Filtering Multilingual Terrorist Content with Graph-Theoretic Classification Tools

Mark Last

doi:10.3233/978-1-58603-898-4-323

Filtering Multilingual Terrorist Content with Graph-Theoretic Classification Tools

Mark Last

Department of Software and Information Systems Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Since the web is increasingly used by terrorist organizations, the ability to automatically detect multilingual terrorist-related content is extremely important. In this chapter, we present an efficient detection methodology based on the recently developed graph-based web document representation models. Evaluation is performed on real-world corpora in English and Arabic languages.

Original language	English
Title of host publication	Advances in Data Mining, Search, Social Networks and Text Mining, and their Applications to Security
Publisher	IOS Press
Pages	323-330
Number of pages	8
ISBN (Electronic)	9781607503620
ISBN (Print)	9781586038984
DOIs	https://doi.org/10.3233/978-1-58603-898-4-323
State	Published - Aug 2007

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10.3233/978-1-58603-898-4-323

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title = "Filtering Multilingual Terrorist Content with Graph-Theoretic Classification Tools",

abstract = "Since the web is increasingly used by terrorist organizations, the ability to automatically detect multilingual terrorist-related content is extremely important. In this chapter, we present an efficient detection methodology based on the recently developed graph-based web document representation models. Evaluation is performed on real-world corpora in English and Arabic languages.",

author = "Mark Last",

year = "2007",

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language = "English",

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AB - Since the web is increasingly used by terrorist organizations, the ability to automatically detect multilingual terrorist-related content is extremely important. In this chapter, we present an efficient detection methodology based on the recently developed graph-based web document representation models. Evaluation is performed on real-world corpora in English and Arabic languages.

U2 - 10.3233/978-1-58603-898-4-323

DO - 10.3233/978-1-58603-898-4-323

M3 - Conference contribution

SN - 9781586038984

SP - 323

EP - 330

BT - Advances in Data Mining, Search, Social Networks and Text Mining, and their Applications to Security

PB - IOS Press

ER -

Filtering Multilingual Terrorist Content with Graph-Theoretic Classification Tools

Abstract

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