04400nam a22005055i 4500001001800000003000900018005001700027007001500044008004100059020001800100024003500118050001500153072001700168072002300185072001600208100008200224245009300306250001800399264007500417300006700492336002600559337002600585338003600611347002400647505054700671520208701218650005203305650003103357650003903388650004603427650002203473650002903495650003903524650003103563650002903594650001803623650002203641650001703663710003403680773002603714776003603740776003603776776003603812856004603848978-3-031-27226-4DE-He21320251030111406.0cr nn 008mamaa240130s2024    sz |    s    |||| 0|eng d  a97830312722647 a10.1007/978-3-031-27226-42doi 4aQA76.9.N38 7aUYQL2bicssc 7aCOM0730002bisacsh 7aUYQL2thema1 aHaralambous, Yannis.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut12aA Course in Natural Language Processingh[electronic resource] /cby Yannis Haralambous.  a1st ed. 2024. 1aCham :bSpringer International Publishing :bImprint: Springer,c2024.  aXVII, 534 p. 102 illus., 74 illus. in color.bonline resource.  atextbtxt2rdacontent  acomputerbc2rdamedia  aonline resourcebcr2rdacarrier  atext filebPDF2rda0 aPreface -- 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.  aNatural 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. 0aNatural language processing (Computer science). 0aComputational linguistics. 0aExpert systems (Computer science). 0aArtificial intelligencexData processing. 0aMachine learning. 0aArtificial intelligence.14aNatural Language Processing (NLP).24aComputational Linguistics.24aKnowledge Based Systems.24aData Science.24aMachine Learning.24aSymbolic AI.2 aSpringerLink (Online service)0 tSpringer Nature eBook08iPrinted edition:z978303127225708iPrinted edition:z978303127227108iPrinted edition:z978303127228840uhttps://doi.org/10.1007/978-3-031-27226-4