Parameterised Queries and Lifted Query Answering

Tanya Braun; Ralf Möller

doi:10.24963/ijcai.2018/691

Parameterised Queries and Lifted Query Answering

Tanya Braun, Ralf Möller

Institut für Informationssysteme

26 Zitate (Scopus)

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. © 2018 International Joint Conferences on Artificial Intelligence.All right reserved.

Originalsprache	Englisch
Titel	Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, IJCAI-18
Seitenumfang	7
Band	2018-July
Herausgeber (Verlag)	International Joint Conferences on Artificial Intelligence Organization
Erscheinungsdatum	01.07.2018
Seiten	4980-4986
ISBN (Print)	978-099924112-7
DOIs	https://doi.org/10.24963/ijcai.2018/691
Publikationsstatus	Veröffentlicht - 01.07.2018
Veranstaltung	27th International Joint Conference on Artificial Intelligence - Stockholm, Schweden Dauer: 13.07.2018 → 19.07.2018 Konferenznummer: 140653

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10.24963/ijcai.2018/691

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Braun, T., & Möller, R. (2018). Parameterised Queries and Lifted Query Answering. in Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, IJCAI-18 (Band 2018-July, S. 4980-4986). (IJCAI International Joint Conference on Artificial Intelligence). International Joint Conferences on Artificial Intelligence Organization. https://doi.org/10.24963/ijcai.2018/691

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title = "Parameterised Queries and Lifted Query Answering",

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. {\textcopyright} 2018 International Joint Conferences on Artificial Intelligence.All right reserved. ",

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doi = "10.24963/ijcai.2018/691",

language = "English",

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pages = "4980--4986",

booktitle = "Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, IJCAI-18",

note = "27th International Joint Conference on Artificial Intelligence, IJCAI 2018 ; Conference date: 13-07-2018 Through 19-07-2018",

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Braun, T & Möller, R 2018, Parameterised Queries and Lifted Query Answering. in Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, IJCAI-18. Bd. 2018-July, IJCAI International Joint Conference on Artificial Intelligence, International Joint Conferences on Artificial Intelligence Organization, S. 4980-4986, 27th International Joint Conference on Artificial Intelligence, Stockholm, Schweden, 13.07.18. https://doi.org/10.24963/ijcai.2018/691

Parameterised Queries and Lifted Query Answering. / Braun, Tanya; Möller, Ralf.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, IJCAI-18. Band 2018-July International Joint Conferences on Artificial Intelligence Organization, 2018. S. 4980-4986 (IJCAI International Joint Conference on Artificial Intelligence).

Publikation: Kapitel in Büchern/Berichten/Konferenzbänden › Konferenzbeitrag › Begutachtung

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N2 - 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. © 2018 International Joint Conferences on Artificial Intelligence.All right reserved.

AB - 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. © 2018 International Joint Conferences on Artificial Intelligence.All right reserved.

UR - https://www.scopus.com/pages/publications/85055689052

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DO - 10.24963/ijcai.2018/691

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Braun T, Möller R. Parameterised Queries and Lifted Query Answering. in Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, IJCAI-18. Band 2018-July. International Joint Conferences on Artificial Intelligence Organization. 2018. S. 4980-4986. (IJCAI International Joint Conference on Artificial Intelligence). doi: 10.24963/ijcai.2018/691

Parameterised Queries and Lifted Query Answering

Abstract

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