Relevant bibliographies by topics / Computational linguistics

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Computational linguistics'

Author: Grafiati
Published: 4 June 2021
Last updated: 30 July 2024

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Journal articles on the topic "Computational linguistics"

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Yatsko, V. A. "Computational linguistics or linguistic informatics?" Automatic Documentation and Mathematical Linguistics 48, no. 3 (May 2014): 149–57. http://dx.doi.org/10.3103/s0005105514030042.

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Bara, Aicha. "Computational Linguistics Approach." Mathematical Linguistics 2, no. 1 (December 31, 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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N. O. Sadiku, Matthew, Chandra M. M. Kotteti, and Janet O. Sadiku. "Computational Linguistics." International Journal of Advances in Scientific Research and Engineering 10, no. 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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Argamon, Shlomo Engelson. "Register in computational language research." Register Studies 1, no. 1 (April 26, 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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Wilks, Yorick. "Corpus linguistics and computational linguistics." International Journal of Corpus Linguistics 15, no. 3 (July 30, 2010): 408–11. http://dx.doi.org/10.1075/ijcl.15.3.12wil.

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Yang, Fan. "A Computational Linguistic Approach to English Lexicography." Transactions on Computer Science and Intelligent Systems Research 2 (December 21, 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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Jäger, Gerhard. "Computational historical linguistics." Theoretical Linguistics 45, no. 3-4 (December 18, 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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Shokhrukh, Juraev B., and 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, no. 10 (October 1, 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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Musthofa, Musthofa. "COMPUTATIONAL LINGUISTICS (Model Baru Kajian Linguistik dalam Perspektif Komputer)." Adabiyyāt: Jurnal Bahasa dan Sastra 9, no. 2 (December 31, 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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Jones, Karen Spärck. "Computational Linguistics: What About the Linguistics?" Computational Linguistics 33, no. 3 (September 2007): 437–41. http://dx.doi.org/10.1162/coli.2007.33.3.437.

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Dissertations / Theses on the topic "Computational linguistics"

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vanCort, Tracy. "Computational Evolutionary Linguistics." Scholarship @ Claremont, 2001. https://scholarship.claremont.edu/hmc_theses/137.

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Languages and species both evolve by a process of repeated divergences, which can be described with the branching of a phylogenetic tree or phylogeny. Taking advantage of this fact, it is possible to study language change using computational tree building techniques developed for evolutionary biology. Mathematical approaches to the construction of phylogenies fall into two major categories: character based and distance based methods. Character based methods were used in prior work in the application of phylogenetic methods to the Indo-European family of languages by researchers at the University of Pennsylvania. Discussion of the limitations of character-based models leads to a similar presentation of distance based models. We present an adaptation of these methods to linguistic data, and the phylogenies generated by applying these methods to several modern Germanic languages and Spanish. We conclude that distance based for phylogenies are useful for historical linguistic reconstruction, and that it would be useful to extend existing tree drawing methods to better model the evolutionary effects of language contact.
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Wang, Pengyu. "Collapsed variational inference for computational linguistics." Thesis, University of Oxford, 2016. https://ora.ox.ac.uk/objects/uuid:13c08f60-1441-4ea5-b52f-7ffd0d7a744f.

