Ranking Companies Based on Multiple Social Networks Mined from the Web
Yingzi Jin, Yutaka Matsuo, Mitsuru Ishizuk · InTech eBooks · 2010
This chapter described methods of learning the ranking of entities from multiple social networks mined from the Web. Various relations and relational embeddedness pertain to our lives: their combinations and their aggregate impacts are influential to predict features of entities. Based on that intuition, we constructed our ranking learning model from social networks to predict the ranking of other actors. We first extracted social networks of different kinds from the Web. Subsequently, we used these networks and a given target ranking to learn the model. We proposed three approaches to obtaining the ranking model.