Information visualization and visual data mining

Keim, Daniel A.

doi:10.1109/2945.981847

Cited by 1,292 publications

(897 citation statements)

References 48 publications

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“…Typically, a details on demand approach is defined by displaying pop-up windows or hierarchical menu. An effective example of location probe is linked brushing, i.e., the cursor passing over one location creates visual effects to other markers [9]. In more details, a selection done in one view should be visible in another view, regardless the different dimensions that may be shown.…”

Section: Information Visualizationmentioning

confidence: 99%

Visual MRI: Merging information visualization and non-parametric clustering techniques for MRI dataset analysis

Castellani

Cristani

Combi

et al. 2008

Artificial Intelligence in Medicine

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SummaryObjective. This paper presents Visual MRI, an innovative tool for the magnetic resonance imaging (MRI) analysis of tumoral tissues. The main goal of the analysis is to separate each magnetic resonance image in meaningful clusters, highlighting zones which are more probably related with the cancer evolution. Such non-invasive analysis serves to address novel cancer treatments, resulting in a less destabilizing and more effective type of therapy than the chemotherapy-based ones. The advancements brought by Visual MRI are two: first, it is an integration of effective infor-

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Section: Information Visualizationmentioning

confidence: 99%

Visual MRI: Merging information visualization and non-parametric clustering techniques for MRI dataset analysis

Castellani

Cristani

Combi

et al. 2008

Artificial Intelligence in Medicine

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“…Unfortunately, these techniques allowed almost no interaction between the human actor and the tool and failed at incorporating valuable expert knowledge into the discovery process (Keim 2002), which is needed to go beyond uncovering the fool's gold. These techniques assume a clear definition of the concepts available in the underlying data which is often not the case.…”

Section: Knowledge Discovery and Data Miningmentioning

confidence: 99%

Formal Concept Analysis in Knowledge Discovery: A Survey

Poelmans

Elzinga²,

Viaene

et al. 2010

Lecture Notes in Computer Science

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Abstract.In this paper, we analyze the literature on Formal Concept Analysis (FCA) using FCA. We collected 702 papers published between 2003-2009 mentioning Formal Concept Analysis in the abstract. We developed a knowledge browsing environment to support our literature analysis process. The pdf-files containing the papers were converted to plain text and indexed by Lucene using a thesaurus containing terms related to FCA research. We use the visualization capabilities of FCA to explore the literature, to discover and conceptually represent the main research topics in the FCA community. As a case study, we zoom in on the 140 papers on using FCA in knowledge discovery and data mining and give an extensive overview of the contents of this literature.

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“…As regards Data Visualization (DV), and specifically Multidimensional (unknown relations between attributes) Multivariate Data Visualization (MMDV), there are four broad categories [6] according to the approaches taken to generate the resulting visualizations. The first, Geometric projection, includes techniques that aim to find informative projections and transformations of multidimensional datasets [7] such as the Scatterplot Matrix [8], the Prosection Matrix [9], Parallel Coordinates [10] and Star Coordinates [11].…”

Section: Related Workmentioning

confidence: 99%

MedVir: An Interactive Representation System of Multidimensional Medical Data Applied to Traumatic Brain Injury’s Rehabilitation Prediction

González

Gracia

Herrero

et al. 2014

Rough Sets and Intelligent Systems Paradigms

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Abstract. Clinicians could model the brain injury of a patient through his brain activity. However, how this model is defined and how it changes when the patient is recovering are questions yet unanswered. In this paper, the use of MedVir framework is proposed with the aim of answering these questions. Based on complex data mining techniques, this provides not only the differentiation between TBI patients and control subjects (with a 72% of accuracy using 0.632 Bootstrap validation), but also the ability to detect whether a patient may recover or not, and all of that in a quick and easy way through a visualization technique which allows interaction.

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Information visualization and visual data mining

Cited by 1,292 publications

References 48 publications

Visual MRI: Merging information visualization and non-parametric clustering techniques for MRI dataset analysis

Visual MRI: Merging information visualization and non-parametric clustering techniques for MRI dataset analysis

Formal Concept Analysis in Knowledge Discovery: A Survey

MedVir: An Interactive Representation System of Multidimensional Medical Data Applied to Traumatic Brain Injury’s Rehabilitation Prediction

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