318 research outputs found
The Vadalog System: Datalog-based Reasoning for Knowledge Graphs
Over the past years, there has been a resurgence of Datalog-based systems in
the database community as well as in industry. In this context, it has been
recognized that to handle the complex knowl\-edge-based scenarios encountered
today, such as reasoning over large knowledge graphs, Datalog has to be
extended with features such as existential quantification. Yet, Datalog-based
reasoning in the presence of existential quantification is in general
undecidable. Many efforts have been made to define decidable fragments. Warded
Datalog+/- is a very promising one, as it captures PTIME complexity while
allowing ontological reasoning. Yet so far, no implementation of Warded
Datalog+/- was available. In this paper we present the Vadalog system, a
Datalog-based system for performing complex logic reasoning tasks, such as
those required in advanced knowledge graphs. The Vadalog system is Oxford's
contribution to the VADA research programme, a joint effort of the universities
of Oxford, Manchester and Edinburgh and around 20 industrial partners. As the
main contribution of this paper, we illustrate the first implementation of
Warded Datalog+/-, a high-performance Datalog+/- system utilizing an aggressive
termination control strategy. We also provide a comprehensive experimental
evaluation.Comment: Extended version of VLDB paper
<https://doi.org/10.14778/3213880.3213888
Constructive Reasoning for Semantic Wikis
One of the main design goals of social software, such as wikis, is to
support and facilitate interaction and collaboration. This dissertation
explores challenges that arise from extending social software with
advanced facilities such as reasoning and semantic annotations and
presents tools in form of a conceptual model, structured tags, a rule
language, and a set of novel forward chaining and reason maintenance
methods for processing such rules that help to overcome the
challenges.
Wikis and semantic wikis were usually developed in an ad-hoc
manner, without much thought about the underlying concepts. A conceptual
model suitable for a semantic wiki that takes advanced features
such as annotations and reasoning into account is proposed. Moreover,
so called structured tags are proposed as a semi-formal knowledge
representation step between informal and formal annotations.
The focus of rule languages for the Semantic Web has been predominantly
on expert users and on the interplay of rule languages
and ontologies. KWRL, the KiWi Rule Language, is proposed as a
rule language for a semantic wiki that is easily understandable for
users as it is aware of the conceptual model of a wiki and as it
is inconsistency-tolerant, and that can be efficiently evaluated as it
builds upon Datalog concepts.
The requirement for fast response times of interactive software
translates in our work to bottom-up evaluation (materialization) of
rules (views) ahead of time – that is when rules or data change, not
when they are queried. Materialized views have to be updated when
data or rules change. While incremental view maintenance was intensively
studied in the past and literature on the subject is abundant,
the existing methods have surprisingly many disadvantages – they
do not provide all information desirable for explanation of derived
information, they require evaluation of possibly substantially larger
Datalog programs with negation, they recompute the whole extension
of a predicate even if only a small part of it is affected by a
change, they require adaptation for handling general rule changes.
A particular contribution of this dissertation consists in a set of
forward chaining and reason maintenance methods with a simple declarative
description that are efficient and derive and maintain information
necessary for reason maintenance and explanation. The reasoning
methods and most of the reason maintenance methods are described
in terms of a set of extended immediate consequence operators the
properties of which are proven in the classical logical programming
framework. In contrast to existing methods, the reason maintenance methods in this dissertation work by evaluating the original Datalog
program – they do not introduce negation if it is not present in the input
program – and only the affected part of a predicate’s extension is
recomputed. Moreover, our methods directly handle changes in both
data and rules; a rule change does not need to be handled as a special
case.
A framework of support graphs, a data structure inspired by justification
graphs of classical reason maintenance, is proposed. Support
graphs enable a unified description and a formal comparison of the
various reasoning and reason maintenance methods and define a notion
of a derivation such that the number of derivations of an atom is
always finite even in the recursive Datalog case.
A practical approach to implementing reasoning, reason maintenance,
and explanation in the KiWi semantic platform is also investigated. It
is shown how an implementation may benefit from using a graph
database instead of or along with a relational database
Ontology-based data access with databases: a short course
Ontology-based data access (OBDA) is regarded as a key ingredient of the new generation of information systems. In the OBDA paradigm, an ontology defines a high-level global schema of (already existing) data sources and provides a vocabulary for user queries. An OBDA system rewrites such queries and ontologies into the vocabulary of the data sources and then delegates the actual query evaluation to a suitable query answering system such as a relational database management system or a datalog engine. In this chapter, we mainly focus on OBDA with the ontology language OWL 2QL, one of the three profiles of the W3C standard Web Ontology Language OWL 2, and relational databases, although other possible languages will also be discussed. We consider different types of conjunctive query rewriting and their succinctness, different architectures of OBDA systems, and give an overview of the OBDA system Ontop
Logical Reduction of Metarules
International audienceMany forms of inductive logic programming (ILP) use metarules, second-order Horn clauses, to define the structure of learnable programs and thus the hypothesis space. Deciding which metarules to use for a given learning task is a major open problem and is a trade-off between efficiency and expressivity: the hypothesis space grows given more metarules, so we wish to use fewer metarules, but if we use too few metarules then we lose expressivity. In this paper, we study whether fragments of metarules can be logically reduced to minimal finite subsets. We consider two traditional forms of logical reduction: subsumption and entailment. We also consider a new reduction technique called derivation reduction, which is based on SLD-resolution. We compute reduced sets of metarules for fragments relevant to ILP and theoretically show whether these reduced sets are reductions for more general infinite fragments. We experimentally compare learning with reduced sets of metarules on three domains: Michalski trains, string transformations, and game rules. In general, derivation reduced sets of metarules outperform subsumption and entailment reduced sets, both in terms of predictive accuracies and learning times
Datalog and Constraint Satisfaction with Infinite Templates
On finite structures, there is a well-known connection between the expressive
power of Datalog, finite variable logics, the existential pebble game, and
bounded hypertree duality. We study this connection for infinite structures.
This has applications for constraint satisfaction with infinite templates. If
the template Gamma is omega-categorical, we present various equivalent
characterizations of those Gamma such that the constraint satisfaction problem
(CSP) for Gamma can be solved by a Datalog program. We also show that
CSP(Gamma) can be solved in polynomial time for arbitrary omega-categorical
structures Gamma if the input is restricted to instances of bounded treewidth.
Finally, we characterize those omega-categorical templates whose CSP has
Datalog width 1, and those whose CSP has strict Datalog width k.Comment: 28 pages. This is an extended long version of a conference paper that
appeared at STACS'06. In the third version in the arxiv we have revised the
presentation again and added a section that relates our results to
formalizations of CSPs using relation algebra
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