A relational framework for information extraction

Ronald Fagin; Benny Kimelfeld; Frederick Reiss; Stijn Vansummeren

doi:10.1145/2935694.2935696

A relational framework for information extraction

Ronald Fagin, Benny Kimelfeld, Frederick Reiss, Stijn Vansummeren

Computer Science

Technion - Israel Institute of Technology

Research output: Contribution to journal › Article › peer-review

Abstract

Information Extraction commonly refers to the task of populating a relational schema, having predefined underlying semantics, from textual content. This task is pervasive in contemporary computational challenges associated with Big Data. In this article we provide an overview of our work on document spanners-a relational framework for Information Extraction that is inspired by rule-based systems such as IBM's SystemT.

Original language	English
Pages (from-to)	5-16
Number of pages	12
Journal	SIGMOD Record
Volume	44
Issue number	4
DOIs	https://doi.org/10.1145/2935694.2935696
State	Published - Dec 2015

Keywords

Automata
Document spanners
Inconsistency
Information extraction
Prioritized repairs
Regular expressions

All Science Journal Classification (ASJC) codes

Software
Information Systems

Access to Document

10.1145/2935694.2935696

Cite this

@article{4e05853bbfec4f5f81900d1be8f0e816,

title = "A relational framework for information extraction",

abstract = "Information Extraction commonly refers to the task of populating a relational schema, having predefined underlying semantics, from textual content. This task is pervasive in contemporary computational challenges associated with Big Data. In this article we provide an overview of our work on document spanners-a relational framework for Information Extraction that is inspired by rule-based systems such as IBM's SystemT.",

keywords = "Automata, Document spanners, Inconsistency, Information extraction, Prioritized repairs, Regular expressions",

author = "Ronald Fagin and Benny Kimelfeld and Frederick Reiss and Stijn Vansummeren",

year = "2015",

month = dec,

doi = "10.1145/2935694.2935696",

language = "الإنجليزيّة",

volume = "44",

pages = "5--16",

journal = "SIGMOD Record",

issn = "0163-5808",

publisher = "Association for Computing Machinery (ACM)",

number = "4",

}

TY - JOUR

T1 - A relational framework for information extraction

AU - Fagin, Ronald

AU - Kimelfeld, Benny

AU - Reiss, Frederick

AU - Vansummeren, Stijn

PY - 2015/12

Y1 - 2015/12

N2 - Information Extraction commonly refers to the task of populating a relational schema, having predefined underlying semantics, from textual content. This task is pervasive in contemporary computational challenges associated with Big Data. In this article we provide an overview of our work on document spanners-a relational framework for Information Extraction that is inspired by rule-based systems such as IBM's SystemT.

AB - Information Extraction commonly refers to the task of populating a relational schema, having predefined underlying semantics, from textual content. This task is pervasive in contemporary computational challenges associated with Big Data. In this article we provide an overview of our work on document spanners-a relational framework for Information Extraction that is inspired by rule-based systems such as IBM's SystemT.

KW - Automata

KW - Document spanners

KW - Inconsistency

KW - Information extraction

KW - Prioritized repairs

KW - Regular expressions

UR - http://www.scopus.com/inward/record.url?scp=84971422149&partnerID=8YFLogxK

U2 - 10.1145/2935694.2935696

DO - 10.1145/2935694.2935696

M3 - مقالة

SN - 0163-5808

VL - 44

SP - 5

EP - 16

JO - SIGMOD Record

JF - SIGMOD Record

IS - 4

ER -

A relational framework for information extraction

Abstract

Keywords

All Science Journal Classification (ASJC) codes

Access to Document

Other files and links

Fingerprint

Cite this