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A node semantic similarity schema-matching method for multi-version Web Coverage Service retrieval

机译:用于多版本Web Coverage Service检索的节点语义相似性模式匹配方法

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摘要

Different versions of the Web Coverage Service (WCS) schemas of the Open Geospatial Consortium (OGC) reflect semantic conflict. When applying the extended FRAG-BASE schema-matching approach (a schema-matching method based on COMA++, including an improved schema decomposition algorithm and schema fragments identification algorithm, which enable COMA++-based support to OGC Web Service schema matching), the average recall of WCS schema matching is only 72%, average precision is only 82% and average overall is only 57%. To improve the quality of multi-version WCS retrieval, we propose a schema-matching method that measures node semantic similarity (NSS). The proposed method is based on WordNet, conjunctive normal form and a vector space model. A hybrid algorithm based on label meanings and annotations is designed to calculate the similarity between label concepts. We translate the semantic relationships between nodes into a propositional formula and verify the validity of this formula to confirm the semantic relationships. The algorithm first computes the label and node concepts and then calculates the conceptual relationship between the labels. Finally, the conceptual relationship between nodes is computed. We then use the NSS method in experiments on different versions of WCS. Results show that the average recall of WCS schema matching is greater than 83%; average precision reaches 92%; and average overall is 67%.
机译:开放地理空间联盟(OGC)的Web Coverage Service(WCS)模式的不同版本反映了语义冲突。当应用扩展的FRAG-BASE模式匹配方法(基于COMA ++的模式匹配方法,包括改进的模式分解算法和模式片段识别算法,使基于COMA ++的支持OGC Web Service模式匹配)时,平均召回率WCS方案匹配的比例仅为72%,平均精度仅为82%,总体平均水平仅为57%。为了提高多版本WCS检索的质量,我们提出了一种测量节点语义相似度(NSS)的模式匹配方法。该方法基于WordNet,合取范式和向量空间模型。设计了一种基于标签含义和注释的混合算法来计算标签概念之间的相似度。我们将节点之间的语义关系转换为命题公式,并验证该公式的有效性以确认语义关系。该算法首先计算标签和节点的概念,然后计算标签之间的概念关系。最后,计算节点之间的概念关系。然后,我们在不同版本的WCS的实验中使用NSS方法。结果表明,WCS模式匹配的平均召回率大于83%;平均精度达到92%;平均为67%。

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