- Corpora - ELRA lists

2 PhD positions in Computational Linguistics / Sociolinguistics for Luxembourgish at the University of Luxembourg
by Christoph PURSCHKE 02 Dec '22

02 Dec '22

dear colleagues, in the context of an upcoming research project (TRAVOLTA – Tracing Attitudes and Variation in Online Luxembourgish Text Archives) we currently have two open positions for doctoral candidates with a background in nlp, computational linguistics, sociolinguistics or variationist linguistics. the candidates will be members of the department of humanities at the university of luxembourg. the project will be the first to monitor the development of luxembourgish into a fully-fledged written language using data from the rtl.lu news portal. we will develop state-of-the-art tools and pipelines for nlp purposes and use them to trace variation and social stances in written text. additional information about the project can be found here<https://purschke.info/en/travolta/>. it would be great if you could share the positions in your respective networks. please also feel free to reach out should you have any questions regarding the positions or would be interested in applying. both positions will be filled for 3 + 1 years max. with a current yearly salary of roughly 38k €. given the multilingual setup of the university and the special requirements of the project, candidates should have proficiency in english and german (intermediate), luxembourgish will be an asset, of course. thx & cheers christoph Position 1) Doctoral candidate in in Computational Linguistics / Variationist Linguistics * Full profile: http://emea3.mrted.ly/39skj * Research in the field of Computational/Variationist Linguistics with a focus on variation in written Luxembourgish * Background in * * Either: Computational Linguistics, Computer Science, or a related field with prior experience in working with language data * Or: Linguistics, Variationist Linguistics, or a related field with prior experience in data science applications (NLP, Python, r) Position 2) Doctoral candiate in Computational Linguistics / Sociolinguistics * Full profile: http://emea3.mrted.ly/39snq * Research in the field of Computational Linguistics/Sociolinguistics with a focus on attitudes & stances in written luxembourgish * Background in * Either: Computational Linguistics, Computer Science, or a related field with prior experience in working with language data * Or: Sociolinguistics, Linguistics, or a related field with prior experience in data science applications (NLP, Python, r) — Christoph Purschke Associate Professor in Computational Linguistics Head of the Culture & Computation Lab Faculty of Humanities, Education and Social Sciences UNIVERSITÉ DU LUXEMBOURG BELVAL CAMPUS 11, Porte des Sciences L-4366 Esch-sur-Alzette T +352 46 66 44 9226 M +352 661 266 323 W purschke.info<http://www.purschke.info> | cucolab.uni.lu<http://cucolab.uni.lu> christoph.purschke(a)uni.lu<mailto:christoph.purschke@uni.lu> | @questoph<https://twitter.com/questoph/> Languages: DEU, ENG, FRA, ITA, LTZ, NDS, PYT Book a meeting: 30 min<https://fantastical.app/questoph/short-meeting> | 60 min<https://fantastical.app/questoph/long-meeting> | office hours<https://fantastical.app/questoph/office-hours>

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Third call, TAL journal, regular issue 64-1
by Emmanuel Morin 02 Dec '22

