Akritidis Leonidas (10 results)

Hardback. Condition: New.

Condition: New.

Hardback. Condition: New.

HRD. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

HRD. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Condition: New. Print on Demand.

Condition: New. Print on Demand.

Condition: New. PRINT ON DEMAND.

Hardcover. Condition: new. Hardcover. The impressive achievements of recent state-of-the-art machine learning models are revolutionizing the area of text and language applications. On the one hand, popular large language models (LLMs) have demonstrated an enormous capability in automatic and reasonable text generation. On the other hand, Transformer-based models have drastically improved the performance of other, highly important natural language tools, including traditional sentiment analyzers, machine (auto)translators, and multimedia annotators. Furthermore, such natural language processing (NLP) techniques are heavily utilized in social networks, microblogs, eCommerce systems, and numerous other disciplines.This Reprint contains 10 high-quality, peer-reviewed original research papers in the field of natural language processing. These articles have been selected with the aim of providing the research community with insights that will open up new directions in this discipline. The authors of these papers have introduced new models, methods, and techniques related to large language models, sentiment analysis applications, effective text representations, text classification and text clustering. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The impressive achievements of recent state-of-the-art machine learning models are revolutionizing the area of text and language applications. On the one hand, popular large language models (LLMs) have demonstrated an enormous capability in automatic and reasonable text generation. On the other hand, Transformer-based models have drastically improved the performance of other, highly important natural language tools, including traditional sentiment analyzers, machine (auto)translators, and multimedia annotators. Furthermore, such natural language processing (NLP) techniques are heavily utilized in social networks, microblogs, eCommerce systems, and numerous other disciplines.This Reprint contains 10 high-quality, peer-reviewed original research papers in the field of natural language processing. These articles have been selected with the aim of providing the research community with insights that will open up new directions in this discipline. The authors of these papers have introduced new models, methods, and techniques related to large language models, sentiment analysis applications, effective text representations, text classification and text clustering.…