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针对跨语言环境下地理本体异构性强、本体实例重叠度低等特点,本文提出了一种半自动的地理本体匹配方法。通过概念化方法提取要素的本体属性,并用翻译工具将跨语言的本体属性转化为Word Net的语义集合,在此基础上进行本体属性的比较和本体概念的匹配。本方法以中国基础地理要素类型本体库和美国地质勘探局的地形图本体库的水系本体要素为依据进行了匹配实验,验证了方法的有效性。  相似文献   
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Volunteered geographic information (VGI) is generated by heterogenous ‘information communities’ that co-operate to produce reusable units of geographic knowledge. A consensual lexicon is a key factor to enable this open production model. Lexical definitions help demarcate the boundaries of terms, forming a thin semantic ground on which knowledge can travel. In VGI, lexical definitions often appear to be inconsistent, circular, noisy and highly idiosyncratic. Computing the semantic similarity of these ‘volunteered lexical definitions’ has a wide range of applications in GIScience, including information retrieval, data mining and information integration. This article describes a knowledge-based approach to quantify the semantic similarity of lexical definitions. Grounded in the recursive intuition that similar terms are described using similar terms, the approach relies on paraphrase-detection techniques and the lexical database WordNet. The cognitive plausibility of the approach is evaluated in the context of the OpenStreetMap (OSM) Semantic Network, obtaining high correlation with human judgements. Guidelines are provided for the practical usage of the approach.  相似文献   
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