A semantic relatedness measurement method based on domain ontology considering all relationships

Zhang Rui, Song Yan, Duan Yong-xuan, Shang Zhao-Xia
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引用次数: 0

Abstract

The rapid expansion of information and knowledge requires a various applications in computational linguistics and artificial intelligence employing semantic similarity to solve challenging tasks, such as information retrieval, text classification, machine translation, document clustering and so on. Today ontology is an extremely essential approach mainly used to represent acquired knowledge as well as to ensure data and knowledge integration. In this situation, a comprehensive semantic similarity measure is required. We propose a semantic relatedness calculation method that considers all the relationships including common and different attributes relations between concepts. To demonstrate the benefits of exploiting all the relations in domain ontology, we use four method for comparison. The results of our proposed method demonstrate an improvement over the benchmark semantic similarity methods.
一种考虑所有关系的基于领域本体的语义相关度度量方法
信息和知识的快速扩展需要在计算语言学和人工智能中应用语义相似度来解决具有挑战性的任务,如信息检索、文本分类、机器翻译、文档聚类等。今天,本体是一种非常重要的方法,主要用于表示已获得的知识,并确保数据和知识的集成。在这种情况下,需要一个综合的语义相似度度量。提出了一种考虑概念间所有关系的语义关联计算方法,包括概念间的共同属性关系和不同属性关系。为了证明利用领域本体中所有关系的好处,我们使用四种方法进行比较。结果表明,该方法比基准语义相似度方法有了改进。
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