DocumentCode :
3029202
Title :
Towards evidence-based ontology for supporting Systematic Literature Review
Author :
Yueming Sun ; Ye Yang ; He Zhang ; Wen Zhang ; Qing Wang
Author_Institution :
Lab. for Internet Software Technol., Inst. of Software, Beijing, China
fYear :
2012
fDate :
14-15 May 2012
Firstpage :
171
Lastpage :
175
Abstract :
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.
Keywords :
case-based reasoning; knowledge acquisition; ontologies (artificial intelligence); software engineering; COSONT; SLR process; concept extraction; evidence-based ontology; extended SLRONT version; knowledge extraction; software engineering research method; structured abstracts; systematic literature review; ontology; software cost estimation; structured abstract; systematic literature review;
fLanguage :
English
Publisher :
iet
Conference_Titel :
Evaluation & Assessment in Software Engineering (EASE 2012), 16th International Conference on
Conference_Location :
Ciudad Real
Electronic_ISBN :
978-1-84919-541-6
Type :
conf
DOI :
10.1049/ic.2012.0022
Filename :
6272511
Link To Document :
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