Shulph Ink
Graph Learning and Network Science for Natural Language Processing
Graph Learning and Network Science for Natural Language Processing
💎 Earn 610 Points (£6.10) on this item.
YOU SAVE £3.00
- Condition: Brand new
- UK Delivery times: Usually arrives within 2 - 3 working days
- UK Shipping: Fee starts at £2.39. Subject to product weight & dimension
Bulk ordering. Want 15 or more copies? Get a personalised quote and bigger discounts. Learn more about bulk orders.
Couldn't load pickup availability
- More about Graph Learning and Network Science for Natural Language Processing
The book covers recent advances in graph-based natural language processing (NLP) and information retrieval, including neural network-based approaches, computational intelligence for learning parameters and feature reduction, and network science for graph-based NLP. It also discusses language generation based on graphical theories and language models.
Format: Hardback
Length: 256 pages
Publication date: 28 December 2022
Publisher: Taylor & Francis Ltd
Graph-based natural language processing (NLP) and information retrieval tasks have gained significant importance due to the advancements in graph-based learning. This comprehensive book delves into the latest developments in graph-based learning, encompassing neural network-based approaches, computational intelligence for learning parameters and feature reduction, and network science for graph-based NLP. It also provides valuable insights into language generation based on graphical theories and language models.
The book offers a comprehensive exploration of the interdisciplinary graphical approach to NLP, covering various aspects. It discusses recent computational intelligence techniques for graph-based neural network models, such as deep learning and convolutional neural networks. Moreover, it explores advances in random walk-based techniques, semantic webs, and lexical networks, which have played pivotal roles in NLP. The book also delves into recent research into NLP for graph-based streaming data, addressing the challenges of processing and analyzing large-scale graph datasets in real-time. Furthermore, it reviews advances in knowledge graph embedding and ontologies for NLP approaches, enabling more efficient and accurate representation of knowledge and relationships.
Designed for researchers and graduate students in computer science, natural language processing, and deep and machine learning, this book provides a thorough understanding of the latest trends and techniques in graph-based learning. It offers valuable insights and practical applications for those working in the field of NLP and related areas.
Weight: 660g
Dimension: 229 x 152 (mm)
ISBN-13: 9781032224565
This item can be found in:
UK and International shipping information
UK and International shipping information
UK Delivery and returns information:
- Delivery within 2 - 3 days when ordering in the UK.
- Shipping fee for UK customers from £2.39. Fully tracked shipping service available.
- Returns policy: Return within 30 days of receipt for full refund.
International deliveries:
Shulph Ink now ships to Australia, Belgium, Canada, France, Germany, Ireland, Italy, India, Luxembourg Saudi Arabia, Singapore, Spain, Netherlands, New Zealand, United Arab Emirates, United States of America.
- Delivery times: within 5 - 10 days for international orders.
- Shipping fee: charges vary for overseas orders. Only tracked services are available for most international orders. Some countries have untracked shipping options.
- Customs charges: If ordering to addresses outside the United Kingdom, you may or may not incur additional customs and duties fees during local delivery.
