| Title | Hierarchical Pattern Mining Based on Swarm Intelligence |
| Publication Type | Conference Paper |
| Year of Publication | 2017 |
| Authors | Tsuboi, Kazuaki, Suga, Satoshi, Kurihara, Satoshi |
| Conference Name | Proceedings of the Genetic and Evolutionary Computation Conference Companion |
| Publisher | ACM |
| Conference Location | New York, NY, USA |
| ISBN Number | 978-1-4503-4939-0 |
| Keywords | Ant colony optimization, composability, hierarchical structure, pubcrawl, sequential pattern mining, swarm intelligence |
| Abstract | The behavior patterns in everyday life such as home, office, and commuting, and buying behavior model by day of the week, sea-son, location have hierarchies of various temporal granularity. Generally, in usual hierarchical data analysis, a basic hierarchical structure is given in advance. But it is difficult to estimate hierarchical structure beforehand for complex data. Therefore, in this study, we propose the algorithm to automatically extract both hierarchical structure and pattern from time series data using swarm intelligent method. We performed the initial operation test and confirmed that patterns can be extracted hierarchically. |
| URL | http://doi.acm.org/10.1145/3067695.3082038 |
| DOI | 10.1145/3067695.3082038 |
| Citation Key | tsuboi_hierarchical_2017 |
Hierarchical Pattern Mining Based on Swarm Intelligence