02 Dec '22

Third Call for submission TAL Journal: regular issue http://tal-64-1.sciencesconf.org/ <http://tal-64-1.sciencesconf.org/> 2023 Volume 64-1 Deadline for submission: 12/15/2022 Editors : Cécile Fabre, Emmanuel Morin, Sophie Rosset and Pascale Sébillot TOPICS The journal Automatic Language Processing has an open call for papers. Submissions may concern theoretical and experimental contributions on all aspects of written, spoken, and signed language processing and computational linguistics, both theoretical and experimental, for example: - Computational models of language - Linguistic resources - Statistical learning and modeling - Intermodality and multimodality - Language multiplicity and diversity - Semantics and comprehension - Information access and text mining - Language production and processing/generation/synthesis - Evaluation - Explicability and reproducibility - NLP in interaction with other disciplines, digital humanities This list is indicative. On all topics, it is essential that the aspects related to natural language processing are emphasized. We also welcome position papers and survey papers. LANGUAGE Manuscripts may be submitted in English or French. Submissions in English are accepted only if one of the co-authors is a non French-speaking person. THE JOURNAL TAL (http://www.atala.org/revuetal_ <http://www.atala.org/revuetal_> - Traitement Automatique des Langues / Natural Language Processing) is an international journal published by ATALA (French Association for Natural Language Processing) since 1960 with the support of CNRS (National Centre for Scientific Research). It has moved to an electronic mode of publication. IMPORTANT DATES Deadline for submission: 12/15/2022 Notification to authors after first review: 02/15/2023 Notification to authors after second review: 04/30/2023 Publication: September, 2023 FORMAT SUBMISSION Papers must be between 20 and 25 pages long, including references and appendices (with no possible derogation on the length). TAL performs double-blind review: it is thus necessary to anonymise the manuscript and the name of the pdf file and to avoid self references. Style sheets are available for download on the Web site of the journal (https://www.atala.org/content/instruction-authors-style-files-0 <https://www.atala.org/content/instruction-authors-style-files-0>). Authors who intend to submit a paper are encouraged to upload your contribution via the menu "Paper submission" (PDF format). To do so, you will need to have an account on the sciencesconf platform. To create an account, go to the site _http://www.sciencesconf.org_ <http://www.sciencesconf.org_/> and click on "create account" next to the "Connect" button at the top of the page. To submit, come back to the page (soon available) http://tal-64-1.sciencesconf.org/ <http://tal-64-1.sciencesconf.org/>, connect to you account and upload your submission.

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Call for papers: Explainable AI in Natural Language Processing
by Somnath Banerjee 01 Dec '22

01 Dec '22

*** Apologies for cross-posting *** Call for papers: Explainable AI in Natural Language Processing Traditional Natural Language Processing (NLP) models (e.g., decision trees, Markov models, etc.) have primarily been based on techniques that are inherently interpretable models, referred to as white-box techniques. However, in recent years, NLP models have employed advanced neural approaches along with language embedding features. Using these advanced approaches, mostly referred to as black-box techniques, the NLP models have yielded state-of-art performance. Nonetheless, the level of interpretability (e.g., how the model arrives at its results) has reduced significantly. This obfuscated interpretability not only lowers the end users’ trust in the NLP models but also makes it challenging for the developers to debug or improve by analyzing the models for further improvement. Therefore, nowadays, researchers in the NLP community are giving significant attention to the emerging field called Explainable AI (XAI) to tackle the obfuscated complexity of AI systems for trust and improvement. Apart from academia, organizations and companies also have launched high-funding projects such as DARPA XAI, People +AI Research (PAIR), etc. As XAI is still a growing field, there is plenty of room for innovation to improve the explainability of NLP systems. In recent works, explainable NLP models have captured linguistic knowledge of neural networks, explain predictions, stress-test models via challenge sets or adversarial examples, and interpret language embeddings. The goal of this Research Topic is to better understand the present status of the XAI in NLP by identifying: new dimensions for a better explanation, evaluation techniques used to measure the quality of explanations, approaches or developments of new software toolkits to explain XAI in NLP, and transparent deep learning models for different NLP task. The scope of this Research Topic covers (but is not restricted to) the following topics: • Survey of XAI in NLP in general or any particular NLP task such as NER, QA, Sentiment analysis, social media (SocialNLP), etc. • Explainable Neural models in Machine Translation • Explainable Neural models in Named Entity Recognition • Explainable Neural models in Question Answering • Explainable Neural models in Sentiment Analysis • Explainable Neural models in Opinion Mining • Explainable Neural models in SocialNLP • Evaluation techniques used to measure the quality of explanations • Tools for explaining explainability • Resources related to XAI in the context of NLP The Research Topic welcomes contributions toward interpretable models for efficient solutions to NLP research problems that explain the explainability of the proposed model using suitable explainability technique(s) (e.g., example-driven, provenance, feature importance, induction, surrogate models, etc.), visualization technique(s) (e.g., raw examples, saliency, raw declarative, etc.), and other aspects. Software toolkits or approaches that can help users express explainability to their models and ML pipelines are also welcome. The full Call for Papers is available at https://www.frontiersin.org/research-topics/48440/explainable-ai-in-natural… Impact of the publication: https://www.frontiersin.org/about/impact The current deadlines are: * Abstract Deadline:16 December 2022 - A soft deadline, thus whilst not mandatory, if you would like feedback on your prospective manuscript’s suitability, I encourage you to submit an abstract around this time. * Manuscript Deadline: 14 April 2023, This is a mandatory deadline for your full manuscript submission. However, we can accommodate personal extensions on a case-by-case basis. Guest Associate Editors: Somnath Banerjee (University of Tartu, somnath.banerjee(a)ut.ee) David Tomás (University of Alicante, dtomas(a)dlsi.ua.es) Somnath Banerjee Lecturer, Institute of Computer Science, University of Tartu, Narva mnt 18, room 3063 51009 Tartu, ESTONIA webpage: http://www.ut.ee//~somnath/

