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Feb 27, 2020 · We present a scalable and distributed framework for semi-supervised link prediction problem (named DSSLP), which is able to handle industrial-scale graphs.
It implements uniform and dynamic sampling approaches, and is able to adaptively construct positive and negative examples to guide the training process.
In this work, we present a scalable and distributed framework for semi-supervised link prediction problem (named DSSLP), which is able to handle industrial ...
This work presents a scalable and distributed framework for semi-supervised link prediction problem (named DSSLP), which is able to handle industrial-scale ...
DSSLP: A Distributed Framework for Semi-supervised Link Prediction ... Instead of training model on the whole graph, DSSLP is proposed to train on the \emph{ k - ...
In this work, we present a scalable and distributed framework for semi-supervised link prediction problem (named DSSLP), which is able to handle industrial- ...
Dsslp: A distributed framework for semi-supervised link prediction. D Zhang, X Song, Z Liu, Z Zhang, X Huang, L Wang, J Zhou. 2019 IEEE International Conference ...
DSSLP: A Distributed Framework for Semi-supervised Link Prediction ... Instead of training model on the whole graph, DSSLP is proposed to train on the \emph{ k - ...
In this work, we present a scalable and distributed framework for semi-supervised link prediction problem (named DSSLP), which is able to handle industrial- ...
DSSLP: A distributed framework for semi-supervised link prediction. Proceedings of the 2019 IEEE International Conference on Big Data (Big Data'19), 2019 ...