| Full text | |
| Author(s): |
Felizardo, Katia R.
;
Salleh, Norsaremah
;
Martins, Rafael M.
;
Mendes, Emilia
;
MacDonell, Stephen G.
;
Maldonado, Jose C.
;
IEEE Comp Soc
Total Authors: 7
|
| Document type: | Journal article |
| Source: | 2011 FIFTH INTERNATIONAL SYMPOSIUM ON EMPIRICAL SOFTWARE ENGINEERING AND MEASUREMENT (ESEM 2011); v. N/A, p. 10-pg., 2011-01-01. |
| Abstract | |
Background: A systematic literature review (SLR) is a methodology used to aggregate all relevant existing evidence to answer a research question of interest. Although crucial, the process used to select primary studies can be arduous, time consuming, and must often be conducted manually. Objective: We propose a novel approach, known as 'Systematic Literature Review based on Visual Text Mining' or simply SLR-VTM, to support the primary study selection activity using visual text mining (VTM) techniques. Method: We conducted a case study to compare the performance and effectiveness of four doctoral students in selecting primary studies manually and using the SLR-VTM approach. To enable the comparison, we also developed a VTM tool that implemented our approach. We hypothesized that students using SLR-VTM would present improved selection performance and effectiveness. Results: Our results show that incorporating VTM in the SLR study selection activity reduced the time spent in this activity and also increased the number of studies correctly included. Conclusions: Our pilot case study presents promising results suggesting that the use of VTM may indeed be beneficial during the study selection activity when performing an SLR. (AU) | |
| FAPESP's process: | 08/02024-6 - PEx tool evolution to support systematic review |
| Grantee: | Rafael Messias Martins |
| Support Opportunities: | Scholarships in Brazil - Master |