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CFP: FICTA-2023, Cardiff Metropolitan University, United Kingdom || Springer SIST Series (Scopus Indexed) || Paper Submission Deadline: 10 December 2022
by Sandeep Sengar 01 Dec '22

01 Dec '22

Dear Researchers, We are happy to inform you that the Eleventh International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA-2023) will be organized by Cardiff Metropolitan University, United Kingdom. We invite you to participate in FICTA-2023: https://ficta.co.uk/ on 11-12 April 2023, being organized in a hybrid mode. Publication: All FICTA 2023 registered and presented papers will be published in conference proceedings by Springer-Smart Innovation, Systems and Technologies (SIST) Series (https://www.springer.com/series/8767). Topics of interest: Submissions of quality papers are expected in all areas of research and application in intelligent computing, refer call for papers at https://ficta.co.uk/call-for-papers. Call for Special Session Proposals: If interested in floating/organizing a special session please visit the link and follow the necessary guidelines: https://ficta.co.uk/call-for-sessions For any queries related to the conference you may feel free to e-mail: FICTA2023(a)cardiffmet.ac.uk Thank you -- Warm Regards, *Sandeep Singh Sengar*, Lecturer in Computer Science Cluster Leader Computer Vision / Image Processing Cardiff Metropolitan University, Cardiff, UK CF5 2YB *-------------------------------------------------------------------------------* *Email: SSSengar(a)cardiffmet.ac.uk <SSSengar(a)cardiffmet.ac.uk>* *Web: **https://sites.google.com/view/sandeepsengar <https://sites.google.com/view/sandeepsengar>*

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Research Associate (post-doc) in Machine Learning for Natural Language Processing @ The University of Sheffield (deadline 07/12)
by Carol Scarton 01 Dec '22

01 Dec '22

Hi all, We are hiring a Research Associate (post-doc) to work on one of our NLP projects at the University of Sheffield. The successful candidate will be expected to lead the design and development of strategies for more transparent machine learning models to generate accurate cross-lingual representations for idiomatic language, as well as to contribute to the design and development of resources and evaluation of downstream tasks, like machine translation. For both lines of research, you will build on state-of-the-art approaches based on deep learning. The applicants should hold a PhD (or be close to completion) or have equivalent work experience and a strong publication record. Solid knowledge of Machine Learning models applied to Natural Language Processing and Deep Learning is required, as is excellent programming skills in Python and deep learning frameworks (esp. Keras, TensorFlow or PyTorch). Previous experience developing word embedding models and/or Machine Translation is also desirable. Deadline for applications: 07/12/2022 More details, including how to apply can be found in the following link: bit.ly/3gnGP4l <https://t.co/KvevJ2LPoS> Kind regards, Carol -- *Carolina Scarton* Lecturer in Natural Language Processing Department of Computer Science University of Sheffield http://staffwww.dcs.shef.ac.uk/people/C.Scarton/

