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2. Processing the structure of documents: Logical Layout Analysis of historical newspapers in French

Author

Nicolas Gutehrlé and Iana Atanassova

Subjects
computer science - computation and language, History of scholarship and learning. The humanities, AZ20-999, Bibliography. Library science. Information resources
Abstract

Background. In recent years, libraries and archives led important digitisation campaigns that opened the access to vast collections of historical documents. While such documents are often available as XML ALTO documents, they lack information about their logical structure. In this paper, we address the problem of Logical Layout Analysis applied to historical documents in French. We propose a rule-based method, that we evaluate and compare with two Machine-Learning models, namely RIPPER and Gradient Boosting. Our data set contains French newspapers, periodicals and magazines, published in the first half of the twentieth century in the Franche-Comt\'e Region. Results. Our rule-based system outperforms the two other models in nearly all evaluations. It has especially better Recall results, indicating that our system covers more types of every logical label than the other two models. When comparing RIPPER with Gradient Boosting, we can observe that Gradient Boosting has better Precision scores but RIPPER has better Recall scores. Conclusions. The evaluation shows that our system outperforms the two Machine Learning models, and provides significantly higher Recall. It also confirms that our system can be used to produce annotated data sets that are large enough to envisage Machine Learning or Deep Learning approaches for the task of Logical Layout Analysis. Combining rules and Machine Learning models into hybrid systems could potentially provide even better performances. Furthermore, as the layout in historical documents evolves rapidly, one possible solution to overcome this problem would be to apply Rule Learning algorithms to bootstrap rule sets adapted to different publication periods.

Published
2022
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7. Report on the Collab-a-Thon at ECIR 2024.

Author

Sean MacAvaney, Adam Roegiest, Aldo Lipani, Andrew Parry, Björn Engelmann 0002, Christin Katharina Kreutz, Chuan Meng, Erlend Frayling, Eugene Yang, Ferdinand Schlatt, Guglielmo Faggioli, Harrisen Scells, Iana Atanassova, Jana Friese, Janek Bevendorff, Javier Sanz-Cruzado, Johanne Trippas, Kanaad Pathak, Kaustubh D. Dhole, Leif Azzopardi, Maik Fröbe, Marc Bertin, Nishchal Prasad, Saber Zerhoudi, Shuai Wang 0032, Shubham Chatterjee, Thomas Jänich, Udo Kruschwitz, Xi Wang 0012, and Zijun Long

Published
2024
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40. Preprint citation practice in PLOS

Author

Marc Bertin and Iana Atanassova

Subjects
General Social Sciences, Library and Information Sciences, Computer Science Applications
Abstract

The role of preprints in the scientific production and their part in citations have been growing over the past 10 years. In this paper we study preprint citations in several different aspects: the progression of preprint citations over time, their relative frequencies in relation to the IMRaD structure of articles, their distributions over time, per preprint database and per PLOS journal. We have processed the PLOS corpus that covers 7 journals and a total of about 240,000 articles up to January 2021, and produced a dataset of 8460 preprint citation contexts that cite 12 different preprint databases. Our results show that preprint citations are found with the highest frequency in the Method section of articles, though small variations exist with respect to journals. The PLOS Computational Biology journal stands out as it contains more than three times more preprint citations than any other PLOS journal. The relative parts of the different preprint databases are also examined. While ArXiv and bioRxiv are the most frequent citation sources, bioRxiv’s disciplinary nature can be observed as it is the source of more than 70% of preprint citations in PLOS Biology, PLOS Genetics and PLOS Pathogens. We have also compared the lexical content of preprint citation contexts to the citation content to peer-reviewed publications. Finally, by performing a lexicometric analysis, we have shown that preprint citation contexts differ significantly from citation contexts of peer-reviewed publications. This confirms that authors make use of different lexical content when citing preprints compared to the rest of citations.

