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This book is a collection of outstanding research papers presented at the World Conference on Artificial... Læs mere
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This book includes chapters which discuss effective and efficient approaches in dealing with various aspects of social media analysis by using machine learning techniques from clustering to deep learning.
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The book covers several entity and relation extraction techniques starting from the traditional feature-based techniques to the recent techniques using deep neural models.
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This open access book introduces Vector semantics, which links the formal theory of word vectors to the cognitive theory of linguistics.
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Deep reinforcement learning (DRL) is the combination of reinforcement learning (RL) and deep learning. The first part introduces the foundations of deep learning, reinforcement learning (RL) and widely used deep RL methods and discusses their implementation.
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Bemærk: Kan ikke leveres før jul.
This volume first explores the potential of machine translation of literature; goes on to explore possibilities for artificial literary... Læs mere
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This textbook provides a contemporary and comprehensive overview of Natural Language Processing (NLP), covering fundamental concepts, core algorithms, and key applications such as AI chatbots, Large Language Models and Generative AI.
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“Understanding natural language understanding”, i.e., understanding how the mind encodes and decodes meaning through language, is a significant milestone in our journey towards creating machines that genuinely comprehend human language.
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The author presents a variety of AQG system architectures, including generating questions from syntactic analyses, semantic resources, neural architectures, ontologies and knowledge graphs, and large language models.
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The use of Artificial Intelligence (AI) within social research has the potential to revolutionize the discipline, but it is crucial to regard the drawbacks... Læs mere