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1st CFP of the 7th International Conference on Innovations and Creativity (ICIC 2023)
by Dariush Alimohammadi 01 Dec '22

01 Dec '22

Dear All, Please share the CFP of 7th International Conference on Innovations and Creativity (ICIC 2023) to be held in Liepaja, Latvia in June 2023 with your colleagues. ICIC covers a wide range of topics from Mathematics and Computer Science to Art, Energy and Environmental Science. Check out Call For Papers and Deadlines at: http://icic.liepu.lv/ Kind regards, -- Dariush Alimohammadi, PhD, Professor, Faculty of Science and Engineering, Liepaja University, Liepaja, Latvia.

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[IberLEF 2023] Last Call for Task Proposals
by Salud María Jiménez Zafra 01 Dec '22

01 Dec '22

================================= *IberLEF 2023 -- Call for Task Proposals* ================================= The goal of IberLEF is to encourage the research community to organize competitive text processing, understanding and generation tasks, with the aim of defining new research challenges and advancing the state of the art in Natural Language Processing challenges involving at least one of the following Iberian languages: Spanish, Portuguese, Catalan, Basque or Galician. Researchers and practitioners from all areas of Natural Language Processing and related communities are invited to submit task proposals that fit IberLEF goals *by December 5, 2022.* Proposals must be submitted (as a pdf file) to iberlef(a)googlegroups.com, and should include the following fields: ● Title of the task. ● Description of the task, highlighting: ○ Relevance and novelty of the task, and the challenges involved. ○ Evaluation measures, and other relevant methodological aspects. ○ Expected target community, and actual or potential industrial take up. ○ Related evaluation activities, if any. ○ Previous editions of the task, if any. If it has been organized previously, what the roadmap is and what the novelties for 2023 are. ○ Linguistic resources to be gathered, created and/or reused. Please include as many details on data gathering, selection and annotation procedures as possible: sources and representativity, training/validation/test sizes, harvesting procedures, profile of annotators (experts, linguists, crowdworkers, etc.), multiple annotation policy, IPR issues, baselines, etc. ● Tentative schedule (note that camera ready versions of the proceedings must be ready *by July 6, 2023*). ● Organization committee: full name and affiliation of the organizers, with a succinct description of their research interests, areas of expertise and experience organizing similar events. ● Funding, if available. ● Contact person. ● Any other relevant issues. *Task organizers duties* Note that organizers of accepted tasks are expected to: ● Setup the evaluation exercise according to the submitted proposal. ● Promote the task within the target research community. ● Manage the submission and scientific evaluation of the system description papers of the corresponding systems submitted by the participants. The accepted papers will be published in the IberLEF proceedings. ● Prepare and submit an overview of the evaluation exercise. ● Present the results of the task at IberLEF 2023. *Task selection procedure* Each submitted proposal will be reviewed by members of the IberLEF steering and program committee, and decisions will be sent back to the task organizers by* January 16, 2023*. *Proceedings* IberLEF 2023 Proceedings including the description of the participating systems will be published at CEUR-WS.org. Task Overviews will be published in the journal *Natural Language Processing* ( http://www.sepln.org/en/journal, indexed in Clarivate ESCI and Elsevier SJR) in its September 2023 issue. Task Organizers are expected to send the camera ready task and system description papers for their task to IberLEF organizers by *July 6, 2023*. *Important dates* ● Task proposals due: December 5, 2022. ● Notification of acceptance: January 16, 2023. ● Camera ready submissions due: July 6, 2023. ● IberLEF Workshop: September 2023. *IberLEF general chairs*: Salud María Jiménez Zafra, SINAI, Universidad de Jaén (Spain) Manuel Montes y Gómez, INAOE (Mexico) Francisco Rangel, Symanto Research (Spain) *Contact* E-mail: iberlef(a)googlegroups.com [image: Universidad de Jaén] <http://www.uja.es/> *Salud María Jiménez Zafra* sjzafra(a)ujaen.es Universidad de Jaén Grupo de Investigación SINAI <http://sinai.ujaen.es/> | Departamento de Informática EPS Jaén, Edificio A3, Despacho 219 Campus Las Lagunillas s/n 23071 - Jaén | +34 953212992 [image: Universidad de Jaén] <http://www.uja.es/>

