Journal of Logic and Computation - current issue

Special Issue on Ontology Dynamics

Flouris, G., d'Aquin, M., Antoniou, G., Pan, J., Plexousakis, D. — Mon, 21 Sep 2009 08:00:31 PDT

Base Revision for Ontology Debugging

Ribeiro, M. M., Wassermann, R. — Mon, 21 Sep 2009 08:00:31 PDT

Belief Revision deals with the problem of adding new information to a knowledge base in a consistent way. Ontology Debugging, on the other hand, aims to find the axioms in a terminological knowledge base which caused the base to become inconsistent. In this article, we propose a belief revision approach in order to find and repair inconsistencies in ontologies represented in some description logic (DL). As the usual belief revision operators cannot be directly applied to DLs, we propose new operators that can be used with more general logics and show that, in particular, they can be applied to the logics underlying OWL-DL and Lite.

On Instance-level Update and Erasure in Description Logic Ontologies

De Giacomo, G., Lenzerini, M., Poggi, A., Rosati, R. — Mon, 21 Sep 2009 08:00:31 PDT

A Description Logic (DL) ontology is constituted by two components, a TBox that expresses general knowledge about the concepts and their relationships, and an ABox that describes the properties of individuals that are instances of concepts. We address the problem of how to deal with changes to a DL ontology, when these changes affect only the ABox, i.e. when the TBox is considered invariant. We consider two basic changes, namely instance-level update and instance-level erasure, roughly corresponding to the addition and the deletion of a set of facts involving individuals. We characterize the semantics of instance-level update and erasure on the basis of the approaches proposed by Winslett and by Katsuno and Mendelzon. Interestingly, DLs are typically not closed with respect to instance-level update and erasure, in the sense that the set of models corresponding to the application of any of these operations to a knowledge base in a DL $$\mathcal{L}$$ may not be expressible by ABoxes in $$\mathcal{L}$$. In particular, we show that this is true for DL-Lite$$\mathcal{F}$$, a tractable DL that is oriented towards data-intensive applications. To deal with this problem, we first introduce DL-Lite$$\mathcal{FS}$$, a DL that minimally extends DL-Lite$$\mathcal{F}$$ and is closed with respect to instance-level update, and present a polynomial algorithm for computing instance-level update in this logic. Then, we provide a principled notion of best approximation with respect to a fixed language $$\mathcal{L}$$ of instance-level update and erasure, and exploit the algorithm for instance-level update for DL-Lite$$\mathcal{FS}$$ to get polynomial algorithms for approximated instance-level update and erasure for DL-Lite$$\mathcal{F}$$. These results confirm the nice computational properties of DL-Lite$$\mathcal{F}$$ for data intensive applications, even where information about instances is not only read, but also written.

Trust-based Revision for Expressive Web Syndication

Golbeck, J., Halaschek-Wiener, C. — Mon, 21 Sep 2009 08:00:31 PDT

Interest in web-based syndication systems has been growing as information streams onto the web at an increasing rate. Technologies, like the standard Semantic Web languages RDF and OWL, make it possible to create expressive representations of the content of publications and subscriptions in a syndication framework. Because these languages are based in description logics, this representation allows the application to reasoning to make more precise matching of user interests with published information. A challenge to this approach is that the consistency of the underlying knowledge base must be maintained for these techniques to work. With the frequent addition of information from new publications, it is likely that inconsistencies will arise. There are many potential mechanisms for choosing which inconsistent information to discard from the KB to regain consistency; in the case of news syndication, we argue keeping the most trusted information is important for generating the most valuable matches. Thus, in this article, we present algorithms for belief-base revision, and specifically look at the user's trust in the information sources as a metric for deciding what to keep in the KB and what to remove.

Category-based Equational Reasoning: An Approach to Ontology Integration

Geldart, J., Song, W. — Mon, 21 Sep 2009 08:00:31 PDT

Incorporating dynamic, general computational knowledge into Semantic Web ontologies is becoming increasingly important. The Semantic Web is now being used to model the behaviour of highly dynamic domains such as web-services, but current approaches to ontologies [such as Web Ontology Language (OWL)] are static and crisp. This article develops a new semantics for Resource Description Framework (RDF) based upon ideas from category theory. In so doing, we not only decouple RDF's semantics from crisp set theory, opening the door to easy adoption of models of uncertainty, but also allow the use of equational reasoning in a principled fashion within RDF. We demonstrate the abilities of equational reasoning, whilst explaining its semantic principles in terms of our RDF category, using an example from the domain of genealogy. We further develop an algebra of (equational) ontologies which allows us to express fine relations between ontologies and to build more complex ontologies out of simpler ones.

Reasoning Support for Mapping Revision

Meilicke, C., Stuckenschmidt, H., Tamilin, A. — Mon, 21 Sep 2009 08:00:31 PDT

Finding correct semantic correspondences between heterogeneous ontologies is one of the most challenging problems in the area of semantic web technologies. As manually constructing such mappings is not feasible in realistic scenarios, a number of automatic matching tools have been developed that propose mappings based on general heuristics. As these heuristics often produce incorrect results, a manual revision is inevitable in order to guarantee the quality of generated mappings. Experiences with benchmarking matching systems revealed that the manual revision of mappings is still a very difficult problem because it has to take the semantics of the ontologies as well as interactions between mappings into account. In this article, we propose methods for supporting human experts in the task of revising automatically created mappings. In particular, we present non-standard reasoning methods for detecting and propagating implications of expert decisions on the correctness of a mapping.

A Multi-Agent System for Dynamic Ontologies

Ottens, K., Hernandez, N., Gleizes, M.-P., Aussenac-Gilles, N. — Mon, 21 Sep 2009 08:00:31 PDT

In the article, we present Dynamo (an acronym of DYNAMic Ontologies), a tool based on an adaptive multi-agent system to construct and maintain an ontology from a domain-specific set of texts. The originality of our proposal is that the adaptative multi-agent system is used both to represent the ontology itself and to produce the ontology. This enables us to propose a system building and maintaining dynamically an ontology according to interactions with the user (also called the ontologist). We present our system and the mechanisms used to build and maintain the ontology from the texts and for the interactions with the ontologist. We also give results of the evaluation of our system.

Multimedia Interpretation for Dynamic Ontology Evolution

Mon, 21 Sep 2009 08:00:31 PDT

The recent success of distributed and dynamic infrastructures for knowledge sharing has raised the need for semiautomatic/automatic ontology evolution strategies. Ontology evolution is generally defined as the timely adaptation of an ontology to changing requirements and the consistent propagation of changes to dependent artifacts. In this article, we present an ontology evolution approach in the context of multimedia interpretation. Ontology evolution in this context relies on the results obtained through reasoning for the interpretation of multimedia resources, through population of the ontology with new individuals or through enrichment of the ontology with new concepts and new semantic relations. The article analyses the results of interpretation, population and enrichment obtained in evaluation experiments in terms of measures such as precision and recall. The evaluation reveals encouraging results.