15 Result(s)
within
Conference Paper
Claudia Plant
Information Systems Applications (incl. Internet)
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Chapter and Conference Paper
Granger Causality for Heterogeneous Processes
Discovery of temporal structures and finding causal interactions among time series have recently attracted attention of the data mining community. Among various causal notions graphical Granger causality is we...
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Chapter and Conference Paper
Clustering of Mixed-Type Data Considering Concept Hierarchies
Most clustering algorithms have been designed only for pure numerical or pure categorical data sets while nowadays many applications generate mixed data. It arises the question how to integrate various types o...
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Chapter and Conference Paper
Parameter Free Mixed-Type Density-Based Clustering
Nowadays many applications generate mixed data objects consisting of numerical and categorical attributes. Simultaneously dealing with mixed objects is more challenging and various approaches convert one type ...
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Chapter and Conference Paper
Information-Theoretic Non-redundant Subspace Clustering
A comprehensive understanding of complex data requires multiple different views. Subspace clustering methods open up multiple interesting views since they support data objects to be assigned to different clust...
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Chapter and Conference Paper
Knowledge Discovery of Complex Data Using Gaussian Mixture Models
With the explosive growth of data quantity and variety, the representation and analysis of complex data becomes a more and more challenging task in many modern applications. As a general class of probabilistic...
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Chapter and Conference Paper
Attributed Graph Clustering with Unimodal Normalized Cut
Graph vertices are often associated with attributes. For example, in addition to their connection relations, people in friendship networks have personal attributes, such as interests, age, and residence. Such ...
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Chapter and Conference Paper
Covariate-Related Structure Extraction from Paired Data
In the biological domain, it is more and more common to apply several high-throughput technologies to the same set of samples. We propose a Covariate-Related Structure Extraction approach (CRSE) that explores ...
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Chapter and Conference Paper
Stroke Lesion Segmentation Using a Probabilistic Atlas of Cerebral Vascular Territories
The accurate segmentation of lesions in magnetic resonance images of stroke patients is important, for example, for comparing the location of the lesion with functional areas and for determining the optimal st...
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Chapter and Conference Paper
Mining Medical Data to Obtain Fuzzy Predicates
The collection of methods known as ‘data mining’ offers methodological and technical solutions to deal with the analysis of medical data and the construction of models. Medical data have a special status based...
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Chapter and Conference Paper
Centroid Clustering of Cellular Lineage Trees
Trees representing hierarchical knowledge are prevalent in biology and medicine. Some examples are phylogenetic trees, the hierarchical structure of biological tissues and cell lines. The increasing throughput...
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Chapter and Conference Paper
Segmentation and Kinetic Analysis of Breast Lesions in DCE-MR Imaging Using ICA
Dynamic Contrast Enhance-Magnetic Resonance Imaging (DCE-MRI) has proved to be a useful tool for diagnosing mass-like breast cancer. For non-mass-like lesions, however, no methods applied on DCE-MRI have shown...
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Chapter and Conference Paper
Integrative Parameter-Free Clustering of Data with Mixed Type Attributes
Integrative mining of heterogeneous data is one of the major challenges for data mining in the next decade. We address the problem of integrative clustering of data with mixed type attributes. Most existing so...
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Chapter and Conference Paper
SkyDist: Data Mining on Skyline Objects
The skyline operator is a well established database primitive which is traditionally applied in a way that only a single skyline is computed. In this paper we use multiple skylines themselves as objects for da...
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Chapter and Conference Paper
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 hierarchical clustering, we have i...
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Chapter and Conference Paper
Synchronization Based Outlier Detection
The study of extraordinary observations is of great interest in a large variety of applications, such as criminal activities detection, athlete performance analysis, and rare events or exceptions identificatio...
