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ISNN
2004
Springer
14 years 28 days ago
Unsupervised Learning for Hierarchical Clustering Using Statistical Information
This paper proposes a novel hierarchical clustering method that can classify given data without specified knowledge of the number of classes. In this method, at each node of a hie...
Masaru Okamoto, Nan Bu, Toshio Tsuji
EUROPAR
2001
Springer
14 years 1 days ago
Experiments in Parallel Clustering with DBSCAN
We present a new result concerning the parallelisation of DBSCAN, a Data Mining algorithm for density-based spatial clustering. The overall structure of DBSCAN has been mapped to a...
Domenica Arlia, Massimo Coppola
ECHT
1994
13 years 11 months ago
VIKI: Spatial Hypertext Supporting Emergent Structure
The emergent nature of structure is a crucial, but often ignored, constraint on authoring hypertexts. VIKI is a spatial hypertext system that supports the emergent s of structure ...
Catherine C. Marshall, Frank M. Shipman III, James...
ICIP
2004
IEEE
14 years 9 months ago
Automatically learning structural units in educational videos with the hierarchical hidden markov models
In this paper we present a coherent approach using the hierarchical HMM with shared structures to extract the structural units that form the building blocks of an education/traini...
Dinh Q. Phung, Svetha Venkatesh, Hung Hai Bui
CPHYSICS
2006
124views more  CPHYSICS 2006»
13 years 7 months ago
Collision-free spatial hash functions for structural analysis of billion-vertex chemical bond networks
State-of-the-art molecular dynamics (MD) simulations generate massive datasets involving billion-vertex chemical bond networks, which makes data mining based on graph algorithms s...
Cheng Zhang, Bhupesh Bansal, Paulo S. Branicio, Ra...