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

Voir la notice de l'article dans European 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.*The research presented in this paper was partially supported by the project FNI-SU- 2017/80 10-128 (St. Kliment Ohridski University of Sofia, Bulgaria) Secure and re-usable software architectures for Technology-enhanced learning.
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, p. 183. https://geodesic-test.mathdoc.fr/item/SJC_2017__11_2_294958/