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All Friends are not Equal: Weight-Aware Egocentric Network-Based User Profiling

机译:所有朋友都不等于:权力感知的自我网络基于网络的用户分析

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Several studies were interested in social shared content as rewarding source to enrich user's profile. In this context, we highlight the importance of considering the user's relationship strength to derive relevant social profile. We focus on egocentric network community-based user profiling process (CoBSP) which considers only binary connections between people. In real life, social connections are not merely binary but have associated weights that record people's relation strength. We aim to enhance the effectiveness of CoBSP process by integrating ties strength in the user's profiling process. Our motivation stems from the intuition that people having the strongest relationships with the profiled user may reveal more valuable information about him. The first experiments conducted on scientific publications networks (DBLP/ResearchGate) are promising and show the relevance of our prior premise. However, we should conduct further experiments to completely validate the effectiveness of our proposition.
机译:几项研究对社交共享内容感兴趣,作为奖励来源,以丰富用户的个人资料。在这种情况下,我们突出了考虑用户的关系力量来推导相关社交概况的重要性。我们专注于基于Egentric网络社区的用户分析过程(COBSP),其仅考虑人与人之间的二进制连接。在现实生活中,社会联系不仅仅是二元的二元,而且具有记录人们的关系力量的相关权重。我们的目标是通过整合用户的分析过程中的关系强度来提高COBSP过程的有效性。我们的动机源于与成本用户有最强的关系的直觉可能会揭示关于他的更有价值的信息。对科学出版物网络(DBLP / Researchgate)进行的第一个实验是有前提的,并显示出先前前提的相关性。但是,我们应该进行进一步的实验,以完全验证我们主张的有效性。

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