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3. ECIR 2023 Workshop: Legal Information Retrieval

Author

Kamps, J., Verberne, S., Kanoulas, E., Wiggers, G., Piroi, F., Vries, A.P. de, Kamps, J., Verberne, S., Kanoulas, E., Wiggers, G., Piroi, F., and Vries, A.P. de

Abstract

ECIR 2023, Item does not contain fulltext

Published
2023

6. Overview of SimpleText 2021 - CLEF Workshop on Text Simplification for Scientific Information Access

Author

Ermakova, L., Bellot, P., Braslavski, P., Kamps, J., Mothe, J., Nurbakova, D., Ovchinnikova, I., SanJuan, E., Candan, K.S., Ionescu, B., Goeuriot, L., Larsen, B., Müller, H., Joly, A., Maistro, M., Piroi, F., Faggioli, G., Ferro, N., ILLC (FGw), Language and Computation (ILLC, FNWI/FGw), Université de Brest (UBO), Héritages et Constructions dans le Texte et l'Image (HCTI), Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Institut Brestois des Sciences de l'Homme et de la Société (IBSHS), Laboratoire d'Informatique et Systèmes (LIS), Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS), Ural Federal University [Ekaterinburg] (UrFU), University of Amsterdam [Amsterdam] (UvA), Systèmes d’Informations Généralisées (IRIT-SIG), Institut de recherche en informatique de Toulouse (IRIT), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Toulouse Mind & Brain Institut (TMBI), Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT), Sechenov First Moscow State Medical University, Laboratoire Informatique d'Avignon (LIA), Avignon Université (AU)-Centre d'Enseignement et de Recherche en Informatique - CERI, Distribution, Recherche d'Information et Mobilité (DRIM), Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS), Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL), and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Contextualization, Correctness, Computer science, Text simplification, MULTI DOCUMENTS SUMMARIZATION, Information access, Scientific literature, (Multi-document) summarization, Background knowledge Everything, DOCUMENT RETRIEVAL, Multi-document summarization, SCIENTIFIC TEXTS, Document retrieval, SCIENTIFIC INFORMATION, (MULTI-DOCUMENT) SUMMARIZATION, Data science, CONTEXTUALIZATION, INFORMATION RETRIEVAL, Clef, SCIENTIFIC TEXT SIMPLIFICATION, NATURAL LANGUAGE PROCESSING SYSTEMS, [INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR], BACKGROUND KNOWLEDGE, INFORMATION ACCESS, Scientific text simplification, FULLY INTEGRATED
Abstract

Information retrieval has moved from traditional document retrieval in which search is an isolated activity, to modern information access where search and the use of the information are fully integrated. But non-experts tend to avoid authoritative primary sources such as scientific literature due to their complex language, internal vernacular, or lacking prior background knowledge. Text simplification approaches can remove some of these barriers, thereby avoiding that users rely on shallow information in sources prioritizing commercial or political incentives rather than the correctness and informational value. The CLEF 2021 SimpleText track addresses the opportunities and challenges of text simplification approaches to improve scientific information access head-on. We aim to provide appropriate data and benchmarks, starting with pilot tasks in 2021, and create a community of NLP and IR researchers working together to resolve one of the greatest challenges of today. © 2021, Springer Nature Switzerland AG.

Published
2021
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8. Preface

Author

Candan, K. S., Ionescu, B., Goeuriot, L., Larsen, B., Muller, H., Joly, A., Maistro, M., Piroi, F., Faggioli, G., and Ferro, N.