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UK Jobs in Computing and Data Science
by Eric Atwell 30 Nov '22

30 Nov '22

Promotion opportunities: Head of the School of Computing<https://jobs.leeds.ac.uk/vacancy.aspx?ref=ASN-84381> University of Leeds Lecturers in Computer Science<https://jobs.leeds.ac.uk/vacancy.aspx?ref=EPSCP1116> University of Leeds Lecturer in Computer Science<https://jobs.leeds.ac.uk/vacancy.aspx?ref=SWJTU1007> University of Leeds Teaching Assistants in Computer Science<https://jobs.leeds.ac.uk/vacancy.aspx?ref=EPSCP1115> University of Leeds Data Engineering Developer<https://jobs.leeds.ac.uk/vacancy.aspx?ref=ITDSV1000> University of Leeds Data Analyst<https://jobs.leeds.ac.uk/vacancy.aspx?ref=ITDSV1002> University of Leeds Professor in Artificial Intelligence<https://www.linkedin.com/jobs/view/3375574406/?eBP=JYMBII_JOBS_HOME_ORGANIC…> Manchester Metropolitan University Professor in Data Science<https://www.linkedin.com/jobs/view/3381166449/?eBP=JYMBII_JOBS_HOME_ORGANIC…> University of the Arts London Deputy Dean, Faculty of Computing,<https://www.linkedin.com/jobs/view/3376789059/?eBP=JYMBII_JOBS_HOME_ORGANIC…> De Montford University Leicester Professor in Creative Computing<https://www.linkedin.com/jobs/view/3381171110/?eBP=JYMBII_JOBS_HOME_ORGANIC…> University of the Arts London Programme Director - Computing<https://www.linkedin.com/jobs/view/3368580632/?eBP=JYMBII_JOBS_HOME_ORGANIC…> Kaplan International, Leeds office Professor/Reader of Statistical Data Science<https://www.linkedin.com/jobs/view/3373317196/?eBP=JYMBII_JOBS_HOME_ORGANIC…> Newcastle University Professor in Fintech<https://www.linkedin.com/jobs/view/3356652057/?eBP=JYMBII_JOBS_HOME_ORGANIC…> University of East London Director of Education<https://www.linkedin.com/jobs/view/3344955080/?eBP=JYMBII_JOBS_HOME_ORGANIC…> HyperionDev Computing Education Senior Lecturer/Associate Professor: Data Science<https://www.linkedin.com/jobs/view/3374847671/?eBP=JYMBII_JOBS_HOME_ORGANIC…> Falmouth University

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NLDB 2023 CFP
by Max Silberztein 30 Nov '22

