摘要
针对传统的商品营销推荐策略仅限于单个服务,忽视服务之间的关联与集成这一现状,结合Web服务组合理论,运用数据挖掘中的关联规则技术,通过实验挖掘Web服务中用户消费行为,分析并提炼了基于用户行为的Web服务组合关联规则,选择最优化Web服务组合,为用户进行智能推荐,达到了提高Web服务组合服务质量的目的。
The traditional commodity marketing recommendation strategy is limited to single service,ignores the association and integration between services.In response to this situation,the web service composition theory was combines with the association rules technology in data mining;users′ consumer behavior in web service was mined by experiments;web service composition association rules were extracted and analyzed based on users behavior;and the optimal web service composition was chosen.Intelligent recommendations were provided for users to improve the service quality of web service composition.
出处
《武汉理工大学学报（信息与管理工程版）》
CAS
2012年第5期588-591,共4页
Journal of Wuhan University of Technology：Information & Management Engineering
基金
国家自然科学基金资助项目(71072077&70972094)
中央高校基本科研业务费专项资金资助项目(2010-II-11)
湖北省自然科学基金资助项目(2009CDB032)
国家科技支撑计划资助项目(2011BAH16B02)
关键词
WEB服务组合
服务推荐
数据挖掘
关联规则
web service composition
service recommendation
data mining
association rules
