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Artículos de revistas sobre el tema "Computational linguistics"

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Autor: Grafiati

Publicado: 4 de junio de 2021

Última modificación: 28 de julio de 2024

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1

Yatsko, V. A. "Computational linguistics or linguistic informatics?" Automatic Documentation and Mathematical Linguistics 48, n.º 3 (mayo de 2014): 149–57. http://dx.doi.org/10.3103/s0005105514030042.

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Bara, Aicha. "Computational Linguistics Approach". Mathematical Linguistics 2, n.º 1 (31 de diciembre de 2022): 100–109. http://dx.doi.org/10.58205/ml.v2i1.155.

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This article aims to explain the field of computational linguistics and its specializations، its interest in computational modeling of natural language، and the study of computational approaches appropriate to linguistic questions. In general، computational linguistics draws on linguistics، computer science، artificial intelligence، mathematics، logic، philosophy، cognitive science، cognitive psychology، psycholinguistics، anthropology، and neuroscience، among others.

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3

N. O. Sadiku, Matthew, Chandra M. M. Kotteti y Janet O. Sadiku. "Computational Linguistics". International Journal of Advances in Scientific Research and Engineering 10, n.º 01 (2024): 01–06. http://dx.doi.org/10.31695/ijasre.2024.1.1.

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Linguistics is concerned with rules that are followed by languages as a system. Computational linguistics(CL)combines the power of machine learning and human language.As a subfield of linguistics, CL is concerned with the computational description of rules that languages follow. Itis what powers anything in a machine or device that has to do with language—speaking, writing, reading, and listening. It is often linked with natural language processing (NLP), which is the use of computers to identify structures in natural language.The boundary between NLP and CL is not so clear-cut. This paper is a primer on computational linguistics

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4

Argamon, Shlomo Engelson. "Register in computational language research". Register Studies 1, n.º 1 (26 de abril de 2019): 100–135. http://dx.doi.org/10.1075/rs.18015.arg.

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Abstract Shlomo Argamon is Professor of Computer Science and Director of the Master of Data Science Program at the Illinois Institute of Technology (USA). In this article, he reflects on the current and potential relationship between register and the field of computational linguistics. He applies his expertise in computational linguistics and machine learning to a variety of problems in natural language processing. These include stylistic variation, forensic linguistics, authorship attribution, and biomedical informatics. He is particularly interested in the linguistic structures used by speakers and writers, including linguistic choices that are influenced by social variables such as age, gender, and register, as well as linguistic choices that are unique or distinctive to the style of individual authors. Argamon has been a pioneer in computational linguistics and NLP research in his efforts to account for and explore register variation. His computational linguistic research on register draws inspiration from Systemic Functional Linguistics, Biber’s multi-dimensional approach to register variation, as well as his own extensive experience accounting for variation within and across text types and authors. Argamon has applied computational methods to text classification and description across registers – including blogs, academic disciplines, and news writing – as well as the interaction between register and other social variables, such as age and gender. His cutting-edge research in these areas is certain to have a lasting impact on the future of computational linguistics and NLP.

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5

Wilks, Yorick. "Corpus linguistics and computational linguistics". International Journal of Corpus Linguistics 15, n.º 3 (30 de julio de 2010): 408–11. http://dx.doi.org/10.1075/ijcl.15.3.12wil.

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6

Yang, Fan. "A Computational Linguistic Approach to English Lexicography". Transactions on Computer Science and Intelligent Systems Research 2 (21 de diciembre de 2023): 39–44. http://dx.doi.org/10.62051/wepk6t89.

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Focusing on computational linguistic approaches to English linguistics, this research explores how computational methods can be applied to dissect, understand and utilise the English language. We first looked at text analysis and processing, delving into natural language processing techniques such as text categorisation, sentiment analysis and machine translation, and their application to social media and automated text processing. In the area of lexicography and semantics, we explored how techniques such as distributed word vectors, semantic role labelling and sentiment analysis can deepen our understanding of vocabulary and semantics. We highlight the importance of these techniques in natural language processing tasks such as sentiment analysis and information retrieval. In addition, we focus on cross-language comparative and multilingual research, emphasising how big data and cross-language comparative research can reveal similarities and differences between languages and their implications for global linguistics. Finally, we explore corpus linguistics and big data analytics, highlighting the richness of linguistic data and tools they provide for linguistic research. Overall, this study highlights the importance of computational linguistic approaches to English linguistics and how they have transformed the way linguistics is studied and language technology has evolved. Future research trends will continue to drive the further development of computational linguistics methods, leading to a closer integration of linguistics with big data analytics and computational methods, creating more opportunities for the future of the field of linguistics.

