Model-theoretic Approaches to Semantic Integration (Extended Abstract)

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A Logic-based Approach for Recognizing Textual Entailment Supported by Ontological Background Knowledge

We present the architecture and the evaluation of a new system for recognizing textual entailment (RTE). In RTE we want to identify automatically the type of a logical relation between two input texts. In particular, we are interested in proving the existence of an entailment between them. We conceive our system as a modular environment allowing for a high-coverage syntactic and semantic text analysis combined with logical inference. For the syntactic and semantic analysis we combine a deep semantic analysis with a shallow one supported by statistical models in order to increase the quality and the accuracy of results. For RTE we use logical inference of first-order employing model-theoretic techniques and automated reasoning tools. The inference is supported with problem-relevant background knowledge extracted automatically and on demand from external sources like, e.g., WordNet, YAGO, and OpenCyc, or other, more experimental sources with, e.g., manually defined presupposition resolutions, or with axiomatized general and common sense knowledge. The results show that fine-grained and consistent knowledge coming from diverse sources is a necessary condition determining the correctness and traceability of results.Comment: 25 pages, 10 figure

Exploiting Deep Semantics and Compositionality of Natural Language for Human-Robot-Interaction

We develop a natural language interface for human robot interaction that implements reasoning about deep semantics in natural language. To realize the required deep analysis, we employ methods from cognitive linguistics, namely the modular and compositional framework of Embodied Construction Grammar (ECG) [Feldman, 2009]. Using ECG, robots are able to solve fine-grained reference resolution problems and other issues related to deep semantics and compositionality of natural language. This also includes verbal interaction with humans to clarify commands and queries that are too ambiguous to be executed safely. We implement our NLU framework as a ROS package and present proof-of-concept scenarios with different robots, as well as a survey on the state of the art

Ontology-based modelling of architectural styles

The conceptual modelling of software architectures is of central importance for the quality of a software system. A rich modelling language is required to integrate the different aspects of architecture modelling, such as architectural styles, structural and behavioural modelling, into a coherent framework. Architectural styles are often neglected in software architectures. We propose an ontological approach for architectural style modelling based on description logic as an abstract, meta-level modelling instrument. We introduce a framework for style definition and style combination. The application of the ontological framework in the form of an integration into existing architectural description notations is illustrated

A formal foundation for ontology alignment interaction models

Ontology alignment foundations are hard to find in the literature. The abstract nature of the topic and the diverse means of practice makes it difficult to capture it in a universal formal foundation. We argue that such a lack of formality hinders further development and convergence of practices, and in particular, prevents us from achieving greater levels of automation. In this article we present a formal foundation for ontology alignment that is based on interaction models between heterogeneous agents on the Semantic Web. We use the mathematical notion of information flow in a distributed system to ground our three hypotheses of enabling semantic interoperability and we use a motivating example throughout the article: how to progressively align two ontologies of research quality assessment through meaning coordination. We conclude the article with the presentation---in an executable specification language---of such an ontology-alignment interaction model

Modular Composition of Language Features through Extensions of Semantic Language Models

Today, programming or specification languages are often extended in order to customize them for a particular application domain or to refine the language definition. The extension of a semantic model is often at the centre of such an extension. We will present a framework for linking basic and extended models. The example which we are going to use is the RSL concurrency model. The RAISE specification language RSL is a formal wide-spectrum specification language which integrates different features, such as state-basedness, concurrency and modules. The concurrency features of RSL are based on a refinement of a classical denotational model for process algebras. A modification was necessary to integrate state-based features into the basic model in order to meet requirements in the design of RSL. We will investigate this integration, formalising the relationship between the basic model and the adapted version in a rigorous way. The result will be a modular composition of the basic process model and new language features, such as state-based features or input/output. We will show general mechanisms for integration of new features into a language by extending language models in a structured, modular way. In particular, we will concentrate on the preservation of properties of the basic model in these extensions

A conceptual architecture for semantic web services development and deployment

Several extensions of the Web Services Framework (WSF) have been proposed. The combination with Semantic Web technologies introduces a notion of semantics, which can enhance scalability through automation. Service composition to processes is an equally important issue. Ontology technology – the core of the Semantic Web – can be the central building block of an extension endeavour. We present a conceptual architecture for ontology-based Web service development and deployment. The development of service-based software systems within the WSF is gaining increasing importance. We show how ontologies can integrate models, languages, infrastructure, and activities within this architecture to support reuse and composition of semantic Web services