30 Nov '22

Dear Madam/Sir, Please forward this CFP to corpora-list's members Regards --Max Silberztein NLDB 2023 The 28th International Conference on Natural Language & Information Systems 21-23 June 2023, University of Derby, United Kingdom. https://www.derby.ac.uk/events/latest-events/nldb-2023/ About NLDB The 28th International Conference on Natural Language & Information Systems will be held at the University of Derby, United Kingdom and will be a face to face event. Since 1995, the NLDB conference brings together researchers, industry practitioners, and potential users interested in various application of Natural Language in the Database and Information Systems field. The term "Information Systems" has to be considered in the broader sense of Information and Communication Systems, including Big Data, Linked Data and Social Networks. The field of Natural Language Processing (NLP) has itself recently experienced several exciting developments. In research, these developments have been reflected in the emergence of neural language models (Deep Learning, Word Embeddings, Transformers) and the importance of aspects such as transparency, bias and fairness, a (renewed) interest in various linguistic phenomena, such as in discourse and argumentation mining, and in new problems such as the detection of disinformation and hate speech in social media, as well of mental health disorders that increased during the recent pandemic. Regarding applications, NLP systems have evolved to the point that they now offer real-life, tangible benefits to enterprises. Many of these NLP systems are now considered a de-facto offering in business intelligence suites, such as algorithms for recommender systems and opinion mining/sentiment analysis. It is against this backdrop of recent innovations in NLP and its applications in information systems that the 28th edition of the NLDB conference takes place. We welcome research and industrial contributions, describing novel, previously unpublished works on NLP and its applications across a plethora of topics as described in the Call for Papers. Call for Papers NLDB 2023 invites authors to submit papers for oral or poster presentations on unpublished research that addresses theoretical aspects, algorithms, applications, architectures for applied and integrated NLP, resources for applied NLP, and other aspects of NLP, as well as survey and discussion papers. This year's edition of NLDB also introduces an Industry Track, to foster fruitful interaction between the industry and the research community. Topics of interest include but are not limited to: Social Media and Web Analytics: Opinion mining/sentiment analysis, irony/sarcasm detection; detection of fake reviews and deceptive language; detection of harmful information: fake news and hate speech; sexism and misogyny; detection of mental health disorders; identification of stereotypes and social biases; robust NLP methods for sparse, ill-formed texts; recommendation systems. Deep Learning and eXplainable Artificial Intelligence (XAI): Deep learning architectures, word embeddings, transparency, interpretability, fairness, debiasing, ethics. • Argumentation Mining and Applications: Automatic detection of argumentation components and relationships; creation of resource (e.g. annotated corpora, treebanks and parsers); Integration of NLP techniques with formal, abstract argumentation structures; Argumentation Mining from legal texts and scientific articles. • Question Answering (QA): Natural language interfaces to databases, QA using web data, multi-lingual QA, non-factoid QA(how/why/opinion questions, lists), geographical QA, QA corpora and training sets, QA over linked data (QALD). • Corpus Analysis: multi-lingual, multi-cultural and multi-modal corpora; machine translation, text analysis, text classification and clustering; language identification; plagiarism detection; information extraction: named entity, extraction of events, terms and semantic relationships. • Semantic Web, Open Linked Data, and Ontologies: Ontology learning and alignment, ontology population, ontology evaluation, querying ontologies and linked data, semantic tagging and classification, ontology-driven NLP, ontology-driven systems integration. • Natural Language in Conceptual Modelling: Analysis of natural language descriptions, NLP in requirement engineering, terminological ontologies, consistency checking, metadata creation and harvesting. • Natural Language and Ubiquitous Computing: Pervasive computing, embedded, robotic and mobile applications; conversational agents; NLP techniques for Internet of Things (IoT); NLP techniques for ambient intelligence • Big Data and Business Intelligence: Identity detection, semantic data cleaning, summarisation, reporting, and data to text. Important Dates: Full paper submission: 14 March, 2023 Paper notification: 10 April, 2023 Camera-ready deadline: 24 April, 2023 Conference: 21-23 June 2023 Submission Guidelines Authors should follow the LNCS format (https://www.springer.com/gp/computer-science/lncs/conference-proceedings-gu… ) and