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Automatic Categorization of Press Articles through Learning: The Case of Senegalese Online Press

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Abstract

Nowadays, the study of online press has become an issue of phenomenal research. From articles collections and merging, opinion mining, artificial intelligence or automatic classification to fact-checking; researches are developing and opening new perspectives. The main objective is to pave the way for the journalistic consumption of the future. However, though the literature review mentions previous studies on online press articles classification, no work on automatic classification of press articles based on a theme has been carried out yet. In this article, we set out a supervised classifier of journalistic articles applied on Senegalese online press.
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hal-02492483 , version 1 (27-02-2020)

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Edouard Ngor Sarr, Ousmane Sall, Mamadou Bousso, Rabiyatou Diouf, B. Birregah, et al.. Automatic Categorization of Press Articles through Learning: The Case of Senegalese Online Press. 2019 IEEE International Conference on Big Data (Big Data), Dec 2019, Los Angeles, United States. pp.6211-6213, ⟨10.1109/BigData47090.2019.9006070⟩. ⟨hal-02492483⟩
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