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CIKM
2009
Springer
13 years 11 months ago
A co-classification framework for detecting web spam and spammers in social media web sites
Social media are becoming increasingly popular and have attracted considerable attention from spammers. Using a sample of more than ninety thousand known spam Web sites, we found ...
Feilong Chen, Pang-Ning Tan, Anil K. Jain
INCDM
2010
Springer
152views Data Mining» more  INCDM 2010»
13 years 10 months ago
Spam Email Filtering Using Network-Level Properties
Abstract. Spam is serious problem that affects email users (e.g. phishing attacks, viruses and time spent reading unwanted messages). We propose a novel spam email filtering appr...
Paulo Cortez, André Correia, Pedro Sousa, M...
PRL
2008
88views more  PRL 2008»
13 years 7 months ago
Time-efficient spam e-mail filtering using n-gram models
In this paper, we propose spam e-mail filtering methods having high accuracies and low time complexities. The methods are based on the n-gram approach and a heuristics which is re...
Ali Çiltik, Tunga Güngör
CEAS
2005
Springer
14 years 29 days ago
Naive Bayes Spam Filtering Using Word-Position-Based Attributes
This paper explores the use of the naive Bayes classifier as the basis for personalised spam filters. Several machine learning algorithms, including variants of naive Bayes, hav...
Johan Hovold