* We apologize if you receive multiple copies of this CFP *
For the online version of this Call, visit: https://nldb2024.di.unito.it/submissions/

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SUBMISSIONS ARE OPEN AT https://easychair.org/conferences/?conf=nldb2024

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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 We welcome research and industrial contributions, describing novel, previously unpublished works on NLP and its applications across a plethora of topics as described in the Call for Papers.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.