Event-driven document selection for terrorism

In this paper, we examine the task of extracting information about terrorism related events hidden in a large document collection. The task assumes that a terrorism related event can be described by a set of entity and relation instances. To reduce the amount of time and efforts in extracting these...

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Main Authors: SUN, Zhen, LIM, Ee Peng, CHANG, Kuiyu, ONG, Teng-Kwee, Gunaratna, Rohan Kumar
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Language:English
Published: Institutional Knowledge at Singapore Management University 2005
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Online Access:https://ink.library.smu.edu.sg/sis_research/890
https://ink.library.smu.edu.sg/context/sis_research/article/1889/viewcontent/Sun2005_Chapter_Event_DrivenDocumentSelectionF.pdf
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spelling sg-smu-ink.sis_research-18892018-06-21T04:58:49Z Event-driven document selection for terrorism SUN, Zhen LIM, Ee Peng CHANG, Kuiyu ONG, Teng-Kwee Gunaratna, Rohan Kumar In this paper, we examine the task of extracting information about terrorism related events hidden in a large document collection. The task assumes that a terrorism related event can be described by a set of entity and relation instances. To reduce the amount of time and efforts in extracting these event related instances, one should ideally perform the task on the relevant documents only. We have therefore proposed some document selection strategies based on information extraction (IE) patterns. Each strategy attempts to select one document at a time such that the gain of event related instance information is maximized. Our IE-based document selection strategies assume that some IE patterns are given to extract event instances. We conducted some experiments for one terrorism related event. Experiments have shown that our proposed IE based document selection strategies work well in the extraction task for news collections of various size. 2005-05-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/890 info:doi/10.1007/11427995_4 https://ink.library.smu.edu.sg/context/sis_research/article/1889/viewcontent/Sun2005_Chapter_Event_DrivenDocumentSelectionF.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Artificial intelligence Pattern extraction Entity relationship model Document selection Information extraction Terrorism Reactive system Computer security Databases and Information Systems Numerical Analysis and Scientific Computing
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Artificial intelligence
Pattern extraction
Entity relationship model
Document selection
Information extraction
Terrorism
Reactive system
Computer security
Databases and Information Systems
Numerical Analysis and Scientific Computing
spellingShingle Artificial intelligence
Pattern extraction
Entity relationship model
Document selection
Information extraction
Terrorism
Reactive system
Computer security
Databases and Information Systems
Numerical Analysis and Scientific Computing
SUN, Zhen
LIM, Ee Peng
CHANG, Kuiyu
ONG, Teng-Kwee
Gunaratna, Rohan Kumar
Event-driven document selection for terrorism
description In this paper, we examine the task of extracting information about terrorism related events hidden in a large document collection. The task assumes that a terrorism related event can be described by a set of entity and relation instances. To reduce the amount of time and efforts in extracting these event related instances, one should ideally perform the task on the relevant documents only. We have therefore proposed some document selection strategies based on information extraction (IE) patterns. Each strategy attempts to select one document at a time such that the gain of event related instance information is maximized. Our IE-based document selection strategies assume that some IE patterns are given to extract event instances. We conducted some experiments for one terrorism related event. Experiments have shown that our proposed IE based document selection strategies work well in the extraction task for news collections of various size.
format text
author SUN, Zhen
LIM, Ee Peng
CHANG, Kuiyu
ONG, Teng-Kwee
Gunaratna, Rohan Kumar
author_facet SUN, Zhen
LIM, Ee Peng
CHANG, Kuiyu
ONG, Teng-Kwee
Gunaratna, Rohan Kumar
author_sort SUN, Zhen
title Event-driven document selection for terrorism
title_short Event-driven document selection for terrorism
title_full Event-driven document selection for terrorism
title_fullStr Event-driven document selection for terrorism
title_full_unstemmed Event-driven document selection for terrorism
title_sort event-driven document selection for terrorism
publisher Institutional Knowledge at Singapore Management University
publishDate 2005
url https://ink.library.smu.edu.sg/sis_research/890
https://ink.library.smu.edu.sg/context/sis_research/article/1889/viewcontent/Sun2005_Chapter_Event_DrivenDocumentSelectionF.pdf
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