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Concept-Based Automatic Amharic Document Categorization

机译:基于概念的自动阿姆哈拉语文档分类

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摘要

Along with the continuously growing volume of information resources, there is a growing interest toward better solutions for finding, filtering and organizing these resources. Automatic text categorization can play an important role in a wide variety of flexible, dynamic, and personalized information management tasks. The aim of this research work is to make use of concepts as a way of improving the categorization process for Amharic' documents. In recent years, ontology-based document categorization method is introduced to solve the problem of document classification. Previous works on keyword-based document categorization miss some important issues of considering semantic relationships between words. In order to resolve the existing problems, this research proposed a framework that automatically categorizes Amharic documents into predefined categories using concepts. The research shows that the use of concepts for an Amharic document categorizer results in 92.9% accuracy.
机译:随着信息资源量的不断增长,人们对寻找,过滤和组织这些资源的更好解决方案的兴趣日益浓厚。自动文本分类可以在各种灵活,动态和个性化的信息管理任务中发挥重要作用。这项研究工作的目的是利用概念来改进Amharic文档的分类过程。近年来,为了解决文档分类问题,引入了基于本体的文档分类方法。以前有关基于关键字的文档分类的著作缺少考虑单词之间语义关系的一些重要问题。为了解决现有的问题,本研究提出了一个框架,该框架使用概念将Amharic文档自动分类为预定义的类别。研究表明,将概念用于Amharic文档分类器可达到92.9%的准确性。

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