Discovery and Visualization of Expertise Evolution and Tendency
This paper presents a technique to discover expertise in research topics that authors have been contributed over the time through their publications. The process starts with typical natural language processing, followed by a topic modeling technique to extract the annual contribution in research topics and the discovery of evolution and tendency for a particular author. A bubble graph for expertise evolution and tendency is drawn over the year. The visualization can improve the perception of research topic evolution for a particular author, which will then be used to form a network of researchers in a particular area. This will support research collaboration in future.
2018 10th International Conference on Knowledge and Smart Technology (KST)