posted by user: aircc_cfp || 884 views || tracked by 2 users: [display]

NLDM 2026 : 6th International Conference on NLP & Data Mining

FacebookTwitterLinkedInGoogle

Link: https://nldm2026.org/
 
When May 23, 2026 - May 24, 2026
Where Vancouver, Canada
Submission Deadline Apr 11, 2026
Notification Due May 9, 2026
Final Version Due May 16, 2026
Categories    data mining   NLP   artificial intelligence   computer science
 

Call For Papers

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 11, 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.

Important Dates

Submission Deadline: April 11, 2026
Authors Notification: May 09, 2026
Final Manuscript Due: May 16, 2026

Co - Located Events

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

Related Resources

MIDAS 2026   The 11th Workshop on MIning DAta for financial applicationS
IEEE-ICECCS 2026   2025 IEEE International Conference on Electronics, Communications and Computer Science (ICECCS 2026)
DATA 2026   15th International Conference on Data Science, Technology and Applications
AMLDS 2026   IEEE--2026 2nd International Conference on Advanced Machine Learning and Data Science
AIChE Spring Meeting & GCPS 2026   2026 AIChE Spring Meeting & 22nd Global Congress on Process Safety
GreeNet Symposium - SGNC 2026   17th Symposium on Green Networking and Computing (SGNC 2026)
DEPLING 2023   International Conference on Dependency Linguistics
DL Frontiers in NLP 2026   Deep Learning Frontiers in Natural Language Processing (DL Frontiers in NLP) at IEEE ISSATK 2026
IJNSA 2026   International Journal of Network Security & Its Applications - ERA Indexed, H Index - 52
CVIPPR 2026   2026 4th Asia Conference on Computer Vision, Image Processing and Pattern Recognition (CVIPPR 2026)