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» Support vector machines for collaborative filtering
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FLAIRS
2008
13 years 10 months ago
On Using SVM and Kolmogorov Complexity for Spam Filtering
As a side effect of e-marketing strategy the number of spam e-mails is rocketing, the time and cost needed to deal with spam as well. Spam filtering is one of the most difficult t...
Sihem Belabbes, Gilles Richard
CAIP
2007
Springer
134views Image Analysis» more  CAIP 2007»
13 years 11 months ago
An Efficient Method for Filtering Image-Based Spam E-mail
Spam e-mail with advertisement text embedded in images presents a great challenge to anti-spam filters. In this paper, we present a fast method to detect image-based spam e-mail. U...
Ngo Phuong Nhung, Tu Minh Phuong
SIGIR
2008
ACM
13 years 7 months ago
Semi-supervised spam filtering: does it work?
The results of the 2006 ECML/PKDD Discovery Challenge suggest that semi-supervised learning methods work well for spam filtering when the source of available labeled examples diff...
Mona Mojdeh, Gordon V. Cormack
ICADL
2005
Springer
112views Education» more  ICADL 2005»
14 years 1 months ago
A Method for Creating a High Quality Collection of Researchers' Homepages from the Web
This paper proposes a method for creating a high quality collection of researchers’ homepages. The proposed method consists of three phases: rough filtering of the possible web p...
Yuxin Wang, Keizo Oyama
ISMIR
2005
Springer
206views Music» more  ISMIR 2005»
14 years 1 months ago
Improving Content-Based Similarity Measures by Training a Collaborative Model
We observed that for multimedia data – especially music - collaborative similarity measures perform much better than similarity measures derived from content-based sound feature...
Richard Stenzel, Thomas Kamps