---
title: "Log-Linear Description Logics"
authors:
  - "Mathias Niepert"
  - "Jan Noessner"
  - "Heiner Stuckenschmidt"
doi: "10.5591/978-1-57735-516-8/IJCAI11-359"
url: "https://ijcai.org/proceedings/2011/359"
pdf: "https://ijcai.org/proceedings/2011/0359.pdf"
venue: "Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence"
year: 2011
pages: "2153-2157"
track: ""
keywords:
---

# Log-Linear Description Logics

Mathias Niepert, Jan Noessner, Heiner Stuckenschmidt

*Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence*, pages 2153-2157. DOI: [10.5591/978-1-57735-516-8/IJCAI11-359](https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-359)

## Abstract

Log-linear description logics are a family of probabilistic logics integrating various concepts and methods from the areas of knowledge representation and reasoning and statistical relational AI. We define the syntax and semantics of log-linear description logics, describe a convenient representation as sets of first-order formulas, and discuss computational and algorithmic aspects of probabilistic queries in the language. The paper concludes with an experimental evaluation of an implementation of a log-linear DL reasoner.