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Proposed a New Way -- Text Clustering Method based on Knowledge Base of the Satellite

机译:提出了一种新的方式 - 基于卫星知识库的文本聚类方法

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The establishment of Satellite Knowledge Base has a strategic, long-term guidance and overall importance. Since satellite every task phase generated information and data are often in the form of a semi-structured or unstructured, different from the traditional relational database in a structured form represented by data, with its unique properties, thus causing the text mining technology on the existing difficulties, often need to adopt different from structured data mining methods. Today, text mining has become a most important in data mining and sub-fields of prosperity. Inductive knowledge base on the information how to satellite, text information organization and management, effectively and quickly, accurately, comprehensively to find and tap, orientation and form of information that users need, promoted to knowledge, making it easy for users to search become the focus of many scholars studies, at the same time also is a focus in the study of this article. This paper proposes a related to natural language processing technology based on the text clustering semantic characteristics method. By means of semantic knowledge of dictionary to category extension of words, to a certain extent, reduce the characteristics of the synonymous, effectively improve the accuracy of the clustering results, so as to improve the management efficiency of text information of satellite knowledge base.
机译:建立卫星知识库具有战略性,长期的指导和总体重要性。由于卫星每个任务阶段生成的信息和数据通常以半结构化或非结构化的形式,以数据库为代表数据所代表的结构化形式的传统关系数据库,从而导致现有的文本挖掘技术困难,通常需要采用不同于结构性数据采矿方法。今天,文本挖掘在数据挖掘和繁荣的子领域成为最重要的。归纳知识基于信息,如何卫星,文本信息组织和管理,有效,快速,准确,全面地找到和点击用户需要的信息,促进知识,让用户易于搜索许多学者研究的焦点,同时也是对本文研究的关注。本文提出了基于文本聚类语义特征方法的自然语言处理技术相关。通过将字典的语义知识进行语义知识,在一定程度上,减少同义的特征,有效提高聚类结果的准确性,从而提高卫星知识库的文本信息的管理效率。

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