Construction of Academic Innovation Chain Based on Multi-level Clustering of Field Literature

Depth exploration and display of the potential correlation of innovation point can be helpful for relevant work such as field innovation discovery and field literature innovation evaluation. First, on the basis of the concept of academic innovation chain, the construction method of academic innovation chain based on multi-level clustering is proposed. Second, combining the text feature mining algorithms of tf-idf, LDA, doc2vec and the Kmeans text clustering algorithm, 639 literatures in the field of “knowledge element” are taken as examples clustering from the three levels of word frequency, topic and semantic. Final, fusion rule method with ALBERT pre-training model to extract the innovation points of literature, then the construction of academic innovation chain is realized. The academic innovation chain connects the originally isolated innovation point linearly. It provides certain references for the research of innovation evaluation and innovation metrics.