A new approach for automatizing the analysis of research topics dynamics: application to optoelectronics research
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The objective of this paper is to propose a new unsupervised incremental approach in order to follow the evolution of research themes for a given scientific discipline in terms of emergence or decline. Such behaviors are detectable by various methods of filtering. However, our choice is made on the exploitation of neural clustering methods in a multi-view context. This new approach makes it possible to take into account the incremental and chronological aspects of information by opening the way to the detection of convergences and divergences of research themes at a large scale.
KeywordsDiachronic analysis Clustering Multiple viewpoint analysis Unsupervised learning Bayesian reasoning Neural networks
The author wishes to thanks Pascal Cuxac (INIST-CNRS) for his valuable help in the results validation task.
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