Probabilistic Inductive Querying Using ProbLog

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De Raedt , L , Kimmig , A , Gutmann , B , Kersting , K , Santos Costa , V & Toivonen , H 2010 , Probabilistic Inductive Querying Using ProbLog . in S Dzeroski , B Goethals & P Panov (eds) , Inductive Databases and Constraint-Based Data Mining . Springer , pp. 229-262 .

Title: Probabilistic Inductive Querying Using ProbLog
Author: De Raedt, Luc; Kimmig, Angelika; Gutmann, Bernd; Kersting, Kristian; Santos Costa, Vitor; Toivonen, Hannu
Other contributor: Dzeroski, Saso
Goethals, Bart
Panov, Pance
Contributor organization: Finnish Centre of Excellence in Algorithmic Data Analysis Research (Algodan)
Helsinki Institute for Information Technology
Department of Computer Science
Discovery Research Group/Prof. Hannu Toivonen
Publisher: Springer
Date: 2010
Language: eng
Belongs to series: Inductive Databases and Constraint-Based Data Mining
ISBN: 978-1-4419-7737-3
Abstract: We study how probabilistic reasoning and inductive querying can be combined within ProbLog, a recent probabilistic extension of Prolog. ProbLog can be regarded as a database system that supports both probabilistic and inductive reasoning through a variety of querying mechanisms. After a short introduction to ProbLog, we provide a survey of the different types of inductive queries that ProbLog supports, and show how it can be applied to the mining of large biological networks.
Subject: 113 Computer and information sciences
Peer reviewed: Yes
Usage restriction: openAccess
Self-archived version: publishedVersion

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