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Domain-Specific Semantic Relatedness from Wikipedia Structure: A Case Study in Biomedical Text

机译:维基百科结构的域特异性语义相关性:生物医学文本的案例研究

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Wikipedia is becoming an important knowledge source in various domain specific applications based on concept representation. This introduces the need for concrete evaluation of Wikipedia as a foundation for computing semantic relatedness between concepts. While lexical resources like WordNet cover generic English well, they are weak in their coverage of domain specific terms and named entities, which is one of the strengths of Wikipedia. Furthermore, semantic relatedness methods that rely on the hierarchical structure of a lexical resource are not directly applicable to the Wikipedia link structure, which is not hierarchical and whose links do not capture well defined semantic relationships like hyponymy. In this paper we (1) Evaluate Wikipedia in a domain specific semantic relatedness task and demonstrate that Wikipedia based methods can be competitive with state of the art ontology based methods and distributional methods in the biomedical domain (2) Adapt and evaluate the effectiveness of bibliometric methods of various degrees of sophistication on Wikipedia (3) Propose a new graph-based method for calculating semantic relatedness that outperforms existing methods by considering some specific features of Wikipedia structure.
机译:维基百科正在成为基于概念表示的各个领域特定应用程序的重要知识来源。这介绍了对维基百科的具体评估需要作为计算概念之间语义相关性的基础。虽然词条资源如Wordnet覆盖通用英语,但它们的域名特定条款和命名实体的覆盖范围很弱,这是维基百科的优势之一。此外,依赖于一个词汇资源的层次结构语义相关方法并不直接适用于维基百科的链接结构,这是不分层,其链接不捕获像下义关系明确的语义关系。在本文中,我们(1)评估维基百科在一个特定领域的语义关联的任务,并表明维基百科为基础的方法可以与艺术本体论在生物医学领域(2)适应基础的方法和分配方法的国家竞争力和评价文献计量学的有效性Wikipedia(3)上各种程度的方法提出了一种新的基于图表的方法,用于计算语义相关性,以考虑维基百科结构的一些特定特征来实现现有方法。

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