Computational Linguistics and Natural Language Processing

This chapter provides an introduction to computational linguistics methods, with focus on their applications to the practice and study of translation. It covers computational models, methods and tools for collection, storage, indexing and analysis of linguistic data in the context of translation, and discusses the main methodological issues and challenges in this field. While an exhaustive review of existing computational linguistics methods and tools is beyond the scope of this chapter, we describe the most representative approaches, and illustrate them with descriptions of typical applications.Comment: This is the unedited author's copy of a text which appeared as a chapter in "The Routledge Handbook of Translation and Methodology'', edited by F Zanettin and C Rundle (2022

Editorial for the First Workshop on Mining Scientific Papers: Computational Linguistics and Bibliometrics

The workshop "Mining Scientific Papers: Computational Linguistics and Bibliometrics" (CLBib 2015), co-located with the 15th International Society of Scientometrics and Informetrics Conference (ISSI 2015), brought together researchers in Bibliometrics and Computational Linguistics in order to study the ways Bibliometrics can benefit from large-scale text analytics and sense mining of scientific papers, thus exploring the interdisciplinarity of Bibliometrics and Natural Language Processing (NLP). The goals of the workshop were to answer questions like: How can we enhance author network analysis and Bibliometrics using data obtained by text analytics? What insights can NLP provide on the structure of scientific writing, on citation networks, and on in-text citation analysis? This workshop is the first step to foster the reflection on the interdisciplinarity and the benefits that the two disciplines Bibliometrics and Natural Language Processing can drive from it.Comment: 4 pages, Workshop on Mining Scientific Papers: Computational Linguistics and Bibliometrics at ISSI 201

COMPUTATIONAL LINGUISTICS (Model Baru Kajian Linguistik dalam Perspektif Komputer)

This paper describes a new discipline in applied linguistics studies, computational linguistics. It’s a new model of applied linguistics which is influenced by computer technology. Computational linguistics is a discipline straddling applied linguistics and computer science that is concerned with the computer processing of natural languages on all levels of linguistic description. Traditionally, computational linguistics was usually performed by computer scientists who had specialized in the application of computers to the processing of a natural language. Computational linguists often work as members of interdisciplinary teams, including linguists (specifically trained in linguistics), language experts (persons with some level of ability in the languages relevant to a given project), and computer scientists. The several areas of computational linguistics study encompasses such practical applications as speech recognition systems, speech synthesis, automated voice response systems, web search engines, text editors, grammar checking, text to speech, corpus linguistics, machine translation, text data mining, and others. This paper presents the definition of computational linguistics, relation between language and computer, and area of computational linguistics studies

Natural Language Processing: Between Theoretical and Computational Linguistics

This research discusses how both theoretical linguistics and computational linguistics process natural language by clarifying the foundations which the two fields are based on. Also, this study attempts to analyze the differences and convergences that can lay a clear foundation for linguistics to be computed by studying the goals and operational procedures in different language systems such as morphology, phonetics, syntax and semantics. The research consists of an introduction and two sections. The first one is theoretical, explaining the linguistic theory with its two parts: Arabic and Western. Then the concept of computational linguistics and its role in studying, understanding, and generating the natural language processing is explored. The second section is applied, discussing the difference between theoretical linguistics and computational theories in terms of their starting points, their objectives, and the way they process linguistic systems. The research aims to represent computational procedures using linguistics in computers in order to achieve the goals of users of natural language in an ideal way

Proceedings of the Seventh Italian Conference on Computational Linguistics CLiC-it 2020

On behalf of the Program Committee, a very warm welcome to the Seventh Italian Conference on Computational Linguistics (CLiC-it 2020). This edition of the conference is held in Bologna and organised by the University of Bologna. The CLiC-it conference series is an initiative of the Italian Association for Computational Linguistics (AILC) which, after six years of activity, has clearly established itself as the premier national forum for research and development in the fields of Computational Linguistics and Natural Language Processing, where leading researchers and practitioners from academia and industry meet to share their research results, experiences, and challenges

La constitution du TAL: Étude historique des dénominations et des concepts

Several terms have been in competition as names for the theoretical and applieddiscipline that lies in the intersection of linguistics, mathematics, computer sciences andcognitive sciences and which developed out of early experiments in Machine Translation.They include Computational Linguistics and Natural Language Processing in English, andTraitement automatique des langues, Informatique linguistique and Linguistique informatiquein French. This paper traces the history of these terms and considers whether theterminological variation may be a symptom of the conflicts at work in the field, concerningthe institutional, economical, theoretical and conceptual issues.Pour désigner le champ d'investigations et d'applications à l'intersection de lalinguistique, des mathématiques, de l'informatique et des sciences cognitives hérité desexpériences pionnières en traduction automatique, plusieurs termes sont ou ont été enconcurrence, Computational Linguistics ou Natural Language Processing dans le domaineanglo-américain, Traitement automatique des langues, Informatique linguistique ouLinguistique informatique en France. Cet article se propose, en retraçant le parcourshistorique de ces dénominations, de montrer que le flottement sur les termes estsymptomatique des tensions à l'oeuvre dans le domaine, sur le plan des enjeux institutionnels,économiques, théoriques et conceptuels

Development of an intelligent information resource model based on modern natural language processing methods

Currently, there is an avalanche-like increase in the need for automatic text processing, respectively, new effective methods and tools for processing texts in natural language are emerging. Although these methods, tools and resources are mostly presented on the internet, many of them remain inaccessible to developers, since they are not systematized, distributed in various directories or on separate sites of both humanitarian and technical orientation. All this greatly complicates their search and practical use in conducting research in computational linguistics and developing applied systems for natural text processing. This paper is aimed at solving the need described above. The paper goal is to develop model of an intelligent information resource based on modern methods of natural language processing (IIR NLP). The main goal of IIR NLP is to render convenient valuable access for specialists in the field of computational linguistics. The originality of our proposed approach is that the developed ontology of the subject area “NLP” will be used to systematize all the above knowledge, data, information resources and organize meaningful access to them, and semantic web standards and technology tools will be used as a software basis