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EDM
2009
105views Data Mining» more  EDM 2009»
15 years 4 months ago
Subspace Clustering of Skill Mastery: Identifying Skills that Separate Students
Abstract. In educational research, a fundamental goal is identifying which skills students have mastered, which skills they have not, and which skills they are in the process of ma...
Rebecca Nugent, Elizabeth Ayers, Nema Dean
DATAMINE
2006
224views more  DATAMINE 2006»
15 years 6 months ago
Characteristic-Based Clustering for Time Series Data
With the growing importance of time series clustering research, particularly for similarity searches amongst long time series such as those arising in medicine or finance, it is cr...
Xiaozhe Wang, Kate A. Smith, Rob J. Hyndman
CLUSTER
2011
IEEE
14 years 6 months ago
A Framework for Data-Intensive Computing with Cloud Bursting
—For many organizations, one attractive use of cloud resources can be through what is referred to as cloud bursting or the hybrid cloud. These refer to scenarios where an organiz...
Tekin Bicer, David Chiu, Gagan Agrawal
PAKDD
2001
ACM
148views Data Mining» more  PAKDD 2001»
15 years 10 months ago
Scalable Hierarchical Clustering Method for Sequences of Categorical Values
Data clustering methods have many applications in the area of data mining. Traditional clustering algorithms deal with quantitative or categorical data points. However, there exist...
Tadeusz Morzy, Marek Wojciechowski, Maciej Zakrzew...
JMLR
2010
225views more  JMLR 2010»
15 years 29 days ago
Hartigan's Method: k-means Clustering without Voronoi
Hartigan's method for k-means clustering is the following greedy heuristic: select a point, and optimally reassign it. This paper develops two other formulations of the heuri...
Matus Telgarsky, Andrea Vattani