Vassilis Spiliopoulos

Mapping Ontologies Elements using Features in a Latent Space

This paper proposes a method for the mapping of ontologies that, in a greater extent than other approaches, discovers and exploits sets of latent features for approximating the intended meaning of ontology elements. This is done by applying the reverse generative process of the Latent Dirichlet Allocation model. Similarity between element pairs is computed by means of the Kullback-Leibler divergence measure. Experimental results show the potential of the method.

Synthesizing Ontology Alignment Methods Using the Max-Sum Algorithm

This paper addresses the problem of synthesizing ontology alignment methods by maximizing the social welfare within a group of interacting agents: Specifically, each agent is responsible for computing mappings concerning a specific ontology element, using a specific alignment method. Each agent interacts with other agents with whom it shares constraints concerning the validity of the mappings it computes. Interacting agents form a bipartite factor graph, composed of variable and function nodes, representing alignment decisions and utilities, respectively. Agents need to reach an agreement to the mapping of the ontology elements consistently to the semantics of specifications with respect to their mapping preferences. Addressing the synthesis problem in such a way allows us to use an extension of the max-sum algorithm to generate near-to-optimal solutions to the alignment of ontologies through local decentralized message passing. We show the potential of such an approach by synthesizing a number of alignment methods, studying their performance in the OAEI benchmark series.

Semantic Web Services and Mobile Agents Integration for Efficient Mobile Services

The requirement for ubiquitous service access in wireless environments presents a great challenge in light of well-known problems like high error rate and frequent disconnections. In order to satisfy this requirement, we propose the integration of two modern service technologies: Web Services and Mobile Agents. This integration allows wireless users to access and invoke semantically enriched Web Services without the need for simultaneous, online presence of the service requestor. Moreover, in order to improve the capabilities of Service registries, we exploit the advantages offered by the Semantic Web framework. Specifically, we use enhanced registries enriched with semantic information that provide semantic matching to service queries and published service descriptions. Finally, we discuss the implementation of the proposed framework and present our performance assessment findings.

AUTOMS-F: A Framework for the Synthesis of Ontology Mapping Methods

Effective information integration is still one of today’s emerging research goals. The explosive growth of heterogeneous information sources makes the task harder and more challenging. Although ontologies promise an effective solution towards information management and coordination, it would be a surprise if two independent parties have constructed the same ontology to manage information for the same domain. Hence, to integrate information effectively, ontology mapping methods are invaluable. This paper presents the AUTOMS-F framework, which aims to facilitate the development of synthesized methods for the efficient and effective automatic mapping of ontologies. AUTOMS-F is highly extendable and customizable, providing facilities for supporting the rapid prototyping of synthesized mapping methods, adapting some well established programming design patterns. The paper presents the AUTOMS mapping method as an evaluated case of AUTOMS-F’s potential.

A Case Based Reasoning Framework for Service Selection and Adaptation in Mobile Networks

Service selection and adaptation is of paramount importance in contemporary mobile networks. Many diverse parameters should be taken into account (e.g., user context, terminal and network capabilities) for the selection of the appropriate service or the required service adaptations. In this paper we propose a framework for service selection and adaptation. A case based reasoning system (CBRS) is used to select the most appropriate service. Services are modelled using formal semantics. The CBRS retrieves the most appropriate service by comparing previous cases with the current service request. This comparison is performed using similarity metrics. We elaborate on the different aspects of the discussed architecture and provide indicative examples to illustrate the versatility of the proposed scheme.