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Complex correspondences for query patterns rewriting

机译:查询模式重写的复杂对应关系

摘要

This paper discusses the use of complex alignments in the task of automatic query patterns rewriting. We apply this approach in SWIP, a system that allows for querying RDF data from natural language-based queries, hiding the complexity of SPARQL. SWIP is based on the use of query patterns that characterise families of queries and that are instantiated with respect to the initial user query expressed in natural language. However, these patterns are specific to the vocabulary used to describe the data source to be queried. For rewriting query patterns, we experiment ontology matching approaches in order to find complex correspondences between two ontologies describing data sources. From the alignments and initial query patterns, we rewrite these patterns in order to be able to query the data described using the target ontology. These experiments have been carried out on an ontology on the music domain and DBpedia ontology.
机译:本文讨论了自动查询模式重写任务中复杂对齐方式的使用。我们在SWIP中应用了这种方法,SWIP是一种系统,可以从基于自然语言的查询中查询RDF数据,从而隐藏了SPARQL的复杂性。 SWIP基于查询模式的使用,这些查询模式表征查询的族群,并且相对于以自然语言表示的初始用户查询实例化。但是,这些模式特定于用于描述要查询的数据源的词汇表。为了重写查询模式,我们尝试了本体匹配方法,以便在描述数据源的两个本体之间找到复杂的对应关系。根据对齐方式和初始查询模式,我们重写了这些模式,以便能够查询使用目标本体描述的数据。这些实验是在音乐领域的本体论和DBpedia本体论上进行的。

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