Predicting Cooperation Relationships in Heterogeneous Movie Networks

  • 洪 偉欽

Student thesis: Master's Thesis

Abstract

In social network analysis relationship prediction among people in the interpersonal network is a broadly discussed problem Nevertheless when modeling a real network as a heterogeneous information network instead of a homogeneous one this problem becomes more challenging In this work we focus on the movie network constituted by multiple types of entities (e g movies participants studios and genres) and multiple types of links among these entities To clearly represent the semantic meanings in such a movie network we utilize the meta-path-based prediction model Advantages of our approach are two-fold First the meta-path-based method systematically retrieves topological features in a movie network Second we use the supervised method to learn the best weights connected with different topological features in building cooperation relationships Empirical studies based on the real IMDb dataset show that our approach precisely predicts cooperation relationships in a large-scale movie network
Date of Award2014 Sep 9
Original languageEnglish
SupervisorWei-Guang Teng (Supervisor)

Cite this

'