Exploiting Data and Human Knowledge for Predicting Wildlife Poaching

@article{Gurumurthy2018ExploitingDA,
  title={Exploiting Data and Human Knowledge for Predicting Wildlife Poaching},
  author={Swaminathan Gurumurthy and Lantao Yu and Chenyan Zhang and Yongchao Jin and W. Li and Haidong Zhang and Fei Fang},
  journal={Proceedings of the 1st ACM SIGCAS Conference on Computing and Sustainable Societies},
  year={2018}
}
Poaching continues to be a significant threat to the conservation of wildlife and the associated ecosystem. Estimating and predicting where the poachers have committed or would commit crimes is essential to more effective allocation of patrolling resources. The real-world data in this domain is often sparse, noisy and incomplete, consisting of a small number of positive data (poaching signs), a large number of negative data with label uncertainty, and an even larger number of unlabeled data… Expand
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