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@inproceedings{378555,
author = {Žižka, Jan and Bourek, Aleš},
address = {Berlin, Heidelberg, Germany},
booktitle = {Third International Conference on Intelligent Text Processing and Computational Linguistics CICLing-2002 Proceedings, Mexico City, February 2002.},
keywords = {machine learnig; text-document classification; automated selection; unstructured text; Bayes classification; dictionary modification},
language = {eng},
location = {Berlin, Heidelberg, Germany},
isbn = {3-540-43219-1},
pages = {402-404},
publisher = {Springer-Verlag},
title = {Automated Selection of Interesting Medical Text Documents by the TEA Text Analyzer},
year = {2002}
}
TY - JOUR
ID - 378555
AU - Žižka, Jan - Bourek, Aleš
PY - 2002
TI - Automated Selection of Interesting Medical Text Documents by the TEA Text Analyzer
PB - Springer-Verlag
CY - Berlin, Heidelberg, Germany
SN - 3540432191
KW - machine learnig
KW - text-document classification
KW - automated selection
KW - unstructured text
KW - Bayes classification
KW - dictionary modification
N2 - The paper briefly describes the experience in the automated selection of interesting medical text documents by the TEA text analyzer based on the naive Bayes classifier. Even if the used type of the classifier provides generally good results, physicians needed certain supporting functions to obtain really interesting medical text documents, for example, from resources like the Internet. The influence of the functions is summarized and discussed. In addition, some remaining problems are mentioned.
ER -
ŽIŽKA, Jan a Aleš BOUREK. Automated Selection of Interesting Medical Text Documents by the TEA Text Analyzer. In \textit{Third International Conference on Intelligent Text Processing and Computational Linguistics CICLing-2002 Proceedings, Mexico City, February 2002.}. Berlin, Heidelberg, Germany: Springer-Verlag, 2002, s.~402-404. ISBN~3-540-43219-1.
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