Visualization of Statistical Information in Concept Lattice Diagrams.
Research output: Contribution to book/Conference proceedings/Anthology/Report › Conference contribution › Contributed › peer-review
Contributors
Abstract
We propose a method of visualizing statistical information in concept lattice diagrams. To this end, we examine the characteristics of support, confidence, and lift, which are parameters used in association analysis. Based on our findings, we develop the notion of cascading line diagrams, a visualization method that combines the properties of additive line diagrams with association analysis. In such diagrams, one can read the size of a concept’s extent from the height of the corresponding node in the diagram and, at the same time, the geometry of the formed quadrangles illustrates whether two attributes are statistically independent or dependent and whether they are negatively or positively correlated. In order to demonstrate this visualization method, we have developed a program generating such diagrams.
Details
| Original language | English |
|---|---|
| Title of host publication | Formal Concept Analysis |
| Editors | Agnès Braud, Aleksey Buzmakov, Tom Hanika, Florence Le Ber |
| Pages | 208-223 |
| Number of pages | 16 |
| ISBN (electronic) | 978-3-030-77867-5 |
| Publication status | Published - Jun 2021 |
| Peer-reviewed | Yes |
Publication series
| Series | Lecture Notes in Computer Science |
|---|---|
| Volume | 12733 |
| ISSN | 0302-9743 |
External IDs
| Scopus | 85111436039 |
|---|