Please use this identifier to cite or link to this item:
https://idr.l3.nitk.ac.in/jspui/handle/123456789/7741Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Kumar, P. | - |
| dc.contributor.author | Ananthanarayana, V.S. | - |
| dc.date.accessioned | 2020-03-30T10:02:43Z | - |
| dc.date.available | 2020-03-30T10:02:43Z | - |
| dc.date.issued | 2010 | - |
| dc.identifier.citation | 2010 The 2nd International Conference on Computer and Automation Engineering, ICCAE 2010, 2010, Vol.5, , pp.718-722 | en_US |
| dc.identifier.uri | http://idr.nitk.ac.in/jspui/handle/123456789/7741 | - |
| dc.description.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. �2010 IEEE. | en_US |
| dc.title | Discovery of weighted association rules mining | en_US |
| dc.type | Book chapter | en_US |
| Appears in Collections: | 2. Conference Papers | |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.