Natural Language Processing: Everything to Vector
(Sprache: Englisch)
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...
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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.
Autoren-Porträt von Xun Liang
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 250 papers and 20 books, and has applied for or obtained more than 50 invention patents.
Bibliographische Angaben
- Autor: Xun Liang
- 2021, 264 Seiten, Maße: 22 cm, Kartoniert (TB), Englisch
- Verlag: LAP Lambert Academic Publishing
- ISBN-10: 6204182099
- ISBN-13: 9786204182094
Sprache:
Englisch
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