A Course in Natural Language Processing (Record no. 87405)
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| fixed length control field | 04748nam a22005895i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 978-3-031-27226-4 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20240730171123.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 240130s2024 sz | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9783031272264 |
| -- | 978-3-031-27226-4 |
| 082 04 - CLASSIFICATION NUMBER | |
| Call Number | 006.35 |
| 100 1# - AUTHOR NAME | |
| Author | Haralambous, Yannis. |
| 245 12 - TITLE STATEMENT | |
| Title | A Course in Natural Language Processing |
| 250 ## - EDITION STATEMENT | |
| Edition statement | 1st ed. 2024. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | XVII, 534 p. 102 illus., 74 illus. in color. |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Remark 2 | Preface -- 1. Introduction -- Part I. Linguistics -- 2. Phonetics/Phonology -- 3. Graphetics/Graphemics -- 4. Morphemes, Words, Terms -- 5. Syntax -- 6. Semantics (and Pragmatics) -- 7. Controlled Natural Languages -- Part II. Mathematical Tools -- 8. Graphs -- 9. Formal Languages -- 10. Logic -- 11 -- Ontologies and Conceptual Graphs -- Part III. Data Formats -- 12. Unicode -- 13. XML, TEI, CDL -- Part IV. Statistical Methods -- 14. Counting Words -- 15. Going Neural -- 16. Hints and Expected Results for Exercises -- Acronyms -- Index. |
| 520 ## - SUMMARY, ETC. | |
| 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 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| General subdivision | Data processing. |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | https://doi.org/10.1007/978-3-031-27226-4 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | eBooks |
| 264 #1 - | |
| -- | Cham : |
| -- | Springer International Publishing : |
| -- | Imprint: Springer, |
| -- | 2024. |
| 336 ## - | |
| -- | text |
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| -- | computer |
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| -- | online resource |
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| -- | text file |
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| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Natural language processing (Computer science). |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computational linguistics. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Expert systems (Computer science). |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Artificial intelligence |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Machine learning. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Artificial intelligence. |
| 650 14 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Natural Language Processing (NLP). |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computational Linguistics. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Knowledge Based Systems. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Data Science. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Machine Learning. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Symbolic AI. |
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| -- | ZDB-2-SCS |
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