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| 基于信任关系和词相关关系的冷启动用户词特征重建 | |
| 引用本文： | 高亨德,王智强,李茹.基于信任关系和词相关关系的冷启动用户词特征重建[J].中文信息学报,2018,32(5):80. |
| 作者姓名： | 高亨德 王智强 李茹 |
| 作者单位： | 1.山西大学 计算机与信息技术学院,山西 太原 030006; 2.山西大学 计算智能与中文信息处理教育部重点实验室,山西 太原 030006; 3.山西大学大数据挖掘与智能技术协同创新中心,山西 太原 030006 |
| 基金项目： | 国家863计划(2015AA015407);国家自然科学基金(61772324) |
| 摘 要： | 文本是社交媒体用户的重要信息之一,从文本中获取用户的词特征是实现用户主题建模、兴趣挖掘及个性化推荐等任务的基础。然而社交媒体中存在许多用户(冷启动用户)只含有少量甚至缺乏文本信息,为此该文提出一种融合用户信任关系及词相关关系的词特征重建方法。该方法通过对用户信任关系矩阵、词相关关系矩阵和用户词特征矩阵进行联合概率矩阵分解来实现对冷启动用户的词特征重建。在新浪微博和Twitter的四组数据集上的实验结果表明,该文所提出的冷启动用户词特征重建算法能够取得较好的词特征重建结果。 |
| 关 键 词： | 社交媒体 词特征 概率矩阵分解 冷启动 |
Word Feature for Cold Start Users Based on Trust Relationships and Word Correlation |
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| GAO Hengde,WANG Zhiqiang,LI Ru.Word Feature for Cold Start Users Based on Trust Relationships and Word Correlation[J].Journal of Chinese Information Processing,2018,32(5):80. | |
| Authors: | GAO Hengde WANG Zhiqiang LI Ru |
| Affiliation: | 1.School of Computer & Information Technology, Shanxi University, Taiyuan, Shanxi 030006, China; 2.Key Laboratory of Computation Intelligence & Chinese Information Processing of Ministry of Education, Shanxi University, Taiyuan, Shanxi 030006, China; 3.Collaborative Innovation Center of Big Data Mining & Intelligent Technology, Shanxi University, Taiyuan, Shanxi 030006, China |
| Abstract: | The user's word feature obtained from the text is the basis for achieving the task of user theme modeling, interest mining, and personalized recommendation. To derive the word feature for cold start users who contain scarcely texts, this paper presents a method of merging the trust relations of the user and the word correlation, Specifically, we combine the user's trust relation matrix, words correlation matrix and the feature word matrix via probabilistic matrix factorization. The experimental results on 4 data sets from Sina microblogging and twitter show that the proposed algorithm achieves better results. |
| Keywords: | social media words feature probabilistic matrix factorization cold start |
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