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CORR
2011
Springer
165views Education» more  CORR 2011»
12 years 8 months ago
Finding Deceptive Opinion Spam by Any Stretch of the Imagination
Consumers increasingly go online to rate, review and research products (Jansen, 2010; Litvin et al., 2008). Consequently, websites containing these reviews are becoming targets of...
Myle Ott, Yejin Choi, Claire Cardie, Jeffrey T. Ha...
HIS
2004
13 years 6 months ago
An Empirical Performance Comparison of Machine Learning Methods for Spam E-Mail Categorization
The increasing volume of unsolicited bulk e-mail (also known as spam) has generated a need for reliable anti-spam filters. Using a classifier based on machine learning techniques ...
Chih-Chin Lai, Ming-Chi Tsai
USENIX
2003
13 years 6 months ago
Learning Spam: Simple Techniques For Freely-Available Software
The problem of automatically filtering out spam e-mail using a classifier based on machine learning methods is of great recent interest. This paper gives an introduction to mach...
Bart Massey, Mick Thomure, Raya Budrevich, Scott L...
CORR
2010
Springer
143views Education» more  CORR 2010»
13 years 4 months ago
Algorithmic Detection of Computer Generated Text
ct Computer generated academic papers have been used to expose a lack of thorough human review at several computer science conferences. We assess the problem of classifying such do...
Allen Lavoie, Mukkai Krishnamoorthy
IJCAI
2007
13 years 6 months ago
Dynamically Weighted Hidden Markov Model for Spam Deobfuscation
Spam deobfuscation is a processing to detect obfuscated words appeared in spam emails and to convert them back to the original words for correct recognition. Lexicon tree hidden M...
Seunghak Lee, Iryoung Jeong, Seungjin Choi