Efficiently mining frequent itemsets from very large databases
Efficient algorithms for mining frequent itemsets are crucial for mining association rules and for other data mining tasks. Methods for mining frequent itemsets and for iceberg data cube computation have been implemented using a prefix-tree structure, known as a FP-tree, for storing compressed frequ...
| Main Author: | |
|---|---|
| Format: | Others |
| Published: |
2004
|
| Online Access: | http://spectrum.library.concordia.ca/8431/1/NQ96957.pdf Zhu, Jianfei <http://spectrum.library.concordia.ca/view/creators/Zhu=3AJianfei=3A=3A.html> (2004) Efficiently mining frequent itemsets from very large databases. PhD thesis, Concordia University. |