research-article

Constant-Delay Enumeration for Nondeterministic Document Spanners

Authors:

Antoine Amarilli,

Pierre Bourhis,

Matthias NiewerthAuthors Info & Claims

ACM SIGMOD Record, Volume 49, Issue 1

Pages 25 - 32

https://doi.org/10.1145/3422648.3422655

Published: 04 September 2020 Publication History

Abstract

One of the classical tasks in information extraction is to extract subparts of texts through regular expressions. In the database theory literature, this approach has been generalized and formalized as document spanners. In this model, extraction is performed by evaluating a particular kind of automata, called a sequential variable-set automaton (VA). The efficiency of this task is then measured in the context of enumeration algorithms: we first run a preprocessing phase computing a compact representation of the answers, and second we produce the results one after the other with a short time between consecutive answers, called the delay of the enumeration. Our goal is to have an algorithm that is tractable in combined complexity, i.e., in the sizes of the input document and the VA, while ensuring the best possible data complexity bounds in the input document size, i.e., a constant delay that does not depend on the document. We present such an algorithm for a variant of VAs called extended sequential VAs and give an experimental evaluation of this algorithm.

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Cited By

Gawrychowski PManea FSchmid M(2024)Revisiting Weighted Information Extraction: A Simpler and Faster Algorithm for Ranked EnumerationProceedings of the ACM on Management of Data10.1145/36958402:5(1-19)Online publication date: 7-Nov-2024
https://dl.acm.org/doi/10.1145/3695840
Thompson SFreydenberger D(2024)Generalized Core Spanner Inexpressibility via Ehrenfeucht-Fraïssé Games for FCProceedings of the ACM on Management of Data10.1145/36511432:2(1-18)Online publication date: 14-May-2024
https://dl.acm.org/doi/10.1145/3651143
Schmid M(2024)The Information Extraction Framework of Document Spanners - A Very Informal SurveySOFSEM 2024: Theory and Practice of Computer Science10.1007/978-3-031-52113-3_1(3-22)Online publication date: 19-Feb-2024
https://dl.acm.org/doi/10.1007/978-3-031-52113-3_1
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Information & Contributors

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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

Editors:
Rada Chirkova
North Carolina State University
,
Vanessa Braganholo
Universidade Federal Fluminense
,
Wim Martens
University of Bayreuth
,
Divesh Srivastava
ATT research
,
Pinar Tözü
IBM Almaden Research Center
,
Marianne Winslett
University of Illinois
,
Jun Yang
Duke University
,
Azza Abouzied
NYU
,
Lyublena Antova
Datometry
,
Aaron J. Elmore
University of Chicago
,
Kyriakos Mouratidis
Singapore Management University
,
Dan Olteanu
University of Oxford
,
Immanuel Trummer
Cornell University
,
Yannis Velegrakis
Utrecht University

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Copyright © 2020 Copyright is held by the owner/author(s).

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

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Published: 04 September 2020

Published in SIGMOD Volume 49, Issue 1

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Cited By

Gawrychowski PManea FSchmid M(2024)Revisiting Weighted Information Extraction: A Simpler and Faster Algorithm for Ranked EnumerationProceedings of the ACM on Management of Data10.1145/36958402:5(1-19)Online publication date: 7-Nov-2024
https://dl.acm.org/doi/10.1145/3695840
Thompson SFreydenberger D(2024)Generalized Core Spanner Inexpressibility via Ehrenfeucht-Fraïssé Games for FCProceedings of the ACM on Management of Data10.1145/36511432:2(1-18)Online publication date: 14-May-2024
https://dl.acm.org/doi/10.1145/3651143
Schmid M(2024)The Information Extraction Framework of Document Spanners - A Very Informal SurveySOFSEM 2024: Theory and Practice of Computer Science10.1007/978-3-031-52113-3_1(3-22)Online publication date: 19-Feb-2024
https://dl.acm.org/doi/10.1007/978-3-031-52113-3_1
Peterfreund L(2023)Enumerating grammar-based extractionsDiscrete Applied Mathematics10.1016/j.dam.2023.08.014341(372-392)Online publication date: Dec-2023
https://doi.org/10.1016/j.dam.2023.08.014
Schmid MSchweikardt NLibkin LBarceló P(2022)Document Spanners - A Brief Overview of Concepts, Results, and Recent DevelopmentsProceedings of the 41st ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems10.1145/3517804.3526069(139-150)Online publication date: 12-Jun-2022
https://dl.acm.org/doi/10.1145/3517804.3526069
Schmid MSchweikardt NLibkin LPichler RGuagliardo P(2021)Spanner Evaluation over SLP-Compressed DocumentsProceedings of the 40th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems10.1145/3452021.3458325(153-165)Online publication date: 20-Jun-2021
https://dl.acm.org/doi/10.1145/3452021.3458325
Martens W(2020)Formal Languages in Information Extraction and Graph DatabasesBeyond the Horizon of Computability10.1007/978-3-030-51466-2_28(306-309)Online publication date: 24-Jun-2020
https://doi.org/10.1007/978-3-030-51466-2_28

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