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7

Jäger, Gerhard. "Computational historical linguistics". Theoretical Linguistics 45, n.º 3-4 (18 de diciembre de 2019): 151–82. http://dx.doi.org/10.1515/tl-2019-0011.

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Abstract Computational approaches to historical linguistics have been proposed for half a century. Within the last decade, this line of research has received a major boost, owing both to the transfer of ideas and software from computational biology and to the release of several large electronic data resources suitable for systematic comparative work. In this article, some of the central research topics of this new wave of computational historical linguistics are introduced and discussed. These are automatic assessment of genetic relatedness, automatic cognate detection, phylogenetic inference and ancestral state reconstruction. They will be demonstrated by means of a case study of automatically reconstructing a Proto-Romance word list from lexical data of 50 modern Romance languages and dialects. The results illustrate both the strengths and the weaknesses of the current state of the art of automating the comparative method.

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8

Shokhrukh, Juraev B. y Shaymardanov H. Abror. "THE DEVELOPMENT TENDENCIES OF COMPUTATIONAL LINGUISTICS IN UZBEKISTAN: NLP, MACHINE TRANSLATION, CORPUS LINGUISTICS AND AUTOMATIC TEXT EDITING". American Journal of Social Science and Education Innovations 04, n.º 10 (1 de octubre de 2022): 01–05. http://dx.doi.org/10.37547/tajssei/volume04issue10-01.

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This paper presents the recent development tendencies in the field of computational linguistics in Uzbekistan. It aims to address the researchers and research papers in computational linguistic areas such as: NLP, Machine translation, Corpus Linguistics and Text Editing. The article also highlights the new branches of Computational linguistics that has gained much importance in recent years in the country.

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9

Musthofa, Musthofa. "COMPUTATIONAL LINGUISTICS (Model Baru Kajian Linguistik dalam Perspektif Komputer)". Adabiyyāt: Jurnal Bahasa dan Sastra 9, n.º 2 (31 de diciembre de 2010): 247. http://dx.doi.org/10.14421/ajbs.2010.09203.

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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.

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10

Jones, Karen Spärck. "Computational Linguistics: What About the Linguistics?" Computational Linguistics 33, n.º 3 (septiembre de 2007): 437–41. http://dx.doi.org/10.1162/coli.2007.33.3.437.

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11

Solovyev, Valery Dmitrievich, Marina Ivanovna Solnyshkina y Danielle S. McNamara. "Computational linguistics and discourse complexology: Paradigms and research methods". Russian Journal of Linguistics 26, n.º 2 (29 de junio de 2022): 275–316. http://dx.doi.org/10.22363/2687-0088-31326.

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The dramatic expansion of modern linguistic research and enhanced accuracy of linguistic analysis have become a reality due to the ability of artificial neural networks not only to learn and adapt, but also carry out automate linguistic analysis, select, modify and compare texts of various types and genres. The purpose of this article and the journal issue as a whole is to present modern areas of research in computational linguistics and linguistic complexology, as well as to define a solid rationale for the new interdisciplinary field, i.e. discourse complexology. The review of trends in computational linguistics focuses on the following aspects of research: applied problems and methods, computational linguistic resources, contribution of theoretical linguistics to computational linguistics, and the use of deep learning neural networks. The special issue also addresses the problem of objective and relative text complexity and its assessment. We focus on the two main approaches to linguistic complexity assessment: “parametric approach” and machine learning. The findings of the studies published in this special issue indicate a major contribution of computational linguistics to discourse complexology, including new algorithms developed to solve discourse complexology problems. The issue outlines the research areas of linguistic complexology and provides a framework to guide its further development including a design of a complexity matrix for texts of various types and genres, refining the list of complexity predictors, validating new complexity criteria, and expanding databases for natural language.

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12

Abu Assi, Adel. "Computational linguistics and its impact on the development of Arabic language: Phonetics as a model". Hebron University Research Journal (HURJ): B- (Humanities) 15, n.º 1 (1 de julio de 2020): 90–113. http://dx.doi.org/10.60138/15120204.

