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Inductive Logic Programming in Databases: from Datalog to DL+log [article]

Francesca A. Lisi
2010 arXiv   pre-print
Both can be reformulated as ILP problems and can benefit from the expressive and deductive power of the KR framework DL+log. We illustrate the application scenarios by means of examples.  ...  Keywords: Inductive Logic Programming, Relational Databases, Ontologies, Description Logics, Hybrid Knowledge Representation and Reasoning Systems.  ...  Acknowledgements We are grateful to Riccardo Rosati for his precious advice on DL+log ¬∨ and Diego Calvanese for his valid support on the Boolean CQ/UCQ containment problem.  ... 
arXiv:1003.2586v1 fatcat:hnnwxc5ty5entgtjz2sljncosy

Integrating Ontologies and Rules: Semantic and Computational Issues [chapter]

Riccardo Rosati
2006 Lecture Notes in Computer Science  
, i.e., DL+log.  ...  In particular, we take into account ontologies expressed in Description Logics and rules expressed in Datalog (and its nonmonotonic extensions).  ...  A special acknowledgment goes to some of the (present and former) members of the Artificial Intelligence research group and the Data and Knowledge Bases research group at the Dipartimento di Informatica  ... 
doi:10.1007/11837787_5 fatcat:yq2djlkxnvctfkhhmfsnaiazxe

Integrating Rules and Ontologies in the First-Order Stable Model Semantics (Preliminary Report) [chapter]

Joohyung Lee, Ravi Palla
2011 Lecture Notes in Computer Science  
We present an approach to integrating rules and ontologies on the basis of the first-order stable model semantics defined by Ferraris, Lee and Lifschitz.  ...  We show that a few existing integration proposals can be uniformly related to the first-order stable model semantics.  ...  We are grateful to David Pearce for pointers to earlier work and anonymous referees for their useful comments.  ... 
doi:10.1007/978-3-642-20895-9_27 fatcat:rqk3dwy5ynfftcysafcdljneei

Learning Onto-Relational Rules with Inductive Logic Programming [article]

Francesca A. Lisi
2012 arXiv   pre-print
In this chapter we show how Inductive Logic Programming (ILP), born at the intersection of Machine Learning and Logic Programming and considered as a major approach to Relational Learning, can be adapted  ...  We refer to these rules as onto-relational since they combine DL-based ontology languages and Knowledge Representation formalisms supporting the relational data model within the tradition of Logic Programming  ...  CARIN [23] AL-LOG[8] DL+LOG ¬∨ [45] DL language any DL ALC any DL CL language Horn clauses DATALOG clauses DATALOG ¬∨ clauses integration tight DL-unsafe tight DL-safe tight weakly DL-safe  ... 
arXiv:1210.2984v2 fatcat:caeq4ahppzhjbddoa5fyhgr4pe

Learning Semantic Web Rules within the Framework of SHIQ+log

Francesca A. Lisi, Floriana Esposito
2008 International Semantic Web Conference  
In this paper we face the problem of learning Semantic Web rules within a decidable instantiation of the DL+log framework which integrates the DL SHIQ and positive Datalog.  ...  To solve the problem, we resort to the methodological apparatus of Inductive Logic Programming.  ...  INTRODUCTION Among the many recent KR proposals for Semantic Web rules, DL+log [9] is a powerful framework for the tight integration of Description Logics (DLs) [1] and disjunctive Datalog with negation  ... 
dblp:conf/semweb/LisiE08 fatcat:loueynmyljhwdhvzwptw2xssom

Learning SHIQ+log Rules for Ontology Evolution

Francesca A. Lisi, Floriana Esposito
2008 Semantic Web Applications and Perspectives  
In this paper we reformulate this task as a machine learning problem and study a solution based on techniques borrowed from that form of logic-based machine learning known under the name of Inductive Logic  ...  More precisely, we propose to adapt previous ILP results to the knowledge representation framework of DL+log in order to learn rules to be used for changing SHIQ ontologies.  ...  Representing Rules with DL+log The KR framework of DL+log [16] allows for the tight integration of DLs [1] and Datalog ¬∨ [6] .  ... 
dblp:conf/swap/LisiE08 fatcat:wjnbiuqqnzgpvfp42acp2llfai

Inductive Logic Programming in Databases: From Datalog to

FRANCESCA A. LISI
2010 Theory and Practice of Logic Programming  
Both can be reformulated as ILP problems and can benefit from the expressive and deductive power of the KR framework$\mathcal{DL}+log}^{\neg\vee}$.  ...  AbstractIn this paper we address an issue that has been brought to the attention of the database community with the advent of the Semantic Web, i.e., the issue of how ontologies (and semantics conveyed  ...  Acknowledgements We are grateful to Riccardo Rosati for his precious advice on DL+log ¬∨ and Diego Calvanese for his valid support on the Boolean CQ/UCQ containment problem.  ... 
doi:10.1017/s1471068410000116 fatcat:fhmx2lyy4vb4dfqk6hayrfi4o4

Guarded Hybrid Knowledge Bases [article]

