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The growing use of informal social text messages on Twitter is one of the known sources of big data. These type of messages are noisy and frequently rife with acronyms, slangs, grammatical errors and non-standard words causing grief for natural language processing (NLP) techniques. In this study, our contribution is to target non-standard words in the short text and propose a method to which the given...
Spam emails are a major threat that negatively impacts email users. Spam wastes time, financial resources of businesses, consumes network bandwidth and slows down email servers. In addition, provides a medium for distributing malicious code and there is currently not one solution to this problem. The Bag of Words (BoW) word content feature extraction method is well established for classifying spam...
The objective of this study is to describe an energy function model base on Geographic Adaptive Fidelity (GAF), which is one of the best known topology management schemes used in saving energy consumption in ad-hoc wireless networks. In wireless ad-hoc network, the nodes responsible for the transmission of data are battery-operated and as a result, there is a need for energy to be conserved in order...
In this study, we experiment with Support Vector Machines (SVM) and Random Forests (RF), which are two of the state-of-the-art machine learning algorithms. The purpose was to examine their suitability for detecting Advanced Fee Fraud (AFF) activities on internet, which due to its inherent vulnerability is often abused for various criminal activities. A set of cluster features was discovered using...
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