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Ein Kurs in natürlicher Sprachverarbeitung von Yannis Haralambous Hardcover Buch-
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eBay-Artikelnr.:396898078802
Artikelmerkmale
- Artikelzustand
- ISBN-13
- 9783031272257
- Book Title
- A Course in Natural Language Processing
- ISBN
- 9783031272257
Über dieses Produkt
Product Identifiers
Publisher
Springer International Publishing A&G
ISBN-10
3031272250
ISBN-13
9783031272257
eBay Product ID (ePID)
28058807473
Product Key Features
Number of Pages
Xvii, 534 Pages
Language
English
Publication Name
Course in Natural Language Processing
Subject
Expert Systems, General, Linguistics / General, Speech & Audio Processing
Publication Year
2024
Type
Textbook
Subject Area
Mathematics, Computers, Language Arts & Disciplines
Format
Hardcover
Dimensions
Item Weight
34.8 Oz
Item Length
9.3 in
Item Width
6.1 in
Additional Product Features
Dewey Edition
23
TitleLeading
A
Number of Volumes
1 vol.
Illustrated
Yes
Dewey Decimal
006.35
Table Of Content
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.
Synopsis
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.
LC Classification Number
QA76.9.N38
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