Name
Abstract | ||
|---|---|---|
The visual senses for humans have a unique status, offering a very broadband channel for information flow. Visual approaches to analysis and mining attempt to take advantage of our abilities to perceive pattern and structure in visual form and to make sense of, or interpret, what we see. Visual Data Mining techniques have proven to be of high value in exploratory data analysis and they also have a high potential for mining large databases. In this work, we try to investigate and expand the area of visual data mining by proposing a new 3-Dimensional visual data mining technique for the representation and mining of classification outcomes and association rules. Categories: I.2.4, I.2.6 Research Paper: Data Bases, Work Flow and Data mining |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1007/11573036_3 | Panhellenic Conference on Informatics |
Keywords | Field | DocType |
exploratory data analysis,3-dimensional visual data mining,data bases,data mining,visual approach,visual form,visual data mining,data mining outcome,visual sense,visual technique,visual data mining technique,mining attempt,3 dimensional,information flow,association rule | Information flow (information theory),Data mining,Concept mining,Text mining,Computer science,Communication channel,Information extraction,Association rule learning,Work flow,Exploratory data analysis | Conference |
Volume | ISSN | ISBN |
3746 | 0302-9743 | 3-540-29673-5 |
Citations | PageRank | References |
6 | 0.48 | 6 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ioannis Kopanakis | 1 | 264 | 16.68 |
| Nikos Pelekis | 2 | 881 | 59.28 |
| Haralampos Karanikas | 3 | 41 | 3.90 |
| Thomas Mavroudkis | 4 | 6 | 0.48 |