Formalizing Natural Languages with NooJ 2019 and Its Natural Language Processing Applications -
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Présentation Formalizing Natural Languages With Nooj 2019 And Its Natural Language Processing Applications Format Broché
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Résumé :
This book constitutes the refereed proceedings of the 13th International Conference, NooJ 2019, held in Hammamet, Tunisia, in June 2019. NooJ is a linguistic development environment that allows linguists to formalize several levels of linguistic phenomena. NooJ provides linguists with tools to develop dictionaries, regular grammars, context-free grammars, context-sensitive grammars and unrestricted grammars as well as their graphical equivalent to formalize each linguistic phenomenon. The 18 full papers presented were carefully reviewed and selected from 54 submissions. The papers are organized in the following tracks: Development of Linguistic Resources, Natural Language Processing Applications, NooJ for the Digital Humanities.
Sommaire:
Recognition of Arabic Phonological Changes by Local Grammars in NooJ.- Lexicon-grammar tables development for Arabic psychological verbs.- The Identification of English Non-Finite Structures Using NooJ Platform.- Automatic recognition and translation of polysemous verbs using the platform NooJ.- Negation of Croatian Nouns.- The automatic generation of NooJ dictionaries from lexicon-grammar tables.- The Data Scientist on LinkedIn: Job advertisement corpus processing with NooJ.- Mining entrepreneurial commitment in university communication: evidence from Italy.- Disambiguation for Arabic Question-Answering system.- Recognition and analysis of opinion questions in standard Arabic.- Automatic Text Generation: How to Write the Plot of a Novel with NooJ.- Arabic learning application to enhance the Educational process in Moroccan MidHigh stage using NooJ platform.- (SLF) for Portuguese Learners using NooJ.- Construction of Educational Games with NooJ.- Detecting Hate Speech Online: A Case ofCroatian.- Dealing with Producing and Consuming Expressions in Italian Sentiment Analysis.- Rule based method for terrorism, violence and threat classification: application to Arabic Tweets.
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