Published
2021

44. The context of multiple in-text references and their signification

Author

Iana Atanassova, Marc Bertin, Laboratoire d'Etudes et de Recherches Appliquées en Sciences Sociales (LERASS), Université Paul-Valéry - Montpellier 3 (UPVM)-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Centre de recherches interdisciplinaires et transculturelles - UFC (EA 3224) (CRIT), Université de Franche-Comté (UFC), and Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC)

Subjects
Structure (mathematical logic), Information retrieval, POS tagging, Point (typography), Computer science, 05 social sciences, Section (typography), Context (language use), Library and Information Sciences, 050905 science studies, Linguistics, Article, [INFO.INFO-TT]Computer Science [cs]/Document and Text Processing, IMRaD structure, Citation analysis, In-text references, Bibliometrics, Noun, Rhetorical question, Multiple in-text references, 0509 other social sciences, 050904 information & library sciences, IMRAD, ComputingMilieux_MISCELLANEOUS, Content citation analysis
Abstract

In this paper, we consider sentences that contain multiple in-text references (MIR) and their position in the rhetorical structure of articles. We carry out the analysis of MIR in a large-scale dataset of about 80,000 research articles published by the Public Library of Science in 7 journals. We analyze two major characteristics of MIR: their positions in the IMRaD structure of articles and the number of in-text references that make up a MIR in the different journals. We show that MIR are rather frequent in all sections of the rhetorical structure. In the Introduction section, sentences containing MIR account for more than half of the sentences with references. We examine the syntactic patterns that are most used in the contexts of both multiple and single in-text references and show that they are composed, for the most part, of noun groups. We point out the specificity of the Methods section in this respect.

Published
2017
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45. Concevoir un dispositif innovant pour professionaliser la formation au référencement web: le projet SEO-ELP

Author

Jean-Claude SAGOT, Sylvain Sagot, Iana Atanassova, Edition, Littératures, Langages, Informatique, Arts, Didactique, Discours - UFC (EA 4661) (ELLIADD), Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC), Centre de recherches interdisciplinaires et transculturelles - UFC (EA 3224) (CRIT), Edition, Littératures, Langages, Informatique, Arts, Didactique, Discours - UFC (UR 4661) (ELLIADD), and Centre de recherches interdisciplinaires et transculturelles - UFC (UR 3224) (CRIT)

Subjects
[SHS.INFO]Humanities and Social Sciences/Library and information sciences, [SCCO.COMP]Cognitive science/Computer science, [SCCO.LING]Cognitive science/Linguistics, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], [INFO.INFO-TT]Computer Science [cs]/Document and Text Processing, [INFO.INFO-FL]Computer Science [cs]/Formal Languages and Automata Theory [cs.FL], [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], [INFO.INFO-CY]Computer Science [cs]/Computers and Society [cs.CY], [INFO.INFO-IT]Computer Science [cs]/Information Theory [cs.IT], [INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR], [INFO.INFO-DL]Computer Science [cs]/Digital Libraries [cs.DL], [INFO.EIAH]Computer Science [cs]/Technology for Human Learning, [INFO.INFO-HC]Computer Science [cs]/Human-Computer Interaction [cs.HC], [SHS.LANGUE]Humanities and Social Sciences/Linguistics, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2020

46. Analyse morphosyntaxique de l'arabe par une approche linguisitique

Author

Youcef Ihab Morsi, Iana Atanassova, Centre de recherches interdisciplinaires et transculturelles - UFC (EA 3224) (CRIT), Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC), Atanassova, Iana, and Centre de recherches interdisciplinaires et transculturelles - UFC (UR 3224) (CRIT)

Subjects
[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], [SHS.INFO]Humanities and Social Sciences/Library and information sciences, [INFO.INFO-TT] Computer Science [cs]/Document and Text Processing, [SCCO.COMP]Cognitive science/Computer science, [SHS.INFO] Humanities and Social Sciences/Library and information sciences, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], [INFO.EIAH] Computer Science [cs]/Technology for Human Learning, [INFO.INFO-FL]Computer Science [cs]/Formal Languages and Automata Theory [cs.FL], [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], [INFO.INFO-CY]Computer Science [cs]/Computers and Society [cs.CY], [SCCO.COMP] Cognitive science/Computer science, [INFO.INFO-DL]Computer Science [cs]/Digital Libraries [cs.DL], [INFO.INFO-HC]Computer Science [cs]/Human-Computer Interaction [cs.HC], [SHS.LANGUE]Humanities and Social Sciences/Linguistics, ComputingMilieux_MISCELLANEOUS, [INFO.INFO-FL] Computer Science [cs]/Formal Languages and Automata Theory [cs.FL], [INFO.INFO-LG] Computer Science [cs]/Machine Learning [cs.LG], [SCCO.LING]Cognitive science/Linguistics, [SHS.LANGUE] Humanities and Social Sciences/Linguistics, [INFO.INFO-TT]Computer Science [cs]/Document and Text Processing, [INFO.INFO-CY] Computer Science [cs]/Computers and Society [cs.CY], [INFO.INFO-IT]Computer Science [cs]/Information Theory [cs.IT], [INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR], [INFO.EIAH]Computer Science [cs]/Technology for Human Learning, [INFO.INFO-IT] Computer Science [cs]/Information Theory [cs.IT], [INFO.INFO-IR] Computer Science [cs]/Information Retrieval [cs.IR], [INFO.INFO-DL] Computer Science [cs]/Digital Libraries [cs.DL], [SCCO.LING] Cognitive science/Linguistics, [INFO.INFO-HC] Computer Science [cs]/Human-Computer Interaction [cs.HC]
Abstract

