图 书 馆
通过使用正面和负面的模式序列分类在社会保障债务检测Debt Detection in Social Security by Sequence Classification Using Both Positive and Negative Patterns |
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| 课程网址: | http://videolectures.net/ecmlpkdd09_zhao_ddss/ |
| 主讲教师: | Yanchang Zhao |
| 开课单位: | 悉尼科技大学 |
| 开课时间: | 2009-10-20 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Debt detection is important for improving payment accuracy in social security. Since debt detection from customer transactional data can be generally modelled as a fraud detection problem, a straightforward solution is to extract features from transaction sequences and build a sequence classifier for debts. The existing sequence classification methods based on sequential patterns consider only positive patterns. However, according to our experience in a large social security application, negative patterns are very useful in accurate debt detection. In this paper, we present a successful case study of debt detection in a large social security application. The central technique is building sequence classification using both positive and negative sequential patterns. |
| 关 键 词: | 债务检测; 交易序列特征; 社会保障付款 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-06-29：yumf |
| 阅读次数: | 40 |