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The study of Arabic language using computational linguistics is one of the latest linguistic trends in contemporary Arabic linguistics. It emerged as a result of the current explosion of knowledge and technology. Arabic is a living language that is coping with this development. Arabic Computational Linguistics aims to convert the skills and sciences of Arabic language from traditional paper space to the Computational side. This research defines Computational Linguistics and reality of the Arabic Computational Linguistics and the ways to improve it. The application adopted will be through Phonetics. The suggested model for the Computational treatment is (consonants and vowels). This research also aims to show the significance of Computational Linguistics to serve Arabic language.

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13

Dunkel, Patricia y Ralph Grishman. "Computational Linguistics: An Introduction". TESOL Quarterly 21, n.º 3 (septiembre de 1987): 556. http://dx.doi.org/10.2307/3586503.

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14

Macías, B. "Computational linguistics: an introduction". Computer Speech & Language 3, n.º 4 (octubre de 1989): 383–85. http://dx.doi.org/10.1016/0885-2308(89)90005-3.

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15

Amieur, Allal y Bachir Moulay lakhdar. "The role of computational linguistics in digitization of linguistic atlases". مجلة قضايا لغوية | Linguistic Issues Journal 2, n.º 3 (15 de diciembre de 2021): 163–70. http://dx.doi.org/10.61850/lij.v2i3.78.

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Isn’t a secret that computational linguistics relys on language computerigation. Ie. To use computer in coonting language results and to benefit from the data of computer to create a relationsluip betueer language and computer in order to study cases such as: ditecting language phenomena according to thir sounds, morphological, grammatical rethorical and computer assisted translation levels and to deal with special statistics operation. In addition to dictionary making and teaching languages. Because of all that, we must creatalinguistic language that forms a kind of a stoke inside those linguistics atlases that facilitates searching and studis.

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16

Ermetova, J. y N. Matyakubova. "Derivational Analysis of Terms of Computational Linguistics". Bulletin of Science and Practice 6, n.º 4 (15 de abril de 2020): 581–86. http://dx.doi.org/10.33619/2414-2948/53/70.

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Describes the derivational analysis of the English terminology of computational linguistics. The study is conducted on a compilation of computer terms with a total volume of 744 units, compiled on the basis of computer and linguistic glossaries and dictionaries. The analysis was done based on the classification of L. Tkacheva. Made it possible to identify the most productive methods of term formation, as well as their structural types. The study may be of interest to researchers in the field of computational linguistics and translation activities.

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17

Baha, Fathi. "The role of computational linguistics in developing digital linguistic atlases: Design and Delivery". مجلة قضايا لغوية | Linguistic Issues Journal 2, n.º 2 (30 de septiembre de 2021): 101–16. http://dx.doi.org/10.61850/lij.v2i2.65.

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This research deals with an important issue in applied linguistics, namely the linguistic Atlas, a new topic which tries to find creative ways to make use of computer and software world in the language industry and its design.This paper attempts to address the following issues; First: what is computational linguistics, secondly: what is linguistic atlases, third: designing linguistic atlases, fourth: linguistic atlases and digital atlases, fifth: haw to benefit from computer linguistics in creating digital atlases, and sixth: haw to benefit from the GPS system to develop linguistic atlases.

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18

Mezhoud, Salim. "Language Mathematics and Mathematics Language, Reading from Computational Linguistics". Mathematical Linguistics 1, n.º 1 (31 de diciembre de 2021): 7–24. http://dx.doi.org/10.58205/ml.v1i1.140.

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The language of mathematics is the system used by mathematicians to communicate mathematical ideas among themselves. This language consists of a substrate of some natural language using technical terms and grammatical conventions that are peculiar to mathematical discourse, supplemented by a highly specialized symbolic notation for mathematical formulas. mathematical characterizations of various notions of linguistic complexity include also computational linguistics, philosophical logic, knowledge representation as a branch of artificial intelligence, theoretical computer science, and computational psychology. Mathematical linguistics has initially served as a foundation for computational linguistics, though its research agenda of designing machines to simulate natural language understanding is clearly more applied. Inductive methods have gained the upper hand in applied computational linguistics The question is whether mathematics is a language, or that language is mathematical, and how computational linguistics employs language as mathematics.

