Anticipatory event detection via classification

The idea of event detection is to identify interesting patterns from a constant stream of incoming news documents. Previous research in event detection has largely focused on identifying the first event or tracking subsequent events belonging to a set of pre-assigned topics such as earthquakes, airl...

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Main Authors: QI, He, CHANG, Kuiyu, LIM, Ee Peng
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Language:English
Published: Institutional Knowledge at Singapore Management University 2007
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Online Access:https://ink.library.smu.edu.sg/sis_research/21
https://ink.library.smu.edu.sg/context/sis_research/article/1020/viewcontent/He2007_Article_AnticipatoryEventDetectionViaC.pdf
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spelling sg-smu-ink.sis_research-10202018-06-21T06:38:24Z Anticipatory event detection via classification QI, He CHANG, Kuiyu LIM, Ee Peng The idea of event detection is to identify interesting patterns from a constant stream of incoming news documents. Previous research in event detection has largely focused on identifying the first event or tracking subsequent events belonging to a set of pre-assigned topics such as earthquakes, airline disasters, etc. In this paper, we describe a new problem, called anticipatory event detection (AED), which aims to detect if a user-specified event has transpired. AED can be viewed as a personalized combination of event tracking and new event detection. We propose using sentence-level and document-level classification approaches to solve the AED problem for some restricted domains; given some user preferred topic event transition, we first train the corresponding event transition model, and then detect the occurrence of the transition for the stream of news covering the topic. Our experimental results on both terrorist-related and commercial events demonstrate the feasibility of our proposed AED solutions. 2007-01-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/21 info:doi/10.1007/s10257-007-0047-z https://ink.library.smu.edu.sg/context/sis_research/article/1020/viewcontent/He2007_Article_AnticipatoryEventDetectionViaC.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 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 Databases and Information Systems
Numerical Analysis and Scientific Computing
spellingShingle Databases and Information Systems
Numerical Analysis and Scientific Computing
QI, He
CHANG, Kuiyu
LIM, Ee Peng
Anticipatory event detection via classification
description The idea of event detection is to identify interesting patterns from a constant stream of incoming news documents. Previous research in event detection has largely focused on identifying the first event or tracking subsequent events belonging to a set of pre-assigned topics such as earthquakes, airline disasters, etc. In this paper, we describe a new problem, called anticipatory event detection (AED), which aims to detect if a user-specified event has transpired. AED can be viewed as a personalized combination of event tracking and new event detection. We propose using sentence-level and document-level classification approaches to solve the AED problem for some restricted domains; given some user preferred topic event transition, we first train the corresponding event transition model, and then detect the occurrence of the transition for the stream of news covering the topic. Our experimental results on both terrorist-related and commercial events demonstrate the feasibility of our proposed AED solutions.
format text
author QI, He
CHANG, Kuiyu
LIM, Ee Peng
author_facet QI, He
CHANG, Kuiyu
LIM, Ee Peng
author_sort QI, He
title Anticipatory event detection via classification
title_short Anticipatory event detection via classification
title_full Anticipatory event detection via classification
title_fullStr Anticipatory event detection via classification
title_full_unstemmed Anticipatory event detection via classification
title_sort anticipatory event detection via classification
publisher Institutional Knowledge at Singapore Management University
publishDate 2007
url https://ink.library.smu.edu.sg/sis_research/21
https://ink.library.smu.edu.sg/context/sis_research/article/1020/viewcontent/He2007_Article_AnticipatoryEventDetectionViaC.pdf
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