Detail publikace

Approach to Visualisation of Evolving Association Rule Models

Originální název

Approach to Visualisation of Evolving Association Rule Models

Anglický název

Approach to Visualisation of Evolving Association Rule Models

Jazyk

en

Originální abstrakt

Visualization of evolving data mining models can allow good insight for a data analyst about these models and their changes in time. This paper presents our approach to visualization of evolving association rule models. This approach is based on graph visualization where nodes of the graph represent itemsets, and edges represent association rules. We show how evolving models, produced by data mining algorithms, are stored in the knowledge base, and then how they can be filtered and visualized. Two ways of graph based visualization of evolving models are shown using force based layout algorithms - local and global layout. Experiments with both are illustrated with emphasis on the latter.

Anglický abstrakt

Visualization of evolving data mining models can allow good insight for a data analyst about these models and their changes in time. This paper presents our approach to visualization of evolving association rule models. This approach is based on graph visualization where nodes of the graph represent itemsets, and edges represent association rules. We show how evolving models, produced by data mining algorithms, are stored in the knowledge base, and then how they can be filtered and visualized. Two ways of graph based visualization of evolving models are shown using force based layout algorithms - local and global layout. Experiments with both are illustrated with emphasis on the latter.

BibTex


@inproceedings{BUT103546,
  author="Martin {Hlosta} and Michal {Šebek} and Jaroslav {Zendulka}",
  title="Approach to Visualisation of Evolving Association Rule Models",
  annote="Visualization of evolving data mining models can allow good insight for a data
analyst about these models and their changes in time. This paper presents our
approach to visualization of evolving association rule models. This approach is
based on graph visualization where nodes of the graph represent itemsets, and
edges represent association rules. We show how evolving models, produced by data
mining algorithms, are stored in the knowledge base, and then how they can be
filtered and visualized. Two ways of graph based visualization of evolving models
are shown using force based layout algorithms - local and global layout.
Experiments with both are illustrated with emphasis on the latter.",
  address="The Society of Digital Information and Wireless Communications",
  booktitle="Proceedings of The Second International Conference on Informatics & Applications (ICIA 2013)",
  chapter="103546",
  edition="NEUVEDEN",
  howpublished="electronic, physical medium",
  institution="The Society of Digital Information and Wireless Communications",
  year="2013",
  month="august",
  pages="47--52",
  publisher="The Society of Digital Information and Wireless Communications",
  type="conference paper"
}