CAJ | 학술논문

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。
표시화관리해량어의신식중소은함영역지식적방법시제약수거알굴기술발전화신식계통연발적핵심문제。통과분석본체도어의항특정화어의항지간적상관성대지식표시적영향,제출일충평개어의항중요도적신표준,건립일투도량어의항지간상관성적신책략,진이제출종어의신식망중구건최대상관본체도적신산법,운용차산법생성적본체도능구경가준학지표시영역지식,병차최소화본체생성과정중적인위교호。
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.