Mastering Text Classification: Cutting-edge Nlp Techniques - Rilegato

Rilegato

ISBN 10: 3031936116 ISBN 13: 9783031936111

Casa editrice: Springer Nature, 2025

Riassunto

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.

Su questo libro

Informazioni sull'autore

Dr. Mourad Abbas is research director at the High Council of Arabic, specializing in the dynamic field of natural language processing with a primary focus on the Arabic language and its diverse dialects. With a passion for pushing the boundaries of NLP, Dr. Abbas' research interests span a wide range of crucial topics, including machine translation, speech recognition, language identification, natural language understanding, and the challenges faced by under-resourced languages. Throughout his career, Dr. Abbas has made many contributions to the academic community, having published over sixty impactful papers. He has also played an important role in editing the proceedings of the International Conference on Natural Language and Speech Processing, featured in prestigious platforms like Elsevier, ACL Anthology, and IEEExplore. Recognized as an expert in his field, Dr. Abbas is actively engaged in peer review activities for distinguished journals, such as Language Resources and Evaluation, and Digital Signal Processing, along with conferences like ICASSP, Interspeech, Coling, and NAACL-HLT. 

Dalla quarta di copertina

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. 

• Explores methods for a variety of natural language processing (NLP) tasks for mastering text classification;
• Showcases applications of NLP in areas like named entity recognition for Arabic and its dialetcs and tackling multilingual and multitask text classification; 
• Presents challenges like limited annotated data and processing less-resourced languages.

Dettagli dell'edizione

• Editore: Springer Nature
• Data di pubblicazione: 2025
• Lingua: Inglese
• ISBN 10: 3031936116
• ISBN 13: 9783031936111
• Rilegatura: Copertina rigida
• Numero di pagine: 150
• Redattore: Abbas Mourad
• Contatto del produttore: ProductSafety@springernature.com; ProductSafety@springernature.com; ; Poststr. 9; Darmstadt; 64293; Germania