Global ETD Search
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Showing 1 to 8 of 8 for “"Spam-Filtering"”.
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Incorporating Three-Way Email Spam Filtering With Game-Theoretic Rough Sets
Email spam filtering commonly is viewed as binary classification problem, that is, classifies incoming email messages into spam or non-spam email. But it has two main limitations. Firstly, binary classification needs people to make definite decisions that are hard. Secondly, binary classification …
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An email spam filtering proxy using secure authentication and micro-bonds
… email. The innate uncertainty of automatic spam detection creates a tension between the desire to filter 100% of spam, and the need to avoid the loss of legitimate mail. Apuma attempts to solve this problem by combining accept-lists with payment systems and content evaluation. Messages from …
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The performance of soft computing techniques on content-based SMS spam filtering
Content-based filtering is one of the most widely used methods to combat SMS (Short Message Service) spam. This method represents SMS text messages by a set of selected features which are extracted from data sets. Most of the available data sets have imbalanced class distribution problem. However, …
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Prediction games : machine learning in the presence of an adversary
… data. Consider, for instance, the task of email spam filtering where one seeks to find a model which automatically assigns new, previously unseen emails to class spam or non-spam. Building such a predictive model based on observed training inputs (e.g., emails) with corresponding outputs (e.g., …
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Learning under differing training and test distributions
… to biased training data. In case studies on spam filtering, HIV therapy screening, targeted advertising, and other applications the performance of the new models is compared to state-of-the-art reference methods.
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Active evaluation of predictive models
… are applicable for many practical tasks such as spam filtering, face and handwritten digit recognition, and personalized product recommendation. In general, they are used to predict a target label for a given data instance. In order to make an informed decision about the deployment of a …
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Discriminative Classification Models for Internet Security
… countermeasures. As an example, inbound email spam filters decide for spam or non-spam. They can base their decision on both the content of each email as well as on features that summarize prior emails received from the sending server. In general, discriminative classification methods learn to …
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Spam Analysis and Detection for User Generated Content in Online Social Networks
… also makes it easy to be polluted andattacked by spammers and malicious users. How users participate in UGCnetworks, especially how users contribute content and share content with theirfriends and other users, is fundamental to spam detection and high qualityknowledge discovery. In this …