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19

Jensen, Kim Ebensgaard. "Linguistics in the digital humanities: (computational) corpus linguistics". MedieKultur: Journal of media and communication research 30, n.º 57 (19 de diciembre de 2014): 20. http://dx.doi.org/10.7146/mediekultur.v30i57.15968.

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<p class="p1">Corpus linguistics has been closely intertwined with digital technology since the introduction of university computer mainframes in the 1960s. Making use of both digitized data in the form of the language corpus and computational methods of analysis involving concordancers and statistics software, corpus linguistics arguably has a place in the digital humanities. Still, it remains obscure and fi gures only sporadically in the literature on the digital humanities. Th is article provides an overview of the main principles of corpus linguistics and the role of computer technology in relation to data and method and also off ers a bird's-eye view of the history of corpus linguistics with a focus on its intimate relationship with digital technology and how digital technology has impacted the very core of corpus linguistics and shaped the identity of the corpus linguist. Ultimately, the article is oriented towards an acknowledgment of corpus linguistics' alignment with the digital humanities.</p>

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20

Steiner, Lydia, Michael Cysouw y Peter Stadler. "A Pipeline for Computational Historical Linguistics". Language Dynamics and Change 1, n.º 1 (2011): 89–127. http://dx.doi.org/10.1163/221058211x570358.

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AbstractThere are many parallels between historical linguistics and molecular phylogenetics. In this paper we describe an algorithmic pipeline that mimics, as closely as possible, the traditional workflow of language reconstruction known as the comparative method. The pipeline consists of suitably modified algorithms based on recent research in bioinformatics, which are adapted to the specifics of linguistic data. This approach can alleviate much of the laborious research needed to establish proof of historical relationships between languages. Equally important to our proposal is that each step in the workflow of the comparative method is implemented independently, so language specialists have the possibility to scrutinize intermediate results. We have used our pipeline to investigate two groups of languages, the Tsezic languages of the Caucasus and the Mataco-Guaicuruan languages of South America, based on the lexical data from the Intercontinental Dictionary Series (IDS). The results of these tests show that the current approach is a viable and useful extension to historical linguistic research.

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21

Hunyadi, L. "Linguistic analysis of large corpora: approaches to computational linguistics in Hungary". Literary and Linguistic Computing 14, n.º 1 (1 de abril de 1999): 77–88. http://dx.doi.org/10.1093/llc/14.1.77.

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22

Alzaben, Ahlam. "فعل الأمر في ضوء اللسانيات الحاسوبية". al-Turāṯ al-adabī 1, n.º 2 (30 de diciembre de 2023): 28–62. http://dx.doi.org/10.52015/al-turathal-adabi.v1i2.20.

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The present study aims to employ computational linguistic as a mold for reconstructing Arabic grammar generally, and imperative verb specifically, in an attempt to exceed the traditional description of the cognitive human awareness to a specification which is close enough to language concept. The study regards "Imperative verb" as a model through which a new perspective of Arabic grammar is presented, taking computational linguistics into account, and going beyond description to specification. The principal objective of the present study is to rim language with computational frames, demonstrate and describe the ambiguities and complexities facing these frames, and base data that are automatically generated about the nature of the speaker’s awareness of the language. This step starts with defining the parts of the words up to identifying the imperative verb-the model investigated in the present study. Also, it goes beyond the computational description that considers linguistic issues that converge with the model under investigation, morphologically, phonologically, syntactically, and semantically. Objectives: Introducing computational linguistics: description and specification Specifying imperative verb in terms of unaugmentation and addition through exploring: trilateral unaugmented imperative verb both strong and weak. Specifying the structure of imperative verb computationally. Complexities of clarifying the imperative verb Results/ Conclusion The present study has reached to a group of results that can be summarized as follows: Considering computational linguistics and computerizing the Arabic language in a way that assists in promoting its contribution in knowledge community and specifying research projects in the field. Presenting a model that suits to be the basis of specifying other areas of grammar. Establishing a mathematical database with the air of giving computer linguistic intuition that is as close as possible to that of the native speaker. The goal is to reach a computational ability that distinguishes right and wrong, permissible, or un-permissible.

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23

Bowern, Claire. "Computational Phylogenetics". Annual Review of Linguistics 4, n.º 1 (14 de enero de 2018): 281–96. http://dx.doi.org/10.1146/annurev-linguistics-011516-034142.

