表示和管理海量语义信息中所隐含领域知识的方法是制约数据挖掘技术发展和信息系统研发的核心问题。通过分析本体图语义项特征和语义项之间的相关性对知识表示的影响，提出一种评价语义项重要度的新标准，建立一套度量语义项之间相关性的新策略，进而提出从语义信息网中构建最大相关本体图的新算法，运用此算法生成的本体图能够更加准确地表示领域知识，并且最小化本体生成过程中的人为交互。%The approach of presenting and managing the massive semantic information in implied domain knowledge is the main factor restricting the technical development of data mining and the research on information systems. By analyzing the features of ontology semantic items and the impact of the correlative semantic items on the knowledge representation, this paper puts forward a new standard of evaluating the importance of semantic items, establishes a new strategy of measuring the correlation between semantic items and proposes a new algo-rithm in building the most relevant ontology mapping in semantic web. The ontology created by this algorithm can represent domain knowledge more accurately and minimize the human interaction.
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