{"type":"ScholarlyArticle","title":"Parameterised Queries and Lifted Query Answering","authors":[{"name":"Tanya Braun","slug":"tanya-braun","given":"Tanya","family":"Braun","affiliation":"Institute of Information Systems , University of Lübeck , Lübeck , Germany"},{"name":"Ralf Möller","slug":"ralf-moller","given":"Ralf","family":"Möller","affiliation":"Institute of Information Systems , University of Lübeck , Lübeck , Germany"}],"abstract":"A standard approach for inference in probabilistic formalisms with first-order constructs is lifted variable elimination (LVE) for single queries. To handle multiple queries efficiently, the lifted junction tree algorithm (LJT) employs a first-order cluster representation of a model and LVE as a subroutine. Both algorithms answer conjunctive queries of propositional random variables, shattering the model on the query, which causes unnecessary groundings for conjunctive queries of interchangeable variables. This paper presents parameterised queries as a means to avoid groundings, applying the lifting idea to queries. Parameterised queries enable LVE and LJT to compute answers faster, while compactly representing queries and answers.","doi":"10.24963/ijcai.2018/691","url":"https://ijcai.org/proceedings/2018/691","pdf":"https://ijcai.org/proceedings/2018/0691.pdf","markdown":"https://ijcai.org/proceedings/2018/691.md","bibtex":"https://ijcai.org/proceedings/2018/bibtex/691","volume":{"slug":"2018","title":"Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2018","url":"https://ijcai.org/proceedings/2018/","year":2018,"location":"Stockholm","dates":"13-19 July 2018","editors":"Jérôme Lang","isbn":"978-0-9992411-2-7","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2018"},"section":"Uncertainty in AI","track":"Main track","number":691,"pages":{"first":4980,"last":4986},"keywords":["Uncertainty in AI: Uncertainty in AI","Uncertainty in AI: Relational Inference","Uncertainty in AI: Exact Probabilistic Inference","Uncertainty in AI: Graphical Models"],"videos":[],"references":[{"position":1,"raw":"[Ahmadi et al., 2013] Babak Ahmadi, Kristian Kersting, Martin Mladenov, and Sriraam Natarajan. 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