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24

Johnson, Austin. "Computational linguistics and temporal perspective". Journal of Research Design and Statistics in Linguistics and Communication Science 3, n.º 2 (7 de diciembre de 2016): 251–67. http://dx.doi.org/10.1558/jrds.30022.

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25

Van Huyssteen, G. B. "Bilingual word list: computational linguistics". Literator 29, n.º 1 (25 de julio de 2008): 249–72. http://dx.doi.org/10.4102/lit.v29i1.109.

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26

Ginestet, Cedric. "Semisupervised Learning for Computational Linguistics". Journal of the Royal Statistical Society: Series A (Statistics in Society) 172, n.º 3 (junio de 2009): 694. http://dx.doi.org/10.1111/j.1467-985x.2009.00595_2.x.

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27

Valiyeva, Kamila. "MODERN AREAS OF COMPUTATIONAL LINGUISTICS". Problems of Information Society 07, n.º 2 (21 de julio de 2016): 91–100. http://dx.doi.org/10.25045/jpis.v07.i2.10.

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28

Divjak, Dagmar, Serge Sharoff y Tomaž Erjavec. "Slavic Corpus and Computational Linguistics". Journal of Slavic Linguistics 25, n.º 2 (2017): 171–99. http://dx.doi.org/10.1353/jsl.2017.0008.

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29

Heinz, Jeffrey, Colin de la Higuera y Menno van Zaanen. "Grammatical Inference for Computational Linguistics". Synthesis Lectures on Human Language Technologies 8, n.º 4 (23 de octubre de 2015): 1–139. http://dx.doi.org/10.2200/s00643ed1v01y201504hlt028.

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30

Feldman, Anna. "Computational Linguistics: Models, Resources, Applications". Computational Linguistics 32, n.º 3 (septiembre de 2006): 443–44. http://dx.doi.org/10.1162/coli.2006.32.3.443.

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31

Manning, Christopher D. "Computational Linguistics and Deep Learning". Computational Linguistics 41, n.º 4 (diciembre de 2015): 701–7. http://dx.doi.org/10.1162/coli_a_00239.

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32

Komalova, L. R. "Modern landscape of Computational Linguistics". Вестник Московского государственного лингвистического университета. Гуманитарные науки, n.º 6 (2022): 40–47. http://dx.doi.org/10.52070/2542-2197_2022_6_861_40.

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33

Greengard, Samuel. "Computational Linguistics Finds its Voice". Communications of the ACM 66, n.º 2 (20 de enero de 2023): 18–20. http://dx.doi.org/10.1145/3575666.

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Nagiyeva, Nigar. "Sources of computational linguistics terminology". Terminology Issues, n.º 2 (2023): 91. http://dx.doi.org/10.59849/2663-8967.2023.2.91.

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35

Imamverdiyev, Yadigar y Adil Aliyev. "AZӘRBAYCAN DİLİ ÜÇÜN LİNQVİSTİK KORPUSLARIN FORMALAŞDIRILMASI PROBLEMLӘRİ". Elmi Əsərlər, n.º 2 (2023): 35–41. http://dx.doi.org/10.61413/fivf6911.

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Currently, computational linguistics and natural language processing technologies are based on the extensive use of data – the corresponding linguistic corpora. Therefore, corpus linguistics, which studies the methods of creating and using such corpuses, has become one of the leading directions in modern linguistics in a relatively short time. Ensuring the widespread use of the Azerbaijani language in the context of globalization is a state policy, and its implementation requires the development and application of appropriate computational linguistics technologies. One of the important prerequisites for the creation of such technologies is the availability of suitable linguistic corpora that meet modern requirements. For this reason, this article analyzes the existing linguistic corpora for the Azerbaijani language, identifies the scientific and practical problems of the formation of these corpora, and gives recommendations for solving them

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Bazylev, V. N. "New achievements in Russian linguistics (neo-psycholinguistics, migration linguistics, contact linguistics, computational linguistics, connectivistics)". Russian language at school 82, n.º 6 (20 de noviembre de 2021): 73–78. http://dx.doi.org/10.30515/0131-6141-2021-82-6-73-78.

