* We apologize if you
      receive multiple copies of this CFP *
      For the online version of this Call, visit: 
https://nldb2024.di.unito.it/submissions/
      
      ===============
      
      SUBMISSIONS ARE OPEN AT 
https://easychair.org/conferences/?conf=nldb2024
      
      ===============
      
      NLDB 2024
      The 29th International Conference on Natural Language &
      Information Systems
      25-27 June 2024, University of Turin, Italy.
      Website: 
https://nldb2024.di.unito.it/
      Submission deadline: 22 March 5 April,
        2024 (Extended)
      
      About NLDB
      The 29th International Conference on Natural Language &
      Information Systems will be held at the University of Turin,
      Italy, and will be a face to face event. Since 1995, the NLDB
      conference brings together researchers, industry practitioners,
      and potential users interested in various applications 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 Large
      Language Models and the importance of aspects such as
      transparency, bias and fairness, Large Multimodal Models and the
      connection of the NLP field with Computer Vision, chatbots and
      dialogue-based pipelines.
      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. Language models
      developed by the open-source community have become widespread and
      commonly used. Businesses are now readily adopting these
      technologies, thanks to the efforts of the open-source community.
      For example, fine-tuning a language model on a company's own
      dataset is now easy and convenient, using modules created by
      thousands of academic researchers and industry experts.
      It is against this backdrop of recent innovations in NLP and its
      applications in information systems that the 29th 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 2024 invites authors to submit papers 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 continues with the
      Industry Track to foster fruitful interaction between the industry
      and the research community.
      
      Topics of interest include but are not limited to:
      * Large Language Models: training, applications, transfer
      learning, interpretability of large language models.
      * Multimodal Models: Integration of text with other modalities
      like images, video, and audio; multimodal representation learning;
      applications of multimodal models.
      * AI Safety and ethics: Safe and ethical use of Generative AI and
      NLP; avoiding and mitigating biases in NLP models and systems;
      explainability and transparency in AI.
      * Natural Language Interfaces and Interaction: design and
      implementation of Natural Language Interfaces, user studies with
      human participants on Conversational User Interfaces, chatbots and
      LLM-based chatbots and their interaction with users.
      * 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.
      
Student Registration:
        We are committed to fostering the participation of young
        researchers and students in the NLDB 2024 conference. To
        accommodate as many young minds as possible, we have reduced the
        student registration fees. We believe that this will provide an
        excellent opportunity for students to engage with the latest
        research and industrial applications of Natural Language
        Processing across information systems.
     Important Dates:
      Full paper submission: 22 March 5
        April, 2024 (Extended)
      Paper notification: 3 May, 2024
      Camera-ready deadline: 10 May, 2024
      Conference: 25-27 June 2024
      
      Submission Guidelines:
      Authors should follow the LNCS format (
https://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines)
      and submit their manuscripts in PDF via Easychair (
https://easychair.org/conferences/?conf=nldb2024)
      
      Papers can be submitted to either the main conference or the
      industry track.
      
      Submissions can be full papers (up to 15 pages including
      references and appendices), short papers (up to 11 pages including
      references and appendices) or papers for a poster presentation or
      system demonstration (6 pages including references). The program
      committee may decide to accept some full papers as short papers or
      poster papers.
      
      All questions about submissions should be emailed to 
federico....@unito.it
      (Web & Publicity Chair)
      
      General Chairs:
      
      Luigi Di Caro, University of Turin
      Farid Meziane, University of Derby
      Amon Rapp, University of Turin
      Vijayan Sugumaran, Oakland University