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Background: Structural genomics initiatives are producing increasing numbers of three-dimensional (3D) structures for which there is little functional information. Structure-based annotation of molecular function is therefore becoming critical. We previous ...
Trajectory data is of crucial importance for a vast range of applications involving analysis of moving objects behavior. Unfortunately, the extraction of relevant knowledge from trajectory data is hindered by the lack of semantics and the presence of error ...
Springer-Verlag New York, Ms Ingrid Cunningham, 175 Fifth Ave, New York, Ny 10010 Usa2008
This paper aims at investigating the use of sequential clustering for speaker diarization. Conventional diarization systems are based on parametric models and agglomerative clustering. In our previous work we proposed a non-parametric method based on the a ...
Precise short-term prediction of traffic parameters such as flow and travel-time is a necessary component for many ITS applications. This work describes the research on a novel, fast, and robust algorithm which is based on a partitioning cluster analysis. ...
Data alone are worth almost nothing. While data collection is increasing exponentially worldwide, a clear distinction between retrieving data and obtaining knowledge has to be made. Data are retrieved while measuring phenomena or gathering facts. Knowledge ...
Clustering similar documents is a difficult task for text data mining. Difficulties stem especially from the way documents are translated into numerical vectors. In this chapter, we will present a method that uses Self Organizing Map (SOM) to cluster medic ...
This paper aims at investigating the use of sequential clustering for speaker diarization. Conventional diarization systems are based on parametric models and agglomerative clustering. In our previous work we proposed a non-parametric method based on the a ...
One of the shortcomings of the existing clustering methods is their problems dealing with different shape and size clusters. On the other hand, most of these methods are designed for especial cluster types or have good performance dealing with particular s ...
Co-clustering has not been much exploited in biomedical in- formatics, despite its success in other domains. Most of the previous applications were limited to analyzing gene expression data. We performed co-clustering analysis on other types of data and ob ...
Institute of Electrical and Electronics Engineers2007
The extension of the likelihood method of Süveges (Extremes, 2007) is presented. The extension allows for finding independent clusters of extreme events and determining the range of dependence on extremal levels, and estimate clustering characteristic of t ...
