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ISNN
2004
Springer
15 years 3 months 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
15 years 2 months 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
15 years 1 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
15 years 11 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»
14 years 9 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...