Stijn Heymans, Jos de Bruijn, Livia Predoiu, Cristina Feier, Davy Van Nieuwenborgh
2007 arXiv   pre-print
that consist of a Description Logic knowledge base and a guarded logic program, similar to the DL+log knowledge bases from (Rosati 2006).  ...  Finally, we discuss advantages and disadvantages of our approach compared with DL+log knowledge bases.  ...  Relation with DL+log and other Related Work In (Rosati 2006) , so-called DL+log knowledge bases combine a Description Logic knowledge base with a weakly-safe disjunctive logic program.  ... 
arXiv:0711.2155v1 fatcat:vteqertlzbhpzmfjb32wdl5muu

Guarded hybrid knowledge bases

STIJN HEYMANS, JOS DE BRUIJN, LIVIA PREDOIU, CRISTINA FEIER, DAVY VAN NIEWENBORGH
2008 Theory and Practice of Logic Programming  
AbstractRecently, there has been a lot of interest in the integration of Description Logics (DL) and rules on the Semantic Web.  ...  enable an integration of Description Logics and Logic Programming where, unlike in other approaches, variables in the rules of a guarded program do not need to appear in positive non-DL atoms of the body  ...  Relation with DL+log and other Related Work In (Rosati 2006) , so-called DL+log knowledge bases combine a Description Logic knowledge base with a weakly-safe disjunctive logic program.  ... 
doi:10.1017/s1471068407003201 fatcat:2gyemstkvbaj5okdifr4lynwe4

Rules and Ontologies for the Semantic Web [chapter]

Thomas Eiter, Giovambattista Ianni, Thomas Krennwallner, Axel Polleres
2008 Lecture Notes in Computer Science  
The remainder of this article is organized as follows. The next section provides some preliminaries, including RDF/RDF Schema and Description Logics as well as OWL.  ...  Furthermore, we review technical problems underlying the integration of rules and ontologies, and classify representative proposals for theoretical integration approaches into different categories.  ...  Tight integration: DL+log DL+log [89] is the latest in a chain of extensions of the DL ALC with rules such as AL-log, r-and r + -hybrid knowledge bases.  ... 
doi:10.1007/978-3-540-85658-0_1 fatcat:x75rrerlzvelbh7vpo6subgzru

The role of semantics in mining frequent patterns from knowledge bases in description logics with rules [article]

Joanna Jozefowska, Agnieszka Lawrynowicz, Tomasz Lukaszewski
2010 arXiv   pre-print
In particular we consider the setting of using a language that combines description logics with DL-safe rules.  ...  Note: To appear in Theory and Practice of Logic Programming (TPLP)  ...  King for valuable discussions on KR and data mining in biology, and the remarks on earlier versions of the paper, to Jan Ramon for explanations on the concept of the semantic freeness of Datalog patterns  ... 
arXiv:1003.2700v2 fatcat:xoevmzoldzaytnrwnjk2c26ruu

The role of semantics in mining frequent patterns from knowledge bases in description logics with rules

JOANNA JÓZEFOWSKA, AGNIESZKA ŁAWRYNOWICZ, TOMASZ ŁUKASZEWSKI
2010 Theory and Practice of Logic Programming  
In particular, we consider the setting of using a language that combines description logics (DLs) with DL-safe rules.  ...  We focus on the relation of the semantics of the representation formalism to the task of frequent pattern discovery, and for the core of our method, we propose an algorithm that exploits the semantics  ...  King for valuable discussions on KR and data mining in biology, and the remarks on earlier versions of the paper, to Jan Ramon for explanations on the concept of the semantic freeness of Datalog patterns  ... 
doi:10.1017/s1471068410000098 fatcat:wxq63fah3zagvg3exwmmr4kp2a

A Faithful Integration of Description Logics with Logic Programming

Boris Motik, Riccardo Rosati
2007 International Joint Conference on Artificial Intelligence  
Integrating description logics (DL) and logic programming (LP) would produce a very powerful and useful formalism.  ...  We also give reasoning algorithms and tight data complexity bounds for several interesting fragments of our logic. * This work was partially funded by the EPSRC project REOL (EP/C537211/1) and the EU project  ...  In this paper, we introduce hybrid MKNF knowledge bases, which integrate an arbitrary description logic DL 1 with disjunctive logic programs and negation-as-failure.  ... 
dblp:conf/ijcai/MotikR07 fatcat:tl3fgk4g6bfj7ntni2pmrqy2iq

Combining OWL with F-Logic Rules and Defaults

Heiko Kattenstroth, Wolfgang May, Franz Schenk
2007 International Conference on Logic Programming  
We describe the combination of OWL and F-Logic for the architecture of Semantic Web application nodes.  ...  The approach provides a tight language coupling, i.e., the same notions can be defined both by OWL definitions and by F-Logic rules.  ...  disjunctive Datalog and allows for DL-safe rules.  ... 
dblp:conf/iclp/KattenstrothMS07 fatcat:2oi7i5rrenb77ghlckmfulb56i

Inline Evaluation of Hybrid Knowledge Bases [chapter]

Guohui Xiao, Thomas Eiter
2011 Lecture Notes in Computer Science  
Tight coupling approaches can be classified, depending on the expressivity of the rule component, to (1) the fragments of first order logics, with only positive Datalog style rules, and (2) DL+ log knowledge  ...  DL+ log and its Variants Compared with first-order combinations, the framework of DL+ log and its variants support more expressive rules, featuring default negations and full answer set semantics.  ... 
doi:10.1007/978-3-642-23580-1_28 fatcat:xnzzbf2imngshokm36ni5vuzni
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