Published
2021

9. Overview of SimpleText CLEF 2021 workshop and pilot tasks

Author

Ermakova, L., Bellot, P., Braslavski, P., Kamps, J., Mothe, J., Nurbakova, D., Ovchinnikova, I., San-Juan, E., Faggioli, G., Ferro, N., Joly, A., Maistro, M., Piroi, F., ILLC (FGw), and Language and Computation (ILLC, FNWI/FGw)

Abstract

Scientific literacy is important for people to make right decisions, evaluate the information quality, maintain physiological and mental health, avoid spending money on useless items. However, since scientific publications are difficult for people outside the domain and so they do not read them at all even if they are accessible. Text simplification approaches can remove some of these barriers to use scientific information, thereby promoting the use of objective scientific findings and avoiding that users rely on shallow information in sources prioritizing commercial or political incentives rather than the correctness and informational value. The CLEF 2021 SimpleText workshop addresses the opportunities and challenges of text simplification approaches to improve scientific information access head-on. This year, we run three pilot tasks trying to answer the following questions: (1) What information should be simplified? (2) Which terms should be contextualized by giving a definition and/or application? (3) How to improve the readability of a given short text (e.g. by reducing vocabulary and syntactic complexity) without significant information distortion?.

Published
2021

10. Preface

Author

Faggioli, G., Ferro, N., Joly, A., Maistro, M., and Piroi, F.

Published
2021

11. Overview of the CLEF eHealth Evaluation Lab 2021

Author

Candan, KS, Ionescu, B, Goeuriot, L, Larsen, B, Müller, H, Joly, A, Maistro, M, Piroi, F, Faggioli, G, Ferro, N, Suominen, H, Kelly, L, Alemany, L, Bassani, E, Brew-Sam, N, Cotik, V, Filippo, D, González-Sáez, G, Luque, F, Mulhem, P, Pasi, G, Roller, R, Seneviratne, S, Upadhyay, R, Vivaldi, J, Viviani, M, Xu, C, Suominen H., Goeuriot L., Kelly L., Alemany L. A., Bassani E., Brew-Sam N., Cotik V., Filippo D., González-Sáez G., Luque F., Mulhem P., Pasi G., Roller R., Seneviratne S., Upadhyay R., Vivaldi J., Viviani M., Xu C., Candan, KS, Ionescu, B, Goeuriot, L, Larsen, B, Müller, H, Joly, A, Maistro, M, Piroi, F, Faggioli, G, Ferro, N, Suominen, H, Kelly, L, Alemany, L, Bassani, E, Brew-Sam, N, Cotik, V, Filippo, D, González-Sáez, G, Luque, F, Mulhem, P, Pasi, G, Roller, R, Seneviratne, S, Upadhyay, R, Vivaldi, J, Viviani, M, Xu, C, Suominen H., Goeuriot L., Kelly L., Alemany L. A., Bassani E., Brew-Sam N., Cotik V., Filippo D., González-Sáez G., Luque F., Mulhem P., Pasi G., Roller R., Seneviratne S., Upadhyay R., Vivaldi J., Viviani M., and Xu C.

Abstract

In this paper, we provide an overview of the ninth annual edition of the CLEF eHealth evaluation lab. CLEF eHealth 2021 continues our evaluation resource building efforts around the easing and support of patients, their next-of-kins, health care professionals, and health scientists in understanding, accessing, and authoring electronic health information in a multilingual setting. The 2021 lab offered two tasks: Task 1 on multilingual Information Extraction (IE), this year extending to a corpus of Spanish radiology reports; and Task 2 on Consumer Health Search (CHS) that builds on the previous year’s Information Retrieval (IR) tasks. In total, 11 teams took part in these tasks (7 in Task 1 on IE and 4 in Task 2 on IR). Herein, we describe the resources created for these tasks and the evaluation methodology adopted, and we provide a brief summary of the participants of this year’s challenges as well as the results obtained. As in previous years, the organizers have made data, tools, and more specific overview papers associated with the lab tasks available for future research and development.

