Application Servers White Papers
Avaya Meeting Exchange for IBM Lotus Notes and Sametime: Release 1.0.5 Installation and Configuration Guide
Overview Systems for learning to detect anomalous email behavior, such as worms and viruses, tend to build either peruser models or a single global model. Global models leverage a larger training corpus but often model individual users poorly. Per-user models capture fine-grained behaviors but can take a long time to accumulate sufficient training data. Approaches that combine global and per-user information have the potential to address these limitations. The Latent Dirichlet Allocation model is used to transition smoothly from the global prior to a particular user's empirical model as the amount of user data grows. Preliminary results demonstrate long-term accuracy comparable to per-user models, while also showing near-ideal performance almost immediately on new users.
| Publisher | Avaya | File Format | |
|---|---|---|---|
| Date Published | February 2007 | ||
| Format | White Papers | ||
| Topics | |||
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