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PWA-PEM for Latent Tree Model and Hierarchical Topic Detection

Abstract : Hierarchical Latent Tree Analysis (HLTA) is a new method of topic detection. However, HLTA data input uses TF-IDF selection term, and relies on EM algorithm for parameter estimation. To solve this problem, a method of accelerating part of speech weight (PWA-PEM-HLTA) is proposed based on Progressive EM-HLTA (PEM-HLTA). Experimental results show that this method improves the execution efficiency of PEM-HLTA, averaging 4.9 times speed, and improves the speed of 6 times in the best case.
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Submitted on : Tuesday, July 30, 2019 - 5:02:08 PM
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Zhuchen Liu, Hao Chen, Jie Li, Yanhua Yu. PWA-PEM for Latent Tree Model and Hierarchical Topic Detection. 10th International Conference on Intelligent Information Processing (IIP), Oct 2018, Nanning, China. pp.183-191, ⟨10.1007/978-3-030-00828-4_19⟩. ⟨hal-02197798⟩

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