Skluma: A Statistical Learning Pipeline for Taming Unkempt Data Repositories. Beckman, P., Skluzacek, T. J., Chard, K., & Foster, I. In Proceedings of the 29th International Conference on Scientific and Statistical Database Management, of SSDBM '17, pages 41:1–41:4, New York, NY, USA, 2017. ACM.
Paper doi bibtex @inproceedings{Beckman:2017:SSL:3085504.3091116,
author = {Beckman, Paul and Skluzacek, Tyler J. and Chard, Kyle and Foster, Ian},
title = {Skluma: A Statistical Learning Pipeline for Taming Unkempt Data Repositories},
booktitle = {Proceedings of the 29th International Conference on Scientific and Statistical Database Management},
series = {SSDBM '17},
year = {2017},
isbn = {978-1-4503-5282-6},
location = {Chicago, IL, USA},
pages = {41:1--41:4},
articleno = {41},
numpages = {4},
url = {http://doi.acm.org/10.1145/3085504.3091116},
doi = {10.1145/3085504.3091116},
acmid = {3091116},
publisher = {ACM},
address = {New York, NY, USA},
keywords = {data integration, data wrangling, metadata extraction, statistical learning},
}
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