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BMVC
2010
13 years 6 months ago
Probabilistic Latent Sequential Motifs: Discovering Temporal Activity Patterns in Video Scenes
This paper introduces a novel probabilistic activity modeling approach that mines recurrent sequential patterns from documents given as word-time occurrences. In this model, docum...
Jagannadan Varadarajan, Rémi Emonet, Jean-M...
NIPS
2001
13 years 9 months ago
Laplacian Eigenmaps and Spectral Techniques for Embedding and Clustering
Drawing on the correspondence between the graph Laplacian, the Laplace-Beltrami operator on a manifold, and the connections to the heat equation, we propose a geometrically motiva...
Mikhail Belkin, Partha Niyogi
COMAD
2009
13 years 9 months ago
Categorizing Concepts for Detecting Drifts in Stream
Mining evolving data streams for concept drifts has gained importance in applications like customer behavior analysis, network intrusion detection, credit card fraud detection. Se...
Sharanjit Kaur, Vasudha Bhatnagar, Sameep Mehta, S...
ICDM
2003
IEEE
92views Data Mining» more  ICDM 2003»
14 years 1 months ago
Validating and Refining Clusters via Visual Rendering
Clustering is an important technique for understanding and analysis of large multi-dimensional datasets in many scientific applications. Most of clustering research to date has be...
Keke Chen, Ling Liu
AMAI
2007
Springer
13 years 8 months ago
Relational concept discovery in structured datasets
Relational datasets, i.e., datasets in which individuals are described both by their own features and by their relations to other individuals, arise from various sources such as d...
Marianne Huchard, Mohamed Rouane Hacene, Cyril Rou...