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KDD
2008
ACM
119views Data Mining» more  KDD 2008»
14 years 10 months ago
SAIL: summation-based incremental learning for information-theoretic clustering
Information-theoretic clustering aims to exploit information theoretic measures as the clustering criteria. A common practice on this topic is so-called INFO-K-means, which perfor...
Junjie Wu, Hui Xiong, Jian Chen
KDD
2007
ACM
191views Data Mining» more  KDD 2007»
14 years 10 months ago
Modeling relationships at multiple scales to improve accuracy of large recommender systems
The collaborative filtering approach to recommender systems predicts user preferences for products or services by learning past useritem relationships. In this work, we propose no...
Robert M. Bell, Yehuda Koren, Chris Volinsky
KDD
2007
ACM
159views Data Mining» more  KDD 2007»
14 years 10 months ago
Domain-constrained semi-supervised mining of tracking models in sensor networks
Accurate localization of mobile objects is a major research problem in sensor networks and an important data mining application. Specifically, the localization problem is to deter...
Rong Pan, Junhui Zhao, Vincent Wenchen Zheng, Jeff...
KDD
2004
ACM
154views Data Mining» more  KDD 2004»
14 years 10 months ago
Diagnosing extrapolation: tree-based density estimation
There has historically been very little concern with extrapolation in Machine Learning, yet extrapolation can be critical to diagnose. Predictor functions are almost always learne...
Giles Hooker
EUROSSC
2009
Springer
14 years 4 months ago
Semantic Rules for Context-Aware Geographical Information Retrieval
Geographical information retrieval (GIR) can benefit from context information to adapt the results to a user’s current situation and personal preferences. In this respect, seman...
Carsten Keßler, Martin Raubal, Christoph Wos...