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Received:November 29, 2015 Revised:January 04, 2016
Received:November 29, 2015 Revised:January 04, 2016
中文摘要: 进入21世纪以来,知识数据大量存储在文档中,但各类文档的粒度和结构不便于知识的加工、整合和管理. 如何从这些无序的、非结构化的数据(知识)源中提取语义,首要任务是将蕴藏在数据、信息中的知识抽取出来,建立文本资源的语义网,采用RDF来表示语义数据,其次采用TFIDF算法计算得出文本特征词的可信度,最后将文本信息录入到数据库中,实现文本类资源的自动分类,最终目的是实现文本资源知识的共享.
Abstract:Since the 21st century, much of the knowledge is stored in the document, but the size and structure of all kinds of documents do not facilitate knowledge processing, integration and management. How to extract semantics from the disordered, unstructured data (knowledge) is a task, the primary task is to extract knowledge which is contained in the data and information, to construct the semantic web which is based text resource, using RDF to represent indicate the semantic data, then using TFIDF algorithm to calculates the credibility of the key of the text, the last to enter text information in the database and to realize automatic text classification, ultimate goal is to realize knowledge sharing.
keywords: semantic web RDF TFIDF classification
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富宇,石金叶.基于语义的文本资源分类.计算机系统应用,2016,25(8):246-249
FU Yu,SHI Jin-Ye.Text Classification Based on Semantic.COMPUTER SYSTEMS APPLICATIONS,2016,25(8):246-249
富宇,石金叶.基于语义的文本资源分类.计算机系统应用,2016,25(8):246-249
FU Yu,SHI Jin-Ye.Text Classification Based on Semantic.COMPUTER SYSTEMS APPLICATIONS,2016,25(8):246-249