Using Visual Text Mining to Support the Study Selection in Systematic Literature Reviews
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 manual...
Disimpan dalam:
| Pengarang-pengarang Utama: | , , , , , |
|---|---|
| Format: | Conference or Workshop Item |
| Bahasa: | English |
| Diterbitkan: |
2011
|
| Subjek-subjek: | |
| Capaian Atas Talian: | http://irep.iium.edu.my/9035/ http://irep.iium.edu.my/9035/1/ESEM2011%28Salleh%29.pdf |
| Penanda-penanda: |
Tambah Penanda
Tiada Penanda, Jadilah orang pertama menanda rekod ini!
|
| Ringkasan: | 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. |
|---|