基于质量的数据挖掘服务选择

在面向服务的数据挖掘系统中各种数据挖掘的算法封装成 Web服务.用户选择合适的数据挖掘服务执行自己的数据挖掘任务,而大多数最终用户并不具备这样的专业知识.从方便用户的角度出发,系统需提供一套服务选择机制,来帮助用户选择高质量的数据挖掘服务.综合通用Web服务的评价标准、数据挖掘领域的专用评价因子及用户评价反馈等多种因素及服务的动态性,给出了一个较全面的数据挖掘服务评价本体,讨论了服务质量的评价方法,给出了基于服务质量评价的动态数据挖掘服务选择方法,用户可根据数据挖掘服务评价本体的语义模型,输入质量约束条件,也可以调整评价因子权值,系统在满足用户约束条件的服务集中,通过计算出服务的综合质量值,挑选最适合的算法执行.

The User-centered Data Mining Ontology Development on Universal Knowledge Grid

In the service-sriented data mining system,the Data Mining(DM)algorithms are packed to Web services.User can define DM task by selecting proper Data Mining Service(DMS),but most users haven't such professional knowledge.One service selection mechanism is needed to help user selecting high quality DMS in view of user usability.A more all-around DMS Quality Evaluation ontology(OntDMQ)is proposed by synthesizing Web service quality of services(QoS),DM unique characteristic,subjective factor such as user feedback and service dynamic characteristic.The evaluation method of QoS is discussed.The QoS-based dynamic service selection method is presented that user can define the QoS constraint of DMS referencing OntQE and adjust the factor fff,the system select the most appropriate DMS in the services fiting the user requirements according to computing compositive quality value.