Mastering Text Classification
Cutting-Edge NLP Techniques
Series: Signals and Communication Technology;
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66 563 Ft
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Product details:
- Publisher Springer Nature Switzerland
- Date of Publication 12 October 2025
- Number of Volumes 1 pieces, Book
- ISBN 9783031936111
- Binding Hardback
- No. of pages142 pages
- Size 235x155 mm
- Language English
- Illustrations VII, 142 p. 51 illus., 36 illus. in color. Illustrations, black & white 700
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Long description:
This book provides cutting-edge natural language processing (NLP) techniques to unlock the power of text data. It presents advanced methods for various text classification tasks, like discourse relation classification, classification in large taxonomies, and leveraging disagreement between annotators for text classification.
This book equips readers whether they are researchers or professionals, looking to apply NLP in real-world settings, with the latest advancements, and gives them the opportunity to explore techniques to handle limited data, and harness the power of pre-trained language models like BERT. By the end, readers will be equipped to tackle specific text classification challenges and advance the field of NLP.
MoreTable of Contents:
Introduction.- Handling Realistic Label Noise in BERT Text Classification.- Discourse Relations Classification and Cross-Framework Discourse Relation Classification through the Lens of Cognitive Dimensions: An Empirical Investigation.- Representation Learning for Hierarchical Classification of Entity Titles.- DAP-LeR-DAug: Techniques for enhanced Online Sexism Detection.- Automatic Detection of Generalized Patterns of Vossian Antonomasia.- Exploring BERT Models for Part-of-Speech Tagging in the Algerian Dialect.- Deep Learning-Based Claim Matching with Multiple Negatives Training.- A Neural Network Approach to Ellipsis Detection in Ancient Greek.- Conclusion.
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