{"type":"ScholarlyArticle","title":"On Constrained Open-World Probabilistic Databases","authors":[{"name":"Tal Friedman","slug":"tal-friedman","given":"Tal","family":"Friedman","affiliation":"University of California , Los Angeles"},{"name":"Guy Van den Broeck","slug":"guy-van-den-broeck","given":"Guy","family":"Van den Broeck","affiliation":"University of California , Los Angeles"}],"abstract":"Increasing amounts of available data have led to a\r\nheightened need for representing large-scale probabilistic knowledge bases. One approach is to\r\nuse a probabilistic database, a model with strong\r\nassumptions that allow for efficiently answering\r\nmany interesting queries. Recent work on open-world probabilistic databases strengthens the semantics of these probabilistic databases by discarding the assumption that any information not present\r\nin the data must be false. While intuitive, these\r\nsemantics are not sufficiently precise to give reasonable answers to queries. We propose overcoming these issues by using constraints to restrict this\r\nopen world. We provide an algorithm for one class\r\nof queries, and establish a basic hardness result for\r\nanother. Finally, we propose an efficient and tight\r\napproximation for a large class of queries.","doi":"10.24963/ijcai.2019/793","url":"https://ijcai.org/proceedings/2019/793","pdf":"https://ijcai.org/proceedings/2019/0793.pdf","markdown":"https://ijcai.org/proceedings/2019/793.md","bibtex":"https://ijcai.org/proceedings/2019/bibtex/793","volume":{"slug":"2019","title":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2019","url":"https://ijcai.org/proceedings/2019/","year":2019,"location":"Macao","dates":"10-16 August 2019","editors":"Sarit Kraus","isbn":"978-0-9992411-4-1","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2019"},"section":"Uncertainty in AI","track":"Main track","number":793,"pages":{"first":5722,"last":5729},"keywords":["Uncertainty in AI: Exact Probabilistic Inference","Multidisciplinary Topics and Applications: Databases","Uncertainty in AI: Relational Inference","Uncertainty in AI: Approximate Probabilistic Inference"],"videos":[],"references":[{"position":1,"raw":"[Abiteboul et al., 1995] Serge Abiteboul, Richard Hull, and Victor Vianu. 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