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Entity-Based Data Source Contextualization for Searching the Web of Data

机译:基于实体的数据源上下文搜索数据网

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摘要

To allow search on the Web of data, systems have to combine data from multiple sources. However, to effectively fulfill user information needs, systems must be able to 'look beyond' exactly matching data sources and offer information from additional/contextual sources (data source contextualization). For this, users should be involved in the source selection process - choosing which sources contribute to their search results. Previous work, however, solely aims at source contextualization for 'Web tables', while relying on schema information and simple relational entities. Addressing these shortcomings, we exploit work from the field of data mining and show how to enable Web data source contextualization. Based on a real-world use case, we built a prototype contextualization engine, which we integrated in a system for searching the Web of data. We empirically validated the effectiveness of our approach - achieving performance gains of up to 29 % over the state-of-the-art.
机译:为了允许在数据Web上进行搜索,系统必须组合来自多个来源的数据。但是,为了有效满足用户信息需求,系统必须能够“超越”精确匹配的数据源,并提供来自其他/上下文源的信息(数据源上下文化)。为此,用户应参与来源选择过程-选择哪些来源有助于其搜索结果。但是,先前的工作仅针对“ Web表”的源上下文,而依赖于模式信息和简单的关系实体。为了解决这些缺点,我们利用了数据挖掘领域的工作,并展示了如何启用Web数据源上下文化。基于一个真实的用例,我们构建了一个原型上下文环境引擎,并将其集成到一个用于搜索数据Web的系统中。我们通过经验验证了我们方法的有效性-与最新技术相比,性能提高了29%。

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