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AI
2006
Springer
15 years 6 months ago
Adaptive Fraud Detection Using Benford's Law
Abstract. Adaptive Benford's Law [1] is a digital analysis technique that specifies the probabilistic distribution of digits for many commonly occurring phenomena, even for in...
Fletcher Lu, J. Efrim Boritz, H. Dominic Covvey
ECML
1987
Springer
15 years 5 months ago
Induction in Noisy Domains
This paper examines the induction of classification rules from examples using real-world data. Real-world data is almost always characterized by two features, which are important ...
Peter Clark, Tim Niblett
NIPS
2008
15 years 3 months ago
Stochastic Relational Models for Large-scale Dyadic Data using MCMC
Stochastic relational models (SRMs) [15] provide a rich family of choices for learning and predicting dyadic data between two sets of entities. The models generalize matrix factor...
Shenghuo Zhu, Kai Yu, Yihong Gong
123
Voted
AAAI
2006
15 years 3 months ago
Mixed Collaborative and Content-Based Filtering with User-Contributed Semantic Features
We describe a recommender system which uses a unique combination of content-based and collaborative methods to suggest items of interest to users, and also to learn and exploit it...
Matthew Garden, Gregory Dudek
AAAI
2000
15 years 3 months ago
Selective Sampling with Redundant Views
Selective sampling, a form of active learning, reduces the cost of labeling training data by asking only for the labels of the most informative unlabeled examples. We introduce a ...
Ion Muslea, Steven Minton, Craig A. Knoblock