A systematic review on literature-based discovery: General overview, methodology, & statistical analysis

Resource type
Journal Article
Authors/contributors
Title
A systematic review on literature-based discovery: General overview, methodology, & statistical analysis
Abstract
The vast nature of scientific publications brings out the importance of Literature-Based Discovery (LBD) research that is highly beneficial to accelerate knowledge acquisition and the research development process. LBD is a knowledge discovery workflow that automatically detects significant, implicit knowledge associations hidden in fragmented knowledge areas by analysing existing scientific literature. Therefore, the LBD output not only assists in formulating scientifically sensible, novel research hypotheses but also encourages the development of cross-disciplinary research. In this systematic review, we provide an in-depth analysis of the computational techniques used in the LBD process using a novel, up-to-date, and detailed classification. Moreover, we also summarise the key milestones of the discipline through a timeline of topics. To provide a general overview of the discipline, the review outlines LBD validation checks, major LBD tools, application areas, domains, and generalisability of LBD methodologies. We also outline the insights gathered through our statistical analysis that capture the trends in LBD literature. To conclude, we discuss the prevailing research deficiencies in the discipline by highlighting the challenges and opportunities of future LBD research.
Publication
ACM Computing Surveys
Volume
52
Issue
6
Pages
129:1–129:34
Date
December 10, 2019
Journal Abbr
ACM Comput. Surv.
ISSN
0360-0300
Short Title
A systematic review on literature-based discovery
Accessed
18/01/2024, 22:37
Library Catalogue
ACM Digital Library
Citation
Thilakaratne, M., Falkner, K., & Atapattu, T. (2019). A systematic review on literature-based discovery: General overview, methodology, & statistical analysis. ACM Computing Surveys, 52(6), 129:1-129:34. https://doi.org/10.1145/3365756