Name
Abstract | ||
|---|---|---|
In this paper we propose an extension of the sequence mining paradigm to (temporally-)annotated sequential patterns, where each transition in a sequential pattern is annotated with a typical transition time derived from the source data. Then, we present a basic solution for the novel mining problem based on the combination of sequential pattern mining and clustering, and assess this solution on two realistic datasets, illustrating how potentially useful patterns of the new form are extracted. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1145/1141277.1141413 | SAC |
Keywords | Field | DocType |
sequential pattern,temporal annotation,realistic datasets,sequence mining paradigm,sequential pattern mining,annotated sequential pattern,mining sequence,useful pattern,basic solution,typical transition time,novel mining problem,new form | Data mining,Computer science,Source data,Transition time,Cluster analysis,Sequential Pattern Mining | Conference |
ISBN | Citations | PageRank |
1-59593-108-2 | 34 | 1.54 |
References | Authors | |
6 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fosca Giannotti | 1 | 2948 | 253.39 |
| Mirco Nanni | 2 | 1412 | 84.47 |
| Dino Pedreschi | 3 | 3083 | 244.47 |
| Fabio Pinelli | 4 | 972 | 50.96 |