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» Mining time-changing data streams
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WSDM
2012
ACM
300views Data Mining» more  WSDM 2012»
12 years 3 months ago
Adding semantics to microblog posts
Microblogs have become an important source of information for the purpose of marketing, intelligence, and reputation management. Streams of microblogs are of great value because o...
Edgar Meij, Wouter Weerkamp, Maarten de Rijke
ICDM
2007
IEEE
132views Data Mining» more  ICDM 2007»
14 years 1 months ago
Granularity Conscious Modeling for Probabilistic Databases
The convergence of embedded sensor systems and stream query processing suggests an important role for database techniques, in managing data that only partially – and often inacc...
Eirinaios Michelakis, Daisy Zhe Wang, Minos N. Gar...
ICDM
2003
IEEE
240views Data Mining» more  ICDM 2003»
14 years 24 days ago
Clustering of Time Series Subsequences is Meaningless: Implications for Previous and Future Research
Given the recent explosion of interest in streaming data and online algorithms, clustering of time series subsequences, extracted via a sliding window, has received much attention...
Eamonn J. Keogh, Jessica Lin, Wagner Truppel
KDD
2002
ACM
186views Data Mining» more  KDD 2002»
14 years 8 months ago
Topic-conditioned novelty detection
Automated detection of the first document reporting each new event in temporally-sequenced streams of documents is an open challenge. In this paper we propose a new approach which...
Yiming Yang, Jian Zhang, Jaime G. Carbonell, Chun ...
TMM
2008
167views more  TMM 2008»
13 years 7 months ago
Mining Appearance Models Directly From Compressed Video
In this paper, we propose an approach to learning appearance models of moving objects directly from compressed video. The appearance of a moving object changes dynamically in vide...
Datong Chen, Qiang Liu, Mingui Sun, Jie Yang