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KDD
2010
ACM
253views Data Mining» more  KDD 2010»
15 years 3 months ago
Mining periodic behaviors for moving objects
Periodicity is a frequently happening phenomenon for moving objects. Finding periodic behaviors is essential to understanding object movements. However, periodic behaviors could b...
Zhenhui Li, Bolin Ding, Jiawei Han, Roland Kays, P...
KDD
2009
ACM
188views Data Mining» more  KDD 2009»
16 years 11 days ago
Mining discrete patterns via binary matrix factorization
Mining discrete patterns in binary data is important for subsampling, compression, and clustering. We consider rankone binary matrix approximations that identify the dominant patt...
Bao-Hong Shen, Shuiwang Ji, Jieping Ye
KDD
2009
ACM
198views Data Mining» more  KDD 2009»
16 years 11 days ago
Pervasive parallelism in data mining: dataflow solution to co-clustering large and sparse Netflix data
All Netflix Prize algorithms proposed so far are prohibitively costly for large-scale production systems. In this paper, we describe an efficient dataflow implementation of a coll...
Srivatsava Daruru, Nena M. Marin, Matt Walker, Joy...
IDEAS
2009
IEEE
192views Database» more  IDEAS 2009»
15 years 6 months ago
A cluster-based approach to XML similarity joins
A natural consequence of the widespread adoption of XML as standard for information representation and exchange is the redundant storage of large amounts of persistent XML documen...
Leonardo Ribeiro, Theo Härder, Fernanda S. Pi...
IS
2010
14 years 10 months ago
Tree pattern mining with tree automata constraints
Most work on pattern mining focuses on simple data structures such as itemsets and sequences of itemsets. However, a lot of recent applications dealing with complex data like chem...
Sandra de Amo, Nyara A. Silva, Ronaldo P. Silva, F...