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A semantic-based approach for querying linked data using natural language

机译:基于语义的使用自然语言查询链接数据的方法

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摘要

The semantic Web aims to provide to Web information with a well-defined meaning and make it understandable not only by humans but also by computers, thus allowing the automation, integration and reuse of high-quality information across different applications. However, current information retrieval mechanisms for semantic knowledge bases are intended to be only used by expert users. In this work, we propose a natural language interface that allows non-expert users the access to this kind of information through formulating queries in natural language. The present approach uses a domain-independent ontology model to represent the question's structure and context. Also, this model allows determination of the answer type expected by the user based on a proposed question classification. To prove the effectiveness of our approach, we have conducted an evaluation in the music domain using LinkedBrainz, an effort to provide the MusicBrainz information as structured data on the Web by means of Semantic Web technologies. Our proposal obtained encouraging results based on the F-measure metric, ranging from 0.74 to 0.82 for a corpus of questions generated by a group of real-world end users.
机译:语义Web旨在为Web信息提供明确定义的含义,并使其不仅可以被人类理解,还可以被计算机理解,从而可以跨不同应用程序自动化,集成和重用高质量信息。但是,当前用于语义知识库的信息检索机制仅打算由专家用户使用。在这项工作中,我们提出了一种自然语言界面,该界面允许非专家用户通过以自然语言编写查询来访问此类信息。本方法使用与领域无关的本体模型来表示问题的结构和上下文。而且,该模型允许基于提议的问题分类来确定用户期望的答案类型。为了证明我们方法的有效性,我们使用LinkedBrainz在音乐领域进行了评估,该工作旨在通过语义Web技术将MusicBrainz信息作为结构化数据提供到Web上。我们的建议基于F量度指标获得了令人鼓舞的结果,对于一组由现实世界中的最终用户产生的问题,其结果范围从0.74到0.82。

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