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Abstract. The paper is focused on relevant directions in modern Russian Linguistics. It is the continuation of the 2019 publication where the ideas of Pedagogical and Anthropo-Oriented Linguistics, Political Communication Studies and Theological Linguistics were introduced. The aim of this paper is to demonstrate the expanding horizons of the science about the language of the 21st century. The particular sections of the text characterize the goals of modern linguistics, its key concepts, objectives and methods currently employed in the sphere of studying language and real discursive practices. The methodology of the research consists in describing new research paradigms. Such paradigms are objectively formed in the course of progressing scientific activity; their changes are triggered by the evolution of society, its socially valuable demand to upgrade not only science but also its educational system on the basis of certain conceptual, value, methodological and technological beliefs. The idea behind this paper is to help teachers to make sense of a big variety of modern linguistic ideas and opt for those which they can use to develop innovative approaches to teaching Russian.

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Benamara, Farah, Maite Taboada y Yannick Mathieu. "Evaluative Language Beyond Bags of Words: Linguistic Insights and Computational Applications". Computational Linguistics 43, n.º 1 (abril de 2017): 201–64. http://dx.doi.org/10.1162/coli_a_00278.

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The study of evaluation, affect, and subjectivity is a multidisciplinary enterprise, including sociology, psychology, economics, linguistics, and computer science. A number of excellent computational linguistics and linguistic surveys of the field exist. Most surveys, however, do not bring the two disciplines together to show how methods from linguistics can benefit computational sentiment analysis systems. In this survey, we show how incorporating linguistic insights, discourse information, and other contextual phenomena, in combination with the statistical exploitation of data, can result in an improvement over approaches that take advantage of only one of these perspectives. We first provide a comprehensive introduction to evaluative language from both a linguistic and computational perspective. We then argue that the standard computational definition of the concept of evaluative language neglects the dynamic nature of evaluation, in which the interpretation of a given evaluation depends on linguistic and extra-linguistic contextual factors. We thus propose a dynamic definition that incorporates update functions. The update functions allow for different contextual aspects to be incorporated into the calculation of sentiment for evaluative words or expressions, and can be applied at all levels of discourse. We explore each level and highlight which linguistic aspects contribute to accurate extraction of sentiment. We end the review by outlining what we believe the future directions of sentiment analysis are, and the role that discourse and contextual information need to play.

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38

DONG, ANDY. "Concept formation as knowledge accumulation: A computational linguistics study". Artificial Intelligence for Engineering Design, Analysis and Manufacturing 20, n.º 1 (febrero de 2006): 35–53. http://dx.doi.org/10.1017/s0890060406060033.

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Language plays at least two roles in design. First, language serves as representations of ideas and concepts through linguistic behaviors that represent the structure of thought during the design process. Second, language also performs actions and creates states of affairs. Based on these two perspectives on language use in design, we apply the computational linguistics tools of latent semantic analysis and lexical chain analysis to characterize how design teams engage in concept formation as the accumulation of knowledge represented by lexicalized concepts. The accumulation is described in a data structure comprised by a set of links between elemental lexicalized concepts. The folding together of these two perspectives on language use in design with the information processing theories of the mind afforded by the computational linguistics tools applied creates a new means to evaluate concept formation in design teams. The method suggests that analysis at a linguistic level can characterize concept formation even where process-oriented critiques were limited in their ability to uncover a formal design method that could explain the phenomenon.

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BENSEDDIK, Abdelbasset Abdelssamed y Taher BRAHIMI. "Employing computational linguistics in the makers and development of digital atlases". مجلة قضايا لغوية | Linguistic Issues Journal 3, n.º 1 (15 de junio de 2022): 22–36. http://dx.doi.org/10.61850/lij.v3i1.81.

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This study aims to introduce computational linguistics, and to show its important role in the manufacture and development of digital atlases, as computational linguistics is one of the most important branches of applied linguistics that is based in its work on the computer on the grounds that it has the ability to retain a large amount of information and knowledge; And documenting this knowledge by computer for ease of reference, in addition to spreading the culture of adapting the computer to serve languages, including the Arabic language, and perhaps the relationship that made computer linguistics take a wide field of interest for linguistic researchers in their attempt to invest computers in the field of linguistics in order to facilitate the exploitation of all that knowledge and information Automatically in a very short time.

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Chandra, Yanto. "Toward a Meta-Linguistic Model of Social Entrepreneurship: Insights from Computational Linguistics". Academy of Management Proceedings 2014, n.º 1 (enero de 2014): 13356. http://dx.doi.org/10.5465/ambpp.2014.13356abstract.

