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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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Abstract:
International audience ; The emerging technologies of wearable wireless devices open entirely new ways to record various aspects of human social interactions in a broad range of settings. Such technologies allow to log the temporal dynamics of face-to-face interactions by detecting the physical proximity of participants. However, despite the wide usage of this technology and the collected datasets, precise reconstruction methods transforming the raw recorded communication data packets to social interactions are still missing.In this study we analyse a proximity dataset collected during a longitudinal social experiment aiming to understand the co-evolution of children’s language development and social network. Physical proximity and verbal communication of hundreds of pre-school children and their teachers are recorded over three years using autonomous wearable low power wireless devices. The dataset is accompanied with three annotated ground truth datasets, which record the time, distance, relative orientation, and interaction state of interacting children for validation purposes.We use this dataset to explore several pipelines of dynamical event reconstruction including earlier applied naïve approaches, methods based on Hidden Markov Model, or on Long Short-Term Memory models, some of them combined with supervised pre-classification of interaction packets. We find that while naïve models propose the worst reconstruction, Long Short-Term Memory models provide the most precise way to reconstruct real interactions up to∼90% accuracy. Finally, we simulate information spreading on the reconstructed networks obtained by the different methods. Results indicate that small improvement of network reconstruction accuracy may lead to significantly different spreading dynamics, while sometimes large differences inaccuracy have no obvious effects on the dynamics. This not only demonstrates the importance of precise network reconstruction but also the careful choice of the reconstruction method in relation with the data collected. Missing this initial step in any study may seriously mislead conclusions made about the emerging properties of the observed network or any dynamical process simulated on it.
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Keyword:
[INFO.INFO-SI]Computer Science [cs]/Social and Information Networks [cs.SI]; Data driven modelling of spreading processes; Physical proximity networks; Supervised learning; Temporal network reconstruction
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URL: https://doi.org/10.1140/epjds/s13688-020-00237-8 https://hal.inria.fr/hal-03117988
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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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