39,434 research outputs found

    Grouping axioms for more coherent ontology descriptions

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    Ontologies and datasets for the Semantic Web are encoded in OWL formalisms that are not easily comprehended by people. To make ontologies accessible to human domain experts, several research groups have developed ontology verbalisers using Natural Language Generation. In practice ontologies are usually composed of simple axioms, so that realising them separately is relatively easy; there remains however the problem of producing texts that are coherent and efficient. We describe in this paper some methods for producing sentences that aggregate over sets of axioms that share the same logical structure. Because these methods are based on logical structure rather than domain-specific concepts or language-specific syntax, they are generic both as regards domain and language

    Towards owl ontologies from relational databases: An HTML-form driven approach

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    The use of ontologies and ontology languages like OWL has attracted much attention, mainly in the Semantic Web research field. In this paper we focus on the problem of automating the generation of domain ontologies, at least partially, by applying reverse engineering technique. We present the complete details of the process of semi-automatically creating an OWL ontology that corresponds to the content of a relational database based on the analysis of its related HTML-forms. The main reason for this construction is to make the relational database information that is available on the Web machine-processable and reduce the time consuming task of ontology creation. Copyright Ā© 2007 by the International Society for Computers and Their Applications (ISCA)

    A review of the state of the art in Machine Learning on the Semantic Web: Technical Report CSTR-05-003

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    Transitioning Applications to Semantic Web Services: An Automated Formal Approach

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    Semantic Web Services have been recognized as a promising technology that exhibits huge commercial potential, and attract significant attention from both industry and the research community. Despite expectations being high, the industrial take-up of Semantic Web Service technologies has been slower than expected. One of the main reasons is that many systems have been developed without considering the potential of the web in integrating services and sharing resources. Without a systematic methodology and proper tool support, the migration from legacy systems to Semantic Web Service-based systems can be a very tedious and expensive process, which carries a definite risk of failure. There is an urgent need to provide strategies which allow the migration of legacy systems to Semantic Web Services platforms, and also tools to support such a strategy. In this paper we propose a methodology for transitioning these applications to Semantic Web Services by taking the advantage of rigorous mathematical methods. Our methodology allows users to migrate their applications to Semantic Web Services platform automatically or semi-automatically

    Ontology-based domain modelling for consistent content change management

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    Ontology-based modelling of multi-formatted software application content is a challenging area in content management. When the number of software content unit is huge and in continuous process of change, content change management is important. The management of content in this context requires targeted access and manipulation methods. We present a novel approach to deal with model-driven content-centric information systems and access to their content. At the core of our approach is an ontology-based semantic annotation technique for diversely formatted content that can improve the accuracy of access and systems evolution. Domain ontologies represent domain-specific concepts and conform to metamodels. Different ontologies - from application domain ontologies to software ontologies - capture and model the different properties and perspectives on a software content unit. Interdependencies between domain ontologies, the artifacts and the content are captured through a trace model. The annotation traces are formalised and a graph-based system is selected for the representation of the annotation traces

    Pragmatic Ontology Evolution: Reconciling User Requirements and Application Performance

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    Increasingly, organizations are adopting ontologies to describe their large catalogues of items. These ontologies need to evolve regularly in response to changes in the domain and the emergence of new requirements. An important step of this process is the selection of candidate concepts to include in the new version of the ontology. This operation needs to take into account a variety of factors and in particular reconcile user requirements and application performance. Current ontology evolution methods focus either on ranking concepts according to their relevance or on preserving compatibility with existing applications. However, they do not take in consideration the impact of the ontology evolution process on the performance of computational tasks ā€“ e.g., in this work we focus on instance tagging, similarity computation, generation of recommendations, and data clustering. In this paper, we propose the Pragmatic Ontology Evolution (POE) framework, a novel approach for selecting from a group of candidates a set of concepts able to produce a new version of a given ontology that i) is consistent with the a set of user requirements (e.g., max number of concepts in the ontology), ii) is parametrised with respect to a number of dimensions (e.g., topological considerations), and iii) effectively supports relevant computational tasks. Our approach also supports users in navigating the space of possible solutions by showing how certain choices, such as limiting the number of concepts or privileging trendy concepts rather than historical ones, would reflect on the application performance. An evaluation of POE on the real-world scenario of the evolving Springer Nature taxonomy for editorial classification yielded excellent results, demonstrating a significant improvement over alternative approaches

    Generating adaptive hypertext content from the semantic web

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    Accessing and extracting knowledge from online documents is crucial for therealisation of the Semantic Web and the provision of advanced knowledge services. The Artequakt project is an ongoing investigation tackling these issues to facilitate the creation of tailored biographies from information harvested from the web. In this paper we will present the methods we currently use to model, consolidate and store knowledge extracted from the web so that it can be re-purposed as adaptive content. We look at how Semantic Web technology could be used within this process and also how such techniques might be used to provide content to be published via the Semantic Web
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