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Using Dictionaries for Biomedical Text Classification

机译:使用字典进行生物医学文本分类

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The purpose of this paper is to study the use of dictionaries in the classification of biomedical texts. Experiments are conducted with three different dictionaries (BioCreative [13], NLPBA [8] and a subset of the UniProt database [4], named Protein) and three types of classifiers (KNN, SVM and Naive-Bayes) when they are applied to search on the PubMed database. Dictionaries have been used during the preprocessing and annotation of documents. The best results were obtained with the NLPBA and Protein dictionaries and the SVM classifier.
机译:本文的目的是研究字典在生物医学文本分类中的使用。使用三种不同的词典(BioCreative [13],NLPBA [8]和UniProt数据库的一个子集[4],称为Protein)和三种类型的分类器(KNN,SVM和Naive-Bayes)进行实验时,在PubMed数据库上搜索。在文档的预处理和注释过程中使用了词典。使用NLPBA和蛋白质词典以及SVM分类器可获得最佳结果。

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