An information-aware framework for exploring multivariate data sets
Information theory provides a theoretical framework for measuring information content for an
observed variable, and has attracted much attention from visualization researchers for its …
observed variable, and has attracted much attention from visualization researchers for its …
Streamstory: exploring multivariate time series on multiple scales
This paper presents an approach for the interactive visualization, exploration and
interpretation of large multivariate time series. Interesting patterns in such datasets usually …
interpretation of large multivariate time series. Interesting patterns in such datasets usually …
Evaluating reordering strategies for cluster identification in parallel coordinates
The ability to perceive patterns in parallel coordinates plots (PCPs) is heavily influenced by
the ordering of the dimensions. While the community has proposed over 30 automatic …
the ordering of the dimensions. While the community has proposed over 30 automatic …
GRay: Ray Casting for Visualization and Interactive Data Exploration of Gaussian Mixture Models
The Gaussian mixture model (GMM) describes the distribution of random variables from
several different populations. GMMs have widespread applications in probability theory …
several different populations. GMMs have widespread applications in probability theory …
Using entropy-related measures in categorical data visualization
A wide variety of real-world applications generate massive high dimensional categorical
datasets. These datasets contain categorical variables whose values comprise a set of …
datasets. These datasets contain categorical variables whose values comprise a set of …
The role of artefact corpus in lsi-based traceability recovery
Latent Semantic Indexing (LSI) is an advanced method widely and successfully employed in
Information Retrieval (IR). It is an extension of Vector Space Model (VSM) and it is able to …
Information Retrieval (IR). It is an extension of Vector Space Model (VSM) and it is able to …
Parallel coordinates metrics for classification visualization
The high dimensionality of data presents a major issue in understanding and interpreting the
results of classification learning. Among the various approaches that address this issue …
results of classification learning. Among the various approaches that address this issue …
Dimensions reordering for visual mining of association rules using parallel set
Mining the interesting association rules from data and clusters presents high demands in
many application fields, such as telephonic operator, social networks, marketing especially …
many application fields, such as telephonic operator, social networks, marketing especially …
[کتاب][B] Supporting interactive visual analytics for high dimensional data exploration
JM Alsakran - 2012 - search.proquest.com
High dimensional data is everywhere in our life and in all sectors of our society: text, image,
audio, video, and other. Analyzing such rich data and understanding its behavioral and …
audio, video, and other. Analyzing such rich data and understanding its behavioral and …
Pattern-Driven Design of Visualizations for High-Dimensional Data
M Blumenschein - 2020 - kops.uni-konstanz.de
Data-informed decision-making processes play a fundamental role across disciplines. To
support these processes, knowledge needs to be extracted from high-dimensional (HD) and …
support these processes, knowledge needs to be extracted from high-dimensional (HD) and …