Abstract
Mining of association rules for basket databases, has been investigated by [1] [3] [4], [9], [12], etc. Most of these works focus on mining binary association rules, i.e, most of the association rules mining algorithms to discover frequent itemsets do not consider the quantity in which items have been purchased. This paper discusses an efficient method for discovering a weighted association rules from a large volumes of data in a single scan of the database. The data structure used here is called Weighted Tree. We found that this algorithm is more efficient than Cai's Algorithm.
| Original language | English |
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| Title of host publication | 2010 The 2nd International Conference on Computer and Automation Engineering, ICCAE 2010 |
| Pages | 718-722 |
| Number of pages | 5 |
| Volume | 5 |
| DOIs | |
| Publication status | Published - 28-05-2010 |
| Externally published | Yes |
| Event | 2nd International Conference on Computer and Automation Engineering, ICCAE 2010 - Singapore, Singapore Duration: 26-02-2010 → 28-02-2010 |
Conference
| Conference | 2nd International Conference on Computer and Automation Engineering, ICCAE 2010 |
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| Country/Territory | Singapore |
| City | Singapore |
| Period | 26-02-10 → 28-02-10 |
All Science Journal Classification (ASJC) codes
- Computer Networks and Communications
- Computer Science Applications
- Control and Systems Engineering