Final Thoughts - Ending Spam: Bayesian Content Filtering and the Art of Statistical Language Classification [Electronic resources] نسخه متنی

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Ending Spam: Bayesian Content Filtering and the Art of Statistical Language Classification [Electronic resources] - نسخه متنی

Jonathan A. Zdziarski

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Final Thoughts



We’ve looked at many different approaches to scaling for a spam-filtering solution. There’s much room for further optimization, including performance tuning, intelligent purging, and even the possibility for neural declustering, as we’ll cover later in this book. All of these approaches require the right amount of human resources and skill. Large nationwide networks have these resources to dedicate to implementing high-performance, distributed solutions on the network. For a filter developer, the key to developing a scalable tool is foresight regarding the many different types of scaling these large providers may require. Including support for different types of scaling, such as user-id distribution and peak hour statistics, can make life easier for the systems administrators installing and maintaining the software on their network.

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