A study on early decision making in objectionable web content classification

Lung Hao Lee; Cheng Jye Luh; Chih Jie Yang

doi:10.1109/ISI.2008.4565026

A study on early decision making in objectionable web content classification

Lung Hao Lee^*, Cheng Jye Luh, Chih Jie Yang

^*此作品的通信作者

智能系統研究所

研究成果 › 同行評審

3 引文斯高帕斯（Scopus）

摘要

This study proposed early decision heuristics for objectionable content classification using an inverse chi-square classifier. The experimental results indicated that only examining the title plus 10% of a web page's content can cost-effectively achieve an average precision of 93%. More importantly, the F₁ measure achieved its best when the title plus 60% of the body was examined. The proposed early decision making heuristics can serve as the trade-off baseline for real-time online filtering.

原文	English
頁面	35-39
頁數	5
DOIs	https://doi.org/10.1109/ISI.2008.4565026
出版狀態	Published - 2008
事件	IEEE International Conference on Intelligence and Security Informatics, 2008, IEEE ISI 2008 - Taipei, 台灣持續時間: 17 6月 2008 → 20 6月 2008

Conference

Conference	IEEE International Conference on Intelligence and Security Informatics, 2008, IEEE ISI 2008
國家/地區	台灣
城市	Taipei
期間	17/06/08 → 20/06/08

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10.1109/ISI.2008.4565026

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Link to publication in Scopus

引用此

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abstract = "This study proposed early decision heuristics for objectionable content classification using an inverse chi-square classifier. The experimental results indicated that only examining the title plus 10% of a web page's content can cost-effectively achieve an average precision of 93%. More importantly, the F1 measure achieved its best when the title plus 60% of the body was examined. The proposed early decision making heuristics can serve as the trade-off baseline for real-time online filtering.",

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AB - This study proposed early decision heuristics for objectionable content classification using an inverse chi-square classifier. The experimental results indicated that only examining the title plus 10% of a web page's content can cost-effectively achieve an average precision of 93%. More importantly, the F1 measure achieved its best when the title plus 60% of the body was examined. The proposed early decision making heuristics can serve as the trade-off baseline for real-time online filtering.

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DO - 10.1109/ISI.2008.4565026

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T2 - IEEE International Conference on Intelligence and Security Informatics, 2008, IEEE ISI 2008

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ER -

A study on early decision making in objectionable web content classification

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