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6th International Conference on NLP & Data Mining (NLDM 2026)

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When :  2024-05-23

Where :  Vancouver, Canada

Submission Deadline :  2026-04-18

Categories :   Artificial Intelligence ,  Machine Learning ,  Data Mining ,  Knowledge Management

https://nldm2026.org/index

6th International Conference on NLP & Data Mining (NLDM 2026)

May 23 ~ 24, 2026, Vancouver, Canada

Hybrid -- Registered authors can present their work online or face to face.

Scope & Topics

6th 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.

Topics of interest include, but are not limited to, the following

    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

Paper Submission

Authors are invited to submit papers through the conference Submission System by April 18, 2026. Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this conference.The proceedings of the conference will be published by The proceedings of the conference will be published by Computer Science Conference Proceedings (H index 46) in Computer Science & Information Technology (CS & IT) series (Confirmed).

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)

Important Dates

Submission Deadline: April 18, 2026
Authors Notification: May 09, 2026
Final Manuscript Due: May 16, 2026

Co - Located Events


  • 15th International Conference on Artificial Intelligence and Soft Computing (AISO 2026)
  • 5th International Conference on Education, Pedagogy and Technology (EDUPT 2026)
  • 13th International Conference on Wireless and Mobile Network (WiMNeT 2026)
  • 15th International Conference on Signal & Image Processing (SIP 2026)
  • 6th International Conference on Big Data, IoT and Machine Learning (BIOM 2026)
  • 6th International Conference on Cryptography and Blockchain (CRBL 2026)
  • 10th International Conference on Computer Science and Information Technology (COMIT 2026)
  • 5th International Conference on Software Engineering Advances and Formal Methods (SOFTFM 2026)

***** The invited talk proposals can be submitted to nldm@nldm2026.org

User Name : Zahra
Posted 10-01-2024 on 20:00:16 AEDT


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