Automated Selection of Interesting Medical Text Documents by the TEA Text Analyzer
| Authors | |
|---|---|
| Year of publication | 2002 |
| Type | Article in Proceedings |
| Conference | Third International Conference on Intelligent Text Processing and Computational Linguistics CICLing-2002 Proceedings, Mexico City, February 2002. |
| MU Faculty or unit | |
| Citation | |
| Field | Use of computers, robotics and its application |
| Keywords | machine learnig; text-document classification; automated selection; unstructured text; Bayes classification; dictionary modification |
| Description | 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. |
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