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» A Unifying Approach to Hard and Probabilistic Clustering
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SIGIR
2006
ACM
13 years 11 months ago
Unifying user-based and item-based collaborative filtering approaches by similarity fusion
Memory-based methods for collaborative filtering predict new ratings by averaging (weighted) ratings between, respectively, pairs of similar users or items. In practice, a large ...
Jun Wang, Arjen P. de Vries, Marcel J. T. Reinders
KDD
2005
ACM
177views Data Mining» more  KDD 2005»
13 years 11 months ago
Combining partitions by probabilistic label aggregation
Data clustering represents an important tool in exploratory data analysis. The lack of objective criteria render model selection as well as the identification of robust solutions...
Tilman Lange, Joachim M. Buhmann
ATAL
2006
Springer
13 years 9 months ago
Efficient agent-based cluster ensembles
Numerous domains ranging from distributed data acquisition to knowledge reuse need to solve the cluster ensemble problem of combining multiple clusterings into a single unified cl...
Adrian K. Agogino, Kagan Tumer
AI
2005
Springer
13 years 7 months ago
Incorporating Evidence in Bayesian Networks with the Select Operator
Abstract. In this paper, we propose that the select operator in relational databases be adopted for incorporating evidence in Bayesian networks. This approach does not involve the ...
Cory J. Butz, F. Fang
ICASSP
2011
IEEE
12 years 9 months ago
Outlier-aware robust clustering
Clustering is a basic task in a variety of machine learning applications. Partitioning a set of input vectors into compact, wellseparated subsets can be severely affected by the p...
Pedro A. Forero, Vassilis Kekatos, Georgios B. Gia...