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SPARQL中的空答案:用RDF嵌入近似查询

Towards Empty Answers in SPARQL: Approximating Querying with RDF Embedding
课程网址: http://videolectures.net/iswc2018_wang_towards_empty_sparql/  
主讲教师: Wang-Meng Zuo
开课单位: 哈尔滨工业大学
开课时间: 2018-11-22
课程语种: 英语
中文简介:
LOD云提供了大量RDF数据源,用户可以通过发出SPARQL查询来发现感兴趣的项目。对于用户来说,一个常见的查询问题是面对空答案:给定一个不返回任何内容的SPARQL查询,如何优化查询以获得非空集合?在本文中,我们提出了一种基于RDF图嵌入的框架来解决连续向量空间中的SPARQL空答案问题。我们首先通过一个专门为SPARQL查询设计的实体上下文保存翻译嵌入模型将RDF图投影到一个连续的向量空间中。然后,给定一个返回空集的SPARQL查询,我们将其划分为几个部分,并利用RDF嵌入和转换机制计算近似答案。我们还为返回的答案生成逻辑和替代查询,这有助于用户识别他们的期望,并最终优化原始查询。为了验证我们框架的有效性和效率,我们在真实世界的RDF数据集上进行了广泛的实验。结果表明,我们的框架可以显著提高近似答案的质量,并加快替代查询的生成。
课程简介: The LOD cloud offers a plethora of RDF data sources where users discover items of interest by issuing SPARQL queries. A common query problem for users is to face with empty answers: given a SPARQL query that returns nothing, how to refine the query to obtain a non-empty set? In this paper, we propose an RDF graph embedding based framework to solve the SPARQL empty-answer problem in terms of a continuous vector space. We first project the RDF graph into a continuous vector space by an entity context preserving translational embedding model which is specially designed for SPARQL queries. Then, given a SPARQL query that returns an empty set, we partition it into several parts and compute approximate answers by leveraging RDF embeddings and the translation mechanism. We also generate logical and alternative queries for returned answers, which helps users recognize their expectations and refine the original query finally. To validate the effectiveness and efficiency of our framework, we conduct extensive experiments on the real-world RDF dataset. The results show that our framework can significantly improve the quality of approximate answers and speed up the generation of alternative queries.
关 键 词: SPARQL查询设计; 大量RDF数据源; SPARQL空答案问题; 真实世界的RDF数据集
课程来源: 视频讲座网
数据采集: 2023-01-14:cyh
最后编审: 2023-01-14:cyh
阅读次数: 32