Name
Title | ||
|---|---|---|
Incremental updating Algorithm Based on Artificial Immune System For Mining Association Rules |
Abstract | ||
|---|---|---|
A new algorithm is developed based on artificial immune system and on the improved model for association rules mining. The algorithm is both scalable and efficient in discovering significant relationships in weighted settings as illustrated by experiments performed on Web usage datasets. We propose a strategy for maintaining association rules in dynamic databases. This method uses weighting technique to highlight new data. The experiments have shown that our approach is efficient and promising |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1109/ICEBE.2006.64 | ICEBE |
Keywords | Field | DocType |
null | Data mining,Artificial immune system,Weighting,Web usage,Computer science,Algorithm,Association rule learning,Scalability | Conference |
Volume | Issue | ISBN |
null | null | 0-7695-2645-4 |
Citations | PageRank | References |
1 | 0.36 | 1 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yidan Su | 1 | 1 | 0.36 |
| Xinyi Gu | 2 | 3 | 0.74 |
| Zhujuan Li | 3 | 1 | 0.36 |