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A ontology semantic similarity algorithm between user's context ontology

机译:用户的上下文本体之间的本体语义相似性算法

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This paper considers a context similarity algorithm based on ontology semantic which recommends commodities to users by the similarity between current user's context and source context recorded. First, we divide the context ontology tree into many subtrees with subtree cutting algorithm. According to calculating the similarity of subtrees with the weight sum, we obtain the similarity between the source context and target context. Meanwhile, during calculating the similarity of subtrees, this paper allows for ontology semantic similarity, and adds the structure similarity degree algorithm on the basis of the old ontology similarity degree algorithm, which makes the result more accord with actual, and finally the experiment is verified.
机译:本文考虑了基于本体语义的上下文相似性算法,它通过当前用户的上下文和源上下文之间的相似性推荐给用户的商品。首先,我们将上下文本体树划分为具有子树切割算法的许多子树。根据计算具有权重和的子树的相似性,我们在源上下文和目标上下文之间获得相似性。同时,在计算子树的相似性期间,本文允许在本体语义相似性,并在旧本体相似度算法的基础上添加结构相似度算法,这使得结果更加符合实际,最后验证了实验。

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