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将真理发现和RDF知识库结合起来以实现其共同优势
Combining Truth Discovery and RDF Knowledge Bases to their mutual advantage |
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| 课程网址: |
http://videolectures.net/iswc2018_beretta_combinin_truth_discover...
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| 主讲教师: |
Valentina Beretta
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| 开课单位: |
IMT Mines Ales公司
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| 开课时间: |
2018-11-22
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| 课程语种: |
英语
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| 中文简介: |
本研究利用RDF知识库（KB）表示的知识来提高真相发现性能。当多个来源提供了相互冲突的主张时，真相发现旨在确定事实（真实主张）。基于真实声明由可靠来源提供，可靠来源提供真实声明的假设，真相发现模型迭代计算价值置信度和来源可信度，以确定哪些声明是真实的。我们提出了一个模型，该模型利用了从现有RDF知识库中提取的规则形式的知识。这些规则用于量化RDF知识库提供的证据，以支持索赔。然后，将该证据集成到值置信度的计算中，以改进其估计。增强真相发现模型可以有效地获得一组更大的可靠事实，反之亦然，可以用来填充RDF知识库。在真实世界数据集上的经验实验显示了所提出的方法的潜力，该方法与我们修改的模型相比提高了18%。
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| 课程简介: |
This study exploits knowledge expressed by RDF Knowledge Bases (KBs) to enhance Truth Discovery performance. Truth Discovery aims to identify facts (true claims) when conflicting claims are provided by several sources. Based on the assumption that true claims are provided by reliable sources and reliable sources provide true claims, Truth Discovery models iteratively compute value confidence and source trustworthiness in order to determine which claims are true. We propose a model that takes advantage of the knowledge extracted from an existing RDF KB in form of rules. These rules are used to quantify the evidence given by the RDF KB to support a claim. Then, this evidence is integrated in the computation of value confidence to improve its estimation. Enhancing truth discovery models allows to efficiently obtain a larger set of reliable facts that vice versa can be used to populate RDF KBs. Empirical experiments on real-world datasets show the potential of the proposed approach which lead to an improvement up to 18% w.r.t. the model we modified.
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| 关 键 词: |
RDF知识库; 可靠来源提供; 增强真相发现模型; 增强真相发现模型
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| 课程来源: |
视频讲座网
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| 数据采集: |
2023-01-11：cyh
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| 最后编审: |
2023-05-15：cyh
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| 阅读次数: |
36
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