submit their manuscripts in pdf via Easychair (https://easychair.org/conferences/?conf=nldb2023 ) Submissions can be full papers (12 pages maximum including references), short papers (8 pages including references) or papers for a poster presentation or system demonstration (6 pages including references). The programme committee may decide to accept some full papers as short papers or poster papers. The reviewing process of NLDB 2023 is double-blind, i.e., submissions to the main conference and to the industry track must not contain author names or other identifying information, such as funding sources, acknowledgments and must use the third person to refer to work the authors have previously undertaken. System demonstration papers may not be anonymous. Committee Conference Chairs: Manning Warren, University of Derby, UK Métais Elisabeth, Conservatoire des Arts et Métiers, Paris, France Meziane Farid, University of Derby, UK Program Chairs: Reiff-Marganiec Stephan, University of Derby, UK Sugumaran Vijayan, Oakland University, Rochester, USA Programme Committee: Abdi Asad, University of Derby, UK. Akoka Jacky, CNAM & TEM, France Anselma Luca, University of Turin, Italy Bajaj Ahsaas, University of Massachusetts Amherst, USA Balakrishna Mithun, Limba Corp, USA Banerjee Somnath, University of Milano-Bicocca, Italy Bensalem Imene, MISC Lab, Constantine 2 University, Algeria Bosco Cristina, University of Turin, Italy Braschler Martin, ZHAW School of Engineering, Switzerland Buscaldi Davide, University Sorbonne Paris Nord, France Cabrio Elena, Université Côte d’Azur, Inria, CNRS, I3S, France Caselli Tommaso, Rijksuniversiteit Groningen, The Netherlands Chiruzzo Luis, Universidad de la República, Uruguay Cignarella Alessandra Teresa, University of Turin, Italy Cimiano Philipp, Bielefeld University, Germany Croce Danilo, University of Rome "Tor Vergata", Italy Delgado Agustín, Universidad Nacional de Educación a Distancia, Spain Dinu Liviu, University of Bucharest, Romania Doucet Antoine, La Rochelle University, France Fersini Elisabetta, University of Milano-Bicocca, Italy Florio Komal, University of Turin, Italy Fomichov Vladimir, Moscow Aviation Institute, Russia Fornaciari Tommaso, Bocconi University Milan, Italy Franco Marc, Symanto, Germany/Spain Frasincar Flavius, Erasmus University Rotterdam, The Netherlands Hacohen-Kerner Yaakov, Jerusalem College of Technology, Israel Horacek Helmut, DFKI, Germany Ienco Dino, IRSTEA, France Iglesias Carlos A., Universidad Politécnica de Madrid, Spain Ittoo Ashwin, HEC, Univ. of Liege, Belgium Kapetanios Epaminondas, University of Hertfordshire, UK Kedad Zoubida, UVSQ, France Kop Christian, University of Klagenfurt, Austria Koufakou Anna, Florida Gulf Coast University, USA Laatar Rim, University of Sfax, Tunisia Lai Mirko, University of Turin, Italy Lopez Cédric, Emvista, Montpellier, France Loukachevitch Natalia, Moscow State University, Russia Aaisha Makkar, University of Derby Mandl Thomas, University of Hildesheim, Germany Martínez Paloma, Universidad Carlos III de Madrid, Spain Martínez Patricio, Universidad de Alicante, Spain Martínez Unanue Raquel, Universidad Nacional de Educación a Distancia, Spain Masmoudi Abir, LIUM, University of Le Mans, France Mazzei Alessandro, University of Turin, Italy Métais Elisabeth, Conservatoire des Arts et Métiers, France Meziane Farid, University of Derby, UK Mich Luisa, University of Trento, Italy Mimouni Nada, Conservatoire des Arts et Métiers, France Mitrović Jelena, University of Passau, Germany Montalvo Soto, Universidad Rey Juan Carlos, Spain Montes y Gómez Manuel, INAOE Puebla, Mexico Monti Johanna, L'Orientale University of Naples, Italy Muñoz Rafael, Universidad de Alicante, Spain Okky-Ibrohim Muhammad, University of Turin, Italy Passaro Lucia, University of Pisa, Italy Patti Viviana, University of Turin, Italy Picca Davide, Columbia University, USA Plaza Laura, Universidad Nacional de Educación a Distancia, Spain Rangel Francisco, Symanto, Germany/Spain Reyes Antonio, Autonomous University of Baja California, Mexico Roche Mathieu, Cirad, TETIS, France Rosso Paolo, Universitat Politècnica de València, Spain Saggion Horacio, Universitat Pompeu Fabra, Spain Sakketou Flora, Philipps-Marburg University Sanguinetti Manuela, Università degli Studi di Cagliari, Italy Silberztein Max, Université de Franche-Comté, France Sprugnoli Rachele, Catholic University of the Sacred Heart Milan, Italy Sugumaran Vijayan, Oakland University, Rochester, USA Tagarelli Andrea, University of Calabria, Italy Taulé Mariona, Universitat de Barcelona, Spain Teisseire Maguelonne, Irstea, TETIS, France Tomás David, Universidad de Alicante, Spain Tufis Dan, RACAI, Bucharest, Romania Uban Ana Sabina, University of Bucharest, Romania Ureña-López Alfonso, Universidad de Jaén, Spain Vadera Sunil, University of Salford, UK Valencia-Garcia Rafael, Universidad de Murcia, Spain Villatoro Esaú, Idiap Research Institute, Switzerland Wattiau Isabelle, ESSEC, France Zaghouani Wajdi, Hamad Bin Khalifa University, Qatar Zubiaga Arkaitz, Queen Mary University of London, UK

