TY - JOUR
T1 - Topic Mapping Approach To Automatic Classification Of Scientific Literature
T2 - A Study On Ecg Monitoring Systems
AU - Ismail, Heba
AU - El Kassabi, Hadeel T.
AU - Serhani, Mohamed Adel
N1 - Publisher Copyright:
© Technomathematics Research Foundation
PY - 2021
Y1 - 2021
N2 - With the significant growth in the number of research papers published in several fields, manual analysis of literature is becoming a resource-consuming and expensive process. This in turn accentuates the need for automated solutions. Hence, we propose an automatic classification approach to scientific literature based on factor analysis and topic enrichment techniques. This framework supports researchers in identifying the main themes and research topics in their areas of research early on before conducting an exhaustive, time-consuming manual review of the literature. The results of the proposed framework lead to a well-informed and focused manual review process later in the research cycle. We illustrated the proposed example with a working example focused on ECG monitoring systems. We further validate the proposed framework with a third-party literature classification tool as well as with an expert’s taxonomy. Validation reveals that the proposed framework generates thematic clusters highly correlated with research themes generated by the third-party tool as well as with the expert’s taxonomy
AB - With the significant growth in the number of research papers published in several fields, manual analysis of literature is becoming a resource-consuming and expensive process. This in turn accentuates the need for automated solutions. Hence, we propose an automatic classification approach to scientific literature based on factor analysis and topic enrichment techniques. This framework supports researchers in identifying the main themes and research topics in their areas of research early on before conducting an exhaustive, time-consuming manual review of the literature. The results of the proposed framework lead to a well-informed and focused manual review process later in the research cycle. We illustrated the proposed example with a working example focused on ECG monitoring systems. We further validate the proposed framework with a third-party literature classification tool as well as with an expert’s taxonomy. Validation reveals that the proposed framework generates thematic clusters highly correlated with research themes generated by the third-party tool as well as with the expert’s taxonomy
KW - ECG monitoring systems
KW - Topic mapping
KW - automatic classification
KW - cluster
KW - factor analysis
UR - http://www.scopus.com/inward/record.url?scp=85104707753&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85104707753&partnerID=8YFLogxK
M3 - Article
AN - SCOPUS:85104707753
SN - 0972-9038
VL - 18
SP - 116
EP - 134
JO - International Journal of Computer Science and Applications
JF - International Journal of Computer Science and Applications
IS - 1
ER -