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The manual construction of formal domain conceptualizations (ontologies) is labor-intensive. Ontology learning, by contrast, provides (semi-)automatic ontology generation from input data such as domain text. This thesis proposes a novel approach for learning labels of non-taxonomic ontology relations. It combines corpus-based techniques with reasoning on Semantic Web data. Corpus-based methods apply vector space similarity of verbs co-occurring with labeled and unlabeled relations to calculate relation label suggestions from a set of candidates. A meta ontology in combination with Semantic Web sources such as DBpedia and OpenCyc allows reasoning to improve the suggested labels. An extensive formal evaluation demonstrates the superior accuracy of the presented hybrid approach.
Based --- Combining --- Corpus --- Data --- from --- Learning --- machine learning --- natural language learning --- Ontology --- Reasoning --- relation labeling --- Relations --- Semantic --- Sources --- Techniques --- Wohlgenannt
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The Open Access version of this book, available at https://www.taylorfrancis.com/books/e/9781351049139, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives 4.0 license. This volume offers an exhaustive look at the latest research on metacognition in language learning and teaching. While other works have explored certain notions of metacognition in language learning and teaching, this book, divided into theoretical and empirical chapters, looks at metacognition from a variety of perspectives, including metalinguistic and multilingual awareness, and language learning and teaching in L2 and L3 settings, and explores a range of studies from around the world. This allows the volume to highlight a diverse set of methodological approaches, including blogging, screen recording software, automatic translation programs, language corpora, classroom interventions, and interviews, and subsequently, to demonstrate the value of metacognition research and how insights from such findings can contribute to a greater understanding of language learning and language teaching processes more generally. This innovative collection is an essential resource for students and scholars in language teaching pedagogy, and applied linguistics.
Linda Fisher --- Odd Eriksen --- Ragnar Arntzen --- Hilde Hasselgård --- Eva Thue Vold --- Gro-Anita Myklevold --- Henrik Bøhn --- Yvonne Knospe --- Karen Forbes --- Gerard Doetjes --- Åsta Haukås --- Magne Dypedahl --- Camilla Bjørke --- metalinguistic awareness --- applied linguistics --- language teaching --- language learning --- metacognition --- Ulrike Jessner --- Lawrence Jun Zhang --- Tony Limin Qin --- Phil Hiver --- George E. K. Whitehead
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