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Creating Expert Knowledge by Relying on Language Learners: a Generic Approach for Mass-Producing Language Resources by Combining Implicit Crowdsourcing and Language Learning
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In: LREC 2020 - Language Resources and Evaluation Conference ; https://hal.inria.fr/hal-02879883 ; LREC 2020 - Language Resources and Evaluation Conference, May 2020, Marseille, France (2020)
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Substituto - A Synchronous Educational Language Game for Simultaneous Teaching and Crowdsourcing
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In: 9th Workshop on Natural Language Processing for Computer Assisted Language Learning (NLP4CALL 2020) ; https://hal.inria.fr/hal-03114898 ; 9th Workshop on Natural Language Processing for Computer Assisted Language Learning (NLP4CALL 2020), Nov 2020, Gothenburg, Sweden. pp.1-9, ⟨10.3384/ecp201759⟩ ; https://www.aclweb.org/anthology/volumes/2020.nlp4call-1/ (2020)
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The FAIR Index of CMC Corpora
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In: CMC Corpora through the prism of Digital Humanities ; https://hal.archives-ouvertes.fr/hal-03121698 ; CMC Corpora through the prism of Digital Humanities, 2020 (2020)
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TRIPLE Deliverable: D2.2 Data Harvesting Best Practices Document for Data Providers ...
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Bouillard, Maxime; Roi, Arnaud; Bunel, Melanie; Capelli, Laurent; De Santis, Luca; Dumouchel, Suzanne; Geogriadis, Haris; Gingold, Arnaud; Goosen, Twan; König, Alexander; Maryl, Maciej; Pacheco, Andre; Polydoratou, Panayiota; Rohden, Jan; Stojanovski, Jadranka; Umerle, Tomasz. - : Zenodo, 2020
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Abstract:
The TRIPLE project intends to address the challenges of the fragmented and heterogeneous landscape of Social Sciences and Humanities, hereafter SSH, research outputs’ dissemination by providing a single yet flexible architecture able to collect data from many sources. Enabling the data ingestion from different data models, the architecture relies itself on an ontology which ensures a better discoverability for SSH scholarly resources and their connection with projects and profiles. The proposed architecture aims at enabling both a broader collection of data, and a uniform quality level between these through the use of a single data model. In order to do so, the architecture distinguishes two main roles, the TRIPLE’s Aggregator, and the TRIPLE’s Provider. The Aggregator is the contact point between the Provider and TRIPLE, and takes charge of the mapping between its own data and the TRIPLE data model. This architecture thus ensures that the discovery platform will provide a large coverage of existing SSH ... : The Report awaits official approval by the EU Project Officer. --- The TRIPLE project (https://www.gotriple.eu/), which is financed under the Horizon 2020 framework (https://cordis.europa.eu/project/id/863420), under Grant Agreement No. 863420, with approx. 5.6 million Euros for a duration of 42 months (2019-2023). --- At the heart of the project is the development of the TRIPLE platform, an innovative multilingual and multicultural discovery solution. ...
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Keyword:
data harvesting; OPERAS; research infrastructure; social sciences and humanities; SSH; TRIPLE
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URL: https://zenodo.org/record/4438651
https://dx.doi.org/10.5281/zenodo.4438651
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TRIPLE Deliverable: D2.2 Data Harvesting Best Practices Document for Data Providers ...
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The CLARIN ERIC deployment infrastructure and its applicability to reproducible research ...
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The CLARIN ERIC deployment infrastructure and its applicability to reproducible research ...
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Ergänzung und Aktualisierung der Stichworte zur Individualversicherung
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