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A Corpus-Based Sentence Classifier for Entity–Relationship Modelling
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In: Electronics; Volume 11; Issue 6; Pages: 889 (2022)
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Multi-National Topics Maps for Parliamentary Debate Analysis
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Which data do elementary school teachers use to determine reading difficulties in their students?
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In: Journal of learning disabilities 54 (2021) 5, S. 349-364 (2021)
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Which data do elementary school teachers use to determine reading difficulties in their students? ...
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Finetuning Pretrained Transformers into Variational Autoencoders ...
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Temporal social network reconstruction using wireless proximity sensors: model selection and consequences
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In: ISSN: 2193-1127 ; EISSN: 2193-1127 ; EPJ Data Science ; https://hal.inria.fr/hal-03117988 ; EPJ Data Science, EDP Sciences, 2020, 9 (1), ⟨10.1140/epjds/s13688-020-00237-8⟩ (2020)
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Inscriptions, Hieroglyphs, Linguistics… and Beyond! The Corpus of Classic Mayan as an Ontological Information Resource ...
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Inscriptions, Hieroglyphs, Linguistics… and Beyond! The Corpus of Classic Mayan as an Ontological Information Resource ...
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Using Bidirectional Encoder Representations from Transformers for Conversational Machine Comprehension ; Användning av BERT-språkmodell för konversationsförståelse
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Semantic modelling and publishing of traditional data collection questionnaires and answers
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In: Abgaz, Yalemisew orcid:0000-0002-3887-5342 , Dorn, Amelie, Piringer, Barbara orcid:0000-0001-9983-1362 , Wandl-Vogt, Eveline orcid:0000-0002-0802-0255 and Way, Andy orcid:0000-0001-5736-5930 (2018) Semantic modelling and publishing of traditional data collection questionnaires and answers. Information, 9 (12). pp. 1-24. ISSN 2078-2489 (2018)
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Unlocking cultural conceptualisation in indigenous language resources: collaborative computing methodologies
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In: Dorn, Amelie, Wandl-Vogt, Eveline orcid:0000-0002-0802-0255 , Abgaz, Yalemisew orcid:0000-0002-3887-5342 , Benito Santos, Alejandro orcid:0000-0001-5317-6390 and Therón, Roberto orcid:0000-0001-6739-8875 (2018) Unlocking cultural conceptualisation in indigenous language resources: collaborative computing methodologies. In: 11th Language Resources and Evaluation Conference, 7-12 May 2018, Miyazaki, Japan. ISBN 979-10-95546-22-1 (2018)
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Abstract:
The world’s indigenous languages and related cultural knowledge are under considerable threat of diminishing given the increasing expansion of the use of standard languages, particularly through the wide-ranging pervasion of digital media and machine readable editions of electronic resources. There is thus a pressing need to preserve and breathe life into traditional data resources containing both valuable linguistic and cultural knowledge. In this paper we demonstrate on the example of an Austrian non-standard language resource (DBÖ/dbo@ema), how the combined application of semantic modelling of cultural concepts and visual exploration tools are key in unlocking the indigenous knowledge system, traditional world views and valuable cultural content contained within this rich resource. The original data collection questionnaires serve as a pilot case study and initial access point to the entire collection. Set within a Digital Humanities context, the collaborative methodological approach described here acts as a demonstrator for opening up traditional/nonstandard language resources for cultural content exploration through computing, ultimately giving access to, re-circulating and preserving otherwise lost immaterial cultural heritage.
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Keyword:
Computational linguistics; cultural conceptualisation; data visualisation; indigenous languages; semantic data modelling
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URL: http://doras.dcu.ie/23189/
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Semantic Modelling and Publishing of Traditional Data Collection Questionnaires and Answers
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In: Information ; Volume 9 ; Issue 12 (2018)
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Semantic Referencing - Determining Context Weights for Similarity Measurement
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Research of the concession from a contrastive perspective French - Vietnamese from oral corpora ; Etude de la concession dans une perspective contrastive français - vietnamien à partir de corpus oraux
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In: https://tel.archives-ouvertes.fr/tel-01526984 ; Linguistique. Université d'Orléans, 2016. Français. ⟨NNT : 2016ORLE1152⟩ (2016)
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