Research on the mining of ideological and political knowledge elements in college courses based on the combination of LDA model and Apriori algorithm

• Published in: Applied mathematics and nonlinear sciences Vol. 8; no. 1; pp. 2345 - 2356
• Main Author: Wang, Long
• Format: Journal Article
• Language: English
• Published: Beirut Sciendo 01.01.2023; De Gruyter Brill Sp. z o.o., Paradigm Publishing Services
• Subjects: Algorithms; Apriori algorithm; Curricula; Ideological and political knowledge element; Ideology; Knowledge; LDA model; Mapping of knowledge domain
• ISSN: 2444-8656; 2444-8656
• DOI: 10.2478/amns.2021.2.00190

In recent years, mapping of knowledge domain and political knowledge has developed rapidly and gradually penetrated into many practical applications. The construction of an ideological and political knowledge framework for colleges has become one of the important applications. Therefore, commencing with the theory of mapping of knowledge domain, and aiming at resolving the difficulty involved in effectively extracting and analysing ideological and political knowledge, a mining method for ideological and political knowledge elements is constructed in this paper, based on LDA model and Apriori algorithm. By setting a three-dimensional matrix of keywords and association rules, an algorithm for mining of ideological and political knowledge elements is proposed, where LDA model is used to acquire ideological and political subject words, and Apriori algorithm is used to discover tacit ideological and political knowledge. It is helpful to solve the problem of excavation and presentation of ideological and political elements in college curriculum, serve the ideological and political construction of curriculum, which is of great significance to dredge students’ learning paths and reduce learners’ learning cost.