Facet Annotation Using Reference Knowledge Bases
Facet Annotation Using Reference Knowledge Bases
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DOI：
10.1145/3178876.3186020
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发表时间：
2018-04
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影响因子：
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通讯作者：
R. Porrini;M. Palmonari;I. Cruz
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文献类型：
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作者：
R. Porrini;M. Palmonari;I. Cruz
分面界面在网络上无处不在，以支持数据探索和过滤。一个方面是一个三元组：一个域（例如，书）、财产（例如，作者、语言），以及一组属性值（例如，奥斯汀、波伏娃、科埃略、陀思妥耶夫斯基、艾柯、凯鲁亚克、苏斯金德......法语，英语，德语，意大利语，葡萄牙语，俄语，... ).给定一个属性（例如，语言），则选择一个或多个值（英语和意大利语）将返回与给定值（用英语或意大利语编写的书籍）匹配的域实体（Book类型）。为了以一种可扩展到非常大的数据集的方式实现面接口，有必要自动化面提取。先前的工作将方面域与一组齐次值相关联，但是没有注释方面属性。在本文中，我们从一个参考知识库（KB）的谓词，以最大限度地提高属性和谓词之间的语义相似性方面的属性进行注释。我们定义语义相似性的三个新的指标：特异性，覆盖率和频率。我们的实验评估使用DBpedia和YAGO知识库，并表明，对于方面的注释问题，我们获得了更好的结果比一个国家的最先进的方法，为Web表的注释修改为注释一组值。
Faceted interfaces are omnipresent on the web to support data exploration and filtering. A facet is a triple: a domain (e.g., Book), a property (e.g., author, language), and a set of property values (e.g., Austen, Beauvoir, Coelho, Dostoevsky, Eco, Kerouac, Suskind, ..., French, English, German, Italian, Portuguese, Russian, ... ). Given a property (e.g., language), selecting one or more of its values (English and Italian) returns the domain entities (of type Book) that match the given values (the books that are written in English or Italian). To implement faceted interfaces in a way that is scalable to very large datasets, it is necessary to automate facet extraction. Prior work associates a facet domain with a set of homogeneous values, but does not annotate the facet property. In this paper, we annotate the facet property with a predicate from a reference Knowledge Base (KB) so as to maximize the semantic similarity between the property and the predicate. We define semantic similarity in terms of three new metrics: specificity, coverage, and frequency. Our experimental evaluation uses the DBpedia and YAGO KBs and shows that for the facet annotation problem, we obtain better results than a state-of-the-art approach for the annotation of web tables as modified to annotate a set of values.