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Between History and Natural Language Processing: Study, Enrichment and Online Publication of French Parliamentary Debates of the Early Third Republic (1881-1899)
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In: ParlaCLARIN III at LREC2022 - Workshop on Creating, Enriching and Using Parliamentary Corpora ; https://hal.archives-ouvertes.fr/hal-03623351 ; ParlaCLARIN III at LREC2022 - Workshop on Creating, Enriching and Using Parliamentary Corpora, Jun 2022, Marseille, France ; https://www.clarin.eu/ParlaCLARIN-III (2022)
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Abstract:
International audience ; We present the AGODA (Analyse sémantique et Graphes relationnels pour l'Ouverture des Débats à l'Assemblée nationale) project, which aims to create a platform for consulting and exploring digitised French parliamentary debates (1881-1940) available in the digital library of the National Library of France. This project brings together historians and NLP specialists: parliamentary debates are indeed an essential source for French history of the contemporary period, but also for linguistics. This project therefore aims to produce a corpus of texts that can be easily exploited with computational methods, and that respect the TEI standard. Ancient parliamentary debates are also an excellent case study for the development and application of tools for publishing and exploring large historical corpora. In this paper, we present the steps necessary to produce such a corpus. We detail the processing and publication chain of these documents, in particular by mentioning the problems linked to the extraction of texts from digitised images. We also introduce the first analyses that we have carried out on this corpus with "bag-of-words" techniques not too sensitive to OCR quality (namely topic modelling and word embedding).
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Keyword:
[INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]; [INFO.INFO-CY]Computer Science [cs]/Computers and Society [cs.CY]; [INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR]; [INFO.INFO-TT]Computer Science [cs]/Document and Text Processing; [SHS.HIST]Humanities and Social Sciences/History; France; OCR; Parliamentary debates; Third Republic; Topic modelling; Word embedding; XML-TEI
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URL: https://hal.archives-ouvertes.fr/hal-03623351/document https://hal.archives-ouvertes.fr/hal-03623351 https://hal.archives-ouvertes.fr/hal-03623351/file/puren_bourgeois_pellet_vernus_agoda2022.pdf
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Chinese-Uyghur Bilingual Lexicon Extraction Based on Weak Supervision
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In: Information; Volume 13; Issue 4; Pages: 175 (2022)
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Investigating the Efficient Use of Word Embedding with Neural-Topic Models for Interpretable Topics from Short Texts
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In: Sensors; Volume 22; Issue 3; Pages: 852 (2022)
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Analysis of the Effects of Lockdown on Staff and Students at Universities in Spain and Colombia Using Natural Language Processing Techniques
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In: International Journal of Environmental Research and Public Health; Volume 19; Issue 9; Pages: 5705 (2022)
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An Enhanced Neural Word Embedding Model for Transfer Learning
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In: Applied Sciences; Volume 12; Issue 6; Pages: 2848 (2022)
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Deep Sentiment Analysis Using CNN-LSTM Architecture of English and Roman Urdu Text Shared in Social Media
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In: Applied Sciences; Volume 12; Issue 5; Pages: 2694 (2022)
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Predicting Academic Performance: Analysis of Students’ Mental Health Condition from Social Media Interactions
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In: Behavioral Sciences; Volume 12; Issue 4; Pages: 87 (2022)
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Vec2Dynamics: A Temporal Word Embedding Approach to Exploring the Dynamics of Scientific Keywords—Machine Learning as a Case Study
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In: Big Data and Cognitive Computing; Volume 6; Issue 1; Pages: 21 (2022)
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Methods, Models and Tools for Improving the Quality of Textual Annotations
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In: Modelling; Volume 3; Issue 2; Pages: 224-242 (2022)
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Creating multi-scripts sentiment analysis lexicons for Algerian, Moroccan and Tunisian dialects
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In: 7th International Conference on Data Mining (DTMN 2021) Computer Science Conference Proceedings in Computer Science & Information Technology (CS & IT) ; https://hal.archives-ouvertes.fr/hal-03308111 ; 7th International Conference on Data Mining (DTMN 2021) Computer Science Conference Proceedings in Computer Science & Information Technology (CS & IT), Sep 2021, Copenhagen, Denmark (2021)
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Bilingual English-German word embedding models for scientific text ...
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Bilingual English-German word embedding models for scientific text ...
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以《Cofacts 真的假的》資料庫為基礎建立中文科學假訊息之探勘模型 ; Text Mining Model for Detecting Chinese Fake Scientific Messages based on Cofacts Open Data
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Automatic Part-of-Speech Tagging for Security Vulnerability Descriptions ...
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Automatic Part-of-Speech Tagging for Security Vulnerability Descriptions ...
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Text ranking based on semantic meaning of sentences ; Textrankning baserad på semantisk betydelse hos meningar
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Efficient Estimate of Low-Frequency Words’ Embeddings Based on the Dictionary: A Case Study on Chinese
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In: Applied Sciences ; Volume 11 ; Issue 22 (2021)
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Acoustic Word Embeddings for End-to-End Speech Synthesis
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In: Applied Sciences ; Volume 11 ; Issue 19 (2021)
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