A Web Application for Text Document Classification Based on K-Nearest Neighbor Algorithm

Authors

  • Adelina Aleksieva-Petrova Computer Systems Department Faculty of Computer Systems and Technologies Technical University of Sofa 8, St. Kliment Ohridski Blvd 1000 Sofa, Bulgaria
  • Emilyan Minkov Faculty of German Engineering Education and Industrial Management Technical University of Sofa 8, St. Kliment Ohridski Blvd 1000 Sofa, Bulgaria
  • Milen Petrov Department of Software Engineering Faculty of Mathematics and Informatics St. Kliment Ohridski University of Sofia 5, J. Baurchier Blvd 1164 Sofia, Bulgaria

DOI:

https://doi.org/10.55630/sjc.2017.11.183-198

Keywords:

Clustering, Document Analysis, Web-Based Services

Abstract

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.

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Published

2018-02-23

Issue

Vol. 11 No. 2 (2017)

Section

Articles