Rough set theory approach for filtering spams from boundary messages in a chat system
Sanjiban Sekhar Roy,Saptarshi Charaborty,Swapnil Sourav,Ajith Abraham +3 more
- pp 28-34
TLDR
Simulation results clearly indicate that the proposed method, can achieve higher accuracy in spam detection as compared to the existing strategies.Abstract:
This paper purports a refreshing spam discovery technology for chat system based on rough set theory. Nowadays, spam is very much allied with a huge chunk of data transferred through internet involving all disturbing and unsolicited contents received via different web-services such as chat systems, e-mail, forums and web logs. In this paper, we have reviewed various past research works of filtering SPAM and propose a novel filtering technique for SPAM especially for chat system with the support of classical rough set theory. Simulation results clearly indicate that our proposed method, can achieve higher accuracy in spam detection as compared to the existing strategies.read more
Citations
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Journal ArticleDOI
Classifying Spam Emails Using Artificial Intelligent Techniques
TL;DR: The capabilities of the extreme learning machine (ELM) and support vector machine (SVM) for the classification of spam emails with the class level (d) are examined.
Book
Quality, Reliability, Security and Robustness in Heterogeneous Networks: 7th International Conference on Heterogeneous Networking for Quality.
TL;DR: The post-conference proceedings of the 7th International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness (QShine 2010) as mentioned in this paper were carefully selected from numerous submissions.
Proceedings ArticleDOI
Improved email spam classification method using integrated particle swarm optimization and decision tree
Harpreet Kaur,Ajay K. Sharma +1 more
TL;DR: The proposed technique has integrated particle swarm optimization based on Decision Tree algorithm with unsupervised filtering to enhance the accuracy rate further and have clearly pointed to better results than the available techniques.
References
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Rough sets
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Posted Content
An Evaluation of Naive Bayesian Anti-Spam Filtering
Ion Androutsopoulos,John Koutsias,Konstantinos Chandrinos,George Paliouras,Constantine D. Spyropoulos +4 more
TL;DR: It is reached that additional safety nets are needed for the Naive Bayesian anti-spam filter to be viable in practice.
Learning to Filter Spam E-Mail: A Comparison of a Naive Bayesian and a Memory-Based Approach
Ion Androutsopoulos,Georgios Paliouras,Vangelis Karkaletsis,Georgios Sakkis,Constantine D. Spyropoulos,Panagiotis Stamatopoulos +5 more
TL;DR: In this article, the authors investigate the performance of two machine learning algorithms in the context of ant-spam filtering and compare them to an alternative memory-based learning approach, after introducing suitable cost-sensitive evaluation measures.