一种动态混合QoS语义的Web服务个性化推荐模型

服务推荐是服务计算中的主要问题之一,当前大多针对功能属性进行推荐,而在Web服务的QoS属性方面考虑较少,并且不支持动态变化的QoS属性。基于动态混合QoS的语义Web服务个性化推荐模型,把语义Web技术引入Web服务中,在QoS监控器下,有效监测Web服务的QoS属性变化并动态更新Web服务的QoS属性。根据建立的用户兴趣模型,向用户推荐具有个性化的Web服务。此外,在个性化推荐系统中使用最广泛的协同过滤推荐技术基础上,对数据进行了一系列的预处理填充,而且充分考虑了不同时间的项目评分对推荐的影响。结合用户兴趣度和用户评分的相似性计算方法,并通过不同的权值来表示它们的重要程度,综合计算目标用户的最近邻居集合,最终对用户u产生推荐。该系统在一定程度上提高了服务推荐的效率和准确度并满足用户查询需求。

Personalized Recommendation Model Based on the Dynamic and Mixed QoS of Semantic Web Service

Service recommendation is a main problem in the services computing. However, most of the current Web service recommender systems make recommend for functional properties, but consider less in the QoS attributes of Web services, and do not support dynamic changes of QoS attributes. The personalized Web service recommender model based on the semantic Web services takes advantages of dynamic mixing QoS attributes, and introduces the semantic Web technology into Web services. Under the supervision of the QoS monitor, it effectively monitors the QoS properties change of Web services,and dynamically updates the QoS attributes of the Web service. According to the establishment of user interest model, the system recommends some personalized Web services to the user .In addition, based on the collaborative filtering recommendation technology widely used in personalized recommendation system, this paper car- ried out a series of pretreatment filling, and fully considered the different time scores impact on the recommendation, combined the user interest degree with the user score similarity, and through different weights showed their importance degrec,comprehensivcly calculaed the nearest neighbor set of the target user, ultimately generated recommendation to the user u. To some extent, the system can effectively improve the efficiency, accuracy of the service recommended, and meet the needs of the user query.