An approach to discovering temporal association rules
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ArticlePublication details: ref_localidad@NULL : , 2000Description: 1 archivo (499,7 kB)Subject(s): Online resources: Summary: The goal of discovering association rules is to discover aH possible associations that accomplish certain restrictions (minimum support and confidence and interesting). However, it is possible to find interesting associations with a high confidence level hut with little support. This problem is caused by the way support is calculated, as the denominator represents the total number of transactions in a time period when the involved items may have not existed. If, on the other hand, we limit the total transactions to the ones belonging to the items' lifetime, those associations would be now discovered, as they would count on enough support. Another difficulty is the large number of rules that could be generated, tbr which many solutions nave been proposed. Using age as an obsolescence tactor for rules helps reduce the number of rules to be presented to the user. In this paper we expand the notion of association rules incorporating time to the frequent itemsets discovered. The concept of temporal support is introduced and. as an example, the known algorithm A priori is modified to incorporate the temporal notions.
| Item type | Current library | Call number | Status | Date due | Barcode |
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Capítulo de libro
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Biblioteca Fac.Informática | A0269 (Browse shelf(Opens below)) | Available | DIF-A0269 |
Formato de archivo: PDF. -- Este documento es producción intelectual de la Facultad de Informática-UNLP (Colección BIPA / Biblioteca)
The goal of discovering association rules is to discover aH possible associations that accomplish certain restrictions (minimum support and confidence and interesting). However, it is possible to find interesting associations with a high confidence level hut with little support. This problem is caused by the way support is calculated, as the denominator represents the total number of transactions in a time period when the involved items may have not existed. If, on the other hand, we limit the total transactions to the ones belonging to the items' lifetime, those associations would be now discovered, as they would count on enough support. Another difficulty is the large number of rules that could be generated, tbr which many solutions nave been proposed. Using age as an obsolescence tactor for rules helps reduce the number of rules to be presented to the user. In this paper we expand the notion of association rules incorporating time to the frequent itemsets discovered. The concept of temporal support is introduced and. as an example, the known algorithm A priori is modified to incorporate the temporal notions.
ACM Symposium on Applied Computing (2000 : Villa Olmo, Como, Italia)
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