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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 3 of 3 1 Sprachpflege und Sprachkritik als gesellschaftliche Aufgaben. - Akten des XIII. Internationalen Germanistenkongresses Shanghai 2015 : Germanistik zwischen Tradition und Innovation ; Band 5 : Sprachpflege und Sprachkritik als gesellschaftliche Aufgaben. - Szurawitzki, Michael (Herausgeber); Li, Yuan (Mitwirkender); Ohm, Udo (Mitwirkender). - Darin enthalten: Wie kann man in der heutigen Zeit der Globalisierung die deutsche Sprache in der Welt (optimal) fördern? Inter- und Transkulturalität bei internationalen Kooperationen im Hochschulbereich: Schwerpunkt Deutsch als Fremdsprache Lernplattformen zum virtuellen Lernen - was bringen sie für Lernen und Lehren und welche Chancen und Möglichkeiten für die internationale Germanistik Bedeutung und Vermittlung des Deutschen für die Fach- und Berufskommunikation weltweit. - Wien : Peter Lang Edition, 2017 BLLDB UB Frankfurt Linguistik Show details 2 Automatic Spatially-aware Fashion Concept Discovery ... Han, Xintong; Wu, Zuxuan; Huang, Phoenix X.. - : arXiv, 2017 BASE Show details 3 Context identification of sentences in related work sections using a conditional random field: towards intelligent digital libraries Angrosh, M. A.; Cranefield, Stephen; Stanger, Nigel. - : ACM, 2017 Abstract: Identification of contexts associated with sentences is becoming increasingly necessary for developing intelligent information retrieval systems. This article describes a supervised learning mechanism employing a conditional random field (CRF) for context identification and sentence classification. Specifically, we focus on sentences in related work sections in research articles. Based on a generic rhetorical pattern, a framework for modelling the sequential flow in these sections is proposed. Adopting a generalization strategy, each of these sentences is transformed into a set of features, which forms our dataset. We distinguish between two kinds of features for each of these sentences viz., citation features and sentence features. While an overall accuracy of 96.51% is achieved by using a combination of both citation and sentence features, the use of sentence features alone yields an accuracy of 93.22%. The results also show F-Scores ranging from 0.99 to 0.90 for various classes indicating the robustness of our application. ; Peer Reviewed Keyword: Citation Classification; Conditional Random Fields; Sentence Classification URL: https://doi.org/10.1145/1816123.1816168 http://hdl.handle.net/10523/7134 BASE Hide details

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