Matching Roles from Temporal Data: Why Joe Biden is not only President, but also Commander-in-Chief

Matching Roles from Temporal Data: Why Joe Biden is not only President, but also Commander-in-Chief
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从时态数据匹配角色:为什么乔·拜登不仅是总统,而且是总司令

DOI:
10.1145/3588919
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发表时间:
2023
期刊:
Proceedings of the ACM on Management of Data
影响因子:
--
通讯作者:
Srivastava, Divesh
Srivastava, Divesh
中科院分区:
--
文献类型:
--
作者:
Bornemann, Leon;Bleifuß, Tobias;Kalashnikov, Dmitri V.;Nargesian, Fatemeh;Naumann, Felix;Srivastava, Divesh

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我们提出了角色匹配,一种新颖的、细粒度的时间事实数据完整性约束,即(主题、谓词、对象、时间戳)四元组。角色是主语和谓语的组合,可以随着现实世界的发展和数据随时间的变化与不同的对象相关联。角色匹配表明两个或多个角色的关联对象应该始终跨时间匹配。角色匹配一旦被发现,就可以作为完整性约束来提高数据质量,例如Wikipedia[3]中的结构化数据。如果违反,角色匹配可以提醒数据所有者或编辑,从而允许他们纠正错误。由于匹配问题固有的二次复杂性,以及需要根据迄今为止观察到的事实的可能较短的历史来识别真正的匹配,找到所有角色匹配是具有挑战性的。为了解决第一个挑战,我们引入了几种用于干净和脏输入数据的阻塞方法。对于第二个挑战,即匹配阶段,我们展示了如何使用实体解析方法Ditto[27]来实现角色匹配任务的令人满意的性能。我们在维基百科信息框的数据集上评估了我们的方法,结果表明,即使在存在脏数据的情况下,我们的阻断方法可以达到95%的召回率,同时保持超过99.99%的还原率。在匹配阶段,我们使用自动生成的标签,在我们的数据集上实现了89%的宏观f1得分。
We present role matching, a novel, fine-grained integrity constraint on temporal fact data, i.e., (subject, predicate, object, timestamp)-quadruples. A role is a combination of subject and predicate and can be associated with different objects as the real world evolves and the data changes over time. A role matching states that the associated object of two or more roles should always match across time. Once discovered, role matchings can serve as integrity constraints to improve data quality, for instance of structured data in Wikipedia[3]. If violated, role matchings can alert data owners or editors and thus allow them to correct the error. Finding all role matchings is challenging due both to the inherent quadratic complexity of the matching problem and the need to identify true matches based on the possibly short history of the facts observed so far.To address the first challenge, we introduce several blocking methods both for clean and dirty input data. For the second challenge, the matching stage, we show how the entity resolution method Ditto[27] can be adapted to achieve satisfactory performance for the role matching task. We evaluate our method on datasets from Wikipedia infoboxes, showing that our blocking approaches can achieve 95% recall, while maintaining a reduction ratio of more than 99.99%, even in the presence of dirty data. In the matching stage, we achieve a macro F1-score of 89% on our datasets, using automatically generated labels.
DOI: --
发表时间: 2017
期刊: Pacific-Asia Conference on Knowledge Discovery and Data Mining
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发表时间: 2018
影响因子: 2.5
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发表时间: 2021
期刊: Synthesis Lectures on Data Management
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作者:
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发表时间: 2012
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