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Graph Learning and Network Science for Natural Language  by Muskan Garg HARDBACK
Graph Learning and Network Science for Natural Language  by Muskan Garg HARDBACK
Graph Learning and Network Science for Natural Language  by Muskan Garg HARDBACK
Graph Learning and Network Science for Natural Language  by Muskan Garg HARDBACK
Graph Learning and Network Science for Natural Language  by Muskan Garg HARDBACK

Graph Learning and Network Science for Natural Language by Muskan Garg HARDBACK

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Brand new product\nFree UK standard delivery 2-3 days from despatch\nTracked secure courier\nPlease check delivery times at top of listing\nBookCurl is a family bookseller - thank you for your business\n\nAdvances 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.\nFeatures:\n--Presents a comprehensive study of the interdisciplinary graphical approach to NLP\n--Covers recent computational intelligence techniques for graph-based neural network models\n--Discusses advances in random walk-based techniques, semantic webs, an/

Graph Learning and Network Science for Natural Language by Muskan Garg HARDBACK

Brand new product\nFree UK standard delivery 2-3 days from despatch\nTracked secure courier\nPlease check delivery times at top of listing\nBookCurl is a family bookseller - thank you for your business\n\nAdvances 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.\nFeatures:\n--Presents a comprehensive study of the interdisciplinary graphical approach to NLP\n--Covers recent computational intelligence techniques for graph-based neural network models\n--Discusses advances in random walk-based techniques, semantic webs, an/

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