ELOG: A Probabilistic Reasoner for OWL EL

Noessner, Jan ; Niepert, Mathias

DOI: https://doi.org/10.1007/978-3-642-23580-1_25
URL: https://link.springer.com/chapter/10.1007%2F978-3-...
Document Type: Conference or workshop publication
Year of publication: 2011
Book title: Web Reasoning and Rule Systems : 5th International Conference, RR 2011, Galway, Ireland; proceedings
The title of a journal, publication series: Lecture Notes in Computer Science
Volume: 6902
Page range: 281-286
Conference title: RR 2011
Location of the conference venue: Galway, Ireland
Date of the conference: August 29 - 30, 2011
Publisher: Rudolph, Sebastian
Place of publication: Berlin [u.a.]
Publishing house: Springer
ISBN: 978-3-642-23579-5
ISSN: 0302-9743 , 1611-3349
Publication language: English
Institution: School of Business Informatics and Mathematics > Practical Computer Science II: Artificial Intelligence (Stuckenschmidt 2009-)
Subject: 004 Computer science, internet
Abstract: Log-linear description logics are probabilistic logics combining several concepts and methods from the areas of knowledge representation and reasoning and statistical relational AI. We describe some of the implementation details of the log-linear reasoner ELOG. The reasoner employs database technology to dynamically transform inference problems to integer linear programs (ILP). In order to lower the size of the ILPs and reduce the complexity we employ a form of cutting plane inference during reasoning.

Dieser Eintrag ist Teil der Universitätsbibliographie.

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