A semantic main path analysis method to identify multiple developmental trajectories

作者：

Highlights：

• A semantic main path analysis approach is put forward to identify simultaneously multiple developmental trajectories in a target field.

• To improve topical coherence of documents along a same trajectory, the conventional link weights are armed with the semantic information based ones.

• After all paths are enumerated effectively with a dynamic programming based search algorithm, a density-based clustering method is used to divide them into several groups.

• The source codes in Python language can be freely accessed at the GitHub and PyPi with detailed API documentation, thus to promote the related studies.

摘要

•A semantic main path analysis approach is put forward to identify simultaneously multiple developmental trajectories in a target field.•To improve topical coherence of documents along a same trajectory, the conventional link weights are armed with the semantic information based ones.•After all paths are enumerated effectively with a dynamic programming based search algorithm, a density-based clustering method is used to divide them into several groups.•The source codes in Python language can be freely accessed at the GitHub and PyPi with detailed API documentation, thus to promote the related studies.

论文关键词：Main path analysis,Developmental trajectory,Patent mining,Topic coherence,Lithium-ion battery

论文评审过程：Received 27 July 2021, Revised 10 March 2022, Accepted 17 March 2022, Available online 6 April 2022, Version of Record 6 April 2022.

论文官网地址：https://doi.org/10.1016/j.joi.2022.101281