5,740 research outputs found

    A Novel Approach to Multimedia Ontology Engineering for Automated Reasoning over Audiovisual LOD Datasets

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    Multimedia reasoning, which is suitable for, among others, multimedia content analysis and high-level video scene interpretation, relies on the formal and comprehensive conceptualization of the represented knowledge domain. However, most multimedia ontologies are not exhaustive in terms of role definitions, and do not incorporate complex role inclusions and role interdependencies. In fact, most multimedia ontologies do not have a role box at all, and implement only a basic subset of the available logical constructors. Consequently, their application in multimedia reasoning is limited. To address the above issues, VidOnt, the very first multimedia ontology with SROIQ(D) expressivity and a DL-safe ruleset has been introduced for next-generation multimedia reasoning. In contrast to the common practice, the formal grounding has been set in one of the most expressive description logics, and the ontology validated with industry-leading reasoners, namely HermiT and FaCT++. This paper also presents best practices for developing multimedia ontologies, based on my ontology engineering approach

    HILT : High-Level Thesaurus Project. Phase IV and Embedding Project Extension : Final Report

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    Ensuring that Higher Education (HE) and Further Education (FE) users of the JISC IE can find appropriate learning, research and information resources by subject search and browse in an environment where most national and institutional service providers - usually for very good local reasons - use different subject schemes to describe their resources is a major challenge facing the JISC domain (and, indeed, other domains beyond JISC). Encouraging the use of standard terminologies in some services (institutional repositories, for example) is a related challenge. Under the auspices of the HILT project, JISC has been investigating mechanisms to assist the community with this problem through a JISC Shared Infrastructure Service that would help optimise the value obtained from expenditure on content and services by facilitating subject-search-based resource sharing to benefit users in the learning and research communities. The project has been through a number of phases, with work from earlier phases reported, both in published work elsewhere, and in project reports (see the project website: http://hilt.cdlr.strath.ac.uk/). HILT Phase IV had two elements - the core project, whose focus was 'to research, investigate and develop pilot solutions for problems pertaining to cross-searching multi-subject scheme information environments, as well as providing a variety of other terminological searching aids', and a short extension to encompass the pilot embedding of routines to interact with HILT M2M services in the user interfaces of various information services serving the JISC community. Both elements contributed to the developments summarised in this report

    OntoMathPROOntoMath^{PRO} Ontology: A Linked Data Hub for Mathematics

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    In this paper, we present an ontology of mathematical knowledge concepts that covers a wide range of the fields of mathematics and introduces a balanced representation between comprehensive and sensible models. We demonstrate the applications of this representation in information extraction, semantic search, and education. We argue that the ontology can be a core of future integration of math-aware data sets in the Web of Data and, therefore, provide mappings onto relevant datasets, such as DBpedia and ScienceWISE.Comment: 15 pages, 6 images, 1 table, Knowledge Engineering and the Semantic Web - 5th International Conferenc

    A Survey of Volunteered Open Geo-Knowledge Bases in the Semantic Web

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    Over the past decade, rapid advances in web technologies, coupled with innovative models of spatial data collection and consumption, have generated a robust growth in geo-referenced information, resulting in spatial information overload. Increasing 'geographic intelligence' in traditional text-based information retrieval has become a prominent approach to respond to this issue and to fulfill users' spatial information needs. Numerous efforts in the Semantic Geospatial Web, Volunteered Geographic Information (VGI), and the Linking Open Data initiative have converged in a constellation of open knowledge bases, freely available online. In this article, we survey these open knowledge bases, focusing on their geospatial dimension. Particular attention is devoted to the crucial issue of the quality of geo-knowledge bases, as well as of crowdsourced data. A new knowledge base, the OpenStreetMap Semantic Network, is outlined as our contribution to this area. Research directions in information integration and Geographic Information Retrieval (GIR) are then reviewed, with a critical discussion of their current limitations and future prospects

    National Center for Biomedical Ontology: Advancing biomedicine through structured organization of scientific knowledge

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    The National Center for Biomedical Ontology is a consortium that comprises leading informaticians, biologists, clinicians, and ontologists, funded by the National Institutes of Health (NIH) Roadmap, to develop innovative technology and methods that allow scientists to record, manage, and disseminate biomedical information and knowledge in machine-processable form. The goals of the Center are (1) to help unify the divergent and isolated efforts in ontology development by promoting high quality open-source, standards-based tools to create, manage, and use ontologies, (2) to create new software tools so that scientists can use ontologies to annotate and analyze biomedical data, (3) to provide a national resource for the ongoing evaluation, integration, and evolution of biomedical ontologies and associated tools and theories in the context of driving biomedical projects (DBPs), and (4) to disseminate the tools and resources of the Center and to identify, evaluate, and communicate best practices of ontology development to the biomedical community. Through the research activities within the Center, collaborations with the DBPs, and interactions with the biomedical community, our goal is to help scientists to work more effectively in the e-science paradigm, enhancing experiment design, experiment execution, data analysis, information synthesis, hypothesis generation and testing, and understand human disease

    Multimedia Information Retrieval nelle biblioteche

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    The paper aims to introduce libraries to the view that operating within the terms of traditional Information Retrieval (IR), only through textual language, is limitative, and that considering broader criteria, as those of Multimedia Information Retrieval (MIR), is necessary. The paper stresses the story of MIR fundamental principles, from early years of questioning on documentation to today’s theories on semantic means. New issues for a LIS methodology of processing and searching multimedia documents are theoretically argued, introducing MIR as a holistic whole composed by content-based and semantic information retrieval methodologies. MIR offers a better information searching way: every kind of digital document can be analyzed and retrieved through the elements of language appropriate to its own nature. MIR approach directly handles the concrete content of documents, also considering semantic aspects. Paper conclusions remark the organic integration of the revolutionary contentual conception of information processing with an improved semantics conception, gathering and composing advantages of both systems for accessing to information.L'articolo vuole introdurre le biblioteche alla prospettiva che operare entro i termini dell'Information Retrieval (IR) tradizionale mediante il solo uso del linguaggio testuale è limitativo, e che prendere in considerazione i criteri più ampi del Multimedia Information Retrieval (MIR) è invece necessario. L'articolo illustra la storia dei principi fondamentali del MIR, a partire dai primi anni di dibattito sulla documentazione fino alle teorie odierne sui significati semantici. Vengono dibattute nuovi argomentazioni teoriche per una metodologia LIS di trattamento e ricerca di documenti multimediali, proponendo il MIR come un tutto olistico composto da metolodogie di information retrieval semantico e basato sul contenuto. Il MIR offre modalità di ricerca migliori: ogni tipologia di documento digitale può essere analizzata e recuperata attraverso elementi del linguaggio appropriato alla sua specifica natura. L'approccio del MIR si basa sulla gestione diretta del contenuto dei documenti, considerando anche gli aspetti semantici. Le conclusioni dell'articolo rimarcano l'integrazione organica della rivoluzione della concezione di tipo contenutistico del trattamento dell'informazione con una concezione semantica migliorata, raccogliendo e componendo i vantaggi di entrambi i sistemi per l'accesso all'informazione
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