摘要
网站智能化推荐能够更好的为用户提供服务,传统的基于关联规则与聚类分析的推荐方法,由于每次采样数据的时间段的随机性,有可能会遗漏重要的用户兴趣点。本文采用了基于时间粒度划分的动态关联规则挖掘法,有依据地划分数据采样时间段,能够为用户提供更为精确的网站智能化推荐服务。
The website intelligent recommendation can provide better service for the user.Traditional recommendation method based on association rules and clustering analysis,due to the randomness of the time period of each sampled data,may be omit important user interest points.In this paper,a dynamic association rule mining method based on time granularity partition is proposed,According to the division of data sampling time,to provide users with more accurate site intelligent recommendation service.
作者
程雅琼
蔡亮
张忠林
Cheng Yaqiong Cai Liang Zhang Zhonglin
出处
《自动化与仪器仪表》
2016年第11期193-195,共3页
Automation & Instrumentation
基金
甘肃省自然科学基金(1508RJZA076)
甘肃省科技支撑计划项目(1011GKCA040)
关键词
网站智能推荐
时间粒度划分
动态关联规则
web site intelligent recommendation
time granularity classification
dynamic association rules
