Advances in graph-based natural language processing (NLP) and information retrieval tasks have shown the importance of processing using the Graph of Words method. This book covers recent concrete information, from the basics to advanced level, about graph-based learning, such as neural network-based approaches, computational intelligence for learning parameters and feature reduction, and network science for graph-based NPL. It also contains information about language generation based on graphical theories and language models.

Features:

Presents a comprehensive study of the interdisciplinary graphical approach to NLP Covers recent computational intelligence techniques for graph-based neural network models Discusses advances in random walk-based techniques, semantic webs, and lexical networks Explores recent research into NLP for graph-based streaming data Reviews advances in knowledge graph embedding and ontologies for NLP approaches

This book is aimed at researchers and graduate students in computer science, natural language processing, and deep and machine learning.

Advances in graph-based natural language processing (NLP) and information retrieval tasks have shown the importance of processing using the Graph of Words method. This book covers recent concrete information, from the basics to advanced level, about graph-based learning, such as neural network-based approaches, computational intelligence for learning parameters and feature reduction, and network science for graph-based NPL. It also contains information about language generation based on graphical theories and language models.

Features:

Presents a comprehensive study of the interdisciplinary graphical approach to NLP Covers recent computational intelligence techniques for graph-based neural network models Discusses advances in random walk-based techniques, semantic webs, and lexical networks Explores recent research into NLP for graph-based streaming data Reviews advances in knowledge graph embedding and ontologies for NLP approaches

This book is aimed at researchers and graduate students in computer science, natural language processing, and deep and machine learning.

Advances in graph-based natural language processing (NLP) and information retrieval tasks have shown the importance of processing using the Graph of Words method. This book covers recent concrete information, from the basics to advanced level, about graph-based learning, such as neural network-based approaches, computational intelligence for learning parameters and feature reduction, and network science for graph-based NPL. It also contains information about language generation based on graphical theories and language models.Features:Presents a comprehensive study of the interdisciplinary graphical approach to NLPCovers recent computational intelligence techniques for graph-based neural network modelsDiscusses advances in random walk-based techniques, semantic webs, and lexical networksExplores recent research into NLP for graph-based streaming dataReviews advances in knowledge graph embedding and ontologies for NLP approachesThis book is aimed at researchers and graduate students in computer science, natural language processing, and deep and machine learning.

Advances in graph-based natural language processing (NLP) and information retrieval tasks have shown the importance of processing using the Graph of Words method. This book covers recent concrete information, from the basics to advanced level, about graph-based learning, such as neural network-based approaches, computational intelligence for learning parameters and feature reduction, and network science for graph-based NPL. It also contains information about language generation based on graphical theories and language models.Features:Presents a comprehensive study of the interdisciplinary graphical approach to NLPCovers recent computational intelligence techniques for graph-based neural network modelsDiscusses advances in random walk-based techniques, semantic webs, and lexical networksExplores recent research into NLP for graph-based streaming dataReviews advances in knowledge graph embedding and ontologies for NLP approachesThis book is aimed at researchers and graduate students in computer science, natural language processing, and deep and machine learning.

Cultural Transformation: The Making of Modern Europe offers a care­fully structured and conceptually grounded account of Europe’s journey from the medieval world to modernity, with culture placed at the centre of historical explanation. Rather than treating political events or economic change in isolation, the book shows how shifts in ideas, social practices, everyday life and material conditions interacted to reshape European society between roughly the fifteenth and eighteenth centuries. It asks students to see modern Europe not as an inevitable outcome but as the product of layered choices, conflicts and adaptations.The study moves from classical and medieval inheritances to the major turning points of early modern history, including the Renaissance, the Reformation, overseas expansion, the Scientific Revolution, the Enlightenment and the Industrial Revolution. Across these themes, attention is given not only to high cultured thinkers and institutions but also to artisans, merchants, families and ordinary believers whose lives reflected and carried cultural change. Discussions of art, science, religion, food, architecture, fashion and domestic life help readers understand how abstract ideas were lived and experienced. Concepts such as humanism, capitalism, secularisation and modernity are ex­plained through concrete historical examples.Written with undergraduate teaching needs in mind, the book en­gages major historiographical debates while remaining clear and read­able. It aligns closely with the University of Delhi syllabus on the Rise of the Modern West and Cultural Transformation, yet it also speaks to a wider audience interested in how societies change over time. By treating culture as a dynamic force rather than a background detail, this book encourages readers to think critically about Europe’s past and to reflect on how historical transformations continue to shape the present.

