Mining and searching association relation of scientific papers based on deep learning
For researchers needing to navigate scientific literature, this work proposes a deep learning approach to uncover paper associations, but the contribution appears incremental.
The paper addresses the problem of mining and searching association relations among scientific papers using deep learning, aiming to analyze scientific big data and serve researchers. No concrete results or numbers are provided.
There is a complex correlation among the data of scientific papers. The phenomenon reveals the data characteristics, laws, and correlations contained in the data of scientific and technological papers in specific fields, which can realize the analysis of scientific and technological big data and help to design applications to serve scientific researchers. Therefore, the research on mining and searching the association relationship of scientific papers based on deep learning has far-reaching practical significance.