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Technical Perspective: Constant-Delay Enumeration for Nondeterministic Document Spanners

Published: 04 September 2020 Publication History

Abstract

The challenge of extracting structured information from text, or sequential data in general, is prevalent across a multitude of data-science domains. This challenge, known as Information Extraction (IE), instantiates to core components in text analytics, and a plethora of IE paradigms have been developed over the past decades. Rules and rule systems have consistently been key components in such paradigms, yet their roles have varied and evolved over time. Analytics engines such as IBM's SystemT use IE rules for materializing relations inside relational query languages. Machinelearning classifiers and probabilistic graphical models (e.g., Conditional Random Fields) use rules for feature generation. They also serve as weak constraints in Markov Logic Networks (and extensions such as DeepDive), and generators of noisy training data in the state-of-the-art Snorkel system.

References

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A. Amarilli, P. Bourhis, S. Mengel, and M. Niewerth. Constant-delay enumeration for nondeterministic document spanners. In ICDT, pages 22:1--22:19, 2019.
[2]
R. Fagin, B. Kimelfeld, F. Reiss, and S. Vansummeren. Document spanners: A formal approach to information extraction. Journal of the ACM, 62(2):12:1--12:51, 2015.
[3]
F. Florenzano, C. Riveros, M. Ugarte, S. Vansummeren, and D. Vrgoc. Constant delay algorithms for regular document spanners. In PODS, pages 165--177. ACM, 2018.
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D. D. Freydenberger, B. Kimelfeld, and L. Peterfreund. Joining extractions of regular expressions. In PODS, pages 137--149. ACM, 2018.
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R. Krishnamurthy, Y. Li, S. Raghavan, F. Reiss, S. Vaithyanathan, and H. Zhu. SystemT: A system for declarative information extraction. SIGMOD Record, 37(4):7--13, 2008.

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Published In

cover image ACM SIGMOD Record
ACM SIGMOD Record  Volume 49, Issue 1
March 2020
72 pages
ISSN:0163-5808
DOI:10.1145/3422648
Issue’s Table of Contents
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 04 September 2020
Published in SIGMOD Volume 49, Issue 1

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