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Davydenko, Viktoriia I. "CONTEMPORARY UKRAINIAN COMPUTATIONAL DICTIONARIES: HISTORY, ACHIEVEMENTS, AND CHALLENGES". Scientific Journal of National Pedagogical Dragomanov University. Series 9. Current Trends in Language Development, n.º 26 (29 de diciembre de 2023): 5–12. http://dx.doi.org/10.31392/npu-nc.series9.2023.26.01.

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The article deals with the factors that led to the emergence of Applied Linguistics, Computational Linguistics, and Computational Lexicography – these are the processes of global digitalization of the world, the expansion of the scale of the scientific and technical revolution in the field of information systems and computer communication, the formation of the knowledge industry, requests on the development of radically new means of creating, storing, transforming and searching for information, as well as the integration of scientific fields. It is noted that at the beginning of the 21st century, lexicography incorporated centuries-old experience of theoretical linguistics and practical linguistics in the works of lexicography, and on the other hand, it received unprecedented development prospects associated with the use of computer technologies. It is emphasized that the social significance of lexicographic products is currently growing steadily. Modern science strives to embody all aspects of acquired knowledge in dictionary form, because dictionaries not only record the totality of certain knowledge, but also serve as a reliable tool for scientific mastering of reality. The works of Ukrainian and foreign scientists on the specific topic were analysed. It has been proven that computational dictionaries as a type of social, research or educational communication are the most popular reference materials, a source of access to any type of information (technical, encyclopaedic, linguistic, etc.) due to the fixation of the modern level of knowledge, completeness, accuracy, reliability, a systematic approach to the organization and presentation of knowledge, accessibility, extreme “comfort” for use, etc. Dictionary works are also the goal and result of scientific work on linguistic and technical issues.

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Darmoroz, Halyna. "Professional Training of Computational Linguists at the University of Stuttgart". Comparative Professional Pedagogy 7, n.º 3 (26 de septiembre de 2017): 75–83. http://dx.doi.org/10.1515/rpp-2017-0039.

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Abstract The paper deals with the aspects of professional training of specialists in computational linguistics by the example of the University of Stuttgart. First of all, we have attempted to define the essence of the terms “applied linguistics” and “computational linguistics” based on the views of Ukrainian and foreign scholars. We have found out that there is an obvious inconsistency in using these terms as Ukrainian scholars view it as a science related to practical application of linguistic achievements with the use of the latest technologies, whereas abroad they believe that computational linguistics is aimed at developing strategies for researches on natural languages. However, applied linguistics is related to language teaching methodology. We have concluded that German scholars view computational linguistics as a cognitive science that attempts to most successfully apply the achievements of linguistics in practice. Based on the view, German universities develop curricula that encompass theoretical and practical aspects of computational linguistics to prepare modern specialists able to comprehend the complexity of the field and be willing to adapt to challenges of a globalized world. Consequently, we have described the peculiarities of the programmes of a Bachelor of Science in Machine Language Programming and a Master of Science in Computational Linguistics. We have defined that duration of the programmes is traditional - three and two years respectively. Their structure comprises obligatory and elective courses, including Computer Science, Mathematics and Linguistics. In addition, future specialists may develop key professional competences attending seminars and colloquiums, participating in research projects, etc. It has been indicated that the list of electives involves those subjects aimed at enhancing future specialists’ skills in linguistics as well as computer science, yet they are entitled to suggest what they are interested in even if such courses are not included. We have also suggested that rather perspective are further studies on the essence of the terms “applied linguistics” and “computational linguistics” based on the research findings of scholars all over the world.

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Serebrianska, Irina. "APPLIED LINGUISTICS, COMPUTATIONAL LINGUISTICS AND OTHER INTERDISCIPLINARY SCIENCES AS EFFECTIVE INTERCULTURAL COMMUNICATION STRATEGIES". Fìlologìčnì traktati 13, n.º 1 (2021): 78–84. http://dx.doi.org/10.21272/ftrk.2021.13(1)-8.

