计算机应用 ›› 2018, Vol. 38 ›› Issue (11): 3081-3083.DOI: 10.11772/j.issn.1001-9081.2018041390

• 第七届中国数据挖掘会议(CCDM 2018) • 上一篇    下一篇

基于评分可靠性的跨域个性化推荐方法

曲立平, 吴家喜   

  1. 哈尔滨工程大学 计算机科学与技术学院, 哈尔滨 150001
  • 收稿日期:2018-04-28 修回日期:2018-07-05 出版日期:2018-11-10 发布日期:2018-11-10
  • 通讯作者: 曲立平
  • 作者简介:曲立平(1973-),女,黑龙江鹤岗人,副教授,博士,主要研究方向:机器学习、推荐系统;吴家喜(1990-),男,江西高安人,硕士研究生,主要研究方向:推荐系统。

Cross-domain personalized recommendation method based on scoring reliability

QU Liping, WU Jiaxi   

  1. College of Computer Science and Technology, Harbin Engineering University, Harbin Heilongjiang 150001, China
  • Received:2018-04-28 Revised:2018-07-05 Online:2018-11-10 Published:2018-11-10

摘要: 在跨域推荐系统中,存在某些用户对所购买的物品进行随意评分的情况。由于对物品进行随意评分的用户的数量较少,当该物品的评分数量较多时随意评分对推荐效果的影响较小,但是当该物品的评分数量较少时,随意评分会对推荐效果产生较大的影响。针对这个问题,提出一种基于评分可靠性的跨域个性化推荐方法。该方法针对不同的评分可靠性,为用户设置不同的阈值。当将辅助域的数据向目标域迁移时,如果用户进行评分的某物品的评分数量低于该用户的阈值,则不将该用户对该物品的评分数据迁移到目标域,否则进行迁移,以此减少随意评分对推荐效果的影响。实验结果表明,整体上,与为所有用户设置统一的阈值和不为用户设置阈值的跨域推荐相比,所提方法具有更高的预测评分的准确度。

关键词: 协同过滤, 跨域推荐, 评分可靠性, 阈值, 个性化

Abstract: In the cross-domain recommendation system, there are cases that some users randomly score the purchased items. Since the number of users who arbitrarily scores is relatively small, when the total number of scorings for the item purchased by the users who arbitrarily score is large, random scorings have less influence on the recommendation effect. However, when the total number of scorings for the item purchased by the users who arbitrarily score is relatively small, random scorings will produce a greater impact on the recommendation effect. To solve this problem, a cross-domain personalized recommendation method based on scoring reliability was proposed. Different thresholds were set for users according to the scoring reliability. When migrating the scores in the auxiliary domain to the target domain, if the total number of scorings for an item by a user was lower than the threshold of the user, the user's scorings of the item were not migrated to the target domain, otherwise migration was performed, thereby reducing the influence of the random scorings on the recommendation effect. The experimental results show that it is better to set the user's threshold personally for different scoring reliability than setting a uniform threshold for all users and not setting a threshold for users.

Key words: collaborative filtering, cross-domain recommendation, scoring reliability, threshold, personalization

中图分类号: