A Study on an Effective Event Detection Method for Event-Focused News Summarization (사건중심 뉴스기사 자동요약을 위한 사건탐지 기법에 관한 연구)

Young-Mee Chung (정영미); Yong-Kwang Kim (김용광)

doi:10.3743/KOSIM.2008.25.4.227

A Study on an Effective Event Detection Method for Event-Focused News Summarization

Journal of the Korean Society for Information Management
Abbr : JKOSIM
2008, 25(4), pp.227~243
DOI : 10.3743/KOSIM.2008.25.4.227
Publisher : 한국정보관리학회
Research Area : Interdisciplinary Studies > Library and Information Science
Received : November 18, 2008
Accepted : December 3, 2008
Published : December 30, 2008

Young-Mee Chung ¹, Yong-Kwang Kim ¹

¹연세대학교

Accredited

ABSTRACT

This study investigates an event detection method with the aim of generating an event-focused news summary from a set of news articles on a certain event using a multi-document summarization technique. The event detection method first classifies news articles into the event related topic categories by employing a SVM classifier and then creates event clusters containing news articles on an event by a modified single pass clustering algorithm. The clustering algorithm applies a time penalty function as well as cluster partitioning to enhance the clustering performance. It was found that the event detection method proposed in this study showed a satisfactory performance in terms of both the F-measure and the detection cost.

KEYWORDS

event detection, event-focused news summarization, support vector machine classifier, single pass algorithm, time penalty function

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Journal of the Korean Society for Information Management 2025 KCI Impact Factor : 1.27

A Study on an Effective Event Detection Method for Event-Focused News Summarization

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* References for papers published after 2025 are currently being built.

Journal of the Korean Society for Information Management 2025 KCI Impact Factor : 1.27

A Study on an Effective Event Detection Method for Event-Focused News Summarization

ABSTRACT

KEYWORDS

Journal Copyright Policy

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