Research

On Exploring Semantic Meanings of Links for Embedding Social Networks

April 16, 2018

Abstract

There are increasing interests in learning low-dimensional and dense node representations from the network structure which is usually high-dimensional and sparse. However, most existing methods fail to consider semantic meanings of links. Different links may have different semantic meanings because the similarities between two nodes can be different, e.g., two nodes share common neighbors and two nodes share similar interests which are demonstrated in node-generated content. In this paper, the former type of links are referred to as structure-close links while the latter type are referred to as content-close links. These two types of links naturally indicate there are two types of characteristics that nodes expose in a social network. Hence, we propose to learn two representations for each node, and render each representation responsible for encoding the corresponding type of node characteristics, which is achieved by jointly embedding the network structure and inferring the type of each link. In the experiments, the proposed method is demonstrated to be more effective than five recent methods on four social networks through applications including visualization, link prediction and multi-label classification.

Download the Paper

AUTHORS

Written by

Publisher

Related Publications

June 27, 2025

Human & Machine Intelligence

Conversational AI

Seamless Interaction: Dyadic Audiovisual Motion Modeling and Large-Scale Dataset

Vasu Agrawal, Akinniyi Akinyemi, Kathryn Alvero, Morteza Behrooz, Julia Buffalini, Fabio Maria Carlucci, Joy Chen, Junming Chen, Zhang Chen, Shiyang Cheng, Praveen Chowdary, Joe Chuang, Antony D'Avirro, Jon Daly, Ning Dong, Mark Duppenthaler, Cynthia Gao, Jeff Girard, Martin Gleize, Sahir Gomez, Hongyu Gong, Srivathsan Govindarajan, Brandon Han, Sen He, Denise Hernandez, Yordan Hristov, Rongjie Huang, Hirofumi Inaguma, Somya Jain, Raj Janardhan, Qingyao Jia, Christopher Klaiber, Dejan Kovachev, Moneish Kumar, Hang Li, Yilei Li, Pavel Litvin, Wei Liu, Guangyao Ma, Jing Ma, Martin Ma, Xutai Ma, Lucas Mantovani, Sagar Miglani, Sreyas Mohan, Louis-Philippe Morency, Evonne Ng, Kam-Woh Ng, Tu Anh Nguyen, Amia Oberai, Benjamin Peloquin, Juan Pino, Jovan Popovic, Omid Poursaeed, Fabian Prada, Alice Rakotoarison, Alexander Richard, Christophe Ropers, Safiyyah Saleem, Vasu Sharma, Alex Shcherbyna, Jie Shen, Anastasis Stathopoulos, Anna Sun, Paden Tomasello, Tuan Tran, Arina Turkatenko, Bo Wan, Chao Wang, Jeff Wang, Mary Williamson, Carleigh Wood, Tao Xiang, Yilin Yang, Zhiyuan Yao, Chen Zhang, Jiemin Zhang, Xinyue Zhang, Jason Zheng, Pavlo Zhyzheria, Jan Zikes, Michael Zollhoefer

June 27, 2025

Read the Paper

June 13, 2025