辽宁石油化工大学学报 ›› 2011, Vol. 31 ›› Issue (4): 76-79.DOI: 10.3696/j.issn.1672-6952.2011.04.020

• 计算机与自动化 • 上一篇    下一篇

一种基于聚类技术的免疫推荐算法

刘 洋1, 李海洋2, 王育才3   

  1. 1.辽宁石油化工大学计算机与通信工程学院,辽宁抚顺 113001; 2.抚顺职业技术学院,辽宁抚顺 113006; 3.北京益虹医通技术服务有限公司,北京 100020
  • 收稿日期:2011-05-29 出版日期:2011-12-25 发布日期:2017-07-14

Immune Network Recommendation Algorithm Based on Clustering

LIU Yang1, LI Hai-yang2, WANG Yu-cai3   

  1. 1.School of Computer and Communication Engineering, Liaoning Shihua University, Fushun Liaoning 113001,  P.R.China; 2.Fushun Vocational Technology Institute, Fushun Liaoning 113006, P.R.China;  3.Ehong General Medical and Technical Services Co.Ltd., Beijing 100020, P.R.China
  • Received:2011-05-29 Published:2011-12-25 Online:2017-07-14

摘要: 在网络时代,如何通过为用户提供更加个性化的服务,提高其商品的吸引力,进而为企业带来更大的收益,成为了网站所面临的核心问题。通过对自然免疫学和人工免疫学理论的研究,着重讨论了将人工免疫网络技术应用于电子商务个性化推荐的思想,提出了使用形态空间模型对推荐技术及其存在问题的解释方法,并提出了聚类免疫推荐算法。实验结果表明:该算法能高效和准确地解决个性化推荐问题,具有很好的应用价值。

关键词: 推荐系统, 人工免疫, 聚类技术, 形态空间模型

Abstract: In internet times, it is an important challenge that how to make more personalized services for user, increase the attraction of the goods, and get greater benefits for company. Through studying the natural immune and the artificial immune theories, it described the idea of using the artificial immune technique in e-commerce personal recommendation, and gave the explaining method for recommender technique and its problems with the shape-space model. The clustering immune network recommendation algorithm was given. Experimental result shows that the proposed algorithm can solve the recommender problem more highly and efficiently, and has the advantage of good application value.

Key words: Recommendation system, Artificial immune, Clustering technique, Shape-space model

引用本文

刘 洋, 李海洋, 王育才. 一种基于聚类技术的免疫推荐算法[J]. 辽宁石油化工大学学报, 2011, 31(4): 76-79.

LIU Yang, LI Hai-yang, WANG Yu-cai. Immune Network Recommendation Algorithm Based on Clustering[J]. Journal of Liaoning Petrochemical University, 2011, 31(4): 76-79.

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链接本文: https://journal.lnpu.edu.cn/CN/10.3696/j.issn.1672-6952.2011.04.020

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