89 research outputs found
Defeasible RDFS via Rational Closure
In the field of non-monotonic logics, the notion of Rational Closure (RC) is
acknowledged as a prominent approach. In recent years, RC has gained even more
popularity in the context of Description Logics (DLs), the logic underpinning
the semantic web standard ontology language OWL 2, whose main ingredients are
classes and roles. In this work, we show how to integrate RC within the triple
language RDFS, which together with OWL2 are the two major standard semantic web
ontology languages. To do so, we start from , which is the logic
behind RDFS, and then extend it to , allowing to state that two
entities are incompatible. Eventually, we propose defeasible via
a typical RC construction. The main features of our approach are: (i) unlike
most other approaches that add an extra non-monotone rule layer on top of
monotone RDFS, defeasible remains syntactically a triple
language and is a simple extension of by introducing some new
predicate symbols with specific semantics. In particular, any RDFS
reasoner/store may handle them as ordinary terms if it does not want to take
account for the extra semantics of the new predicate symbols; (ii) the
defeasible entailment decision procedure is build on top of the
entailment decision procedure, which in turn is an extension of
the one for via some additional inference rules favouring an
potential implementation; and (iii) defeasible entailment can be
decided in polynomial time.Comment: 47 pages. Preprint versio
Logic-based Technologies for Intelligent Systems: State of the Art and Perspectives
Together with the disruptive development of modern sub-symbolic approaches to artificial intelligence (AI), symbolic approaches to classical AI are re-gaining momentum, as more and more researchers exploit their potential to make AI more comprehensible, explainable, and therefore trustworthy. Since logic-based approaches lay at the core of symbolic AI, summarizing their state of the art is of paramount importance now more than ever, in order to identify trends, benefits, key features, gaps, and limitations of the techniques proposed so far, as well as to identify promising research perspectives. Along this line, this paper provides an overview of logic-based approaches and technologies by sketching their evolution and pointing out their main application areas. Future perspectives for exploitation of logic-based technologies are discussed as well, in order to identify those research fields that deserve more attention, considering the areas that already exploit logic-based approaches as well as those that are more likely to adopt logic-based approaches in the future
Computer Science & Technology Series : XVIII Argentine Congress of Computer Science. Selected papers
CACIC’12 was the eighteenth Congress in the CACIC series. It was organized by the School of Computer Science and Engineering at the Universidad Nacional del Sur.
The Congress included 13 Workshops with 178 accepted papers, 5 Conferences, 2 invited tutorials, different meetings related with Computer Science Education (Professors, PhD students, Curricula) and an International School with 5 courses.
CACIC 2012 was organized following the traditional Congress format, with 13 Workshops covering a diversity of dimensions of Computer Science Research.
Each topic was supervised by a committee of 3-5 chairs of different Universities.
The call for papers attracted a total of 302 submissions. An average of 2.5 review reports were collected for each paper, for a grand total of 752 review reports that involved about 410 different reviewers.
A total of 178 full papers, involving 496 authors and 83 Universities, were accepted and 27 of them were selected for this book.Red de Universidades con Carreras en Informática (RedUNCI
Proceedings of the 11th Workshop on Nonmonotonic Reasoning
These are the proceedings of the 11th Nonmonotonic Reasoning Workshop. The aim of this series is to bring together active researchers in the broad area of nonmonotonic reasoning, including belief revision, reasoning about actions, planning, logic programming, argumentation, causality, probabilistic and possibilistic approaches to KR, and other related topics. As part of the program of the 11th workshop, we have assessed the status of the field and discussed issues such as: Significant recent achievements in the theory and automation of NMR; Critical short and long term goals for NMR; Emerging new research directions in NMR; Practical applications of NMR; Significance of NMR to knowledge representation and AI in general
JURI SAYS:An Automatic Judgement Prediction System for the European Court of Human Rights
In this paper we present the web platform JURI SAYS that automatically predicts decisions of the European Court of Human Rights based on communicated cases, which are published by the court early in the proceedings and are often available many years before the final decision is made. Our system therefore predicts future judgements of the court. The platform is available at jurisays.com and shows the predictions compared to the actual decisions of the court. It is automatically updated every month by including the prediction for the new cases. Additionally, the system highlights the sentences and paragraphs that are most important for the prediction (i.e. violation vs. no violation of human rights)
A semantic web rule language for geospatial domains
Retrieval of geographically-referenced information on the Internet is now a common activity. The web is increasingly being seen as a medium for the storage and exchange of geographic data sets in the form of maps. The geospatial-semantic web (GeoWeb) is being developed to address the need for access to current and accurate geo-information. The potential applications of the GeoWeb are numerous, ranging from specialised application domains for storing and analysing geo-information to more common applications by casual users for querying and visualising geo-data, e.g. finding locations of services, descriptions of routes, etc. Ontologies are at the heart of W3C's semantic web initiative to provide the necessary machine understanding to the sheer volumes of information contained on the internet. For the GeoWeb to succeed the development of ontologies for the geographic domain are crucial. Semantic web technologies to represent ontologies have been developed and standardised. OWL, the Web Ontology Language, is the most expressive of these enabling a rich form of reasoning, thanks to its formal description logic underpinnings. Building geo-ontologies involves a continuous process of update to the originally modelled data to reflect change over time as well as to allow for ontology expansion by integrating new data sets, possibly from different sources. One of the main challenges in this process is finding means of ensuring the integrity of the geo-ontology and maintaining its consistency upon further evolution. Representing and reasoning with geographic ontologies in OWL is limited. Firstly, OWL is not an integrity checking language due to it's non-unique name and open world assumptions. Secondly, it can not represent spatial datatypes, can not compute information using spatial operators and does not have any form of spatial index. Finally, OWL does not support complex property composition needed to represent qualitative spatial reasoning over spatial concepts. To address OWL's representational inefficiencies, new ontology languages have been proposed based on the intersection or union of OWL (in particular the DL family corresponding to OWL) with logic programs (rule languages). In this work, a new Semantic Web Spatial Rule Language (SWSRL) is proposed, based on the syntactic core of the Description Logic Programs paradigm (DLP), and the semantics of a Logic Program. The language is built to support the expression of geospatial ontological axioms and geospatial integrity and deduction rules. A hybrid framework to integrate both qualitative symbolic information in SWSRL with quantitative, geometric information using spatial datatypes in a spatial database is proposed. Two notable features of SWSRL are 1) the language is based on a prioritised de fault logic that allows the expression of default integrity rules and their exceptions and 2) the implementation of the language uses an interleaved mode of inference for on the fly computation (either qualitative or quantitative) deduction of spatial relations. SWSRL supports an OGC complaint spatial syntax, and a standardised definition of rule meta data. Both features aid the construction, description, identification and categorisation of designed and implemented rules within large rule sets. The language and the developed engine are evaluated using synthetic as well as real data sets in the context of developing geographic ontologies for geographic information retrieval on the Semantic Web. Empirical experiments are also presented to test the scalability and applicability of the developed framework
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
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