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PRL
2006
207views more  PRL 2006»
13 years 7 months ago
On-line trajectory clustering for anomalous events detection
In this paper we propose a trajectory clustering algorithm suited for video surveillance systems. Trajectories are clustered on-line, as the data are collected, and clusters are o...
Claudio Piciarelli, Gian Luca Foresti
BMCBI
2004
96views more  BMCBI 2004»
13 years 7 months ago
A hybrid clustering approach to recognition of protein families in 114 microbial genomes
Background: Grouping proteins into sequence-based clusters is a fundamental step in many bioinformatic analyses (e.g., homology-based prediction of structure or function). Standar...
Timothy J. Harlow, J. Peter Gogarten, Mark A. Raga...
IGPL
2011
13 years 2 months ago
A new clustering algorithm applying a hierarchical method neural network
Clustering is a branch of multivariate analysis that is used to create groups of data. While there are currently a variety of techniques that are used for creating clusters, many ...
Javier Bajo, Juan Francisco de Paz, Sara Rodr&iacu...
ACIVS
2008
Springer
14 years 2 months ago
Knee Point Detection in BIC for Detecting the Number of Clusters
Bayesian Information Criterion (BIC) is a promising method for detecting the number of clusters. It is often used in model-based clustering in which a decisive first local maximum ...
Qinpei Zhao, Ville Hautamäki, Pasi Fränt...
IJIS
2007
155views more  IJIS 2007»
13 years 7 months ago
Clustering web search results using fuzzy ants
Algorithms for clustering web search results have to be efficient and robust. Furthermore they must be able to cluster a dataset without using any kind of a priori information, s...
Steven Schockaert, Martine De Cock, Chris Cornelis...