基于协同过滤的个性化Web服务选择方法

doi:10.3724/SP.J.1087.2013.00239

计算机应用 ›› 2013, Vol. 33 ›› Issue (01): 239-242.DOI: 10.3724/SP.J.1087.2013.00239

基于协同过滤的个性化Web服务选择方法

贺春林¹,谢琪²,³

1. 西华师范大学计算机学院，四川南充 637002
2. 西南民族大学计算机科学与技术学院，成都 610041
3. 重庆大学计算机学院，重庆 400043

收稿日期:2012-07-30 修回日期:2012-09-10 出版日期:2013-01-01 发布日期:2013-01-09
通讯作者: 谢琪
作者简介:贺春林(1971-)，男，四川广安人，教授，主要研究方向：计算机网络安全；谢琪(1983-)，女，四川简阳人，博士，主要研究方向：服务计算、个性化服务推荐。
基金资助:
国家自然科学基金重点项目(90818028);西华师范大学校级项目(08B009)

Personalized Web services selection method based on collaborative filtering

HE Chunlin¹,XIE Qi²,³

1. College of Computer Science, China West Normal University, Nanchong Sichuan 637002, China
2. College of Computer Science, Chongqing University, Chongqing 400043, China
3. School of Computer Science and Technology, Southwest University for Nationalities, Chengdu Sichuan 610041, China

Received:2012-07-30 Revised:2012-09-10 Online:2013-01-01 Published:2013-01-09
Contact: XIE Qi

摘要/Abstract

摘要： 对传统的Web服务选择算法进行分析，并指出其在动态环境下存在的问题。为了解决该问题，提出了基于协同过滤算法的个性化Web服务选择方法，并设计了一个动态的Web服务选择架构，架构使用协同过滤算法对Web服务的服务质量(QoS)值进行预测并选择最优的Web服务以满足用户的需求。使用150万条真实Web服务的QoS数据与其他4类算法进行了对比实验，结果表明所提方法的可行性和准确性。

关键词: Web服务, 服务选择, 协同过滤, 服务质量, 相似性

Abstract: The traditional Web services selection algorithms were analyzed and the problems existing in dynamic environment were pointed out. A personalized Web services selection method based on collaborative filtering was proposed to address these problems. And a personalized Web service selection framework was designed, which used the collaborative filtering to predict the Quality of Service (QoS) and selected the best service that met users' requirements. About 1.5 million real world QoS data were employed to evaluate the proposal with other four methods and the experimental results demonstrate that the proposed method is a feasible manner and it provides better prediction results.

Key words: Web service, service selection, collaborative filtering, Quality of Service (QoS), similarity

中图分类号:

TP391.1

贺春林谢琪. 基于协同过滤的个性化Web服务选择方法[J]. 计算机应用, 2013, 33(01): 239-242.

HE Chunlin XIE Qi. Personalized Web services selection method based on collaborative filtering[J]. Journal of Computer Applications, 2013, 33(01): 239-242.

参考文献

［1］YU T, LIN K J. Service selection algorithms for Web services with end-to-end QoS constraints ［C］// Proceedings of the 2004 IEEE International Conference on E-Commerce Technology. Washington, DC: IEEE Computer Society, 2004: 129-136.

［2］MENASCE D A. Composing Web services: a QoS view ［J］. IEEE Internet Computing, 2004, 8(6): 88-90.

［3］ZHENG Z B, MA H, LYU M R, et al. WSRec: a collaborative filtering based Web service recommender system ［C］// ICWS2009: Proceedings of the 7th IEEE International Conference on Web Services. Washington, DC: IEEE Computer Society, 2009: 437-444.

［4］CASATI F, SHAN M C. Dynamic and adaptive composition of E-services ［J］. Information Systems, 2001, 26(3): 143-163.

［5］JURCA R, FALTINGS B, BINDER W. Reliable QoS monitoring based on client feedback ［C］// Proceedings of the 16th International Conference on World Wide Web. Washington, DC: IEEE Computer Society, 2007: 1003-1012.

［6］HUANG C L, LO C C, CHAO K M, et al. Reaching consensus: a moderated fuzzy Web services discovery method ［J］. Information and Software Technology, 2006, 48(6): 410-423.

［7］ARDAGNA D, PERNICI B. Global and local QoS constraints guarantee in Web service selection ［C］ // Proceedings of the 2005 IEEE International Conference on Web Services. Washington, DC: IEEE Computer Society, 2005: 805-806.

［8］LAMPARTER S, ANKOLEKAR A, STUDER R, et al. Preference-based selection of highly configurable Web services ［C］// Proceedings of the 16th International Conference on World Wide Web. Washington, DC: IEEE Computer Society, 2007:1013-1022.