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The article deals with the issues of interaction of linguistics and modern computer information technologies. It systematizes the actual problems and ways of their integration based on the analysis of the latest scientific works and the appropriate educational programs in higher education institutions all over the world. It draws attention to interdisciplinary sciences such as applied linguistics, computational linguistics, linguistic informatics, quantitative linguistics, mathematical linguistics, Internet linguistics, and integrated knowledge. The cooperation of two different areas is very productive and prospective. It contributes to the development of artificial intelligence and provides wider professional opportunities, effective intercultural communication and further improvement of society. The representatives of two, very different fields become mutually beneficial and complete each other successfully. The result of this interaction is a universal specialist which is in great demand nowadays. The main issues of the interaction of linguistics and modern information technologies are the following: 1) the role of virtual space and modern information technology in the development of linguistics; 2) the role of linguistics in the development of virtual space and information technologies, and the training of computer specialists; 3) the place of virtual space and modern information technologies in preparing linguists and translators (machine translation, translation systems, etc.); 4) the emergence of interdisciplinary sciences and educational courses at the intersection of two areas to provide society with professionals with integrated knowledge; duplication of their conceptual and terminological apparatus and research methods (due to their novelty); methodological support of the integrated educational process.

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Jäger, Gerhard. "Model evaluation in computational historical linguistics". Theoretical Linguistics 45, n.º 3-4 (18 de diciembre de 2019): 299–307. http://dx.doi.org/10.1515/tl-2019-0020.

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Abstract This is a reply to the comments by Hammarström et al. (This volume) and List (This volume) on the target article Computational Historical Linguistics (This volume). There I proposed several methodological principles for research in Computational Historical Linguistics pertaining to suitable techniques for model fitting and model evaluation. Hammarström et al. debate the usefulness of these principles, and List proposes a novel evaluation measure specifically aimed at the task of proto-form reconstruction. This reply will focus on the role of model evaluation in our field.

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Sampson, G. "The Oxford Handbook of Computational Linguistics". Literary and Linguistic Computing 18, n.º 3 (1 de septiembre de 2003): 333–36. http://dx.doi.org/10.1093/llc/18.3.333.

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Grabowski, Lukasz. "Interfacing corpus linguistics and computational stylistics". International Journal of Corpus Linguistics 18, n.º 2 (27 de septiembre de 2013): 254–80. http://dx.doi.org/10.1075/ijcl.18.2.04gra.

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This study attempts to examine the potential of selected corpus linguistics and computational stylistics methods in the investigation of translation universals in translational literary Polish. It deals with T-universals (Chesterman 2004), with emphasis on the simplification hypothesis, as manifested in the core patterns of lexical use (Laviosa 1998) and the levelling out hypothesis (Baker 1996). To that end, the purpose-designed corpora, each with approximately 350,000 tokens, of contemporary translational and non-translational literary Polish were compiled. The results confirm the simplification and the levelling out hypotheses but only with reference to the mean sentence length and variance for the mean sentence length. On the other hand, the results of multivariate analyses (Principal Components Analysis and Cluster Analysis) confirm the levelling out hypothesis that translations are more alike as compared with native texts.

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47

Starosta, Stanley. "Valency and case in computational linguistics". Machine Translation 5, n.º 1 (marzo de 1990): 79–96. http://dx.doi.org/10.1007/bf00310043.

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List, Johann-Mattis, Mary Walworth, Simon J. Greenhill, Tiago Tresoldi y Robert Forkel. "Sequence comparison in computational historical linguistics". Journal of Language Evolution 3, n.º 2 (1 de julio de 2018): 130–44. http://dx.doi.org/10.1093/jole/lzy006.

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Wintner, Shuly. "Hebrew Computational Linguistics: Past and Future". Artificial Intelligence Review 21, n.º 2 (abril de 2004): 113–38. http://dx.doi.org/10.1023/b:aire.0000020865.73561.bc.

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Artstein, Ron y Massimo Poesio. "Inter-Coder Agreement for Computational Linguistics". Computational Linguistics 34, n.º 4 (diciembre de 2008): 555–96. http://dx.doi.org/10.1162/coli.07-034-r2.

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This article is a survey of methods for measuring agreement among corpus annotators. It exposes the mathematics and underlying assumptions of agreement coefficients, covering Krippendorff's alpha as well as Scott's pi and Cohen's kappa; discusses the use of coefficients in several annotation tasks; and argues that weighted, alpha-like coefficients, traditionally less used than kappa-like measures in computational linguistics, may be more appropriate for many corpus annotation tasks—but that their use makes the interpretation of the value of the coefficient even harder.

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