| 000 -LEADER |
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| fixed length control field |
a |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
250225b xxu||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9783031272257 |
| Terms of availability |
(hbk) |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Classification number |
006.35 |
| Item number |
HAR |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Haralambous, Yannis |
| 245 ## - TITLE STATEMENT |
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| Title |
A course in natural language processing |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
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| Name of publisher, distributor, etc |
Springer, |
| Date of publication, distribution, etc |
2024 |
| Place of publication, distribution, etc |
Cjham : |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xvii, 534 p. ; |
| Other physical details |
ill., (some col.), |
| Dimensions |
25 cm |
| 365 ## - TRADE PRICE |
|---|
| Price amount |
99.99 |
| Price type code |
€ |
| Unit of pricing |
93.20 |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
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| Bibliography, etc |
Includes bibliographical references and index. |
| 520 ## - SUMMARY, ETC. |
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| Summary, etc |
Natural Language Processing is the branch of Artificial Intelligence involving language, be it in spoken or written modality. Teaching Natural Language Processing (NLP) is difficult because of its inherent connections with other disciplines, such as Linguistics, Cognitive Science, Knowledge Representation, Machine Learning, Data Science, and its latest avatar: Deep Learning. Most introductory NLP books favor one of these disciplines at the expense of others. Based on a course on Natural Language Processing taught by the author at IMT Atlantique for over a decade, this textbook considers three points of view corresponding to three different disciplines, while granting equal importance to each of them. As such, the book provides a thorough introduction to the topic following three main threads: the fundamental notions of Linguistics, symbolic Artificial Intelligence methods (based on knowledge representation languages), and statistical methods (involving both legacy machine learning and deep learning tools). Complementary to this introductory text is teaching material, such as exercises and labs with hints and expected results. Complete solutions with Python code are provided for educators on the SpringerLink webpage of the book. This material can serve for classes given to undergraduate and graduate students, or for researchers, instructors, and professionals in computer science or linguistics who wish to acquire or improve their knowledge in the field. The book is suitable and warmly recommended for self-study. With a PhD in Algebraic Topology (Lille, 1990), Yannis Haralambous is a TeX aficionado and Full Professor at IMT Atlantique in Brest, France. His research interests cover Text Mining, Controlled Natural Languages, Knowledge Representation, and Grapholinguistics, topics in which he has published over 120 research or scientific popularization papers and a book on Fonts and Encodings (O’Reilly, 2007). He is in charge of IMT Atlantique’s “Data Science” Master track program, where he has been teaching the course that inspired this book. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Artificial intelligence |
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| Topical term or geographic name as entry element |
Computational linguistics |
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| Topical term or geographic name as entry element |
Natural language processing |
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| Topical term or geographic name as entry element |
Computational Linguistics |
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| Topical term or geographic name as entry element |
Controlled Natural Languages |
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| Topical term or geographic name as entry element |
Formal Languages |
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| Topical term or geographic name as entry element |
Graphemics |
|
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| Topical term or geographic name as entry element |
LaTeX |
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| Topical term or geographic name as entry element |
Natural Language Processing |
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| Topical term or geographic name as entry element |
Semantics |
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| Topical term or geographic name as entry element |
Syntax |
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| Topical term or geographic name as entry element |
Text Mining |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
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| Source of classification or shelving scheme |
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| Item type |
Books |