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Named entity recognition for tamil biomedical documents

机译:泰米尔生物医学文件的命名实体认可

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Valuable Information about tamil traditional medicines are available in various forms like books, magazines and websites. These instructions are however very large and unstructured. Our system focuses on constructing a NER identification module using SVM classifier to identify named entities and to classify them into their corresponding categories. The two main categories considered are name of disorders and name of ingredients used. The system uses features such as unigrams/bigrams, case markers, substring clues and tf-idf score to classify the entities into their classes. These named entities are stored in the NE Dictionary based on their categories.
机译:有关泰米尔传统药物的宝贵信息以各种形式提供,例如书籍,杂志和网站。但是,这些指令非常大且结构化。我们的系统着重于使用SVM分类器构建NER识别模块,以识别命名实体并将其分类为相应的类别。考虑的两个主要类别是疾病名称和所用成分的名称。系统使用诸如字母组合图/字母组合图,大小写标记,子字符串线索和tf-idf分数之类的功能将实体分类到其类别中。这些命名实体根据其类别存储在NE词典中。

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