基于社交的用户画像研究

发布时间：2018-05-19 16:24

本文选题：社交网络 + 用户兴趣　；参考：《北京邮电大学》2016年硕士论文

【摘要】：Facebook、微博等社交网络将人们的线下社交生活搬到了线上,使人们的虚拟化生活越来越丰富[1]。这些丰富的社交信息可以充分的刻画一个人的性格和形象,是一个人的信息化的表现。用户画像是个性化搜索、推荐的基础,蕴藏着巨大的商业价值。针对上述背景,本文主要研究了基于社交的用户画像问题。由于用户画像涵盖的范围很广,所以本文选取了其中的兴趣和职业这两个比较重要的研究点。本文调研了多个领域的研究理论和成果,对其进行分析对比,提出了基于社交标签的用户兴趣发现算法和基于分类的社交用户职业发现算法。本文在兴趣发现算法中主要利用了词提取算法和归一化社交标签的方法。对于用户职业发现,国内外研究比较少,所以本文做了一些尝试性的研究,提出了基于分类的用户职业发现算法。实验结果表明,本文提出的算法在具体的应用场景下能够保证用户兴趣和职业发现结果的准确性,能够很好地满足中文社交网络对用户特征挖掘的需求。为了对分析结果进行简单直观的展示,本文开发了“UPS”用户画像构建系统,并将用户兴趣发现算法应用到了推荐领域,证明了本文算法的可靠性和准确性。
[Abstract]:Social networks such as Facebook, Weibo, and other social networks have brought their offline social lives online, making their virtual lives richer and richer. These rich social information can fully depict a person's character and image, is a person's information performance. User portrait is a personalized search, the basis of recommendation, contains a huge commercial value. In view of the above background, this paper mainly studies the problem of social-based user portrait. Because of the wide range of user portraits, this paper selects two important research points: interest and occupation. This paper investigates the research theories and achievements in many fields and compares them and proposes the user interest discovery algorithm based on social label and the social user occupation discovery algorithm based on classification. This paper mainly uses the word extraction algorithm and the normalized social label method in the interest discovery algorithm. There are few researches on user occupation discovery at home and abroad, so this paper makes some tentative research and proposes a classification-based user occupation discovery algorithm. Experimental results show that the proposed algorithm can ensure the accuracy of user interest and occupation discovery results in specific application scenarios and can meet the needs of Chinese social networks for user feature mining. In order to show the analysis results simply and intuitively, this paper develops a "UPS" user portrait construction system, and applies the user interest discovery algorithm to the recommended field, which proves the reliability and accuracy of the proposed algorithm.
【学位授予单位】：北京邮电大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TP393.09;TP311.13

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