Name
Abstract | ||
|---|---|---|
Association rule mining, a critical technology for decision making, faces two key challenges: (a.) performance: unacceptably high response times that are not capable of supporting interactive analysis, and (b.) usability: lack of support for sense-making of rule relationships. In this paper I describe two solutions proposed in my dissertation research that tackle these challenges. Our proposed COLARM system addresses the online mining of local association rules. Further, our proposed PARAS and FIRE systems provide solutions for interactive mining of global association rules. Overall, this research encompasses contributions at the intersection of data mining, knowledge management and visual analytics. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1145/2663714.2668053 | PIKM@CIKM |
Keywords | Field | DocType |
association rule mining,general,interactive information visualization | Data science,Data mining,Interactive analysis,Information retrieval,Computer science,Usability,Visual analytics,Association rule learning | Conference |
Citations | PageRank | References |
0 | 0.34 | 25 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Abhishek Mukherji | 1 | 79 | 6.27 |
| Elke A. Rundensteiner | 2 | 4076 | 700.65 |
| Matthew O. Ward | 3 | 1757 | 189.48 |