학술논문

Detection of Research Trends using Dynamic Topic Modeling
Document Type
Conference
Source
2022 7th International Conference on Data Science and Machine Learning Applications (CDMA) CDMA Data Science and Machine Learning Applications (CDMA), 2022 7th International Conference on. :157-162 Mar, 2022
Subject
Computing and Processing
Analytical models
Correlation
Decision making
Machine learning
Data science
Market research
Data models
Topic Modeling
Research trend
LDA
DTM
Language
Abstract
Discovering trends in research areas is helpful for researchers in finding the recent advances in a field or area of research. In addition, policy makers in universities can utilize this information in decision making. Different factors have direct influence on the growth and evolution of research topics. These include the funding, community interest and national needs. In this paper, we propose an unsupervised Dynamic Topic Modeling approach to discover and analyze the most trending research topics in a set of research areas using a collection of publications from the corresponding research areas. Furthermore, we study the correlation between emerging research trends and the different influencing factors.