000			a
999			_c33733 _d33733
008			250225b xxu||||| |||| 00| 0 eng d
020			_a9783031272257 _c(hbk)
082			_a006.35 _bHAR
100			_aHaralambous, Yannis
245			_aA course in natural language processing
260			_bSpringer, _c2024 _aCjham :
300			_axvii, 534 p. ; _bill., (some col.), _c25 cm
365			_b99.99 _c€ _d93.20
504			_aIncludes bibliographical references and index.
520			_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.
650			_aArtificial intelligence
650			_aComputational linguistics
650			_aNatural language processing
650			_aComputational Linguistics
650			_aControlled Natural Languages
650			_aFormal Languages
650			_aGraphemics
650			_aLaTeX
650			_aNatural Language Processing
650			_aSemantics
650			_aSyntax
650			_aText Mining
942			_2ddc _cBK