3 resultados para vocabularies

em Aston University Research Archive


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Textbooks are an integral part of structured syllabus coverage in higher education. The argument advanced in this article is that textbooks are not simply products of inscription and embodied scholarly labour for pedagogical purposes, but embedded institutional artefacts that configure entire academic subject fields. Empirically, this article shows the various ways that motives of the (non-) adoption of textbooks have field institutional configuration effects. The research contribution of our study is threefold. First, we re-theorise the textbook as an artefact that is part of the institutional work and epistemic culture of academia. Second, we empirically show that the vocabularies of motive of textbook (non-) adoption and rhetorical strategies form the basis for social action and configuration across micro, meso and macro field levels. Our final contribution is a conceptualization of the ways that textbook (non-) adoption motives ascribe meaning to the legitimating processes in the configuration of whole subject fields.

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The growing use of a variety of information systems in crisis management both by non-governmental organizations (NGOs) and emergency management agencies makes the challenges of information sharing and interoperability increasingly important. The use of semantic web technologies is a growing area and is a technology stack specifically suited to these challenges. This paper presents a review of ontologies, vocabularies and taxonomies that are useful in crisis management systems. We identify the different subject areas relevant to crisis management based on a review of the literature. The different ontologies and vocabularies available are analysed in terms of their coverage, design and usability. We also consider the use cases for which they were designed and the degree to which they follow a variety of standards. While providing comprehensive ontologies for the crisis domain is not feasible or desirable there is considerable scope to develop ontologies for the subject areas not currently covered and for the purposes of interoperability.

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Social media has become an effective channel for communicating both trends and public opinion on current events. However the automatic topic classification of social media content pose various challenges. Topic classification is a common technique used for automatically capturing themes that emerge from social media streams. However, such techniques are sensitive to the evolution of topics when new event-dependent vocabularies start to emerge (e.g., Crimea becoming relevant to War Conflict during the Ukraine crisis in 2014). Therefore, traditional supervised classification methods which rely on labelled data could rapidly become outdated. In this paper we propose a novel transfer learning approach to address the classification task of new data when the only available labelled data belong to a previous epoch. This approach relies on the incorporation of knowledge from DBpedia graphs. Our findings show promising results in understanding how features age, and how semantic features can support the evolution of topic classifiers.