【摘要】 随着本体在信息检索、人工智能等领域的广泛应用,面向本体的概念相似度计算成为了本体研究的一大热点。当前领域本体中概念相似度的研究主要是利用概念的上下位关系进行计算,但这并没有完整反映出概念的语义信息。论文提出的算法将概念相似度计算分为两层,一层是概念语义初始相似度层,其主要利用概念之间的距离来计算概念的初始相似度。另一层是概念非上下位关系相似度层,其在概念初始相似度的基础上,计算概念通过非上下位关系体现出的相似度。最后通过综合计算,得到领域本体中概念的实际相似度。实验证明,该方法充分利用了本体中概念的语义信息,得到的结果也比较合理。更多还原

【Abstract】 With the widespread application of ontology in the fields of information retrieval,artificial intelligence etc,the concept similarity computation of domain ontology has become the focus research field.Currently,most research on concept similarity computation is based on "is a" relation between concepts,however,it does not utilize the concept semantic information completely.The method proposed in the article divides the concept similarity computation into two levels. One is the layer of concept semantic initial similarity which computes the concept initial similarity based on the distance between concepts.The other one is the layer of concept non-hyponymy relationship similarity.Based on the concept initial similarity,it computes the similarity reflected by the non-hyponymy relations.And through integration computation,we can get the true concept similarity.The experiment shows that the method utilizes the concept semantic information fully and the computation result is reasonable.更多还原