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» Massive Data Pre-Processing with a Cluster Based Approach
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KDD
2007
ACM
178views Data Mining» more  KDD 2007»
14 years 7 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
CVIU
1999
238views more  CVIU 1999»
13 years 7 months ago
A Coarse to Fine 3D Registration Method Based on Robust Fuzzy Clustering
An important problem in computer vision is to determine how features extracted from images are connected to an existing model. In this paper, we focus on solving the registration ...
Jean-Philippe Tarel, Nozha Boujemaa
CAMP
2005
IEEE
14 years 29 days ago
Reinforcement Learning for P2P Searching
— For a peer-to-peer (P2P) system holding massive amount of data, an efficient and scalable search for resource sharing is a key determinant to its practical usage. Unstructured...
Luca Gatani, Giuseppe Lo Re, Alfonso Urso, Salvato...
EDBT
2004
ACM
268views Database» more  EDBT 2004»
14 years 7 months ago
DBDC: Density Based Distributed Clustering
Abstract. Clustering has become an increasingly important task in modern application domains such as marketing and purchasing assistance, multimedia, molecular biology as well as m...
Eshref Januzaj, Hans-Peter Kriegel, Martin Pfeifle
ICPR
2002
IEEE
14 years 8 months ago
Fast Hierarchical Clustering Based on Compressed Data
: One way to scale up clustering algorithms is to squash the data by some intelligent compression technique and cluster only the compressed data records. Such compressed data recor...
Erendira Rendon, Ricardo Barandela