Mining Patterns with a Balanced Interval
| dc.creator | Kosters, Edgar de Graaf Joost Kok Walter | |
| dc.date | 2007-05-08 | |
| dc.date.accessioned | 2026-07-07T08:00:01Z | |
| dc.date.available | 2026-07-07T08:00:01Z | |
| dc.description | In many applications it will be useful to know those patterns that occur with a balanced interval, e.g., a certain combination of phone numbers are called almost every Friday or a group of products are sold a lot on Tuesday and Thursday. In previous work we proposed a new measure of support (the number of occurrences of a pattern in a dataset), where we count the number of times a pattern occurs (nearly) in the middle between two other occurrences. If the number of non-occurrences between two occurrences of a pattern stays almost the same then we call the pattern balanced. It was noticed that some very frequent patterns obviously also occur with a balanced interval, meaning in every transaction. However more interesting patterns might occur, e.g., every three transactions. Here we discuss a solution using standard deviation and average. Furthermore we propose a simpler approach for pruning patterns with a balanced interval, making estimating the pruning threshold more intuitive. | |
| dc.identifier | https://arxiv.org/abs/0705.1110 | |
| dc.identifier | http://arxiv.org/abs/0705.1110 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/128583 | |
| dc.subject | Artificial Intelligence | |
| dc.subject | Databases | |
| dc.title | Mining Patterns with a Balanced Interval | |
| dc.type | text |