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Bayesian modelling is a natural fit for tasks in computational linguistics, since it can provide interpretable structures, useful prior controls, and coherent management of uncertainty. However, exact Bayesian inference is intractable for many models of practical interest. Developing both accurate and efficient approximate Bayesian inference algorithms remains a fundamental challenge, especially for the field of computational linguistics where datasets are large and growing and models consist of complex latent structures. Collapsed variational inference (CVI) is an important milestone that combines the efficiency of variational inference (VI) and the accuracy of Markov chain Monte Carlo (MCMC) (Teh et al., 2006). However, its previous applications were limited to bag-of-words models whose hidden variables are conditionally independent given the parameters, whereas in computational linguistics, the hidden variable dependencies are crucial for modelling the underlying syntactic and semantic relations. To enlarge the application domain of CVI as well as to address the above Bayesian inference challenge, we investigate the applications of collapsed variational inference to computational linguistics. In this thesis, our contributions are three-fold. First, we solve a number of inference challenges arising from the hidden variable dependencies and derive a set of new CVI algorithms for the two ubiquitous and foundational models in computational linguistics, namely hidden Markov models (HMMs) and probabilistic context free grammars. We also propose CVI for hierarchical Dirichlet process (HDP) HMMs that are Bayesian nonparametric extensions of HMMs. Second, along the way we propose a set of novel algorithmic techniques, which are generally applicable to a wide variety of probabilistic graphical models in the conjugate exponential family and computational linguistic models using non-conjugate HDP constructions. Therefore, our work represents one step in bridging the gap between increasingly richer Bayesian models in computational linguistics and recent advances in approximate Bayesian inference. Third, we empirically evaluate our proposed CVI algorithms and their stochastic versions in a range of computational linguistic tasks, such as part-of-speech induction, grammar induction and many others. Experimental results consistently demonstrate that, using our techniques for handling the hidden variable dependencies, the empirical advantages of both VI and MCMC can be combined in a much larger domain of CVI applications.
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Penton, Dave. "Linguistic data models : presentation and representation /." Connect to thesis, 2006. http://eprints.unimelb.edu.au/archive/00002875.

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Fujinami, Tsutomu. "A process algebraic approach to computational linguistics." Thesis, University of Edinburgh, 1996. http://hdl.handle.net/1842/521.

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The thesis presents a way to apply process algebra to computational linguistics. We are interested in how contexts can affect or contribute to language understanding and model the phenomena as a system of communicating processes to study the interaction between them in detail. For this purpose, we turn to the pie-calculus and investigate how communicating processes may be defined. While investigating the computational grounds of communication and concurrency,we devise a graphical representation for processes to capture the structure of interaction between them. Then, we develop a logic, combinatory intuitionistic linear logic with equality relation, to specify communicating processes logically. The development enables us to study Situation Semantics with process algebra. We construct semantic objects employed in Situation Semantics in the pi-calculus and then represent them in the logic. Through the construction,we also relate Situation Semantics with the research on the information flow, Channel Theory, by conceiving of linear logic as a theory of the information flow. To show how sentences can be parsed as the result of interactions between processes, we present a concurrent chart parser encoded in the pi-calculus. We also explain how a semantic representation can be generated as a process by the parser. We conclude the thesis by comparing the framework with other approaches.
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Holmqvist, Maria. "Word Alignment by Re-using Parallel Phrases." Licentiate thesis, Linköping University, Linköping University, NLPLAB - Natural Language Processing Laboratory, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-15463.

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In this thesis we present the idea of using parallel phrases for word alignment. Each parallel phrase is extracted from a set of manual word alignments and contains a number of source and target words and their corresponding alignments. If a parallel phrase matches a new sentence pair, its word alignments can be applied to the new sentence. There are several advantages of using phrases for word alignment. First, longer text segments include more  context and will be more likely to produce correct word alignments than shorter segments or single words. More importantly, the use of longer phrases makesit possible to generalize words in the phrase by replacing words by parts-of-speech or other grammatical information. In this way, the number of words covered by the extracted phrases can go beyond the words and phrases that were present in the original set of manually aligned sentences. We present  experiments with phrase-based word alignment on three types of English–Swedish parallel corpora: a software manual, a novel and proceedings of the European Parliament. In order to find a balance between improved coverage and high alignment accuracy we investigated different properties of generalised phrases to identify which types of phrases are likely to produce accurate alignments on new data. Finally, we have compared phrase-based word alignments to state-of-the-art statistical alignment with encouraging results. We show that phrase-based word alignments can be used to enhance statistical word alignment. To evaluate word alignments an English–Swedish reference set for the Europarl corpus was constructed. The guidelines for producing this reference alignment are presented in the thesis.

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Moilanen, Karo. "Compositional entity-level sentiment analysis." Thesis, University of Oxford, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.559817.

