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Text Classification Based on Topic Modeling and Chi-square

  • Yujia SunEmail author
  • Jan Platoš
Conference paper
  • 23 Downloads
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1107)

Abstract

This paper compares two topic modeling algorithms - Latent Dirichlet Allocation (LDA), Latent Semantic Index (LSI), and a feature selection algorithm chi-square to extract news feature words. After feature extraction, the three classifiers (Logistics Regression, Naive Bayes and SVM) are compared in news classification. Based on the test results, combined LSI and Logistics Regression gives the highest result compared to the other algorithms, with precision of 96% and recall of 95%.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.Technical University of OstravaOstrava-PorubaCzech Republic
  2. 2.Hebei GEO UniversityShijiazhuangChina

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