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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.

Natural language processing (Computer science) --- Natural language processing (Computer science). --- Computational linguistics. --- Expert systems (Computer science). --- Artificial intelligence --- Machine learning. --- Artificial intelligence. --- Natural Language Processing (NLP). --- Computational Linguistics. --- Knowledge Based Systems. --- Data Science. --- Machine Learning. --- Symbolic AI. --- Data processing.

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Computer: lettertypes. --- Computer:typografie. --- Fonts. --- Character sets (Data processing) --- Computer fonts --- Type and type-founding --- Unicode (Computer character set) --- Web typography --- 655.2 --- 766:655.2 --- Typografie ; fonts ; computerletters ; naslagwerken --- Typography, Web --- Graphic design (Typography) --- Digital type and type-founding --- Digital electronics --- Fonts, Computer --- Font editors --- Character codes (Data processing) --- Coded character sets (Data processing) --- Programming languages (Electronic computers) --- Sets, Character (Data processing) --- Symbol sets (Data processing) --- Alphabet --- Signs and symbols --- Digital techniques --- Grafische industrie ; typografie ; letterzetten --- Gebruiksgrafiek ; typografie --- Character sets --- Data processing --- 766.22.02 --- Grafische industrie en ontwerp ; schrift ; typografie ; technieken

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This volume contains the papers that were accepted for presentation at the International Conference on T X,XML, and Digital Typography, jointly held with E the 25th Annual Meeting of the T X Users Group in Xanthi, Greece in the sum- E mer of 2004. The term “Digital Typography” refers to the preparation of printed matter using only electronic computers and electronic printing devices, such as laser-jet printers. The document preparation process involves mainly the use of a digital typesetting system as well as data representation technologies. TXand E its offspring are beyond doubt the most successful current digital typesetters, while XML is the standard for text-based data representation for both business and scientific activities. All papers appearing in this volume were fully refereed by the members of the program committee. The papers were carefully selected to reflect the research work that is being done in the field of digital typography using T X and/or its E o?spring. The problems for which comprehensive solutions have been proposed include proper multilingual document preparation and XML document processing and generation. The proposed solutions deal not simply with typesetting issues, but also related issues in document preparation, such as the manipulation of complex bibliographic databases, and automatic conversion of text expressed in one grammatical system to a more recent one (as for the Greek language,converting between monotonic Greek and polytonic Greek). The conference is being graciously hosted by the Democritus University of Thrace in Xanthi and by the Greek T X Friends. We wish to thank Basil K.

Computer science. --- Text processing (Computer science. --- Computer Science. --- Document Preparation and Text Processing. --- Computerized typesetting --- XML (Document markup language) --- Type and type-founding --- Book Studies & Arts --- Education --- Social Sciences --- Digital techniques --- Digital techniques. --- TeX (Computer file) --- Digital type and type-founding --- Automated typesetting --- Computer typesetting --- Typesetting --- Computer programs --- Data processing --- Tau epsilon chi --- TeX (Computer system) --- Text processing (Computer science). --- Digital electronics --- Word processing --- Natural language processing (Computer science). --- Natural Language Processing (NLP). --- NLP (Computer science) --- Artificial intelligence --- Electronic data processing --- Human-computer interaction --- Semantic computing --- Natural language processing (Computer science)