Towards a dynamic and polarity-aware social user profile modeling

Abir Gorrab, Ferihane Kboubi, H. Ghézala, B. L. Grand
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引用次数: 4

Abstract

The emergence of social networks and the communication facilities they offer have generated an enormous informational mass. This social content is used in several research and industrial works and has had a great impact in different processes. In this paper, we present an overview of social information use in Information Retrieval (IR) and Recommendation systems. We first describe several user profile models using social information. A special attention is given to the following points: the analysis of the different user profiling models incorporating social content in Information Retrieval (IR) and in social recommendation methods. We distinguish between the models using social signals and relations, and the models using temporal information. We also present current and future challenges and research directions to enhance IR and recommendation process. We then describe our proposed model of social polarized and temporal user profile building and use in social recommendation context. Our proposal tries to address open challenges and establish a new model of user profile that fits information needs in recommender systems.
朝着动态和极性感知的社交用户档案建模
社交网络的出现及其提供的通讯设施产生了大量的信息。这一社会内容在若干研究和工业作品中使用,并在不同的过程中产生了很大的影响。在本文中,我们概述了社会信息在信息检索(IR)和推荐系统中的应用。我们首先描述了使用社会信息的几个用户概要模型。特别关注以下几点:分析了信息检索(IR)和社交推荐方法中包含社交内容的不同用户特征模型。我们区分了使用社会信号和关系的模型和使用时间信息的模型。提出了当前和未来的挑战和研究方向,以加强IR和推荐过程。然后,我们描述了我们提出的社会极化模型和在社会推荐背景下建立和使用时间用户档案。我们的建议试图解决开放的挑战,并建立一个新的用户档案模型,以适应推荐系统的信息需求。
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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