Abstract: To mining the frequent Resource Service Sequence (RSS) and improve the resource selection efficiency,the method based on RSS and the influence between resource services was proposed.For RSS,an approach to identify key feature sequence was proposed to resolve the influence degree between resource services.By using PrefixSpan algorithm,the patterns of RSSs was analyzed and resolved.Based on time-series of executing business activities,the key feature sequences were identified for RSS,and the synthetical degree of influence was resolved.The feasibility of proposed approach was tested with simulation experiments.

Key words: resource service sequence, key feature sequence, influence degree, collaborative task

摘要： 为挖掘频繁的资源服务序列,进而提高协同任务的资源选取效率,提出基于资源服务特征以及特征间影响关系的方法。针对资源服务序列,为求解资源服务间的影响度,提出一种关键特征序列识别方法。首先,采用PrefixSpan算法分析并获得资源服务序列模式;然后,针对资源服务序列提出基于时间序列的影响度计算方法,并从中识别出关键特征序列,进而计算出资源服务序列的综合影响度;最后,通过仿真实验分析验证了所提方法的可行性。

关键词: 资源服务序列, 关键特征序列, 影响度, 协同任务