.0022
- ISBN: 978-1-84919-541-6
- Location: Ciudad Real, Spain
- Conference date: 14-15 May 2012
- Format: PDF
Systematic Literature Review (SLR) has become an important software engineering research method but costs tremendous efforts. This paper proposes an approach to leverage on empirically evolved ontology to support automating key SLR activities. [Method]: First, we propose an ontology, SLRONT, built on SLR experiences and best practices as a groundwork to capture common terminologies and their relationships during SLR processes; second, we present an extended version of SLRONT, the COSONT and instantiate it with the knowledge and concepts extracted from structured abstracts. Case studies illustrate the details of applying it for supporting SLR steps. Results show that through using COSONT, we acquire the same conclusion compared with sheer manual works, but the efforts involved is significantly reduced. The approach of using ontology could effectively and efficiently support the conducting of systematic literature review.
Inspec keywords: knowledge acquisition; ontologies (artificial intelligence); case-based reasoning; software engineering
Subjects: Software engineering techniques; Knowledge engineering techniques
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