Uncertainty Annotated Databases - A Lightweight Approach for Approximating Certain Answers

Authors

• 1. Su Feng (Illinois Institute of Technology)
• 2. Aaron Huber (State University of New York at Buffalo)
• 3. Boris Glavic (Illinois Institute of Technology)
• 4. Oliver Kennedy (State University of New York at Buffalo)

@inproceedings{feng_sigmod19,
        title = {{Uncertainty Annotated Databases - A Lightweight Approach for Approximating Certain Answers}},
        author = {Feng, Su and Huber, Aaron and Glavic, Boris and Kennedy, Oliver},
        series = {{SIGMOD} '19},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3299869.3319887},
        url = {https://dl.acm.org/doi/10.1145/3299869.3319887},
        year = {2019}
}

Incoming Citations (Sorted by Pagerank)

Showing 8 of 8 citing papers.

Outgoing Citations (Sorted by Pagerank)

Showing 16 of 16 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Semantically Similar Papers