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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 and 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, p.~402-404. ISBN~3-540-43219-1.
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