图 书 馆
为大量用户群集单个事务数据Clustering Individual Transactional Data for Masses of Users |
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| 课程网址: | http://videolectures.net/kdd2017_guidotti_transactional_data/ |
| 主讲教师: | Riccardo Guidotti |
| 开课单位: | 国家研究委员会 |
| 开课时间: | 2017-10-09 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Mining a large number of datasets recording human activities for making sense of individual data is the key enabler of a new wave of personalized knowledge-based services. In this paper we focus on the problem of clustering individual transactional data for a large mass of users. Transactional data is a very pervasive kind of information that is collected by several services, often involving huge pools of users. We propose txmeans, a parameter-free clustering algorithm able to efficiently partitioning transactional data in a completely automatic way. Txmeans is designed for the case where clustering must be applied on a massive number of different datasets, for instance when a large set of users need to be analyzed individually and each of them has generated a long history of transactions. A deep experimentation on both real and synthetic datasets shows the practical effectiveness of txmeans for the mass clustering of different personal datasets, and suggests that txmeans outperforms existing methods in terms of quality and efficiency. Finally, we present a personal cart assistant application based on txmeans. |
| 关 键 词: | 记录数据; 知识服务; 事务数据 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2023-04-16：chenxin01 |
| 最后编审: | 2023-05-21：chenxin01 |
| 阅读次数: | 20 |