Save up to 99% of your time in mapping validation

Identifying semantic correspondences between different vocabularies has been recognized as a fundamental step towards achieving interoperability. Several manual and automatic techniques have been recently proposed. Fully manual approaches are very precise, but extremely costly. Conversely, automatic approaches tend to fail when domain specific background knowledge is needed. Consequently, they typically require a manual validation step. Yet, when the number of computed correspondences is very large, the validation phase can be very expensive. In order to reduce the problems above, we propose to compute the minimal set of correspondences, that we call the minimal mapping, which are sufficient to compute all the other ones. We show that by concentrating on such correspondences we can save up to 99% of the manual checks required for validation

Argumentation over Ontology Correspondences in MAS

laera2007aInternational audienceIn order to support semantic interoperation in open environments, where agents can dynamically join or leave and no prior assumption can be made on the ontologies to align, the different agents involved need to agree on the semantics of the terms used during the interoperation. Reaching this agreement can only come through some sort of negotiation process. Indeed, agents will differ in the domain ontologies they commit to; and their perception of the world, and hence the choice of vocabulary used to represent concepts. We propose an approach for supporting the creation and exchange of different arguments, that support or reject possible correspondences. Each agent can decide, according to its preferences, whether to accept or refuse a candidate correspondence. The proposed framework considers arguments and propositions that are specific to the matching task and are based on the ontology semantics. This argumentation framework relies on a formal argument manipulation schema and on an encoding of the agents' preferences between particular kinds of arguments

Web Explanations for Semantic Heterogeneity Discovery

Managing semantic heterogeneity is a complex task. One solution involves matching like terms to each other. We view Match as an operator that takes two graph-like structures (e.g.,concept hierarchies or ontologies) and returns a mapping between the nodes of the graphs that correspond semantically to each other. While some state of the art matching systems may produce effective mappings, these mappings may not be intuitively obvious to human users. In order for users to trust the mappings, and thus, use them, they need information about them (e.g.,they need access to the sources that were used to determine semantic correspondences between terms). In this paper we describe how a matching system can explain its answers using the Inference Web (IW) infrastructure thus making the matching process transparent. The proposed solution is based on the assumption that mappings are computed by logical reasoning. There,S-Match a semantic matching system, produces proofs and explanations for mappings it has discovered

Toward Shared Understanding : An Argumentation Based Approach for Communication in Open Multi-Agent Systems

Open distributed computing applications are becoming increasingly commonplace nowadays. In many cases, these applications are composed of multiple autonomous agents, each with its own aims and objectives. In such complex systems, communication between these agents is usually essential for them to perform their task, to coordinate their actions and share their knowledge. However, successful and meaningful communication can only be achieved by a shared understanding of each other's messages. Therefore efficient mechanisms are needed to reach a mutual understanding when exchanging expressions from each other's world model and background knowledge. We believe the de facto mechanisms for achieving this are ontologies, and this is the area explored in this thesis [88]. However, supporting shared understanding mechanisms for open distributed applications is a major research challenge. Specifically, one consequence of a system being open is the heterogeneity of the agents. Agents may have conflicting goals, or may be heterogeneous with respect to their beliefs or their knowledge. Forcing all agents to use a common vocabulary defined in one or more shared ontologies is, thus, an oversimplified solution, particularly when these agents are designed and deployed independently of each other. This thesis proposes a novel approach to overcome vocabulary heterogeneity, where the agents dynamically negotiate the meaning of the terms they use to communicate. While many proposals for aligning two agent ontologies have been presented in the literature as the current standard approaches to resolve heterogeneity, they are lacking when dealing with important features of agents and their environment. Motivated by the hypothesis that ontology alignment approaches should reflect the characteristics of autonomy and rationality that are typical of agents, and should also be tailored to the requirements of an open environment, such as dynamism, we propose a way for agents to define and agree upon the semantics of the terms used at run-time, according to their interests and preferences. Since agents are autonomous and represent different stakeholders, the process by which they come to an agreement will necessarily only come through negotiation. By using argumentation theory, agents generate and exchange different arguments, that support or reject possible mappings between vocabularies, according to their own preferences. Thus, this work provides a concrete instantiation of the meaning negotiation process that we would like agents to achieve, and that may lead to shared understanding. Moreover, in contrast to current ontology alignment approaches, the choice of a mapping is based on two clearly identified elements: (i) the argumentation framework, which is common to all agents, and (ii) the preference relations, which are private to each agent. Despite the large body of work in the area of semantic interoperabiJity, we are not aware of any research in this area that has directly addressed these important requirements for open Multi-Agent Systems as we have done in this thesis. Supplied by The British Library - 'The world's knowledge