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Proceedings of the First International Conference on Computing, Communication and Control System, I3CAC 2021, 7-8 June 2021, Bharath University, Chennai, India
Topic models can give us a knowledge into the basic latent design of an enormous corpus of documents. A scope of strategies have been planned in the writing, including probabilistic topic models and methods dependent on matrix factorization. Notwithstanding, the subsequent topics frequently address just broad, in this manner excess information about the data instead of minor, yet possibly significant information to clients. To handle this issue, we propose a novel sparseness improvement modeldoi:10.4108/eai.7-6-2021.2308681 fatcat:mbr7yowkzbftvoirmxsnymrkby