Search Results for author: Yijun Su

Found 6 papers, 5 papers with code

A Cross-City Federated Transfer Learning Framework: A Case Study on Urban Region Profiling

no code implementations31 May 2022 Gaode Chen, Yijun Su, Xinghua Zhang, Anmin Hu, Guochun Chen, Siyuan Feng, Ji Xiang, Junbo Zhang, Yu Zheng

To address the above challenging problems, we propose a novel Cross-city Federated Transfer Learning framework (CcFTL) to cope with the data insufficiency and privacy problems.

Transfer Learning

Neural Demographic Prediction in Social Media with Deep Multi-View Multi-Task Learning

1 code implementation International Conference on Database Systems for Advanced Applications(DASFAA) 2021 Yantong Lai, Yijun Su, Cong Xue, Daren Zha

Then, we learn a unified user representation from context, sentiment and topic representations and apply multi-task learning for inferring user’s gender and age simultaneously.

Multi-Task Learning

FGCRec: Fine-Grained Geographical Characteristics Modeling for Point-of-Interest Recommendation

1 code implementation IEEE International Conference on Communications 2020 Yijun Su, Xiang Li, Baoping Liu, Daren Zha, Ji Xiang, Wei Tang and Neng Gao.

With the popularity of location-based social networks (LBSNs), Point-of-Interest (POI) recommendation has become an essential location-based service to help people explore novel locations.

Recommendation Systems

CARec: Content-Aware Point-of-Interest Recommendation via Adaptive Bayesian Personalized Ranking

1 code implementation International Conference on Neural Information Processing 2019 Baoping Liu, Yijun Su, Daren Zha, Neng Gao, Ji Xiang.

First, we make full use of users’ check-in records and reviews to capture users’ intrinsic preferences (i. e., check-in, sentiment, and topic preferences).

Recommendation Systems

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