Scope 

6^th International Conference on NLP & Data Mining (NLDM 2026) offers a premier global platform for researchers, practitioners, and industry experts to exchange knowledge, discuss breakthroughs, and explore emerging trends in Natural Language Processing and Data Mining. As these fields, continue to evolve rapidly driven by advances in large language models, deep learning, multimodal systems, and scalable data analytics. NLDM 2026 aims to foster collaboration and inspire innovative solutions to complex real world challenges.

Authors are invited to submit original research papers, case studies, survey articles, and industrial experiences that showcase significant progress or novel insights. Submissions may address any of the conference topics, including, but not limited to the areas listed below.

Natural Language Processing


• Corpus Linguistics and Large Scale Corpus Analysis
• Information Extraction and Information Retrieval
• Text Mining and Document Understanding
• Question Answering, Reading Comprehension and Machine Reasoning
• Argumentation Mining and Discourse Analysis
• Semantic Processing, Semantic Role Labeling and Meaning Representation
• Knowledge Processing and Knowledge Enhanced NLP
• Natural Language in Conceptual Modeling

Machine Learning, Deep Learning and Foundation Models


• Deep Learning for NLP (Transformers, Attention Models, RNNs, etc.)
• Large Language Models (LLMs) and Foundation Models
• Prompt Engineering, Fine Tuning and Adaptation Techniques
• Multimodal Learning (Text + Vision, Speech, Graphs)
• Self Supervised, Weakly Supervised and Unsupervised NLP
• Generative Models (LLMs, Diffusion Models for Text)
• Efficient NLP (Model Compression, Distillation, Quantization)
• Trustworthy, Explainable and Robust NLP

Applied NLP and Emerging Domains


• NLP for Internet of Things (IoT) and Ambient Intelligence
• Conversational AI, Dialogue Systems and Chatbots
• Speech Language Integration and Multimodal Conversational Systems
• NLP for Healthcare, Legal, Finance and Scientific Texts
• NLP for Education, Assessment and Intelligent Tutoring
• Social Media NLP, Misinformation Detection and Sentiment Analysis
• Computational Social Science and Digital Humanities
• Cross Lingual, Multilingual and Low Resource NLP

Data Mining Foundations


• Data Mining Theory, Algorithms and Optimization
• Pattern Recognition, Clustering and Classification
• Graph Mining, Network Analysis and Knowledge Graphs
• Temporal, Spatial and Spatio Temporal Data Mining
• Big Data Analytics and Scalable Data Mining Architectures
• Data Quality, Data Cleaning and Data Integration

Data Mining Applications


• Business Intelligence and Predictive Analytics
• Recommender Systems and Personalization
• Fraud Detection, Anomaly Detection and Risk Analytics
• Web Mining, Social Network Mining and Behavioral Analytics
• Mining Scientific, Biomedical and Sensor Data
• Edge, Cloud and Distributed Data Mining

Semantic Web, Linked Data and Knowledge Technologies


• Semantic Web, Ontologies and Open Linked Data
• Knowledge Graph Construction, Completion and Reasoning
• Hybrid Neuro Symbolic AI
• Semantic Search and Intelligent Information Systems

Ethics, Safety and Responsible AI


• Fairness, Accountability and Transparency in NLP and Data Mining
• Bias Detection and Mitigation in Language Models
• Privacy Preserving NLP and Federated Learning
• Ethical Data Collection, Annotation and Benchmarking

Selected papers from NLDM 2026, after further revisions, will be published in the special issue of the following journals

• International Journal on Natural Language Computing (IJNLC)
• International Journal of Web & Semantic Technology (IJWesT) - IS Indexed
• International Journal of Ubiquitous Computing (IJU)
• International Journal of Data Mining & Knowledge Management Process ( IJDKP )
• The International Journal of Ambient Systems and Applications (IJASA)
• The International Journal of Grid Computing & Applications (IJGCA)
• Information Technology in Industry (ITII)