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NET-LDA: a novel topic modeling method based on semantic document similarity
2020
Turkish Journal of Electrical Engineering and Computer Sciences
Topic models, such as latent Dirichlet allocation (LDA), allow us to categorize each document based on the topics. It builds a document as a mixture of topics and a topic is modeled as a probability distribution over words. However, the key drawback of the traditional topic model is that it cannot handle the semantic knowledge hidden in the documents. Therefore, semantically related, coherent and meaningful topics cannot be obtained. However, semantic inference plays a significant role in topic
doi:10.3906/elk-1912-62
fatcat:wx62lg46yfarpj5wik7mdpkiae