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» Tight results for clustering and summarizing data streams
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ICDE
2012
IEEE
237views Database» more  ICDE 2012»
11 years 10 months ago
On Discovery of Traveling Companions from Streaming Trajectories
— The advance of object tracking technologies leads to huge volumes of spatio-temporal data collected in the form of trajectory data stream. In this study, we investigate the pro...
Lu An Tang, Yu Zheng, Jing Yuan, Jiawei Han, Alice...
JDCTA
2010
228views more  JDCTA 2010»
13 years 2 months ago
Research and Progress of Cluster Algorithms based on Granular Computing
Granular Computing (GrC), a knowledge-oriented computing which covers the theory of fuzzy information granularity, rough set theory, the theory of quotient space and interval comp...
Shifei Ding, Li Xu, Hong Zhu, Liwen Zhang
KDD
2007
ACM
178views Data Mining» more  KDD 2007»
14 years 8 months ago
Density-based clustering for real-time stream data
Existing data-stream clustering algorithms such as CluStream are based on k-means. These clustering algorithms are incompetent to find clusters of arbitrary shapes and cannot hand...
Yixin Chen, Li Tu
DEXA
2006
Springer
121views Database» more  DEXA 2006»
13 years 11 months ago
DCF: An Efficient Data Stream Clustering Framework for Streaming Applications
Streaming applications, such as environment monitoring and vehicle location tracking require handling high volumes of continuously arriving data and sudden fluctuations in these vo...
Kyungmin Cho, SungJae Jo, Hyukjae Jang, Su Myeon K...
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...