Elements of information theory
Elements of information theory
On the Optimality of the Simple Bayesian Classifier under Zero-One Loss
Machine Learning - Special issue on learning with probabilistic representations
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Naive (Bayes) at Forty: The Independence Assumption in Information Retrieval
ECML '98 Proceedings of the 10th European Conference on Machine Learning
A Comparative Study on Feature Selection in Text Categorization
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Feature Selection for Unbalanced Class Distribution and Naive Bayes
ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
Support vector machines for spam categorization
IEEE Transactions on Neural Networks
Fighting the spam wars: A remailer approach with restrictive aliasing
ACM Transactions on Internet Technology (TOIT)
"In vivo" spam filtering: a challenge problem for KDD
ACM SIGKDD Explorations Newsletter
Mining Online Deal Forums for Hot Deals
WI '04 Proceedings of the 2004 IEEE/WIC/ACM International Conference on Web Intelligence
An evaluation of statistical spam filtering techniques
ACM Transactions on Asian Language Information Processing (TALIP)
Combining email models for false positive reduction
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
A suffix tree approach to anti-spam email filtering
Machine Learning
Automatic web pages categorization with ReliefF and Hidden Naive Bayes
Proceedings of the 2007 ACM symposium on Applied computing
Spam Filtering Using Statistical Data Compression Models
The Journal of Machine Learning Research
Effective spam filtering: A single-class learning and ensemble approach
Decision Support Systems
Asymmetric support vector machines: low false-positive learning under the user tolerance
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
A Comparative Impact Study of Attribute Selection Techniques on Naïve Bayes Spam Filters
ICDM '08 Proceedings of the 8th industrial conference on Advances in Data Mining: Medical Applications, E-Commerce, Marketing, and Theoretical Aspects
Searching for Interacting Features for Spam Filtering
ISNN '08 Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks
Email Spam Filtering: A Systematic Review
Foundations and Trends in Information Retrieval
Review: A review of machine learning approaches to Spam filtering
Expert Systems with Applications: An International Journal
The ineffectiveness of within-document term frequency in text classification
Information Retrieval
Anti-spam Filters Based on Support Vector Machines
ISICA '09 Proceedings of the 4th International Symposium on Advances in Computation and Intelligence
Commercial Internet filters: Perils and opportunities
Decision Support Systems
ProMail: using progressive email social network for spam detection
PAKDD'07 Proceedings of the 11th Pacific-Asia conference on Advances in knowledge discovery and data mining
Frequent variable sets based clustering for artificial neural networks particle classification
APWeb/WAIM'07 Proceedings of the joint 9th Asia-Pacific web and 8th international conference on web-age information management conference on Advances in data and web management
Meta learning intrusion detection in real time network
ICANN'07 Proceedings of the 17th international conference on Artificial neural networks
IITA'09 Proceedings of the 3rd international conference on Intelligent information technology application
A neural tree and its application to spam e-mail detection
Expert Systems with Applications: An International Journal
Using GMDH-based networks for improved spam detection and email feature analysis
Applied Soft Computing
Enhanced Topic-based Vector Space Model for semantics-aware spam filtering
Expert Systems with Applications: An International Journal
BioDM'06 Proceedings of the 2006 international conference on Data Mining for Biomedical Applications
An effective spam filter based on a combined support vector machine approach
International Journal of Internet Technology and Secured Transactions
NASC: a novel approach for spam classification
ICIC'06 Proceedings of the 2006 international conference on Computational Intelligence and Bioinformatics - Volume Part III
Text categorization using SVMs with rocchio ensemble for internet information classification
ICCNMC'05 Proceedings of the Third international conference on Networking and Mobile Computing
Generating estimates of classification confidence for a case-based spam filter
ICCBR'05 Proceedings of the 6th international conference on Case-Based Reasoning Research and Development
Word sense disambiguation for spam filtering
Electronic Commerce Research and Applications
Using probabilistic generative models for ranking risks of Android apps
Proceedings of the 2012 ACM conference on Computer and communications security
Developing methods and heuristics with low time complexities for filtering spam messages
NLDB'07 Proceedings of the 12th international conference on Applications of Natural Language to Information Systems
Reversing the effects of tokenisation attacks against content-based spam filters
International Journal of Security and Networks
Using naive bayes to detect spammy names in social networks
Proceedings of the 2013 ACM workshop on Artificial intelligence and security
Genetic optimized artificial immune system in spam detection: a review and a model
Artificial Intelligence Review
Data Mining and Knowledge Discovery
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We describe experiments with a Naive Bayes text classifier in the context of anti-spam E-mail filtering, using two different statistical event models: a multi-variate Bernoulli model and a multinomial model. We introduce a family of feature ranking functions for feature selection in the multinomial event model that take account of the word frequency information. We present evaluation results on two publicly available corpora of legitimate and spam E-mails. We find that the multinomial model is less biased towards one class and achieves slightly higher accuracy than the multi-variate Bernoulli model.