［9］GAO Y, ZHANG B, NA J, et al. Optimal selection of Web services for composition based on interface-matching and weighted multistage graph ［C］// Proceedings of the 6th International Conference on Parallel and Distributed Computing Applications and Technologies. Washington, DC: IEEE Computer Society, 2005: 336-338.

［10］CANFORA G, di PENTA M, ESPOSITO R, et al. An approach for QoS-aware service composition based on genetic algorithms ［C］// Proceedings of the 2005 Conference on Genetic and Evolutionary Computation. New York: ACM Press, 2005: 1069-1075.

［11］ZENG L Z, BENATALLAH B, NGU A H, et al. QoS-aware middleware for Web services composition ［J］. IEEE Transactions on Software Engineering, 2004, 30(5): 311-327.

［12］BREESE J S, HECKERMAN D, KADIE C. Empirical analysis of predictive algorithms for collaborative filtering ［C］// UAI-98: Proceedings of the 14th Conference on Uncertainty in Artificial Intelligence. San Francisco: Morgan Kaufmann Publishers, 1998: 43-52.

［13］ZHENG Z B, ZHANG Y L, LYU M R. Distributed QoS evaluation for real-world Web services ［C］// Proceedings of the 8th International Conference on Web Services. Washington, DC: IEEE Computer Society, 2010: 83-90.

[1]	包玄, 陈红梅, 肖清. 融入时间的兴趣点协同推荐算法[J]. 计算机应用, 2021, 41(8): 2406-2411.
[2]	周烁, 仇润鹤, 唐旻俊. 基于禁忌搜索和Q-learning的CR-NOMA系统的功率分配算法[J]. 计算机应用, 2021, 41(7): 2026-2032.
[3]	王月, 江逸茗, 兰巨龙. 基于改进三元组网络和K近邻算法的入侵检测[J]. 计算机应用, 2021, 41(7): 1996-2002.
[4]	杨蒙蒙, 张爱华. 基于灰度共生矩阵和同步正交匹配追踪的分形图像压缩[J]. 计算机应用, 2021, 41(5): 1445-1449.
[5]	冉家敏, 倪志伟, 彭鹏, 朱旭辉. 考虑空间众包工作者服务质量的任务分配策略及其萤火虫群优化算法求解[J]. 计算机应用, 2021, 41(3): 794-802.
[6]	胡立华, 左威健, 聂瑶瑶. 基于加权相似性度量的特征匹配方法[J]. 计算机应用, 2021, 41(2): 511-516.
[7]	周玉彬, 肖红, 王涛, 姜文超, 熊梦, 贺忠堂. 基于动作周期退化相似性度量的机械轴健康指标构建与剩余寿命预测[J]. 《计算机应用》唯一官方网站, 2021, 41(11): 3192-3199.
[8]	雷鹰, 郑万波, 魏嵬, 夏云霓, 李晓波, 刘诚武, 谢洪. 基于概率性能感知演化博弈策略的“云+边”混合环境中任务卸载方法[J]. 《计算机应用》唯一官方网站, 2021, 41(11): 3302-3308.
[9]	李翔锟, 贾彩燕. 融合重叠社区正则化及隐式反馈的协同过滤方法[J]. 计算机应用, 2021, 41(1): 53-59.
[10]	李卫中. 基于场景局部特征的多曝光图像融合[J]. 计算机应用, 2020, 40(8): 2365-2371.
[11]	朱琳, 于海涛, 雷新宇, 刘静, 王若凡. 基于MRI图像的阿尔茨海默症患者脑网络特征识别算法[J]. 计算机应用, 2020, 40(8): 2455-2459.
[12]	田保军, 刘爽, 房建东. 融合主题信息和卷积神经网络的混合推荐算法[J]. 计算机应用, 2020, 40(7): 1901-1907.
[13]	徐金荣, 郭彩萍, 童恩栋. 面向服务遥感图像处理平台中时间感知的服务质量预测[J]. 计算机应用, 2020, 40(6): 1714-1721.
[14]	郭曙杰, 李志华, 蔺凯青. 云环境下基于模糊隶属度的虚拟机放置算法[J]. 计算机应用, 2020, 40(5): 1374-1381.
[15]	葛宇, 梁静. 基于相遇概率时效性和重复扩散感知的机会网络消息转发算法[J]. 计算机应用, 2020, 40(5): 1397-1402.

基于协同过滤的个性化Web服务选择方法

Personalized Web services selection method based on collaborative filtering

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics