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NATURAL LANGUAGE PROCESSING

CODICE 90541
ANNO ACCADEMICO 2021/2022
CFU
  • 6 cfu al 2° anno di 10852 COMPUTER SCIENCE (LM-18) - GENOVA
    		•
    SETTORE SCIENTIFICO DISCIPLINARE INF/01
    LINGUA Inglese
    SEDE
  • GENOVA
    		•
    PERIODO 1° Semestre
    MATERIALE DIDATTICO AULAWEB

    PRESENTAZIONE

    The Natural Language Processing course provides an introduction to the most challenging issues in processing natural languages, driven by the three layers of syntax, semantics, pragmatics; the most recent applications of natural language processing tools are discussed, including the design and development of ontologies and of chatbots. 

    OBIETTIVI E CONTENUTI

    OBIETTIVI FORMATIVI

    Learning how to process and represent natural language, and the main software components of a system able to understand natural language.

    OBIETTIVI FORMATIVI (DETTAGLIO) E RISULTATI DI APPRENDIMENTO

    After the course students will be able to use existing tools and design and implement new ones for solving Natural Language Processing problems at the syntactic and semantic level. They will also be able to design and implement a chatbot using one of the most widespread chatbot languages. 

    MODALITA' DIDATTICHE

    Traditional: frontal lessons and laboratories

    PROGRAMMA/CONTENUTO

    NLP Introduction and Terminology
    Regular Expressions
    Syntax at Word Level: Stop Words, TF-IDF, Stemming, Normalization, Minimum Edit Distance
    Syntax at Sentence Level: Grammars, Part Of Speech (POS) Tagging with Definite Clause Grammars, POS Tagging with Hidden Markov Models, A critical comparison of DCG and HMM for POS Tagging
    Semantics: Distributional semantics, word2vect, Frame Semantics, Model-theoretic semantics, Lexical Semantics, WordNet, BabelNet, Named Entity Recognition, Ontologies and the Semantic Web, Ontologies and their applications, Ontology Learning and Ontology Matching
    Pragmatics
    NLP applications and recap of the Most common (non-trivial) NLP features, with examples of how and when using them
    Applications: Chatbots​

    TESTI/BIBLIOGRAFIA

    The notes of the course

    DOCENTI E COMMISSIONI

    Commissione d'esame

    VIVIANA MASCARDI (Presidente)

    BARBARA CATANIA

    GIOVANNA GUERRINI (Presidente Supplente)

    LEZIONI

    Orari delle lezioni

    L'orario di tutti gli insegnamenti è consultabile su EasyAcademy.

    ESAMI

    MODALITA' D'ESAME

    The exam will consist in a quiz, a written part (traditional open/closed questions, exercises) plus an individual project (requiring about 1 man/week to be completed).

    MODALITA' DI ACCERTAMENTO

    The acquisition of the skills foreseen by this course will be assessed via the quiz and written exam + the project which have been carefully designed to allow the teachers to verify whether a student is actually able to design and implement a tool solving some (simplified) NLP problem and to understand, present and discuss in a critical way the most challenging issues raised by its development.

    Calendario appelli

    Data Ora Luogo Tipologia Note
    22/07/2022 09:00 GENOVA Esame su appuntamento
    16/09/2022 09:00 GENOVA Esame su appuntamento
    10/02/2023 09:00 GENOVA Esame su appuntamento