A Collaborative Tag Recommendation Based on User Profile

Dihua Xu, Zhijian Wang, Yanli Zhang, Ping Zong
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引用次数: 4

Abstract

With the increasing popularity of social tagging, services that assist the user in the task of tagging, such as tag recommenders, are more and more required. As we all known, crucial to the performance of a recommendation system is the accuracy of the user profiles used to represent the interests of the users. We propose a tag recommendation based on user profile which represents user preferences by taking user's ranking pairwise tag preferences. Although the dataset is obtained indirectly, the experiments show that the tag recommendation based on the proposed user profile has outperformed the baseline tag recommendation.
基于用户档案的协同标签推荐
随着社交标签的日益普及,人们越来越需要标签推荐等辅助用户完成标签任务的服务。众所周知,推荐系统性能的关键是用于代表用户兴趣的用户配置文件的准确性。我们提出了一种基于用户配置文件的标签推荐方法,该用户配置文件通过对用户的标签偏好进行排序来表示用户偏好。虽然数据集是间接获得的,但实验表明,基于提议的用户配置文件的标签推荐优于基线标签推荐。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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