Extraction of Validating Shapes from Very Large Knowledge Graphs

Author:

Rabbani Kashif1,Lissandrini Matteo1,Hose Katja1

Affiliation:

1. Aalborg University, Denmark

Abstract

Knowledge Graphs (KGs) represent heterogeneous domain knowledge on the Web and within organizations. There exist shapes constraint languages to define validating shapes to ensure the quality of the data in KGs. Existing techniques to extract validating shapes often fail to extract complete shapes, are not scalable, and are prone to produce spurious shapes. To address these shortcomings, we propose the Quality Shapes Extraction (QSE) approach to extract validating shapes in very large graphs, for which we devise both an exact and an approximate solution. QSE provides information about the reliability of shape constraints by computing their confidence and support within a KG and in doing so allows to identify shapes that are most informative and less likely to be affected by incomplete or incorrect data. To the best of our knowledge, QSE is the first approach to extract a complete set of validating shapes from WikiData. Moreover, QSE provides a 12x reduction in extraction time compared to existing approaches, while managing to filter out up to 93% of the invalid and spurious shapes, resulting in a reduction of up to 2 orders of magnitude in the number of constraints presented to the user, e.g., from 11,916 to 809 on DBpedia.

Publisher

Association for Computing Machinery (ACM)

Subject

General Earth and Planetary Sciences,Water Science and Technology,Geography, Planning and Development

Reference54 articles.

1. Rulehub: A public corpus of rules for knowledge graphs;Ahmadi Naser;Journal of Data and Information Quality (JDIQ),2020

2. Magic shapes for SHACL validation

3. ABSTAT-HD: a scalable tool for profiling very large knowledge graphs

4. Sören Auer , Christian Bizer , Georgi Kobilarov , Jens Lehmann , Richard Cyganiak , and Zachary G . Ives . 2007 . DBpedia: A Nucleus for a Web of Open Data. In The Semantic Web, 6th International Semantic Web Conference (Lecture Notes in Computer Science), Vol. 4825 . Springer , Busan, Korea, 722--735. Sören Auer, Christian Bizer, Georgi Kobilarov, Jens Lehmann, Richard Cyganiak, and Zachary G. Ives. 2007. DBpedia: A Nucleus for a Web of Open Data. In The Semantic Web, 6th International Semantic Web Conference (Lecture Notes in Computer Science), Vol. 4825. Springer, Busan, Korea, 722--735.

5. Iovka Boneva , Jérémie Dusart , Daniel Fernández-Álvarez , and José Emilio Labra Gayo . 2019 . Shape Designer for ShEx and SHACL constraints . In Proceedings of the ISWC 2019 Satellite Tracks (CEUR Workshop Proceedings) , Vol. 2456 . CEUR-WS.org, Auckland, New Zealand, 269--272. Iovka Boneva, Jérémie Dusart, Daniel Fernández-Álvarez, and José Emilio Labra Gayo. 2019. Shape Designer for ShEx and SHACL constraints. In Proceedings of the ISWC 2019 Satellite Tracks (CEUR Workshop Proceedings), Vol. 2456. CEUR-WS.org, Auckland, New Zealand, 269--272.

Cited by 11 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3