Communications of the ACM
MetaCost: a general method for making classifiers cost-sensitive
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
An Evaluation of Statistical Approaches to Text Categorization
Information Retrieval
Support vector machines for spam categorization
IEEE Transactions on Neural Networks
Evaluating cost-sensitive Unsolicited Bulk Email categorization
Proceedings of the 2002 ACM symposium on Applied computing
Combining email models for false positive reduction
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
A methodology for comparing classifiers that allow the control of bias
Proceedings of the 2006 ACM symposium on Applied computing
Content based SMS spam filtering
Proceedings of the 2006 ACM symposium on Document engineering
Applying lazy learning algorithms to tackle concept drift in spam filtering
Expert Systems with Applications: An International Journal
SpamHunting: An instance-based reasoning system for spam labelling and filtering
Decision Support Systems
Adaptive e-mail intention finding mechanism based on e-mail words social networks
Proceedings of the 2007 workshop on Large scale attack defense
Mining categories for emails via clustering and pattern discovery
Journal of Intelligent Information Systems
An evaluation of Naive Bayes variants in content-based learning for spam filtering
Intelligent Data Analysis
Email Spam Filtering: A Systematic Review
Foundations and Trends in Information Retrieval
ECUE: A Spam Filter that Uses Machine Learning to Track Concept Drift
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
Anti-spam Filters Based on Support Vector Machines
ISICA '09 Proceedings of the 4th International Symposium on Advances in Computation and Intelligence
Fuzzy logic for e-mail spam deduction
ACACOS'11 Proceedings of the 10th WSEAS international conference on Applied computer and applied computational science
Combining multiple email filters based on multivariate statistical analysis
ISMIS'06 Proceedings of the 16th international conference on Foundations of Intelligent Systems
Grindstone4Spam: An optimization toolkit for boosting e-mail classification
Journal of Systems and Software
Review spam detector with rating consistency check
Proceedings of the 51st ACM Southeast Conference
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Spam filtering is a text categorization task that shows especial features that make it interesting and difficult. First, the task has been performed traditionally using heuristics from the domain. Second, a cost model is required to avoid misclassification of legitimate messages. We present a comparative evaluation of several machine learning algorithms applied to spam filtering, considering the text of the messages and a set of heuristics for the task. Cost-oriented biasing and evaluation is performed.