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An Early Decision Algorithm to Accelerate Web Content Filtering

机译:加速Web内容过滤的早期决策算法

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摘要

Real-time content analysis can be a bottleneck in Web filtering. This work presents a simple, but effective early decision algorithm to accelerate the filtering process by examining only part of the Web content. The algorithm can make the filtering decision, either to block or to pass the Web content, as soon as it is confident with a high probability that the content should belong to a banned or an allowable category. The experiments show the algorithms can examine only around one-fourth of the Web content on average, while the accuracy remains fairly good: 89% in the banned content and 93% in the allowable content. This algorithm can complement other Web filtering approaches to filter the Web content with high efficiency.
机译:实时内容分析可能是Web筛选的瓶颈。这项工作提出了一种简单但有效的早期决策算法,可以通过仅检查Web内容的一部分来加速过滤过程。一旦确信该内容应该属于禁止或允许的类别,该算法就可以做出过滤决策,以阻止或传递Web内容。实验表明,这些算法平均只能检查大约四分之一的Web内容,而准确性仍然相当不错:被禁止的内容占89%,允许的内容占93%。该算法可以补充其他Web过滤方法,以高效地过滤Web内容。

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