A web system for reasoning with probabilistic OWL. (13th May 2016)

• Record Type: Journal Article
• Authors: Bellodi, Elena; Lamma, Evelina; Riguzzi, Fabrizio; Zese, Riccardo; Cota, Giuseppe
• Is Part Of: Software, practice & experience. Volume 47:Number 1(2017)
• Page Start: 125
• Page End: 142
• Publication Date: 2016-05-13
• Subjects: semantic web -- web applications -- description logics -- probabilistic description logics -- SWI‐Prolog -- logic programming; Computer software -- Periodicals; Computer programming -- Periodicals; Computer programs -- Periodicals; 005.3
• DOI: 10.1002/spe.2410
• Languages: English
• ISSNs: 0038-0644

Abstract

Summary: We present the web application Tableau Reasoner for descrIption Logics in proLog on SWI‐Prolog for SHaring (TRILL on SWISH) which allows the user to write probabilistic description logic (DL) theories and compute the probability of queries with just a web browser. Various probabilistic extensions of DLs have been proposed in the recent past, because uncertainty is a fundamental component of the Semantic Web. We consider probabilistic DL theories following our distribution semantics for probabilistic ontologies (DISPONTE) semantics. Axioms of a DISPONTE knowledge base can be annotated with a probability, and the probability of queries can be computed with inference algorithms. TRILL is a probabilistic reasoner for DISPONTE knowledge base that is implemented in Prolog and exploits its backtracking facilities for handling the non‐determinism of the tableau algorithm. TRILL on SWISH is based on SWISH, a recently proposed web framework for logic programming, based on various features and packages of SWI‐Prolog (e.g., a web server and a library for creating remote Prolog engines and posing queries to them). TRILL on SWISH also allows users to cooperate in writing a probabilistic DL theory. It is free, open, and accessible on the Web at the url:http://trill.lamping.unife.it ; it includes a number of examples that cover a wide range of domains and provide interesting Probabilistic Semantic Web applications. By building a web‐based system, we allow users to experiment with probabilistic DLs without the need to install a complex software stack. In this way, we aim to reach out to a wider audience and popularize the Probabilistic Semantic Web. Copyright © 2016 John Wiley & Sons, Ltd.