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» Learning at Low False Positive Rates
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WWW
2009
ACM
14 years 8 months ago
A hybrid phish detection approach by identity discovery and keywords retrieval
Phishing is a significant security threat to the Internet, which causes tremendous economic loss every year. In this paper, we proposed a novel hybrid phish detection method based...
Guang Xiang, Jason I. Hong
TON
2002
175views more  TON 2002»
13 years 7 months ago
Compressed bloom filters
A Bloom filter is a simple space-efficient randomized data structure for representing a set in order to support membership queries. Although Bloom filters allow false positives, f...
Michael Mitzenmacher
KDD
2007
ACM
139views Data Mining» more  KDD 2007»
14 years 8 months ago
Raising the baseline for high-precision text classifiers
Many important application areas of text classifiers demand high precision and it is common to compare prospective solutions to the performance of Naive Bayes. This baseline is us...
Aleksander Kolcz, Wen-tau Yih
ISSRE
2010
IEEE
13 years 6 months ago
DoDOM: Leveraging DOM Invariants for Web 2.0 Application Robustness Testing
—Web 2.0 applications are increasing in popularity. However, they are also prone to errors because of their dynamic nature. This paper presents DoDOM, an automated system for tes...
Karthik Pattabiraman, Benjamin G. Zorn
SDM
2007
SIAM
198views Data Mining» more  SDM 2007»
13 years 9 months ago
Learning from Time-Changing Data with Adaptive Windowing
We present a new approach for dealing with distribution change and concept drift when learning from data sequences that may vary with time. We use sliding windows whose size, inst...
Albert Bifet, Ricard Gavaldà