A Short Introduction to Probabilistic Soft Logic


Probabilistic soft logic (PSL) is a framework for collective, probabilistic reasoning in relational domains. PSL uses first order logic rules as a template language for graphical models over random variables with soft truth values from the interval [0, 1]. Inference in this setting is a continuous optimization task, which can be solved efficiently. This paper provides an overview of the PSL language and its techniques for inference and weight learning. An implementation of PSL is available at http://psl.umiacs.umd.edu/.

Extracted Key Phrases

Citations per Year

106 Citations

Semantic Scholar estimates that this publication has 106 citations based on the available data.

See our FAQ for additional information.

Cite this paper

@inproceedings{Kimmig2012ASI, title={A Short Introduction to Probabilistic Soft Logic}, author={Angelika Kimmig and Stephen H. Bach and Matthias Broecheler and Bert Huang and Lise Getoor}, year={2012} }