EPIA 2026

Track Description

The Track on Natural Language, Text Mining and Applications (NLP-TeMA 2026) brings together researchers and practitioners working in Human Language Technologies, including Natural Language Processing (NLP), Computational Linguistics (CL), Natural Language Engineering (NLE), Text Mining (TM), Information Retrieval (IR), Large Language Model Research and Applications (LLMs), and related areas. As text remains the primary medium for creating and sharing knowledge, vast amounts of natural language data are generated daily across the Web and other digital platforms. This continuous growth presents significant opportunities and challenges for developing methods that can effectively understand, analyze, and extract value from textual information. Advances in NLP, Machine Learning, and Deep Learning have strengthened the role of language technologies in transforming semi-structured and unstructured data into actionable knowledge. NLP-TeMA 2026 welcomes contributions addressing both theoretical foundations and practical applications, fostering research that connects methodological innovation with real-world impact.

Topics of Interest

• Theories, Algorithms and Models (Language Modeling, Syntax, Semantics, LLMs, etc.)
• Text Mining and NLP Applications (Text Clustering, Information Extraction, Machine Translation, Sentiment Analysis, etc.)

Track Chairs

• Joaquim Silva - Universidade Nova de Lisboa
• Pablo Gamallo - Universidade de Santiago de Compostela
• Alípio Jorge - Universidade do Porto