Loris Bozzato

A decidable constructive description logic

Recently, there has been a growing interest in constructive reinterpretations of description logics. This has been motivated by the need to model in the DLs setting problems that have a consolidate tradition in constructive logics. In this paper we introduce a constructive description logic for the language of ALC based on the Kripke semantics for Intuitionistic Logic. Moreover we give a tableau calculus and we show that it is sound, complete and terminating.

Composition of semantic web services in a constructive description logic

We formalize the problem of service composition in the framework of a constructive description logic. We propose a declarative service specification language and a calculus for service composition.

Actions Over a Constructive Semantics for Description Logics

Following the approaches given in recent works about action languages over description logics, we propose an action formalism based on a constructive information terms semantics for ALC. We discuss how a notion of state can be naturally encoded by this semantics. We address the problems of determining executability of an action, building the state obtained by an action application and checking its consistency: we present an algorithm to solve the latter two problems.

Classification of News by Topic Using Location Data

In this work, we will consider news articles to determine geo-localization of their information and classify their topics on the basis of an available open data source: OpenStreetMap (OSM). We propose a knowledge-based conceptual and computational approach that disambiguates place names (i.e., geo-objects and regions) mentioned in news articles in terms of geographic coordinates. The geo-located news articles are analyzed to identify local topics: we found that the mentioned geo-objects are a good proxy to classify news topics.

Knowledge Propagation in Contextualized Knowledge Repositories: An Experimental Evaluation

As the interest in the representation of context dependent knowledge in the Semantic Web has been recognized, a number of logic based solutions have been proposed in this regard. In our recent works, in response to this need, we presented the description logic-based Contextualized Knowledge Repository (CKR) framework. CKR is not only a theoretical framework, but it has been effectively implemented over state-of-the-art tools for the management of Semantic Web data: inference inside and across contexts has been realized in the form of forward SPARQL-based rules over different RDF named graphs. In this paper we present the first evaluation results for such CKR implementation. In particular, in our first experiment we study its scalability with respect to different reasoning regimes. In a second experiment we analyze the effects of knowledge propagation on the reasoning process. In the last experiment we study the effects of modularization of global knowledge with respect to local reasoning.

Enhancing Context Knowledge Repositories with Justifiable Exceptions (Extended Abstract).

The Contextualized Knowledge Repository (CKR) framework was conceived as a logic-based approach for representing context dependent knowledge, which is a well-known area of study in AI. The framework has a two-layer structure with a global context that contains context-independent knowledge and meta-information about the contexts, and a set of local contexts with specific knowledge bases. In many practical cases, it is desirable that inherited global knowledge can be “overridden” at the local level. In order to address this need, we present an extension of CKR with global defeasible axioms: these axioms locally apply to (tuples of) individuals unless an exception for overriding exists; such an exception, however, requires a justification that is provable from the knowledge base. We formalize this intuition and study its semantic and computational properties. Furthermore, we present a translation of extended CKRs to datalog programs under the answer set (i.e., stable) semantics and we present an implementation prototype. Our work adds to the body of results on using deductive database technology in these areas, and provides an expressive formalism for exception handling by overriding.

Enhancing context knowledge repositories with justifiable exceptions

Abstract Dealing with context dependent knowledge is a well-known area of study that roots in John McCarthys seminal work. More recently, the Contextualized Knowledge Repository (CKR) framework has been conceived as a logic-based approach in which knowledge bases have a two layered structure, modeled by a global context and a set of local contexts. The global context not only contains the meta-knowledge defining the properties of local contexts, but also holds the global (context independent) object knowledge that is shared by all of the local contexts. In many practical cases, however, it is desirable to leave the possibility to “override” the global object knowledge at the local level: in other words, it is interesting to recognize the pieces of knowledge that can admit exceptional instances in the local contexts that do not need to satisfy the general axiom. To address this need, we present in this paper an extension of CKR in which defeasible axioms can be included in the global context. The latter are verified in the local contexts only for the instances for which no exception to overriding exists, where exceptions require a justification in terms of facts that are provable from the knowledge base. We formally define this semantics and study some semantic and computational properties, where we characterize the complexity of the major reasoning tasks, among them satisfiability testing, instance checking, and conjunctive query answering. Furthermore, we present a translation of extended CKRs with knowledge bases in the Description Logic SROIQ -RL under the novel semantics to datalog programs under the stable model (answer set) semantics. We also present an implementation prototype and examine its scalability with respect to the size of the input CKR and the amount (level) of defeasibility in experiments. Finally, we compare our representation approach with some major formalisms for expressing defeasible knowledge in Description Logics and contextual knowledge representation. Our work adds to the body of results on using deductive database technology such as SQL and datalog in these areas, and provides an expressive formalism (in terms of intrinsic complexity) for exception handling by overriding.

Towards integration of ontology and text-extracted data for event coreference reasoning

Recently, systems for automatic extraction of semantic information about events from large textual resources have been made available. These tools generate RDF datasets about the events described in the texts, enabling logical reasoning over the extracted information.. Ontological reasoning can be exploited to implement tasks that improve the quality of the extracted information, as, for example in event coreference (i.e., recognizing whether two textual descriptions refer to the same event). Starting from the observation that state of the art tools for event coreference do not exploit ontological information, in this paper, we propose a method to enrich event coreference detection on text-extracted event data by semantic-based rule reasoning.

Combining reasoning on semantic web metadata

As the amount of available linked data expand and the number of related applications increases, the management of aspects such as provenance and access control of such data begin to become an issue. Current approaches do not provide sufficient support for automatic reasoning over different metadata types and their possible interdependencies. MetaReasons is a framework that supports representation and automated reasoning over metadata in a single logical formalism. Different types of metadata, like data-provenance and accessibility-restrictions, are represented as distinct meta-theories and dependencies between metadata types are represented by rules between different meta-theories. In this paper we present the definition of the MetaReasons framework and two examples meta-theories for provenance and access control. Moreover, we propose a materialization calculus for forward reasoning on the two aspects.

ExpTime Tableaux Algorithm for Contextualized

Contextualized Knowledge Repository CKR is a DL-based framework for representation and reasoning with context dependent knowledge. It addresses the widely recognized need for contextualization of the Semantic Web data sources. Reasoning with CKR is possible thanks to a reduction to standard DL, and more recently a NExpTime tableaux algorithm was introduced for