计算机科学 ›› 2016, Vol. 43 ›› Issue (10): 242-247.doi: 10.11896/j.issn.1002-137X.2016.10.046
郑志蕴,阮春阳,李伦,李钝
ZHENG Zhi-yun, RUAN Chun-yang, LI Lun and LI Dun
摘要： 本体语义相似度计算是解决语义网中语义异构的关键环节。通过对传统语义相似度计算方法的分析研究,引入本体层次结构,给出基于信息内容、距离、属性的语义相似度改进计算方法,并采用主成分分析法,提出一种自适应相似度综合加权计算方法(ACWA),以解决传统综合加权计算时人工赋权的不足。实验结果表明,提出的ACWA算法的计算结果与参照标准之间的皮尔森系数较传统算法平均高出了8.1%,有效提升了本体语义相似度计算的准确性。
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