TY - GEN
T1 - Embedding identity and interest for social networks
AU - Xu, Linchuan
AU - Wei, Xiaokai
AU - Yu, Philip S.
AU - Cao, Jiannong
PY - 2019/1/1
Y1 - 2019/1/1
N2 - Network embedding fills the gap of applying tuple-based data mining models to networked datasets through learning latent representations or embeddings. However, it may not be likely to associate latent embeddings with physical meanings just as the name, latent embedding, literally suggests. Hence, models built on embeddings may not be interpretable. In this paper, we thus propose to learn identity embeddings and interest embeddings, where user identity includes demographic and affiliation information, and interest is demonstrated by activities or topics users are interested in. With identity and interest information, we can make data mining models not only more interpretable, but also more accurate, which is demonstrated on three real-world social networks in link prediction and multi-task classification.
AB - Network embedding fills the gap of applying tuple-based data mining models to networked datasets through learning latent representations or embeddings. However, it may not be likely to associate latent embeddings with physical meanings just as the name, latent embedding, literally suggests. Hence, models built on embeddings may not be interpretable. In this paper, we thus propose to learn identity embeddings and interest embeddings, where user identity includes demographic and affiliation information, and interest is demonstrated by activities or topics users are interested in. With identity and interest information, we can make data mining models not only more interpretable, but also more accurate, which is demonstrated on three real-world social networks in link prediction and multi-task classification.
UR - http://www.scopus.com/inward/record.url?scp=85046288497&partnerID=8YFLogxK
U2 - 10.1145/3041021.3054268
DO - 10.1145/3041021.3054268
M3 - Conference article published in proceeding or book
AN - SCOPUS:85046288497
T3 - 26th International World Wide Web Conference 2017, WWW 2017 Companion
SP - 859
EP - 860
BT - 26th International World Wide Web Conference 2017, WWW 2017 Companion
PB - International World Wide Web Conferences Steering Committee
T2 - 26th International World Wide Web Conference, WWW 2017 Companion
Y2 - 3 April 2017 through 7 April 2017
ER -