Malaysian Journal of Computer Science (ISSN 0127-9084)
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Title:Using Suffix Tree Clustering Method To Support The Planning Phase Of Systematic Literature Review
Auhtor(s): Luyi Feng,Yin Kia Chiam,Erma Rahayu Mohd Faiza,Unaizah Obaidellah,
Journal:Malaysian Journal of Computer Science (ISSN 0127-9084)
Volume:30, No 4
Year:2017
Keywords:Systematic Literature Review (SLR), planning phase; decision-making, Suffix Tree Clustering (STC), text mining (TM)
Abstract:Systematic Literature Review (SLR) is an information-based process throughout which each stage must be carefully and systematically designed in planning phase. Important decisions need to be made about the various choices involved in the SLR planning phase. However, due to the necessarily comprehensive and rigorous nature of SLR, many researchers have difficulties in planning SLRs sufficiently and effectively. In recent decades, the use of text mining (TM) techniques has been introduced to facilitate SLR process, especially at conducting review phase to support the searching and selection of studies. However, so far, TM techniques have not been applied to support any activities during SLR planning phase. In this research, we proposed a method that apply Suffix Tree Clustering (STC) method to support decision-making activities within the SLR planning phase. This method also known as SLR Planning Based on Suffix Tree Clustering (SLRP-STC) method. It aims to help reviewers in three ways: 1) to extract research topics easily; 2) to better interpret extracted information; and 3) to quickly realize and refine a proposed search string that is poorly formulated or inappropriate. A case study was conducted by comparing the proposed method with manual approach. It is observed that the use of SLRP-STC method can improve the planning of SLR.
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