Abstract
In this paper we present an information visualization approach for visualizing the intersection between multiple feature hierarchies. In cases where a dataset has multiple complex features of interest, especially ones that have been hierarchically clustered, it is often very difficult to grasp the commonalities between them. Understanding the overlap between features can help researchers discover correlations or hot spots in their data. Our method steps back from actual data features, simplifying their representation, and presenting them in a fashion which facilitates interpretation of their inter-feature relationships. We call this new representation a knowledge graph, and we show how it can be used to investigate the overlap of multiple features in a photo database and a social network dataset.
| Original language | English (US) |
|---|---|
| Title of host publication | DMS 2010 - Proceedings of the 16th International Conference on Distributed Multimedia Systems |
| Pages | 251-256 |
| Number of pages | 6 |
| State | Published - Dec 1 2010 |
| Event | 16th International Conference on Distributed Multimedia Systems, DMS 2010 - Oak Brook, IL, United States Duration: Oct 14 2010 → Oct 16 2010 |
Other
| Other | 16th International Conference on Distributed Multimedia Systems, DMS 2010 |
|---|---|
| Country | United States |
| City | Oak Brook, IL |
| Period | 10/14/10 → 10/16/10 |
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ASJC Scopus subject areas
- Computer Graphics and Computer-Aided Design
- Human-Computer Interaction
- Software
Cite this
Visualizing the commonalities between hierarchically structured data queries. / Jones, Chad; Armstrong, Ryan; Ma, Kwan-Liu.
DMS 2010 - Proceedings of the 16th International Conference on Distributed Multimedia Systems. 2010. p. 251-256.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Visualizing the commonalities between hierarchically structured data queries
AU - Jones, Chad
AU - Armstrong, Ryan
AU - Ma, Kwan-Liu
PY - 2010/12/1
Y1 - 2010/12/1
N2 - In this paper we present an information visualization approach for visualizing the intersection between multiple feature hierarchies. In cases where a dataset has multiple complex features of interest, especially ones that have been hierarchically clustered, it is often very difficult to grasp the commonalities between them. Understanding the overlap between features can help researchers discover correlations or hot spots in their data. Our method steps back from actual data features, simplifying their representation, and presenting them in a fashion which facilitates interpretation of their inter-feature relationships. We call this new representation a knowledge graph, and we show how it can be used to investigate the overlap of multiple features in a photo database and a social network dataset.
AB - In this paper we present an information visualization approach for visualizing the intersection between multiple feature hierarchies. In cases where a dataset has multiple complex features of interest, especially ones that have been hierarchically clustered, it is often very difficult to grasp the commonalities between them. Understanding the overlap between features can help researchers discover correlations or hot spots in their data. Our method steps back from actual data features, simplifying their representation, and presenting them in a fashion which facilitates interpretation of their inter-feature relationships. We call this new representation a knowledge graph, and we show how it can be used to investigate the overlap of multiple features in a photo database and a social network dataset.
UR - http://www.scopus.com/inward/record.url?scp=79952430482&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79952430482&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:79952430482
SN - 1891706284
SN - 9781891706288
SP - 251
EP - 256
BT - DMS 2010 - Proceedings of the 16th International Conference on Distributed Multimedia Systems
ER -