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ICDM
2007
IEEE
159views Data Mining» more  ICDM 2007»
16 years 27 days ago
Incremental Subspace Clustering over Multiple Data Streams
Data streams are often locally correlated, with a subset of streams exhibiting coherent patterns over a subset of time points. Subspace clustering can discover clusters of objects...
Qi Zhang, Jinze Liu, Wei Wang 0010
KDD
2010
ACM
300views Data Mining» more  KDD 2010»
15 years 10 months ago
Mining top-k frequent items in a data stream with flexible sliding windows
We study the problem of finding the k most frequent items in a stream of items for the recently proposed max-frequency measure. Based on the properties of an item, the maxfrequen...
Hoang Thanh Lam, Toon Calders
AAAI
2010
15 years 3 months ago
Multilinear Maximum Distance Embedding Via L1-Norm Optimization
Dimensionality reduction plays an important role in many machine learning and pattern recognition tasks. In this paper, we present a novel dimensionality reduction algorithm calle...
Yang Liu, Yan Liu, Keith C. C. Chan
CVPR
2004
IEEE
16 years 8 months ago
Alignment of Continuous Video onto 3D Point Clouds
We propose a general framework for aligning continuous (oblique) video onto 3D sensor data. We align a point cloud computed from the video onto the point cloud directly obtained f...
Wen-Yi Zhao, David Nistér, Steven C. Hsu
ICDM
2006
IEEE
86views Data Mining» more  ICDM 2006»
16 years 19 days ago
Turning Clusters into Patterns: Rectangle-Based Discriminative Data Description
The ultimate goal of data mining is to extract knowledge from massive data. Knowledge is ideally represented as human-comprehensible patterns from which end-users can gain intuiti...
Byron J. Gao, Martin Ester