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DMKD
2003
ACM
148views Data Mining» more  DMKD 2003»
16 years 25 days ago
A symbolic representation of time series, with implications for streaming algorithms
The parallel explosions of interest in streaming data, and data mining of time series have had surprisingly little intersection. This is in spite of the fact that time series data...
Jessica Lin, Eamonn J. Keogh, Stefano Lonardi, Bil...
TDP
2010
166views more  TDP 2010»
15 years 2 months ago
Communication-Efficient Privacy-Preserving Clustering
The ability to store vast quantities of data and the emergence of high speed networking have led to intense interest in distributed data mining. However, privacy concerns, as well ...
Geetha Jagannathan, Krishnan Pillaipakkamnatt, Reb...
KDD
2007
ACM
139views Data Mining» more  KDD 2007»
16 years 8 months ago
Looking for Great Ideas: Analyzing the Innovation Jam
We discuss the Innovation Jam that IBM carried out in 2006, with the objective of identifying innovative and promising "Big Ideas" through a moderated on-line discussion...
Wojciech Gryc, Mary E. Helander, Richard D. Lawren...
KDD
2004
ACM
103views Data Mining» more  KDD 2004»
16 years 8 months ago
An objective evaluation criterion for clustering
We propose and test an objective criterion for evaluation of clustering performance: How well does a clustering algorithm run on unlabeled data aid a classification algorithm? The...
Arindam Banerjee, John Langford
KDD
2004
ACM
127views Data Mining» more  KDD 2004»
16 years 8 months ago
A generative probabilistic approach to visualizing sets of symbolic sequences
There is a notable interest in extending probabilistic generative modeling principles to accommodate for more complex structured data types. In this paper we develop a generative ...
Peter Tiño, Ata Kabán, Yi Sun