Published
2021

12. Profiling Hate Speech Spreaders on Twitter task at PAN 2021

Author

Faggioli ì, G, Ferro, N, Piroi, F, Rangel, F, de la Pena Sarracen, G, Chulvi, B, Fersini, E, Rosso, P, Rangel F., de la Pena Sarracen G. L., Chulvi B., Fersini E., Rosso P., Faggioli ì, G, Ferro, N, Piroi, F, Rangel, F, de la Pena Sarracen, G, Chulvi, B, Fersini, E, Rosso, P, Rangel F., de la Pena Sarracen G. L., Chulvi B., Fersini E., and Rosso P.

Abstract

This overview presents the Author Profiling shared task at PAN 2021. The focus of this year's task is on determining whether or not the author of a Twitter feed is keen to spread hate speech. The main aim is to show the feasibility of automatically identifying potential hate speech spreaders on Twitter. For this purpose a corpus with Twitter data has been provided, covering the English and Spanish languages. Altogether, the approaches of 66 participants have been evaluated.

Published
2021

13. Consumer Health Search at CLEF eHealth 2021

Author

Faggioli G, Ferro N, Joly A, Maistro M, Piroi F, Goeuriot, L, Suominen, H, Pasi, G, Bassani, E, Brew-Sam, N, Gonzalez-Saez, G, Kelly, L, Mulhem, P, Seneviratne, S, Upadhyay, R, Viviani, M, Xu, C, Goeuriot L., Suominen H., Pasi G., Bassani E., Brew-Sam N., Gonzalez-Saez G., Kelly L., Mulhem P., Seneviratne S., Upadhyay R., Viviani M., Xu C., Faggioli G, Ferro N, Joly A, Maistro M, Piroi F, Goeuriot, L, Suominen, H, Pasi, G, Bassani, E, Brew-Sam, N, Gonzalez-Saez, G, Kelly, L, Mulhem, P, Seneviratne, S, Upadhyay, R, Viviani, M, Xu, C, Goeuriot L., Suominen H., Pasi G., Bassani E., Brew-Sam N., Gonzalez-Saez G., Kelly L., Mulhem P., Seneviratne S., Upadhyay R., Viviani M., and Xu C.

Abstract

This paper details materials, methods, results, and analyses of the Consumer Health Search Task of the CLEF eHealth 2021 Evaluation Lab. This task investigates the effectiveness of information retrieval (IR) approaches in providing access to medical information to laypeople. For this a TREC-style evaluation methodology was applied: a shared collection of documents and queries is distributed, participants' runs received, relevance assessments generated, and participants' submissions evaluated. The task generated a new representative web corpus including web pages acquired from a 2021 CommonCrawl and social media content from Twitter and Reddit, along with a new collection of 55 manually generated layperson medical queries and their respective credibility, understandability, and topicality assessments for returned documents. This year's task focused on three subtask: (i) ad-hoc IR, (ii) weakly supervised IR, and (iii) document credibility prediction. In total, 15 runs were submitted to the three subtasks: eight addressed the ad-hoc IR task, three the weakly supervised IR challenge, and 4 the document credibility prediction challenge. As in previous years, the organizers have made data and tools associated with the task available for future research and development.

Published
2021

20. PROMISE Retreat Report: Prospects and Opportunities for Information Access Evaluation: Brainstorming workshop held on May 30-31, 2012, Padua, Italy

Author

Ferro, N., Berendsen, R., Hanbury, A., Lupu, M., Petras, V., de Rijke, M., Silvello, G., Agosti, M., Bogers, T., Braschler, M., Buitelaar, P., Choukri, K., Di Nunzio, G.M., Forner, P., Friberg Heppin, K., Hansen, P., Järvelin, A., Larsen, B., Masiero, I., Müller, H., Peruzzo, S., Piroi, F., Santucci, G., Toms, E., and Information and Language Processing Syst (IVI, FNWI)

Abstract

The PROMISE network of excellence organized a two-days brainstorming workshop on 30th and 31st May 2012 in Padua, Italy, to discuss and envisage future directions and perspectives for the evaluation of information access and retrieval systems in multiple languages and multiple media. This document reports on the outcomes of this event and provides details about the six envisaged research lines: search applications; contextual evaluation; challenges in test collection design and exploitation; component-based evaluation; ongoing evaluation; and signal-aware evaluation. The ultimate goal of the PROMISE retreat is to stimulate and involve the research community along these research lines and to provide funding agencies with effective and scientifically sound ideas for coordinating and supporting information access research.