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Research internship: Quantifying diversity of language phenomena: Case study of multiword expressions (5-6 months, LIFAT, Blois, France)
by Agata Savary 30 Nov '22

30 Nov '22

RESEARCH INTERNSHIP *Quantifying diversity of language phenomena: Case study of multiword expressions* (LIFAT, Blois, France) We propose a master internship position in Blois (France). Please send an email to apply, with a CV, a transcript of bachelor and master grades, and a few lines explaining your motivation to Arnaud Soulet <arnaud.soulet(a)univ-tours.fr> <mailto:arnaud.soulet@univ-tours.fr>, as well as Agata Savary and Thomas Lavergne <first.last(a)universite-paris-saclay.fr> <mailto:first.last@universite-paris-saclay.fr>. Internship proposal description: https://selexini.lis-lab.fr/jobs/2022/11/26/internship Application deadline: *December 8*, 2022 (or until filled) ------ MOTIVATION AND CONTEXT *Diversity* of naturally occurring phenomena is a vital heritage to be preserved in the current progress- and optimization-driven globalization era. Diversity has been quantified in many domains: ecology, economy, information science, etc. but less so in *Natural Language Processing* (NLP). Recently, we have been addressing this aspect with respect to a particular linguistic phenomenon: the one of *multiword expressions * (MWEs). MWEs, such as (FR) /casser sa pipe/ ‘to die’ (literally to break one’s pipe) or (FR) /sortir du lot /'to be better than others' (literally to quit the batch), are groups of words which exhibit unexpected properties (Baldwin & Kim, 2010; Constant et al. 2017). Most prominently, their meaning does not straightforwardly derive from the meanings of their components. Language resources dedicated to MWEs include MWE lexicons and MWE-annotated corpora (Savary et al., 2017), while a major computational task is to *automatically identify MWEs *in running text. The PARSEME network has been addressing the MWE identification task via a series of *shared tasks* on automatic identification of verbal MWEs (Ramisch et al. 2020). Our recent work (Lion-Bouton, 2021; Lion-Bouton et al. 2022) is explicitly dedicated to *quantifying diversity in MWE language resources and MWE identification systems*. We have adapted measures of *variety* (number of types in a system), *balance* (equity of items in various types) and *disparity* (differences between types), stemming notably from ecology and information theory (Morales 2021). ------ OBJECTIVE The objective of this internship is to extend the formalisation of the diversity by benefiting from *Good-Turing frequency estimation*. Successfully used to estimate the biomass, Good-Turing frequency estimation is a statistical technique for estimating the probability of encountering an object of an unseen species, given a set of past observations of objects from different species (Good, 1953). Under this same principle, the idea would be to *estimate the number of unseen MWEs from the MWEs observed *in the corpus. Thus, it will be possible to correct the diversity measures to take the unseen MWEs into account and to evaluate the possible selection bias of the corpus.

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