Advances in graph-based natural language processing (NLP) and information retrieval tasks have shown the importance of processing using the Graph of Words method. This book covers recent concrete information, from the basics to advanced level, about graph-based learning, such as neural network-based approaches, computational intelligence for learning parameters and feature reduction, and network science for graph-based NPL. It also contains information about language generation based on graphical theories and language models.

Features:

Presents a comprehensive study of the interdisciplinary graphical approach to NLP Covers recent computational intelligence techniques for graph-based neural network models Discusses advances in random walk-based techniques, semantic webs, and lexical networks Explores recent research into NLP for graph-based streaming data Reviews advances in knowledge graph embedding and ontologies for NLP approaches

This book is aimed at researchers and graduate students in computer science, natural language processing, and deep and machine learning.

Advances in graph-based natural language processing (NLP) and information retrieval tasks have shown the importance of processing using the Graph of Words method. This book covers recent concrete information, from the basics to advanced level, about graph-based learning, such as neural network-based approaches, computational intelligence for learning parameters and feature reduction, and network science for graph-based NPL. It also contains information about language generation based on graphical theories and language models.

Features:

Presents a comprehensive study of the interdisciplinary graphical approach to NLP Covers recent computational intelligence techniques for graph-based neural network models Discusses advances in random walk-based techniques, semantic webs, and lexical networks Explores recent research into NLP for graph-based streaming data Reviews advances in knowledge graph embedding and ontologies for NLP approaches

This book is aimed at researchers and graduate students in computer science, natural language processing, and deep and machine learning.

Advances in graph-based natural language processing (NLP) and information retrieval tasks have shown the importance of processing using the Graph of Words method. This book covers recent concrete information, from the basics to advanced level, about graph-based learning, such as neural network-based approaches, computational intelligence for learning parameters and feature reduction, and network science for graph-based NPL. It also contains information about language generation based on graphical theories and language models.Features:Presents a comprehensive study of the interdisciplinary graphical approach to NLPCovers recent computational intelligence techniques for graph-based neural network modelsDiscusses advances in random walk-based techniques, semantic webs, and lexical networksExplores recent research into NLP for graph-based streaming dataReviews advances in knowledge graph embedding and ontologies for NLP approachesThis book is aimed at researchers and graduate students in computer science, natural language processing, and deep and machine learning.

Advances in graph-based natural language processing (NLP) and information retrieval tasks have shown the importance of processing using the Graph of Words method. This book covers recent concrete information, from the basics to advanced level, about graph-based learning, such as neural network-based approaches, computational intelligence for learning parameters and feature reduction, and network science for graph-based NPL. It also contains information about language generation based on graphical theories and language models.Features:Presents a comprehensive study of the interdisciplinary graphical approach to NLPCovers recent computational intelligence techniques for graph-based neural network modelsDiscusses advances in random walk-based techniques, semantic webs, and lexical networksExplores recent research into NLP for graph-based streaming dataReviews advances in knowledge graph embedding and ontologies for NLP approachesThis book is aimed at researchers and graduate students in computer science, natural language processing, and deep and machine learning.

Cultural Transformation: The Making of Modern Europe offers a care­fully structured and conceptually grounded account of Europe’s journey from the medieval world to modernity, with culture placed at the centre of historical explanation. Rather than treating political events or economic change in isolation, the book shows how shifts in ideas, social practices, everyday life and material conditions interacted to reshape European society between roughly the fifteenth and eighteenth centuries. It asks students to see modern Europe not as an inevitable outcome but as the product of layered choices, conflicts and adaptations.The study moves from classical and medieval inheritances to the major turning points of early modern history, including the Renaissance, the Reformation, overseas expansion, the Scientific Revolution, the Enlightenment and the Industrial Revolution. Across these themes, attention is given not only to high cultured thinkers and institutions but also to artisans, merchants, families and ordinary believers whose lives reflected and carried cultural change. Discussions of art, science, religion, food, architecture, fashion and domestic life help readers understand how abstract ideas were lived and experienced. Concepts such as humanism, capitalism, secularisation and modernity are ex­plained through concrete historical examples.Written with undergraduate teaching needs in mind, the book en­gages major historiographical debates while remaining clear and read­able. It aligns closely with the University of Delhi syllabus on the Rise of the Modern West and Cultural Transformation, yet it also speaks to a wider audience interested in how societies change over time. By treating culture as a dynamic force rather than a background detail, this book encourages readers to think critically about Europe’s past and to reflect on how historical transformations continue to shape the present.