# Systematic Biases in Link Prediction: comparing heuristic and graph embedding based methods

@inproceedings{Sinha2018SystematicBI, title={Systematic Biases in Link Prediction: comparing heuristic and graph embedding based methods}, author={Aakash Sinha and R{\'e}my Cazabet and R{\'e}mi Vaudaine}, booktitle={COMPLEX NETWORKS}, year={2018} }

Link prediction is a popular research topic in network analysis. In the last few years, new techniques based on graph embedding have emerged as a powerful alternative to heuristics. In this article, we study the problem of systematic biases in the prediction, and show that some methods based on graph embedding offer less biased results than those based on heuristics, despite reaching lower scores according to usual quality scores. We discuss the relevance of this finding in the context of the…

## 6 Citations

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This work proposes and implements a novel efficient architecture, capable of producing similar speed-up and performance than baseline but at a fraction of its hardware requirements and power consumption, and demonstrates the unique functional qualities of the approach as a flexible and fault-tolerant solution that makes it an interesting alternative for an anthology of applicative scenarios.

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