东北大学学报（自然科学版）

东北大学学报(自然科学版) ›› 2011, Vol. 32 ›› Issue (2): 202-206.DOI: -

• 论著 • 上一篇    下一篇

预测Web QoS的协作过滤算法

张莉;张斌;黄利萍;朱志良;   

  1. 东北大学软件学院;东北大学信息科学与工程学院;
  • 收稿日期:2013-06-19 修回日期:2013-06-19 发布日期:2013-04-04
  • 通讯作者: -
  • 作者简介:-
  • 基金资助:
    国家自然科学基金资助项目(61073062);;

A collaborative filtering approach for web QoS prediction

Zhang, Li (1); Zhang, Bin (2); Huang, Li-Ping (1); Zhu, Zhi-Liang (1)   

  1. (1) School of Software, Northeastern University, Shenyang 110819, China; (2) School of Information Science and Engineering, Northeastern University, Shenyang 110819, China
  • Received:2013-06-19 Revised:2013-06-19 Published:2013-04-04
  • Contact: Zhang, B.
  • About author:-
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摘要： 不同环境中用户对同一服务质量的感受可能存在较大差别,针对这一问题,提出了一种QoS预测方法.该方法不仅使用了历史QoS信息,还将环境因素、用户输入等对QoS的影响考虑进去.以这些信息为基础,首先通过高斯法对原始信息数据进行规范化处理,然后计算其他服务与待预测服务的相似度,找到与目标服务相似度较大的服务集,并根据服务相似度预测空白信息,在此基础上计算用户的相似度,从而为用户预测目标服务的QoS值.实验结果表明,这种方法可以显著提高Web服务质量预测的准确性.

关键词: Web服务, 协作过滤, QoS预测, 相似性计算, 相关系数

Abstract: Due to the different backgrounds and experiences, users often have different impressions of the same QoS though they have been served all the same. An approach to predict QoS was therefore proposed, based on not only the historical QoS data, but also the factors of environment and users' inputs. Normalizing the original data by Gauss method, a set of Web services highly similar to the target service was picked out via the similarity computation to compare the target service to be predicted with other services. Then, the blank datasheet was predicted according to the service similarity so as to compute the similarity between users for the pridiction of QoS data of users' target service. Experimental results showed that the approach proposed can improve the prediction accuracy of QoS for Web service.

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