Publication Topic Selection Algorithm Based on Association Analysis
In the process of traditional education publishing, publication topic selection is completed by subjective experience of editorial team, which is difficult for editorial team to take into account complex factors such as needs of readers, knowledge update and market change. A large number of teaching materials are unsalable and publications can hardly meet actual needs of reader and market. Theme and content of traditional textbooks are lagging behind, which are difficult to meet the needs of today’s education development. To solve these problems, this paper focuses on Publication topic selection algorithm based on association analysis. First of all, an algorithm for automatically acquiring data and information from web pages is designed. Then, this paper designs similarity degree calculation method, score prediction algorithm and prediction score updating algorithm. Finally, effectiveness of the algorithm is verified by experiments.
KeywordsPublication Topic selection Association analysis
This work was supported by the Curriculum construction project-Linux Program design (22150118005/014), doctoral research funding (04190117003/044), Construction of school teachers- doctoral research funding (27170118003/007), Construction of the publication data asset evaluation platform (04190118002/039) and Construction of computer science and technology in predominant construction (22150118010/006) and Printing electronic technology (Collaborative innovation) (PXM2017_014223_000055).
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