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A Framework of Chinese Semantic Text Mining Based on Ontology Learning

机译:基于本体学习的中文语义文本挖掘框架

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摘要

Text mining and ontology learning can be effectively employed to acquire the Chinese semantic information. This paper explores a framework of semantic text mining based on ontology learning to find the potential semantic knowledge from the immensity text information on the Internet. This framework consists of four parts: Data Acquisition, Feature Extraction, Ontology Construction, and Text Knowledge Pattern Discovery. Then the framework is applied into an actual case to try to find out the valuable information, and even to assist the consumers with selecting proper products. The results show that this framework is reasonable and effective.
机译:可以有效地利用文本挖掘和本体学习来获取中文语义信息。本文探索了一种基于本体学习的语义文本挖掘框架,从互联网上的大量文本信息中寻找潜在的语义知识。该框架包括四个部分:数据获取,特征提取,本体构建和文本知识模式发现。然后将该框架应用于实际案例,以试图找出有价值的信息,甚至帮助消费者选择合适的产品。结果表明,该框架是合理有效的。

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