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» Spam, spam, spam, spam: how can we stop it
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DIS
2007
Springer
14 years 1 months ago
Unsupervised Spam Detection Based on String Alienness Measures
We propose an unsupervised method for detecting spam documents from Web page data, based on equivalence relations on strings. We propose 3 measures for quantifying the alienness (...
Kazuyuki Narisawa, Hideo Bannai, Kohei Hatano, Mas...
AIRWEB
2009
Springer
14 years 2 months ago
Tag spam creates large non-giant connected components
Spammers in social bookmarking systems try to mimick bookmarking behaviour of real users to gain the attention of other users or search engines. Several methods have been proposed...
Nicolas Neubauer, Robert Wetzker, Klaus Obermayer
DOCENG
2011
ACM
12 years 7 months ago
Contributions to the study of SMS spam filtering: new collection and results
The growth of mobile phone users has lead to a dramatic increasing of SMS spam messages. In practice, fighting mobile phone spam is difficult by several factors, including the lo...
Tiago A. Almeida, José María G&oacut...
CEAS
2004
Springer
14 years 29 days ago
The Impact of Feature Selection on Signature-Driven Spam Detection
Signature-driven spam detection provides an alternative to machine learning approaches and can be very effective when near-duplicates of essentially the same message are sent in h...
Aleksander Kolcz, Abdur Chowdhury, Joshua Alspecto...
NIPS
2007
13 years 9 months ago
SpAM: Sparse Additive Models
We present a new class of models for high-dimensional nonparametric regression and classification called sparse additive models (SpAM). Our methods combine ideas from sparse line...
Pradeep D. Ravikumar, Han Liu, John D. Lafferty, L...