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Found 11 papers, 0 papers with code
Linear Time Visualization and Search in Big Data using Pixellated Factor Space Mapping
It is demonstrated how linear computational time and storage efficient approaches can be adopted when analyzing very large data sets.
Core Conflictual Relationship: Text Mining to Discover What and When
The Correspondence Analysis methodology, also termed Geometric Data Analysis, is shown in a case study to be comprehensive and revealing.
Massive Data Clustering in Moderate Dimensions from the Dual Spaces of Observation and Attribute Data Clouds
Cluster analysis of very high dimensional data can benefit from the properties of such high dimensionality.
Contextualizing Geometric Data Analysis and Related Data Analytics: A Virtual Microscope for Big Data Analytics
The relevance and importance of contextualizing data analytics is described.
Qualitative Judgement of Research Impact: Domain Taxonomy as a Fundamental Framework for Judgement of the Quality of Research
The appeal of metric evaluation of research impact has attracted considerable interest in recent times.
Visualization of Jacques Lacan's Registers of the Psychoanalytic Field, and Discovery of Metaphor and of Metonymy. Analytical Case Study of Edgar Allan Poe's "The Purloined Letter"
In a first investigation, a Lacan-motivated template of the Poe story is fitted to the data.
Big Data Scaling through Metric Mapping: Exploiting the Remarkable Simplicity of Very High Dimensional Spaces using Correspondence Analysis
A particular benefit of Correspondence Analysis is its suitability for carrying out an orthonormal mapping, or scaling, of power law distributed data.
Correspondence Factor Analysis of Big Data Sets: A Case Study of 30 Million Words; and Contrasting Analytics using Apache Solr and Correspondence Analysis in R
A further novelty is that querying is supported in Solr based on the principal factor plane mapping of all the data.
Pattern Recognition in Narrative: Tracking Emotional Expression in Context
Using geometric data analysis, our objective is the analysis of narrative, with narrative of emotion being the focus in this work.
Ultrametric Component Analysis with Application to Analysis of Text and of Emotion
We do this in order to have a framework (including visualization and supporting interpretation) for the parts of the data that are determined to be ultrametric.
A History of Cluster Analysis Using the Classification Society's Bibliography Over Four Decades
In earlier decades it was distributed as a diskette or CD with the Journal of Classification.
