Browsing by Subject "H.3.3 [Information Search and Retrieval]"
Now showing items 1-5 of 5
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DaaG: Visual Analytics Clustering Using Network Representation
(The Eurographics Association, 2017)Finding useful patterns in datasets has attracted considerable interest in the field of visual analytics. One of the most common solutions is the identification and representation of clusters. In this work, we propose a ... -
Grontocrawler: Graph-Based Ontology Exploration
(The Eurographics Association, 2015)Biomedical ontologies helps discover hidden semantic links between heterogeneous and multi-scale biomedical datasets. Computational methods to ontology analysis may provide a semantic flavor to data analysis of biomedical ... -
Hierarchical Clustering with Multiple-Height Branch-Cut Applied to Short Time-Series Gene Expression Data
(The Eurographics Association, 2016)Rigid adherence to pre-specified thresholds and static graphical representations can lead to incorrect decisions on merging of clusters. As an alternative to existing automated or semi-automated methods, we developed a ... -
MLCut: Exploring Multi-Level Cuts in Dendrograms for Biological Data
(The Eurographics Association, 2016)Choosing a single similarity threshold for cutting dendrograms is not sufficient for performing hierarchical clustering analysis of heterogeneous data sets. In addition, alternative automated or semi-automated methods that ... -
Visual Comparative Case Analytics
(The Eurographics Association, 2017)Criminal Intelligence Analysis (CIA) faces a challenging task in handling high-dimensional data that needs to be investigated with complex analytical processes. State-of-the-art crime analysis tools do not fully support ...