在用户档案建模中可视化社会关系的相关性

Dieudonné Tchuente, Marie-Françoise Canut, N. Jessel, A. Péninou, F. Sèdes
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引用次数: 9

摘要

现有的用户配置文件建模工作总是将用户作为一个独立的实体进行建模。然而,在社会科学领域,许多研究表明,用户的行为受到其社会关系和/或社会互动的强烈影响。由于在信息系统中获取用户的社会数据的问题,这些结果很难集成到用户画像建模中。例如,随着社交网络的出现,这一障碍可以在网络上被打破,我们可以合理地考虑从社交数据中丰富用户的个人资料。本文提出了一种利用社交数据建立用户档案的技术。我们从文本用户的活动数据中建立了个人资料,并通过可视化的时间图展示了社会关系在建立的个人资料中的相关性,并对7081个Facebook个人资料进行了实验。这些结果激发了基于用户社交网络的新分析技术的潜在实现,以丰富用户的个人资料并解决个性化或推荐系统中的“冷启动问题”等悬而未决的问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Visualizing the relevance of social ties in user profile modeling
Existing works about user profile modeling always model the user as an independent entity. However, in social sciences, many works show the user's behavior as strongly influenced by his social ties and/or social interactions. These results were difficult to integrate in user profile modeling because of the problem of capturing social data about users in infor-mation systems. With the advent of the social web for example, this barrier can be broken on the Web, and we can reasonably think about enriching users' profiles from social data. In this paper we propose a technique to develop users' profiles with social data. We built profiles from textual users' activities data, and we show through visualization of temporal graphs the relevance of social ties on built profiles with an experimentation carried out on 7, 081 Facebook profiles. These results motivated the potential implementation of new profiling techniques based on users' social networks, to enrich users' profiles and solve pending problems such as 'cold start problem' in personalized or recommender systems.
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