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Named entity recognition for tamil biomedical documents

机译:命名为泰米尔生物医学文件的实体识别

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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有价值的信息,可以各种形式提供书籍,杂志和网站。然而,这些说明非常大而非结构化。我们的系统侧重于使用SVM分类器构造一个NER识别模块,以识别命名实体并将它们分类为它们的相应类别。考虑的两种主要类别是使用的障碍名称和使用成分的名称。该系统使用Unigrams / Bigrams,案例标记,子字符串线索和TF-IDF分数等功能,以将实体分类为其类。这些命名实体基于其类别存储在网元字典中。

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