本体构建的粒计算学习模型

发布时间：2018-05-22 12:30

本文选题：粒计算 + 本体学习　；参考：《计算机工程与应用》2017年01期

【摘要】：粒计算的核心是粒子、粒层和粒结构。应用粒计算思想和本体论模型定义了本体粒和相容粒概念,给出了计算本体粒集和本体树的生成算法。该算法通过相容类产生初始本体粒集,应用本体粒的内涵分量IG扩展其他本体粒,最后联合关系分量RG和本体粒的关系构建本体粒集的格分层结构,借助加权树思想生成本体的概念树模型。经过中医喘证本体的实证研究,说明算法正确高效,为本体学习提供了很好的技术途径。
[Abstract]:The core of particle computing is particle, granular layer and grain structure. The concepts of ontology particle and compatible grain are defined by using the idea of granular computing and ontology model, and the algorithm of generating computational ontology particle set and ontology tree is given. In this algorithm, the initial ontology grains are generated by compatible classes, and other ontology grains are extended by using the connotation component IG of ontology grains. Finally, the lattice hierarchical structure of ontology grains is constructed by combining the relationship between relational components RG and ontology grains. The concept tree model of ontology is generated by the idea of weighted tree. Through the empirical study of TCM wheezing syndrome ontology, it shows that the algorithm is correct and efficient, and provides a good technical approach for ontology learning.
【作者单位】：华北理工大学理学院;
【基金】：国家自然科学基金(No.61370168) 河北省自然科学基金(No.F2014209238)
【分类号】：TP18

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