S-Space College of Engineering/Engineering Practice School (공과대학/대학원) Dept. of Computer Science and Engineering (컴퓨터공학부) Theses (Master's Degree_컴퓨터공학부)
Heterogeneous Social Network Graph Matching using Structural Features
그래프 구조적 특성을 이용한 사회망 그래프 매칭 기법
- Jiyoung Kim
- 공과대학 컴퓨터공학부
- Issue Date
- 서울대학교 대학원
- Heterogeneous Social Networks; Graph Matching; Network Structure; Social Network Integration
- 학위논문 (석사)-- 서울대학교 대학원 : 컴퓨터공학부, 2017. 2. 김종권.
- Social Information from social networks has been used in diverse research areas. Since social networks can provide abundant information, employment of social information commonly regards as the solution of data sparsity problem. In recommender system, for example, numerous researchers uses social information to solve cold start problem, which is that the system cannot draw any inferences for object who has not yet gathered sufficient information. However the information provided by one social network is very limited to surmount data sparsity problem. Graph matching techniques which combines information of heterogeneous social network can be broad and firm base of
other social network related research areas. Nowadays, users are opt to involve in multiple social networks simultaneously. Due to the fact that each social networks offer distinct service function and that data published for research is usually anonymized, there are not sufficient common information among heterogeneous social networks services. However, the graph structure formed by a same user tends to remain similar. In light of above, we propose novel approach to integrate heterogeneous social networks. Differ from other heterogeneous graph matching, we use not only simple in-and-out degree of social networks, but also Jaccard coefficient, Adamic/Adar score, Clustering coefficient, and Page rank to evaluate social status of user. Extensive experiments conducted on multiple real-world data and prove that our proposed method outperforms existed graph matching algorithm.