为了改进web服务推荐的准确性,通过分析现有Web服务推荐算法的面临的主要问题,提出了一种基于地域划分的web服务推荐方法。该算法对Web服务进行区域划分,并对区域内Web服务进行分类,根据用户区域位置,计算消费者之间及服务之间的相似程度,并以此相似度为基础对使用者并未调用过的服务的质量进行预测。基于大量真实数据的实验显示,该算法在推荐准确性方面优于现有的基于协同过滤的Web服务推荐算法。
To improve the accuracy of Web services recommendation, a recommendation method is studied Dasecl on Web services geographical information by analyzing the existing algorithms. The algorithm divide region of Web services, and Web services within the region are classified according to the regional location of the user to calculate the consumer and the degree of similarity between the services. A large number of experiments based on real data show the accuracy of the algorithm is superior to the recommended existing Web services-based collaborative filtering recommendation algorithm.