Journal article
Learning models over relational data using sparse tensors and functional dependencies
- Abstract:
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Integrated solutions for analytics over relational databases are of great practical importance as they avoid the costly repeated loop data scientists have to deal with on a daily basis: select features from data residing in relational databases using feature extraction queries involving joins, projections, and aggregations; export the training dataset defined by such queries; convert this dataset into the format of an external learning tool; and train the desired model using this tool. The...
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- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
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(Accepted manuscript, 867.7KB)
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- Publisher copy:
- 10.1145/3375661
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Authors
Funding
European Commission
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Bibliographic Details
- Publisher:
- Association for Computing Machinery Publisher's website
- Journal:
- ACM Transactions on Database Systems Journal website
- Volume:
- 45
- Issue:
- 2
- Article number:
- 7
- Publication date:
- 2020-06-27
- Acceptance date:
- 2019-12-01
- DOI:
- EISSN:
-
1557-4644
- ISSN:
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0362-5915
Item Description
- Language:
- English
- Keywords:
- Pubs id:
-
1085366
- Local pid:
- pubs:1085366
- Deposit date:
- 2020-02-06
Terms of use
- Copyright holder:
- Association for Computing Machinery
- Copyright date:
- 2020
- Rights statement:
- © 2020 ACM.
- Notes:
- This is the accepted manuscript version of the article. The final version is available online from the Association for Computing Machinery at: https://doi.org/10.1145/3375661
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