参与式信息推荐中基于用户角色分析的社交流组织

Xiaokang Zhou, Bo Wu, Qun Jin, Shoji Nishimura, Julong Pan, Wenbin Zheng, Jianhua Ma
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引用次数: 4

摘要

在本研究中,我们提出了一种整合的方法,根据社会数据和社会角色在社会群体中的分析来组织和提炼社会流。社交流数据将首先根据用户的个性化需求进行收集和整理。通过对用户群体内用户动态社会角色的识别和分类,对用户重要性进行计算和分析后,开发了一种机制,对社交流进行组织和细化,进而从更多相关的用户中为用户提供更适合、更有用、最符合其需求的信息,从而更好地辅助社交网络环境下的参与式信息搜索和推荐过程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Social Stream Organization Based on User Role Analysis for Participatory Information Recommendation
In this study, we propose an integrated approach to organize and refine the social streams in accordance with the analysis of both social data and social roles within a social group. The social stream data will be first collected and organized based on users' individual needs. After the calculation and analysis of users' importance based on the identification and classification of users' dynamical social roles within a user group, a mechanism is developed to organize and refine social streams and further provide users with more suitable and useful information that best fits their needs from more related users, in order to better assist the participatory information search and recommendation process in the social networking environment.
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