The DOI matches its Crossref record; 70 of the 70 references it cites were found in a registry or an index.
From visual data exploration to visual data mining: A survey
Abstract
We survey work on the different uses of graphical mapping and interaction techniques for visual data mining of large data sets represented as table data. Basic terminology related to data mining, data sets, and visualization is introduced. Previous work on information visualization is reviewed in light of different categorizations of techniques and systems. The role of interaction techniques is discussed, in addition to work addressing the question of selecting and evaluating visualization techniques. We review some representative work on the use of information visualization techniques in the context of mining data. This includes both visual data exploration and visually expressing the outcome of specific mining algorithms. We also review recent innovative approaches that attempt to integrate visualization into the DM/KDD process, using it to enhance user interaction and comprehension.
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Cites
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Hierarchical Aggregation for Information Visualization: Overview, Techniques, and Design Guidelines
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A Visual Text Mining approach for Systematic Reviews
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Metadata
- Authors
- de Oliveira, M. C. F., & Levkowitz, H.
- Venue
- IEEE Transactions on Visualization and Computer Graphics
- Published
- 2003-07
- Volume
- 9
- Issue
- 3
- Pages
- 378-394
- ISSN
- 1077-2626 (ISSN-L)
- OpenAlex
- W2119111481
- Cited by
- 511
- References
- 70
- FWCI
- 15.66
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
