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» Mining time-changing data streams
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ICDM
2009
IEEE
167views Data Mining» more  ICDM 2009»
13 years 5 months ago
Self-Adaptive Anytime Stream Clustering
Clustering streaming data requires algorithms which are capable of updating clustering results for the incoming data. As data is constantly arriving, time for processing is limited...
Philipp Kranen, Ira Assent, Corinna Baldauf, Thoma...
SDM
2004
SIAM
123views Data Mining» more  SDM 2004»
13 years 9 months ago
Nonlinear Manifold Learning for Data Stream
There has been a renewed interest in understanding the structure of high dimensional data set based on manifold learning. Examples include ISOMAP [25], LLE [20] and Laplacian Eige...
Martin H. C. Law, Nan Zhang 0002, Anil K. Jain
KDD
2012
ACM
205views Data Mining» more  KDD 2012»
11 years 10 months ago
Searching and mining trillions of time series subsequences under dynamic time warping
Most time series data mining algorithms use similarity search as a core subroutine, and thus the time taken for similarity search is the bottleneck for virtually all time series d...
Thanawin Rakthanmanon, Bilson J. L. Campana, Abdul...
WSDM
2012
ACM
245views Data Mining» more  WSDM 2012»
12 years 3 months ago
The early bird gets the buzz: detecting anomalies and emerging trends in information networks
In this work we propose a novel approach to anomaly detection in streaming communication data. We first build a stochastic model for the system based on temporal communication pa...
Brian Thompson
WWW
2011
ACM
13 years 2 months ago
Truthy: mapping the spread of astroturf in microblog streams
Online social media are complementing and in some cases replacing person-to-person social interaction and redefining the diffusion of information. In particular, microblogs have ...
Jacob Ratkiewicz, Michael Conover, Mark Meiss, Bru...