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...
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...
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...
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...
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...