International audience

Published
2019

47. Editorial: Mining Scientific Papers: NLP-enhanced Bibliometrics

Author

Marc Bertin, Iana Atanassova, Philipp Mayr, Centre Interuniversitaire de Rercherche sur la Science et la Technologie (CIRST), Université du Québec à Montréal = University of Québec in Montréal (UQAM), Equipe de recherche de Lyon en sciences de l'information et de la communication (ELICO), Université Lumière - Lyon 2 (UL2)-École nationale supérieure des sciences de l'information et des bibliothèques (ENSSIB), Université de Lyon-Université de Lyon-Sciences Po Lyon - Institut d'études politiques de Lyon (IEP Lyon), Université de Lyon-Université Jean Moulin - Lyon 3 (UJML), Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon, Laboratoire d'Etudes et de Recherches Appliquées en Sciences Sociales (LERASS), Université Paul-Valéry - Montpellier 3 (UPVM)-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Unité Régionale de Formation à l'Information Scientifique et Technique Occitanie (URFIST Occitanie), Université Fédérale Toulouse Midi-Pyrénées, Langues, logiques, informatiques, cognition (LaLIC), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Leibniz-Institute for the Social Sciences [Mannheim] (GESIS ), Université Paul-Valéry - Montpellier 3 (UPVM)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT), Université Paris-Sorbonne (UP4)-Centre National de la Recherche Scientifique (CNRS), and Leibniz-Institute for the Social Sciences [Mannheim] (GESIS)

Subjects
Computer science, [SHS.INFO]Humanities and Social Sciences/Library and information sciences, text mining, Bibliometrics, 050905 science studies, computer.software_genre, scientific papers, scientometrics, [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL], Bibliography. Library science. Information resources, computational linguistics, [SHS.HISPHILSO]Humanities and Social Sciences/History, Philosophy and Sociology of Sciences, natural language processing, [SHS.LANGUE]Humanities and Social Sciences/Linguistics, ComputingMilieux_MISCELLANEOUS, citation content analysis, business.industry, 05 social sciences, Scientometrics, [INFO.INFO-TT]Computer Science [cs]/Document and Text Processing, [INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR], Artificial intelligence, 0509 other social sciences, Computational linguistics, 050904 information & library sciences, business, computer, Natural language processing
Abstract

International audience

Published
2019
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48. INFuture2017 - Integrating ICT in Society

Author

Iana Atanassova, wajdi zaghouani, Bruno Kragić, Kuldar Aas, Hrvoje Stančić, Sanja Seljan, Centre de recherches interdisciplinaires et transculturelles - UFC (EA 3224) (CRIT), Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC), Department of Information and Communication Sciences Faculty of Humanities and Social Sciences, University of Zagreb, Croatia, The Miroslav Krleža Institute of Lexicography Zagreb, Croatia, Iana Atanassova, Wajdi Zaghouani, Bruno Kragić, Kuldar Aas, Hrvoje Stančić, Sanja Seljan, and Centre de recherches interdisciplinaires et transculturelles - UFC (UR 3224) (CRIT)

Subjects
[INFO.INFO-TT]Computer Science [cs]/Document and Text Processing, [SHS.INFO]Humanities and Social Sciences/Library and information sciences, [INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR], [SHS.LANGUE]Humanities and Social Sciences/Linguistics, ComputingMilieux_MISCELLANEOUS, [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]
Abstract

