Name
Abstract | ||
|---|---|---|
Membership classification belongs to target customer analysis in the customer relationship management. For membership classification, an improved ant colony classification algorithm named mAnt-Miner+ is proposed. This algorithm on the basis of Ant-Miner, draws on the idea of mAnt-Miner (Ant-Miner that uses a population of many ants), and introduces a new heuristic strategy. Experimental results show that, in terms of prediction accuracy, mAnt-Miner+ is competitive with Ant-Miner and higher than mAnt-Miner; in terms of running efficiency, mAnt-Miner+ is more efficient than mAnt-Miner and Ant-Miner. © 2013 Springer-Verlag Berlin Heidelberg. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1007/978-3-642-38703-6_33 | ICSI (1) |
Keywords | Field | DocType |
ant-miner,customer relationship management,heuristic,membership classification | Customer relationship management,Population,Heuristic,Computer science,Algorithm,Artificial intelligence,Ant colony,Machine learning | Conference |
Volume | Issue | ISSN |
7928 LNCS | PART 1 | 16113349 |
Citations | PageRank | References |
1 | 0.36 | 2 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hongxing Wu | 1 | 1 | 0.36 |
| Kai Sun | 2 | 33 | 7.71 |