Web Cluster is an effective mechanism used in Web site construction to deal with the system capacity prob-lem. Researchers proposed several strategies or algorithms, which improve the performance and scalability of the Webcluster system. In this paper, a content-based load distribution algorithm is proposed. It takes the processing ability ofback-end severs and the request load weight into account, and ensure the request locality. The emulation results illus-trate that this algorithm performs better in different kinds of Web site, comparing with other relative algorithms.
针对推荐算法的信息过期问题,结合遗忘函数和信息保持期的改进时间权重引入矩阵分解模型,提出一种基于改进时间权重的矩阵分解协同过滤算法(MFTWCF,MF-based and improved time weighted collabora tive filtering),相比前人提出的基于改进时间权重的邻域协同过滤算法(NTWCF,neighborhood-based and improved time weighted collaboratire filering algorithm),准确性显著提升了26.58%。由于过去的信息所包含的特征在随后的时间里可能被用户持续关注,从而增强过期信息对推荐的影响力,所以提出了融合时间权重和类型影响力加强权重的改进算法(MFTTWCF,MF-bosed and imporved time and type weighteel collaborative filtering)修正上述时间权重。电影数据集的实验证明,MFTTWCF算法预测的准确性比MFTWCF算法提高了3.58%,能够取得更好的推荐效果,适用于通过预测评分进行推荐的系统。
针对当前Web服务的应用和研究只关注于对业务功能的封装和重用以及相应服务的组合,而对用户界面缺乏相应的支持,提出了一种动态的、面向服务的Web用户界面(web user interface,WebUI)组合框架。在此框架中,WebUI构件被封装为可重用的Web服务,因此可以被发现、选择和绑定,并根据WebUI建模时所生成的WebUI组合描述被动态地组合为相应的WebUI,显著地简化了WebUI的开发和维护工作。