Topic paper author

The dataset is collected for the purpose of cross domain recommendation.

 

• Data Mining: We use papers of the following data mining conferences: KDD, SDM, ICDM, WSDM and PKDD as ground truth, which result in a network with 6,282 authors and 22,862 co-author relationships.
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• Medical Informatics: We include the following journals: Journal of the American Medical Informatics Association, Journal of Biomedical Informatics, Artificial Intelligence in Medicine, IEEE Trans. Med. Imaging and IEEE Transactions on Information and Technology in Biomedicine, from which we obtain a network of 9,150 authors and 31,851 coauthor relationships.
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• Theory: We include the following conferences, i.e., STOC, FOCS and SODA, from which we get 5,449 authors and 27,712 co-author  relationships.
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• Visualization: We include the following conferences and journals, CVPR, ICCV, VAST, TVCG, IEEE Visualization and Information Visualization. The obtained coauthor network is comprised of 5,268 authors and 19,261 co-author relationships.
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• Database: We include the following conferences, i.e., SIGMOD, VLDB and ICDE. From those conferences, we extract 7,590 authors and 37,592 co-author relationships.

https://lfs.aminer.cn/lab-datasets/crossdomain/Cross-Domain_data.zip

1. Jie Tang, Sen Wu, Jimeng Sun, and Hang Su. Cross-domain Collaboration Recommendation. In Proceedings of the Eighteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'2012). [PDF] [Slides] [Data&Code] [System]