A survey of event extraction methods from text for decision support systems

F.P. Hoogenboom, Flavius Frasincar, Uzay Kaymak, Franciska de Jong, E.A.M. Caron

Research output: Contribution to journalArticleScientificpeer-review

Abstract

Event extraction, a specialized stream of information extraction rooted back into the 1980s, has greatly gained in popularity due to the advent of big data and the developments in the related fields of text mining and natural language processing. However, up to this date, an overview of this particular field remains elusive. Therefore, we give a summarization of event extraction techniques for textual data, distinguishing between data-driven, knowledge-driven, and hybrid methods, and present a qualitative evaluation of these. Moreover, we discuss common decision support applications of event extraction from text corpora. Last, we elaborate on the evaluation of event extraction systems and identify current research issues.
Original languageEnglish
Pages (from-to)12-22
JournalDecision Support Systems
Volume85
Issue numberC
DOIs
Publication statusPublished - 2016

Fingerprint

Decision support systems
Natural Language Processing
Data Mining
Information Storage and Retrieval
Surveys and Questionnaires
Processing
Evaluation

Cite this

Hoogenboom, F.P. ; Frasincar, Flavius ; Kaymak, Uzay ; de Jong, Franciska ; Caron, E.A.M. / A survey of event extraction methods from text for decision support systems. In: Decision Support Systems. 2016 ; Vol. 85, No. C. pp. 12-22.
@article{18524174a005421280971b1bfae49bc9,
title = "A survey of event extraction methods from text for decision support systems",
abstract = "Event extraction, a specialized stream of information extraction rooted back into the 1980s, has greatly gained in popularity due to the advent of big data and the developments in the related fields of text mining and natural language processing. However, up to this date, an overview of this particular field remains elusive. Therefore, we give a summarization of event extraction techniques for textual data, distinguishing between data-driven, knowledge-driven, and hybrid methods, and present a qualitative evaluation of these. Moreover, we discuss common decision support applications of event extraction from text corpora. Last, we elaborate on the evaluation of event extraction systems and identify current research issues.",
author = "F.P. Hoogenboom and Flavius Frasincar and Uzay Kaymak and {de Jong}, Franciska and E.A.M. Caron",
year = "2016",
doi = "10.1016/j.dss.2016.02.006",
language = "English",
volume = "85",
pages = "12--22",
journal = "Decision Support Systems",
issn = "0167-9236",
publisher = "Elsevier",
number = "C",

}

A survey of event extraction methods from text for decision support systems. / Hoogenboom, F.P.; Frasincar, Flavius; Kaymak, Uzay; de Jong, Franciska ; Caron, E.A.M.

In: Decision Support Systems, Vol. 85, No. C, 2016, p. 12-22.

Research output: Contribution to journalArticleScientificpeer-review

TY - JOUR

T1 - A survey of event extraction methods from text for decision support systems

AU - Hoogenboom, F.P.

AU - Frasincar, Flavius

AU - Kaymak, Uzay

AU - de Jong, Franciska

AU - Caron, E.A.M.

PY - 2016

Y1 - 2016

N2 - Event extraction, a specialized stream of information extraction rooted back into the 1980s, has greatly gained in popularity due to the advent of big data and the developments in the related fields of text mining and natural language processing. However, up to this date, an overview of this particular field remains elusive. Therefore, we give a summarization of event extraction techniques for textual data, distinguishing between data-driven, knowledge-driven, and hybrid methods, and present a qualitative evaluation of these. Moreover, we discuss common decision support applications of event extraction from text corpora. Last, we elaborate on the evaluation of event extraction systems and identify current research issues.

AB - Event extraction, a specialized stream of information extraction rooted back into the 1980s, has greatly gained in popularity due to the advent of big data and the developments in the related fields of text mining and natural language processing. However, up to this date, an overview of this particular field remains elusive. Therefore, we give a summarization of event extraction techniques for textual data, distinguishing between data-driven, knowledge-driven, and hybrid methods, and present a qualitative evaluation of these. Moreover, we discuss common decision support applications of event extraction from text corpora. Last, we elaborate on the evaluation of event extraction systems and identify current research issues.

U2 - 10.1016/j.dss.2016.02.006

DO - 10.1016/j.dss.2016.02.006

M3 - Article

VL - 85

SP - 12

EP - 22

JO - Decision Support Systems

JF - Decision Support Systems

SN - 0167-9236

IS - C

ER -