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Detection of Review Abuse via Semi-Supervised Binary Multi-..:

, In: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining,

Yelundur, Anil R. ; Chaoji, Vineet ; Mishra, Bamdev - p. 2134-2144 , 2019

Link: https://dl.acm.org/doi/10.1145/3292500.3330678

RT 
T1 <cTitle>Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining</cTitle>: T1 <Title>Detection of Review Abuse via Semi-Supervised Binary Multi-Target Tensor Decomposition</Title>

UL https://suche.suub.uni-bremen.de/peid=acm-3330678&Exemplar=1&LAN=DE
				
A1 Yelundur, Anil R.
A1 Chaoji, Vineet
A1 Mishra, Bamdev
PB ACM
YR 2019
K1 e-commerce
K1 reviewers
K1 reviews data
K1 sellers
K1 stochastic partial natural gradients
K1 tensor decomposition
K1 Mathematics of computing
K1 Probability and statistics
K1 Computing methodologies
K1 Machine learning
K1 Learning paradigms
K1 Unsupervised learning
K1 Anomaly detection
K1 Machine learning approaches
K1 Learning in probabilistic graphical models
K1 Latent variable models
K1 Maximum a posteriori modeling
K1 Machine learning algorithms
K1 Regularization
K1 Factorization methods
K1 Factor analysis
K1 Probabilistic algorithms
K1 Probabilistic inference problems
K1 Bayesian computation
K1 Probabilistic representations
K1 Nonparametric representations
K1 Bayesian nonparametric models
SP 2134
OP 2144
LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3292500.3330678
DO https://dl.acm.org/doi/10.1145/3292500.3330678
SF ELIB - SuUB Bremen

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