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SIGMOD
2004
ACM
157views Database» more  SIGMOD 2004»
16 years 6 months ago
Adaptive Ordering of Pipelined Stream Filters
We consider the problem of pipelined filters, where a continuous stream of tuples is processed by a set of commutative filters. Pipelined filters are common in stream applications...
Shivnath Babu, Rajeev Motwani, Kamesh Munagala, It...
EDBT
2004
ACM
142views Database» more  EDBT 2004»
16 years 6 months ago
Iterative Incremental Clustering of Time Series
We present a novel anytime version of partitional clustering algorithm, such as k-Means and EM, for time series. The algorithm works by leveraging off the multi-resolution property...
Jessica Lin, Michail Vlachos, Eamonn J. Keogh, Dim...
ICSE
2003
IEEE-ACM
16 years 6 months ago
Beyond the Personal Software Process: Metrics collection and analysis for the differently disciplined
Pedagogies such as the Personal Software Process (PSP) shift metrics definition, collection, and analysis from the organizational level to the individual level. While case study r...
Philip M. Johnson, Hongbing Kou, Joy Agustin, Chri...
DCC
2005
IEEE
16 years 6 months ago
The Markov Expert for Finding Episodes in Time Series
We describe a domain-independent, unsupervised algorithm for refined segmentation of time series data into meaningful episodes, focusing on the problem of text segmentation. The V...
Jimming Cheng, Michael Mitzenmacher
SDM
2009
SIAM
144views Data Mining» more  SDM 2009»
16 years 3 months ago
CORE: Nonparametric Clustering of Large Numeric Databases.
Current clustering techniques are able to identify arbitrarily shaped clusters in the presence of noise, but depend on carefully chosen model parameters. The choice of model param...
Andrej Taliun, Arturas Mazeika, Michael H. Bö...
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