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MMM
2012
Springer
294views Multimedia» more  MMM 2012»
7 years 3 months ago
Improving Cluster Selection and Event Modeling in Unsupervised Mining for Automatic Audiovisual Video Structuring
Abstract. Can we discover audio-visually consistent events from videos in a totally unsupervised manner? And, how to mine videos with different genres? In this paper we present our...
Anh-Phuong Ta, Mathieu Ben, Guillaume Gravier
AAAI
2011
7 years 8 months ago
Improving Semi-Supervised Support Vector Machines Through Unlabeled Instances Selection
Semi-supervised support vector machines (S3VMs) are a kind of popular approaches which try to improve learning performance by exploiting unlabeled data. Though S3VMs have been fou...
Yu-Feng Li, Zhi-Hua Zhou
IGPL
2011
8 years 3 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...
ICDM
2009
IEEE
147views Data Mining» more  ICDM 2009»
8 years 6 months ago
Greedy Optimization for Contiguity-Constrained Hierarchical Clustering
The discovery and construction of inherent regions in large spatial datasets is an important task for many research domains such as climate zoning, eco-region analysis, public heal...
Diansheng Guo
ICPR
2010
IEEE
8 years 6 months ago
User Adaptive Clustering for Large Image Databases
Abstract--Searching large image databases is a time consuming process when done manually. Current CBIR methods mostly rely on training data in specific domains. When source and dom...
Mohammad Mehdi Saboorian, Mansour Jamzad, Hamid R....
ICDM
2010
IEEE
198views Data Mining» more  ICDM 2010»
8 years 6 months ago
Hierarchical Ensemble Clustering
Ensemble clustering has emerged as an important elaboration of the classical clustering problems. Ensemble clustering refers to the situation in which a number of different (input)...
Li Zheng, Tao Li, Chris H. Q. Ding
PKDD
2010
Springer
177views Data Mining» more  PKDD 2010»
8 years 6 months ago
ITCH: Information-Theoretic Cluster Hierarchies
Hierarchical clustering methods are widely used in various scientific domains such as molecular biology, medicine, economy, etc. Despite the maturity of the research field of hie...
Christian Böhm, Frank Fiedler, Annahita Oswal...
BMCBI
2004
113views more  BMCBI 2004»
8 years 8 months ago
Influence of microarrays experiments missing values on the stability of gene groups by hierarchical clustering
Background: Microarray technologies produced large amount of data. The hierarchical clustering is commonly used to identify clusters of co-expressed genes. However, microarray dat...
Alexandre G. de Brevern, Serge A. Hazout, Alain Ma...
SIAMSC
2008
159views more  SIAMSC 2008»
8 years 8 months ago
Hierarchical Clustering of Massive, High Dimensional Data Sets by Exploiting Ultrametric Embedding
Coding of data, usually upstream of data analysis, has crucial implications for the data analysis results. By modifying the data coding
Fionn Murtagh, Geoff Downs, Pedro Contreras
PR
2006
116views more  PR 2006»
8 years 8 months ago
Shared farthest neighbor approach to clustering of high dimensionality, low cardinality data
Clustering algorithms are routinely used in biomedical disciplines, and are a basic tool in bioinformatics. Depending on the task at hand, there are two most popular options, the ...
Stefano Rovetta, Francesco Masulli
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