September 1, 2018

Spam Message Filtering Recognition System Based on TensorFlow

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Abstract

In order to make the spam short message filtering and recognition system more accuracy and efficiency, we have been debugged Recurrent Neural Network, Convolutional Neural Network, Naive Bayesian and many other algorithms on the TensorFlow platform by using the basis theoretical of deep learning.Finally, the core of the algorithm is Recurrent Neural Network with a test accuracy of 89.0%. We developed a simple spam filtering and recognition system.

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Cite This Study

Hao Chen (Sat,) studied this question.

synapsesocial.com/papers/6a192e80fa25ab5db6d9344e https://doi.org/https://doi.org/10.1109/icmcce.2018.00124

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1Context-Dependent Pre-Trained Deep Neural Networks for Large-Vocabulary Speech Recognition2011 · 3,077 citations
2A comparative study for content-based dynamic spam classification using four machine learning algorithms2008 · 122 citations
3Content based SMS spam filtering2006 · 217 citations
4Comparative Graph Theoretical Characterization of Networks of Spam and Legitimate Email2005 · 34 citations
5Spam message self-adaptive filtering system based on Naive Bayes and support vector machine2008 · 8 citations

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