Research on Interdisciplinary Subject Recognition Based on Feature Measure and PhraseLDA Model——Taking Application of Nanotechnology in Agricultural Environment for Example
Zhang Zhenqing,Sun Wei
(Institute of Agricultural Information, Chinese Academy of Agricultural Sciences, Beijing 100081, China)
[Objective] To identify the interdisciplinary subjects based on the feature measure method and PhraseLDA model.
[Methods] Through the analysis of the interdisciplinary characteristics of subjects, the measurement index system of interdisciplinary subjects was constructed, and the interdisciplinary subjects were identified in combination with the PhraseLDA model. Finally, an empirical study was carried out in the field of agricultural environmental application of nanotechnology.
[Results] A total of 24 cross topics were objectively identified, including catalyst preparation, soil bioremediation and so on. Compared with traditional identification methods, the cross topic recognition rate of the proposed method was increased by 71.4%, and the recognition rate of fine-grained topics was increased by 42.86%.
[Limitations] The number of topics and interdisciplinary topic identification indicators of PhraseLDA topic model are set after repeated calculation and debugging. Therefore, the proposed method has a certain dependence on the rationality of the setting of relevant thresholds.
[Conclusions] The method proposed in this paper can effectively identify interdisciplinary topics in the field and provide auxiliary reference for scientific decision-making and scientific and technological innovation research in related fields.
张振青, 孙巍.
基于特征测度和PhraseLDA模型的领域学科交叉主题识别研究——以纳米技术的农业环境应用领域为例
[J]. 数据分析与知识发现, 10.11925/infotech.2096-3467.2022-0651.
Zhang Zhenqing, Sun Wei.
Research on Interdisciplinary Subject Recognition Based on Feature Measure and PhraseLDA Model——Taking Application of Nanotechnology in Agricultural Environment for Example
. Data Analysis and Knowledge Discovery, 0, (): 1-.
