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Safety Content Filtering Based on Incremental Induction of Decision Trees

Authors: Yuanyuan Fu;

Safety Content Filtering Based on Incremental Induction of Decision Trees

Abstract

This paper presents a novel method of safety content filtering exploiting incremental induction of decision trees. Via defining an appropriate attribute space, this approach adapts the security content filtering task to online incremental induction of decision trees learning framework. Experiments on benchmark datasets show that this technique dells well with safety content filtering task.

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
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