International audience

Published
2017

49. Recommending Scientific Papers: The Role of Citation Contexts

Author

Iana Atanassova, Marc Bertin, Equipe de recherche de Lyon en sciences de l'information et de la communication (ELICO), Sciences Po Lyon - Institut d'études politiques de Lyon (IEP Lyon), Université de Lyon-Université de Lyon-École nationale supérieure des sciences de l'information et des bibliothèques (ENSSIB), Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université Jean Moulin - Lyon 3 (UJML), Université de Lyon-Université Lumière - Lyon 2 (UL2), Centre de recherches interdisciplinaires et transculturelles - UFC (UR 3224) (CRIT), Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC), Université Lumière - Lyon 2 (UL2)-École nationale supérieure des sciences de l'information et des bibliothèques (ENSSIB), Université de Lyon-Université de Lyon-Sciences Po Lyon - Institut d'études politiques de Lyon (IEP Lyon), Université de Lyon, and Centre de recherches interdisciplinaires et transculturelles - UFC (EA 3224) (CRIT)

Subjects
Computer science, [SHS.INFO]Humanities and Social Sciences/Library and information sciences, 05 social sciences, Recommender Systems, 02 engineering and technology, Bibliometrics, Recommender system, Data science, Citation Context Analysis, [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL], [SHS.HISPHILSO]Humanities and Social Sciences/History, Philosophy and Sociology of Sciences, [INFO.INFO-TT]Computer Science [cs]/Document and Text Processing, Context analysis, Information Retrieval, 0202 electrical engineering, electronic engineering, information engineering, Scientific Papers, 020201 artificial intelligence & image processing, Citation context analysis, 0509 other social sciences, [SHS.LANGUE]Humanities and Social Sciences/Linguistics, 050904 information & library sciences, Citation, GeneralLiterature_REFERENCE(e.g.,dictionaries,encyclopedias,glossaries), Natural Language Processing
Abstract

International audience; This paper addresses the problem of building recommender systems for scientific papers based on the linguistic and contextual analysis of citation contexts. We explain the importance of taking into consideration citation contexts and the different methodologies that exist as well as the ways that citations impact recommender systems. We also discuss the limits of using citation contexts to generate recommendations.

Published
2018
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50. Une étude de l'incertitude dans les textes scientifiques : vers la construction d'une ontologie

Author

François-C. Rey, Marc Bertin, Iana Atanassova, Centre de recherches interdisciplinaires et transculturelles - UFC (EA 3224) (CRIT), Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC), Equipe de recherche de Lyon en sciences de l'information et de la communication (ELICO), Université Lumière - Lyon 2 (UL2)-École nationale supérieure des sciences de l'information et des bibliothèques (ENSSIB), Université de Lyon-Université de Lyon-Sciences Po Lyon - Institut d'études politiques de Lyon (IEP Lyon), Université de Lyon-Université Jean Moulin - Lyon 3 (UJML), Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon, Christophe Roche, Centre de recherches interdisciplinaires et transculturelles - UFC (UR 3224) (CRIT), Sciences Po Lyon - Institut d'études politiques de Lyon (IEP Lyon), Université de Lyon-Université de Lyon-École nationale supérieure des sciences de l'information et des bibliothèques (ENSSIB), Université de Lyon-Université Lumière - Lyon 2 (UL2), and Bertin, Marc

Subjects
[INFO.INFO-CL] Computer Science [cs]/Computation and Language [cs.CL], [SHS.INFO]Humanities and Social Sciences/Library and information sciences, [SCCO.LING] Cognitive science/Linguistics, [SCCO.LING]Cognitive science/Linguistics, [SHS.INFO] Humanities and Social Sciences/Library and information sciences, [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]
Abstract

The problem of uncertainty in sciences is related to the discipline, to the object of study and to the methodologies used. However, taking into account scientific uncertainty is essential challenge for society, together with the need of creating tools for the analysis of scientific discourse. The problem that we address in this paper is the definition, typology and undestanding of uncertainty, through an interdisciplinary view. We aim at studying a corpus of scientific papers on climate change in order to construct an ontology of uncertainty in science., L'incertitude en sciences est une problématique de nature disciplinaire, liée à l'objet de l'étude et aux méthodologies mises en œuvre. Cependant, l'enjeu de traiter l'incertitude est essentiel sur le plan sociétal, rappelant la nécessité de disposer d'outils permettant l'analyse du discours scientifique, afin de répondre aux problématiques actuelles. La problématique que nous abordons ici est celle de la compréhension interdisciplinaire et conceptuelle de la notion d'incertitude à travers la constitution et l'étude d'un corpus d'articles scientifiques traitant du changement climatique.

Published
2018

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