A Web Application for Text Document Classification Based on K-Nearest Neighbor Algorithm
Serdica Journal of Computing, Tome 11 (2017) no. 2, pp. 183-198.

Voir la notice de l'article dans Bulgarian Digital Mathematics Library

The paper gives insight on how the text document categorization problem can be solved and implemented in a software product. On that score, it specifies how input data are provided, processed and transformed into output data. The goal of the paper is not only to suggest a simple theoretical solution to the text document categorization problem but to provide a real-life implementation as part of a software system. ACM Computing Classication System (1998): H.3.3, H.3.5, I.7.5.
Mots-clés : Clustering, Document Analysis, Web-Based Services 
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Aleksieva-Petrova, Adelina; Minkov, Emilyan; Petrov, Milen. A Web Application for Text Document Classification Based on K-Nearest Neighbor Algorithm. Serdica Journal of Computing, Tome 11 (2017) no. 2, pp. 183-198. https://geodesic-test.mathdoc.fr/item/SJC_2017_11_2_a5/