@inproceedings{7a7590437a2745f5bac858fcdf530095,
title = "Inferring missing attributes of users in large-scale social networks",
abstract = "User attribute inference plays an important role in personalized recommendation and precision marketing. However, in large-scale social networks, user attributes are often missing. To address the problem, this paper introduces an inference framework for deriving missing attributes of users in largescale social networks. We use Sina Weibo as our experimental platform. The framework leverages various collaborative filtering methods and a similarity learning scheme to infer missing user attribute values. Experimental results demonstrate the proposed framework is able to generate satisfactory inference results.",
keywords = "Collaborative Filtering, Similarity Learning, User Attribute Inference, User Profile",
author = "Huadeng Wang and Songhua Xu and Lihui Liu and Xiaonan Luo",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 11th International Conference on Advanced Computational Intelligence, ICACI 2019 ; Conference date: 07-06-2019 Through 09-06-2019",
year = "2019",
month = jun,
doi = "10.1109/ICACI.2019.8778611",
language = "英语",
series = "11th International Conference on Advanced Computational Intelligence, ICACI 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "207--211",
booktitle = "11th International Conference on Advanced Computational Intelligence, ICACI 2019",
}