Enhanced Actionable Knowledge Mining for Effective Customer Relationship Management using Neural Networks
| dc.category | Conference Proceedings | |
| dc.contributor.author | Vasantha Kalyani David | |
| dc.date.accessioned | 2017-03-30T01:05:06Z | |
| dc.date.available | 2017-03-30T01:05:06Z | |
| dc.date.issued | 2010 | |
| dc.department | Computer Science | en_US |
| dc.description.abstract | Most Data Mining algorithms and tools stop at discovered customer models, producing distribution information on customer profiles. Such techniques when applied to industrial problems such as CRM (Customer Relationship Management) are useful in pointing out customers who are likely attrittors and customers who are loyal, but they require human experts to post process the discovered knowledge manually. Most of the post processing techniques did not directly suggest actions that will lead to increase in the objective function such as profit .A novel algorithm is proposed in this paper that suggest actions to change the customers from undesired status to desired ones. This approach combines data mining with decision trees using neural networks to realistic insurance application domain and UCI benchmark data. | en_US |
| dc.identifier.uri | https://ir.avinuty.ac.in/handle/avu/2364 | |
| dc.lang | English | en_US |
| dc.publisher.name | Proceedings of the National Conference on Advanced Computing Technologies | en_US |
| dc.publisher.type | National | en_US |
| dc.title | Enhanced Actionable Knowledge Mining for Effective Customer Relationship Management using Neural Networks | en_US |
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