NLDB 2025: Call for Papers

The 30th International Conference on Natural Language & Information Systems (NLDB 2025) invites authors to submit papers for oral presentations on unpublished research that addresses theoretical aspects, algorithms, applications, architectures for applied and integrated NLP, resources for applied NLP, and other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.

NLDB 2025 will be held in Kanazawa, Japan, from July 4-6, 2025.

Tracks

Main Track

This track solicits novel and significant research contributions addressing theoretical aspects, algorithms, applications, architectures, resources, and other aspects of NLP, as well as survey and discussion papers. We welcome work describing original and replicable research showing evidence of significant contribution to the NLP community.

Industry Track

This track covers all aspects of innovative commercial or industrial-strength NLP technologies in order to showcase the state of adoption. It welcomes contributions about case studies of success stories, discussion reports of obstacles that stand in the way of adoption of NLP technologies, and experience reports in applying recent research advances to relevant industry problems. We encourage results and ideas from companies small and large.

Topics of Interest

Topics 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.

Paper Types & Lengths

All submissions will be in LNCS in PDF format:

• Full paper: 15 pages maximum
• Short paper: 11 pages maximum
• Demo paper: 6 pages maximum

Important Dates

All deadlines are 11:59PM UTC-12:00 AoE:

1. Call for papers: October 1, 2024
2. Submission deadline (Extended): March 16, 2025
3. Authors notification (Extended): April 25, 2025
4. Authors registration deadline: May 9, 2025
5. Camera ready: May 9, 2025
6. Conference: July 4-6, 2025

Publication

• The conference proceedings will be published in Lecture Notes in Computer Science (LNCS, Springer).
• Best papers will be invited to publish in the special issue of Data & Knowledge Engineering (DKE, Elsevier) and Journal of Web Engineering (JWE, River Publisher).

Author Guide

For more information on submission guidelines and formatting, please refer to the Author Guide.