Published
2012

21. PROMISE Retreat Report - Prospects and Opportunities for Information Access

Author

Agosti, Maristella, Berendsen, R., Bogers, T., Braschler, M., Buitelaar, P., Choukri, K., DI NUNZIO, GIORGIO MARIA, Ferro, Nicola, Forner, P., Hanbury, A., Friberg Heppin, K., Hansen, P., Järvelin, A., Larsen, B., Lupu, M., Masiero, Ivano, Müller, H., Peruzzo, Simone, Petras, V., Piroi, F., de Rijke, M., Santucci, G., Silvello, Gianmaria, and Toms, E.

Published
2012

24. Profiling Hate Speech Spreaders on Twitter task at PAN 2021

Author

Rangel F., de la Pena Sarracen G. L., Chulvi B., Fersini E., Rosso P., Faggioli ì, G, Ferro, N, Piroi, F, Rangel, F, de la Pena Sarracen, G, Chulvi, B, Fersini, E, and Rosso, P

Subjects
Artificial intelligence, Natural language processing, Hate speech spreader, Author profiling, Hate speech
Abstract

This overview presents the Author Profiling shared task at PAN 2021. The focus of this year's task is on determining whether or not the author of a Twitter feed is keen to spread hate speech. The main aim is to show the feasibility of automatically identifying potential hate speech spreaders on Twitter. For this purpose a corpus with Twitter data has been provided, covering the English and Spanish languages. Altogether, the approaches of 66 participants have been evaluated.

Published
2021

25. Consumer Health Search at CLEF eHealth 2021

Author

Goeuriot, L., Suominen, H., Pasi, G., Bassani, E., Brew-Sam, N., González-Sáez, G., Kelly, L., Mulhem, P., Seneviratne, S., Rishabh Upadhyay, Viviani, M., Xu, C., Faggioli G, Ferro N, Joly A, Maistro M, Piroi F, Goeuriot, L, Suominen, H, Pasi, G, Bassani, E, Brew-Sam, N, Gonzalez-Saez, G, Kelly, L, Mulhem, P, Seneviratne, S, Upadhyay, R, Viviani, M, and Xu, C

Subjects
Health record, EHealth, Self-diagnosi, Information storage and retrieval, Test-set generation, Medical informatic, Evaluation, Dimensions of relevance
Abstract

This paper details materials, methods, results, and analyses of the Consumer Health Search Task of the CLEF eHealth 2021 Evaluation Lab. This task investigates the effectiveness of information retrieval (IR) approaches in providing access to medical information to laypeople. For this a TREC-style evaluation methodology was applied: a shared collection of documents and queries is distributed, participants' runs received, relevance assessments generated, and participants' submissions evaluated. The task generated a new representative web corpus including web pages acquired from a 2021 CommonCrawl and social media content from Twitter and Reddit, along with a new collection of 55 manually generated layperson medical queries and their respective credibility, understandability, and topicality assessments for returned documents. This year's task focused on three subtask: (i) ad-hoc IR, (ii) weakly supervised IR, and (iii) document credibility prediction. In total, 15 runs were submitted to the three subtasks: eight addressed the ad-hoc IR task, three the weakly supervised IR challenge, and 4 the document credibility prediction challenge. As in previous years, the organizers have made data and tools associated with the task available for future research and development.

