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» Approximate data mining in very large relational data
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TKDE
2012
270views Formal Methods» more  TKDE 2012»
13 years 4 months ago
Low-Rank Kernel Matrix Factorization for Large-Scale Evolutionary Clustering
—Traditional clustering techniques are inapplicable to problems where the relationships between data points evolve over time. Not only is it important for the clustering algorith...
Lijun Wang, Manjeet Rege, Ming Dong, Yongsheng Din...
KDD
2009
ACM
189views Data Mining» more  KDD 2009»
15 years 8 months ago
CoCo: coding cost for parameter-free outlier detection
How can we automatically spot all outstanding observations in a data set? This question arises in a large variety of applications, e.g. in economy, biology and medicine. Existing ...
Christian Böhm, Katrin Haegler, Nikola S. M&u...
PAKDD
2009
ACM
103views Data Mining» more  PAKDD 2009»
15 years 8 months ago
Hot Item Detection in Uncertain Data
Abstract. An object o of a database D is called a hot item, if there is a sufficiently large population of other objects in D that are similar to o. In other words, hot items are ...
Thomas Bernecker, Hans-Peter Kriegel, Matthias Ren...
JCIT
2010
174views more  JCIT 2010»
14 years 8 months ago
Efficient Ming of Top-K Closed Sequences
Sequence mining is an important data mining task. In order to retrieve interesting sequences from a large database, a minimum support threshold is needed to be specified. Unfortun...
Panida Songram
KDD
2012
ACM
271views Data Mining» more  KDD 2012»
13 years 4 months ago
GigaTensor: scaling tensor analysis up by 100 times - algorithms and discoveries
Many data are modeled as tensors, or multi dimensional arrays. Examples include the predicates (subject, verb, object) in knowledge bases, hyperlinks and anchor texts in the Web g...
U. Kang, Evangelos E. Papalexakis, Abhay Harpale, ...