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KDD
2012
ACM
235views Data Mining» more  KDD 2012»
11 years 10 months ago
A near-linear time approximation algorithm for angle-based outlier detection in high-dimensional data
Outlier mining in d-dimensional point sets is a fundamental and well studied data mining task due to its variety of applications. Most such applications arise in high-dimensional ...
Ninh Pham, Rasmus Pagh
CIKM
2008
Springer
13 years 9 months ago
SoRec: social recommendation using probabilistic matrix factorization
Data sparsity, scalability and prediction quality have been recognized as the three most crucial challenges that every collaborative filtering algorithm or recommender system conf...
Hao Ma, Haixuan Yang, Michael R. Lyu, Irwin King
SIGIR
2005
ACM
14 years 1 months ago
An industrial-strength content-based music recommendation system
We present a metadata free system for the interaction with massive collections of music, the MusicSurfer. MusicSurfer automatically extracts descriptions related to instrumentatio...
Pedro Cano, Markus Koppenberger, Nicolas Wack
KDD
2009
ACM
305views Data Mining» more  KDD 2009»
14 years 8 months ago
Grocery shopping recommendations based on basket-sensitive random walk
We describe a recommender system in the domain of grocery shopping. While recommender systems have been widely studied, this is mostly in relation to leisure products (e.g. movies...
Ming Li, M. Benjamin Dias, Ian H. Jarman, Wael El-...
KDD
2004
ACM
158views Data Mining» more  KDD 2004»
14 years 8 months ago
A generalized maximum entropy approach to bregman co-clustering and matrix approximation
Co-clustering is a powerful data mining technique with varied applications such as text clustering, microarray analysis and recommender systems. Recently, an informationtheoretic ...
Arindam Banerjee, Inderjit S. Dhillon, Joydeep Gho...