A study on early decision making in objectionable web content classification
Lung‐Hao Lee, Cheng‐Jye Luh, Chih-Jie Yang · 2008
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 F1measure 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.