Published
2021

26. Overview of the CLEF eHealth Evaluation Lab 2021

Author

Rishabh Upadhyay, Nicola Brew-Sam, Jorge Vivaldi, Marco Viviani, Viviana Cotik, Hanna Suominen, Elias Bassani, Roland Roller, Chenchen Xu, Gabriela Nicole González-Sáez, Darío Filippo, Philippe Mulhem, Liadh Kelly, Gabriella Pasi, Lorraine Goeuriot, Franco M. Luque, Laura Alonso Alemany, Sandaru Seneviratne, Candan, KS, Ionescu, B, Goeuriot, L, Larsen, B, Müller, H, Joly, A, Maistro, M, Piroi, F, Faggioli, G, Ferro, N, Suominen, H, Kelly, L, Alemany, L, Bassani, E, Brew-Sam, N, Cotik, V, Filippo, D, González-Sáez, G, Luque, F, Mulhem, P, Pasi, G, Roller, R, Seneviratne, S, Upadhyay, R, Vivaldi, J, Viviani, M, Xu, C, Australian National University (ANU), Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), University of Turku, Modélisation et Recherche d’Information Multimédia [Grenoble] (MRIM ), Laboratoire d'Informatique de Grenoble (LIG), Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Computer Science Department [Maynooth], National University of Ireland Maynooth (Maynooth University), Universidad Nacional de Córdoba [Argentina], Università degli Studi di Milano-Bicocca [Milano] (UNIMIB), Consorzio per il Trasferimento Tecnologico (C2T), Departamento de Computación [Buenos Aires], Facultad de Ciencias Exactas y Naturales [Buenos Aires] (FCEyN), Universidad de Buenos Aires [Buenos Aires] (UBA)-Universidad de Buenos Aires [Buenos Aires] (UBA), CONICET / IICE-UBA, Instituto de Investigación en Ciencias de la Computación [Buenos Aires] (ICC), Consejo Nacional de Investigaciones Científicas y Técnicas [Buenos Aires] (CONICET)-Facultad de Ciencias Exactas y Naturales [Buenos Aires] (FCEyN), Modélisation et Recherche d’Information Multimédia [Grenoble] (MRIM), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF), Deutsches Forschungszentrum für Künstliche Intelligenz GmbH = German Research Center for Artificial Intelligence (DFKI), Universitat Pompeu Fabra [Barcelona] (UPF), and ANR-19-CE23-0029,Kodicare,Variations de l'environnement d'évaluation : caractérisation du delta et impact sur l'évolution continue des systèmes de recherche d'information(2019)

Subjects
Ninth, Text segmentation, Information extraction, Computer science, Self-diagnosi, 02 engineering and technology, computer.software_genre, Health informatics, Task (project management), World Wide Web, Health record, Entity linking, Resource (project management), 020204 information systems, Health care, 0202 electrical engineering, electronic engineering, information engineering, eHealth, Information retrieval, Test-set generation, Medical informatic, Evaluation, ComputingMilieux_MISCELLANEOUS, business.industry, Clef, 3. Good health, [INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR], Text classification, 020201 artificial intelligence & image processing, business, computer
Abstract

In this paper, we provide an overview of the ninth annual edition of the CLEF eHealth evaluation lab. CLEF eHealth 2021 continues our evaluation resource building efforts around the easing and support of patients, their next-of-kins, health care professionals, and health scientists in understanding, accessing, and authoring electronic health information in a multilingual setting. The 2021 lab offered two tasks: Task 1 on multilingual Information Extraction (IE), this year extending to a corpus of Spanish radiology reports; and Task 2 on Consumer Health Search (CHS) that builds on the previous year’s Information Retrieval (IR) tasks. In total, 11 teams took part in these tasks (7 in Task 1 on IE and 4 in Task 2 on IR). Herein, we describe the resources created for these tasks and the evaluation methodology adopted, and we provide a brief summary of the participants of this year’s challenges as well as the results obtained. As in previous years, the organizers have made data, tools, and more specific overview papers associated with the lab tasks available for future research and development.

Published
2021
Full Text
View/download PDF

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