Emerging Approaches in Data Mining and Natural Language Processing Applications

Dear Colleagues,

In the rapidly evolving field of data science, the ability to gather, analyze, and extract information from vast datasets is both a challenge and a necessity. This Special Issue explores the innovative methods and applications that are pushing the boundaries of what is possible in data mining and NLP.

Data mining technologies empower us to extract meaningful patterns from large quantities of structured data, while text mining applies knowledge discovery techniques to unstructured text, transforming it into valuable insights. This issue delves into a range of topics, highlighting advanced techniques and their applications in various domains.

Key areas of focus include the following:

• Text Mining and Natural Language Processing (NLP): This section explores the latest algorithms and tools for processing and understanding unstructured text data. Topics such as information retrieval, document classification, sentiment analysis, topic modeling, and semantic analysis are covered, with researchers presenting new methods that enhance linguistic and semantic analysis for more accurate and efficient data interpretation.
• Sentiment Analysis and Opinion Mining: This section features techniques for analyzing sentiments, opinions, and emotions in textual data. Contributions discuss sentiment classification, aspect-based sentiment analysis, sentiment lexicon creation, and sentiment-aware recommendation systems, providing critical insights for applications in social media analytics, customer feedback, and market sentiment prediction.
• Large Language Models and Deep Learning: Articles in this domain highlight the transformative impact of large language models (LLMs) and deep learning in knowledge discovery. Researchers explore state-of-the-art models like transformers for language understanding, text generation, and dialogue systems, while addressing model interpretability, scalability, and ethical considerations.
• Applications Across Domains: This issue showcases the application of data mining and NLP in fields such as healthcare, cybersecurity, finance, and environmental monitoring. Researchers demonstrate how data-driven approaches can solve complex problems and provide actionable insights across diverse industry sectors.

This Special Issue seeks original, unpublished articles that address these recent advances in data mining and text mining techniques as well as their applications. We invite you to explore this Special Issue and gain valuable insights into the emerging approaches transforming data mining and NLP.

Dr. Arjun Mukherjee
Dr. Leonardo Ranaldi
Guest Editors

Giulia Pucci
Guest Editor Assistant
Department of Computing Science, University of Aberdeen, Aberdeen AB10, Scotland, UK
Email: [email protected]
Webpage: https://scholar.google.com/citations?user=FGRnGL8AAAAJ&hl=it
Interests: dialogue, priming, and studying the in-context dynamics of LLMs

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• data mining
• natural language processing
• sentiment analysis
• large language models