Hybrid Rules with Well-Founded Semantics

A general framework is proposed for integration of rules and external first order theories. It is based on the well-founded semantics of normal logic programs and inspired by ideas of Constraint Logic Programming (CLP) and constructive negation for logic programs. Hybrid rules are normal clauses extended with constraints in the bodies; constraints are certain formulae in the language of the external theory. A hybrid program is a pair of a set of hybrid rules and an external theory. Instances of the framework are obtained by specifying the class of external theories, and the class of constraints. An example instance is integration of (non-disjunctive) Datalog with ontologies formalized as description logics. The paper defines a declarative semantics of hybrid programs and a goal-driven formal operational semantics. The latter can be seen as a generalization of SLS-resolution. It provides a basis for hybrid implementations combining Prolog with constraint solvers. Soundness of the operational semantics is proven. Sufficient conditions for decidability of the declarative semantics, and for completeness of the operational semantics are given

OWL2Vec*: Embedding of OWL Ontologies

Semantic embedding of knowledge graphs has been widely studied and used for prediction and statistical analysis tasks across various domains such as Natural Language Processing and the Semantic Web. However, less attention has been paid to developing robust methods for embedding OWL (Web Ontology Language) ontologies. In this paper, we propose a language model based ontology embedding method named OWL2Vec*, which encodes the semantics of an ontology by taking into account its graph structure, lexical information and logic constructors. Our empirical evaluation with three real world datasets suggests that OWL2Vec* benefits from these three different aspects of an ontology in class membership prediction and class subsumption prediction tasks. Furthermore, OWL2Vec* often significantly outperforms the state-of-the-art methods in our experiments

LoLa: a modular ontology of logics, languages and translations

The Distributed Ontology Language (DOL), currently being standardised within the OntoIOp (Ontology Integration and Interoperability) activity of ISO/TC 37/SC 3, aims at providing a unified framework for (i) ontologies formalised in heterogeneous logics, (ii) modular ontologies, (iii) links between ontologies, and (iv) annotation of ontologies.\ud \ud This paper focuses on the LoLa ontology, which formally describes DOL's vocabulary for logics, ontology languages (and their serialisations), as well as logic translations. Interestingly, to adequately formalise the logical relationships between these notions, LoLa itself needs to be axiomatised heterogeneously---a task for which we choose DOL. Namely, we use the logic RDF for ABox assertions, OWL for basic axiomatisations of various modules concerning logics, languages, and translations, FOL for capturing certain closure rules that are not expressible in OWL (For the sake of tool availability it is still helpful not to map everything to FOL.), and circumscription for minimising the extension of concepts describing default translations

Evaluating Knowledge Representation and Reasoning Capabilites of Ontology Specification Languages

The interchange of ontologies across the World Wide Web (WWW) and the cooperation among heterogeneous agents placed on it is the main reason for the development of a new set of ontology specification languages, based on new web standards such as XML or RDF. These languages (SHOE, XOL, RDF, OIL, etc) aim to represent the knowledge contained in an ontology in a simple and human-readable way, as well as allow for the interchange of ontologies across the web. In this paper, we establish a common framework to compare the expressiveness of "traditional" ontology languages (Ontolingua, OKBC, OCML, FLogic, LOOM) and "web-based" ontology languages. As a result of this study, we conclude that different needs in KR and reasoning may exist in the building of an ontology-based application, and these needs must be evaluated in order to choose the most suitable ontology language(s)

Predicting Network Attacks Using Ontology-Driven Inference

Graph knowledge models and ontologies are very powerful modeling and re asoning tools. We propose an effective approach to model network attacks and attack prediction which plays important roles in security management. The goals of this study are: First we model network attacks, their prerequisites and consequences using knowledge representation methods in order to provide description logic reasoning and inference over attack domain concepts. And secondly, we propose an ontology-based system which predicts potential attacks using inference and observing information which provided by sensory inputs. We generate our ontology and evaluate corresponding methods using CAPEC, CWE, and CVE hierarchical datasets. Results from experiments show significant capability improvements comparing to traditional hierarchical and relational models. Proposed method also reduces false alarms and improves intrusion detection effectiveness.Comment: 9 page

The Distributed Ontology Language (DOL): Use Cases, Syntax, and Extensibility

The Distributed Ontology Language (DOL) is currently being standardized within the OntoIOp (Ontology Integration and Interoperability) activity of ISO/TC 37/SC 3. It aims at providing a unified framework for (1) ontologies formalized in heterogeneous logics, (2) modular ontologies, (3) links between ontologies, and (4) annotation of ontologies. This paper presents the current state of DOL's standardization. It focuses on use cases where distributed ontologies enable interoperability and reusability. We demonstrate relevant features of the DOL syntax and semantics and explain how these integrate into existing knowledge engineering environments.Comment: Terminology and Knowledge Engineering Conference (TKE) 2012-06-20 to 2012-06-21 Madrid, Spai

Justification Patterns for OWL DL Ontologies

For debugging OWL-DL ontologies, natural language explanations of inconsistencies and undesirable entailments are of great help. From such explanations, ontology developers can learn why an ontology gives rise to specific entailments. Unfortunately, commonly used tableaux-based reasoning services do not provide a basis for such explanations, since they rely on a refutation proof strategy and normalising transformations that are difficult for human ontology editors to understand. For this reason, we investigate the use of automatically generated justifications for entailments (i.e., minimal sets of axioms from the ontology that cause entailments to hold). We show that such justifications fall into a manageable number of patterns, which can be used as a basis for generating natural language explanations by associating each justification pattern with a rhetorical pattern in natural language