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Assessing the impact of OCR noise on multilingual event detection over digitised documents
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In: ISSN: 1432-5012 ; EISSN: 1432-1300 ; International Journal on Digital Libraries ; https://hal.archives-ouvertes.fr/hal-03635985 ; International Journal on Digital Libraries, Springer Verlag, 2022, ⟨10.1007/s00799-022-00325-2⟩ (2022)
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Abstract:
International audience ; Event detection (ED) is a crucial task for natural language processing (NLP) and it involves the identification of instances of specified types of events in text and their classification into event types. The detection of events from digitised documents could enable historians to gather and combine a large amount of information into an integrated whole, a panoramic interpretation of the past. However, the level of degradation of digitised documents and the quality of the optical character recognition (OCR) tools might hinder the performance of an event detection system. While several studies have been performed in detecting events from historical documents, the transcribed documents needed to be hand-validated which implied a great effort of human expertise and manual labor-intensive work. Thus, in this study, we explore the robustness of two different event detection language-independent models to OCR noise, over two datasets that cover different event types and multiple languages. We aim at analysing their ability to mitigate problems caused by the low quality of the digitised documents and we simulate the existence of transcribed data, synthesised from clean annotated text, by injecting synthetic noise. For creating the noisy synthetic data, we chose to utilise four main types of noise that commonly occur after the digitisation process: Character Degradation, Bleed Through, Blur, and Phantom Character. Finally, we conclude that the imbalance of the datasets, the richness of the different annotation styles, and the language characteristics are the most important factors that can influence event detection in digitised documents.
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Keyword:
[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]; [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]; [INFO.INFO-HC]Computer Science [cs]/Human-Computer Interaction [cs.HC]; [INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR]; [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]; [INFO.INFO-TT]Computer Science [cs]/Document and Text Processing; Digitised Documents; Event Detection; Information Extraction
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URL: https://hal.archives-ouvertes.fr/hal-03635985/file/IJDL2022-Assessing%20the%20Impact%20of%20OCR%20Noise%20on%20Multilingual%20Event%20Detection%20over%20Digitised%20Documents.pdf https://doi.org/10.1007/s00799-022-00325-2 https://hal.archives-ouvertes.fr/hal-03635985/document https://hal.archives-ouvertes.fr/hal-03635985
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Introducing the HIPE 2022 Shared Task: Named Entity Recognition and Linking in Multilingual Historical Documents
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In: Advances in Information Retrieval. 44th European Conference on IR Research, ECIR 2022, Stavanger, Norway, April 10–14, 2022, Proceedings, Part II ; https://hal.archives-ouvertes.fr/hal-03635971 ; Matthias Hagen; Suzan Verberne; Craig Macdonald; Christin Seifert; Krisztian Balog; Kjetil Nørvåg; Vinay Setty. Advances in Information Retrieval. 44th European Conference on IR Research, ECIR 2022, Stavanger, Norway, April 10–14, 2022, Proceedings, Part II, 13186, Springer International Publishing, pp.347-354, 2022, Lecture Notes in Computer Science, 978-3-030-99738-0. ⟨10.1007/978-3-030-99739-7_44⟩ (2022)
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Assessing the Impact of OCR Noise on Multilingual Event Detection over Digitised Documents ...
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Event Related Document Retrieval with Multilingual Real World Event Representation ...
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Event Related Document Retrieval with Multilingual Real World Event Representation ...
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Data set for "Token-Level Multilingual Epidemic Dataset for Event Extraction" ...
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Assessing the Impact of OCR Noise on Multilingual Event Detection over Digitised Documents ...
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L3i at SemEval-2022 Task 11: Straightforward Additional Context for Multilingual Named Entity Recognition ...
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Data set for "Token-Level Multilingual Epidemic Dataset for Event Extraction" ...
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L3i at SemEval-2022 Task 11: Straightforward Additional Context for Multilingual Named Entity Recognition ...
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HIPE-2022 Shared Task Named Entity Datasets
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In: http://infoscience.epfl.ch/record/292174 (2022)
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État de l'art du changement sémantique à partir de plongements contextualisés
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In: COnférence en Recherche d'Informations et Applications - CORIA 2021, French Information Retrieval Conference ; https://hal.archives-ouvertes.fr/hal-03320337 ; COnférence en Recherche d'Informations et Applications - CORIA 2021, French Information Retrieval Conference, Apr 2021, Grenoble (virtuel), France (2021)
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L3i_LBPAM at the FinSim-2 task: Learning Financial Semantic Similarities with Siamese Transformers
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In: WWW '21: Companion Proceedings of the Web Conference 2021 ; WWW '21: The Web Conference 2021 ; https://hal.sorbonne-universite.fr/hal-03256324 ; WWW '21: The Web Conference 2021, Apr 2021, Ljubljana (virtual), Slovenia. pp.302-306, ⟨10.1145/3442442.3451384⟩ (2021)
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Atténuer les erreurs de numérisation dans la reconnaissance d'entités nommées pour les documents historiques
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In: Conférence en Recherche d'Informations et Applications (CORIA 2021) ; https://hal.archives-ouvertes.fr/hal-03320332 ; Conférence en Recherche d'Informations et Applications (CORIA 2021), ARIA : Association Francophone de Recherche d’Information (RI) et Applications, Apr 2021, Grenoble (virtuel), France. pp.1 - 7 ; http://coria.asso-aria.org/2021/articles/mini_24/main.pdf (2021)
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Multilingual Epidemic Event Extraction
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In: Towards Open and Trustworthy Digital Societies. 23rd International Conference on Asia-Pacific Digital Libraries, ICADL 2021, Virtual Event, December 1–3, 2021, Proceedings ; https://hal.archives-ouvertes.fr/hal-03480551 ; Hao-Ren Ke; Chei Sian Lee; Kazunari Sugiyama. Towards Open and Trustworthy Digital Societies. 23rd International Conference on Asia-Pacific Digital Libraries, ICADL 2021, Virtual Event, December 1–3, 2021, Proceedings, 13133, Springer, pp.139-156, 2021, Lecture Notes in Computer Science, 978-3-030-91668-8. ⟨10.1007/978-3-030-91669-5_12⟩ (2021)
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Étude comparative de méthodes de classification multilingue appliquées à l'épidémiologie
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In: COnférence en Recherche d'Informations et Applications - CORIA 2021, French Information Retrieval Conference ; https://hal.archives-ouvertes.fr/hal-03320343 ; COnférence en Recherche d'Informations et Applications - CORIA 2021, French Information Retrieval Conference, Apr 2021, Grenoble (virtuel), France (2021)
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