Topic Mining Analysis Based on the LDA Model for Petroleum Engineering Texts
Pengpeng Gao, Zihan Xu · 2024
Latent Dirichlet Allocation (LDA) emerged as a new Topic model in Text Analysis, Data Mining, and Machine Learning. This paper presents a method for a topic model based on the LDA algorithm and the construction of a petroleum engineering text. The ten topics were obtained according to the corresponding characteristic words of the topics by the LDA method, and the study of high-frequency vocabulary and word clouds revealed the research text. In the future, machine learning, semantic web strategy, DTM dynamic Topic model, and other analysis technologies can be used to expand the breadth and depth of research fields.