Building Relation Network between People by Considering Aggregative Dynamics
Date Issued
2014
Date
2014
Author(s)
Liu, Yen-Chun
Abstract
In the social services, the relation networks between people bring us valuable information to make these services more convenient. Therefore, how to predict the relation between users is an important issue. In this thesis, we propose a new research direction that predicts the hidden relations and their strengths between people according to the observed interaction between them. We have two ideas to solve this problem. First, if two people are friends, they may appear together many times. Second, if two people are friends, they may appear in the object which there are no anyone else. We make observations to verify our ideas first. Then, based on these two ideas, we purpose an unsupervised model by Beta distribution and use gradient descent method to infer the relation between users. In our experiments, our methodology outperforms other three baselines. Moreover, the relation network inferred by us satisfies the constraints for a real social network.
Subjects
社群網路
鍵結預測
關係強度
貝塔分布
梯度下降法
Type
thesis
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