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

Aleksieva-Petrova, Adelina, Minkov, Emilyan, and Petrov, Milen. "A Web Application for Text Document Classification Based on K-Nearest Neighbor Algorithm." Serdica Journal of Computing 11.2 (2017): 183-198. <http://eudml.org/doc/294958>.

@article{Aleksieva2017,
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.},
author = {Aleksieva-Petrova, Adelina, Minkov, Emilyan, Petrov, Milen},
journal = {Serdica Journal of Computing},
keywords = {Clustering; Document Analysis; Web-Based Services},
language = {eng},
number = {2},
pages = {183-198},
publisher = {Institute of Mathematics and Informatics Bulgarian Academy of Sciences},
title = {A Web Application for Text Document Classification Based on K-Nearest Neighbor Algorithm},
url = {http://eudml.org/doc/294958},
volume = {11},
year = {2017},
}

TY - JOUR
AU - Aleksieva-Petrova, Adelina
AU - Minkov, Emilyan
AU - Petrov, Milen
TI - A Web Application for Text Document Classification Based on K-Nearest Neighbor Algorithm
JO - Serdica Journal of Computing
PY - 2017
PB - Institute of Mathematics and Informatics Bulgarian Academy of Sciences
VL - 11
IS - 2
SP - 183
EP - 198
AB - 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.
LA - eng
KW - Clustering; Document Analysis; Web-Based Services
UR - http://eudml.org/doc/294958
ER -