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Personal Name Resolution Crossover Documents by a Semantics-Based Approach

机译:基于语义的方法进行人名解析交叉文档

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Cross-document personal name resolution is the process of identifying whether or not a common personal name mentioned in different documents refers to the same individual. Most previous approaches usually rely on lexical matching such as the occurrence of common words surrounding the entity name to measure the similarity between documents, and then clusters the documents according to their referents. In spite of certain successes, measuring similarity based on lexical comparison sometimes ignores important linguistic phenomena at the semantic level such as synonym or paraphrase. This paper presents a semantics-based approach to the resolution of personal name crossover documents that can make the most of both lexical evidences and semantic clues. In our method, the similarity values between documents are determined by estimating the semantic relatedness between words. Further, the semantic labels attached to sentences allow us to highlight the common personal facts that are potentially available among documents. An evaluation on three web datasets demonstrates that our method achieves the better performance than the previous work.
机译:跨文档个人名称解析是识别不同文档中提到的通用个人名称是否指向同一个人的过程。先前的大多数方法通常都依赖词法匹配,例如实体名称周围常见词的出现,以测量文档之间的相似性,然后根据文档的引用对象对文档进行聚类。尽管取得了一些成功,但基于词汇比较的相似性度量有时会忽略语义级别上的重要语言现象,例如同义词或释义。本文提出了一种基于语义的方法来解决个人姓名交叉文档,该方法可以充分利用词汇证据和语义线索。在我们的方法中,文档之间的相似度值是通过估计单词之间的语义相关度来确定的。此外,附加在句子上的语义标签使我们能够突出显示文档之间潜在的常见个人事实。对三个Web数据集的评估表明,我们的方法比以前的工作具有更好的性能。

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