Natural language processing is a discipline that integrates computer science, linguistics and mathematics. A common view is that knowledge graph is the cornerstone of natural language processing. Vectorization is an essential step in natural language processing and knowledge graph. Vector space is by far the most complete and perfect modeling space in mathematics. A vector can be used to represent any object in a linear space as long as a suitable basis is found. Natural language can also be mapped to a vector space and transformed into a machine-friendly form - a vector - that allows computers to process it quickly. Once vectors are obtained, they can be analyzed using various mathematical tools. It is from vectorization that this book brings together natural language processing and knowledge graphs, combines different application perspectives, introduces the way to vectorize different research objects from multiple dimensions, and further proposes an everything2vector model.
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Natural language processing is a discipline that integrates computer science, linguistics and mathematics. A common view is that knowledge graph is the cornerstone of natural language processing. Vectorization is an essential step in natural language processing and knowledge graph. Vector space is by far the most complete and perfect modeling space in mathematics. A vector can be used to represent any object in a linear space as long as a suitable basis is found. Natural language can also be mapped to a vector space and transformed into a machine-friendly form - a vector - that allows computers to process it quickly. Once vectors are obtained, they can be analyzed using various mathematical tools. It is from vectorization that this book brings together natural language processing and knowledge graphs, combines different application perspectives, introduces the way to vectorize different research objects from multiple dimensions, and further proposes an everything2vector model. 264 pp. Englisch. Seller Inventory # 9786204182094
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Liang XunXun Liang has worked in the fields of social networks, machine learning, and financial information systems for more than 20 years. He is the chief expert of many research and industrial projects. He has published more than 2. Seller Inventory # 490749826
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Natural language processing is a discipline that integrates computer science, linguistics and mathematics. A common view is that knowledge graph is the cornerstone of natural language processing. Vectorization is an essential step in natural language processing and knowledge graph. Vector space is by far the most complete and perfect modeling space in mathematics. A vector can be used to represent any object in a linear space as long as a suitable basis is found. Natural language can also be mapped to a vector space and transformed into a machine-friendly form - a vector - that allows computers to process it quickly. Once vectors are obtained, they can be analyzed using various mathematical tools. It is from vectorization that this book brings together natural language processing and knowledge graphs, combines different application perspectives, introduces the way to vectorize different research objects from multiple dimensions, and further proposes an everything2vector model.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 264 pp. Englisch. Seller Inventory # 9786204182094
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Natural language processing is a discipline that integrates computer science, linguistics and mathematics. A common view is that knowledge graph is the cornerstone of natural language processing. Vectorization is an essential step in natural language processing and knowledge graph. Vector space is by far the most complete and perfect modeling space in mathematics. A vector can be used to represent any object in a linear space as long as a suitable basis is found. Natural language can also be mapped to a vector space and transformed into a machine-friendly form - a vector - that allows computers to process it quickly. Once vectors are obtained, they can be analyzed using various mathematical tools. It is from vectorization that this book brings together natural language processing and knowledge graphs, combines different application perspectives, introduces the way to vectorize different research objects from multiple dimensions, and further proposes an everything2vector model. Seller Inventory # 9786204182094
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Taschenbuch. Condition: Neu. Natural Language Processing: Everything to Vector | Xun Liang | Taschenbuch | Englisch | 2021 | LAP LAMBERT Academic Publishing | EAN 9786204182094 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Seller Inventory # 120379240
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