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Relational Learning with Social Status Analysis
2016
Proceedings of the Ninth ACM International Conference on Web Search and Data Mining - WSDM '16
Relational learning has been proposed to cope with the interdependency among linked instances in social network analysis, which often adopts network connectivity and social media content for prediction. A common assumption in existing relational learning methods is that data instances are equally important. The algorithms developed based on the assumption may be significantly affected by outlier data and thus less robust. In the meantime, it has been well established in social sciences that
doi:10.1145/2835776.2835782
dblp:conf/wsdm/WuHL16
fatcat:g2jfoyb2wbcj5hhdj43yz3gd4a