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This thesis presents a computational text analysis tool called AFFECTiS (Affect Interpretation/Inference System) which focuses on the task of interpreting natural language text based on its subjective, non-factual, affective properties that go beyond the 'traditional' factual, objective dimensions of meaning that have so far been the main focus of Natural Language Processing and Computational Linguistics. The thesis presents a fully compositional uniform wide-coverage computational model of sentiment in text that builds on a number of fundamental compositional sentiment phenomena and processes discovered by detailed linguistic analysis of the behaviour of sentiment across key syntactic constructions in English. Driven by the Principle of Semantic Compositionality, the proposed model breaks sentiment interpretation down into strictly binary combinatory steps each of which explains the polarity of a given sentiment expression as a function of the properties of the sentiment carriers contained in it and the grammatical and semantic context(s) involved. An initial implementation of the proposed compositional sentiment model is de- scribed which attempts direct logical sentiment reasoning rather than basing compu- tational sentiment judgements on indirect data-driven evidence. Together with deep grammatical analysis and large hand-written sentiment lexica, the model is applied recursively to assign sentiment to all (sub )sentential structural constituents and to concurrently equip all individual entity mentions with gradient sentiment scores. The system was evaluated on an extensive multi-level and multi-task evaluation framework encompassing over 119,000 test cases from which detailed empirical ex- perimental evidence is drawn. The results across entity-, phrase-, sentence-, word-, and document-level data sets demonstrate that AFFECTiS is capable of human-like sentiment reasoning and can interpret sentiment in a way that is not only coherent syntactically but also defensible logically - even in the presence of the many am- biguous extralinguistic, paralogical, and mixed sentiment anomalies that so tellingly characterise the challenges involved in non-factual classification.
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Wahle, Johannes [Verfasser]. "Algorithmic advancements in Computational Historical Linguistics / Johannes Wahle." Tübingen : Universitätsbibliothek Tübingen, 2021. http://d-nb.info/1241537038/34.

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Chew, Peter. "A computational phonology of Russian." Thesis, University of Oxford, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.324285.

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Senaldi, Marco Silvio Giuseppe. "Working both sides of the street: computational and psycholinguistic investigations on idiomatic variability." Doctoral thesis, Scuola Normale Superiore, 2019. http://hdl.handle.net/11384/86016.

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Over the years, the original conception of idioms as semantically empty and formally frozen units (Bobrow and Bell, 1973; Swinney and Cutler, 1979) has been replaced by a more complex view, whereby some idioms display an analyz able semantic structure (Nunberg, 1978) that allows for greater formal plasticity (Nunberg et al., 1994; Gibbs and Nayak, 1989). Corpus data have anyway shown that all types of idioms allow for a certain degree of manipulation if an appropriate context is provided (Duffley, 2013; Vietri, 2014). On the other hand, psycholin guistic data have revealed that the processing of idiom variants is not necessarily harder than the processing of idiom canonical forms or that it can be similar to the processing of literal language (McGlone et al., 1994; Geeraert et al., 2017a). Despite this possible variability, in two computational studies we show that focus ing on lexical fixedness is still an effective method for automatically telling apart non-compositional idiomatic expressions and compositional non-idiomatic expres sions by means of distributional-semantic indices of compositionality that compute the cosine similarity between the vector of a given phrase to be classified and the vectors of lexical variants of the same phrase that are generated distributionally or from the Italian section of MultiWordNet (Pianta et al., 2002). Idioms all in all result to be less similar to the vectors of their lexical variants with respect to compositional expressions, confirming that they tend to be employed in a more formally conservative way in language use. In two eye-tracking studies we then compare the reading times of idioms and literals in the active form, in a passive form with preverbal subject and in a passive form with postverbal subject, which preserves the verb-noun order of the canonical active form. The first experiment reveals that passives are longer to read than actives with no significant effect of idiomaticity in passive forms. A second experiment with more ecological dialogic stimuli reveals that preserving the surface verb-noun order of the active form fa cilitates the processing of passive idioms, suggesting that one of the core issues with idiom passivization could be the violation of canonical verb-noun order rather than verb voice per se.
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Kof, Leonid. "Text analysis for requirements engineering : application of computational linguistics /." Saarbrücken : VDM Verl. Dr. Müller, 2007. http://deposit.d-nb.de/cgi-bin/dokserv?id=3021639&prov=M&dok_var=1&dok_ext=htm.

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Books on the topic "Computational linguistics"

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Dershowitz, Nachum, and Ephraim Nissan, eds. Language, Culture, Computation. Computational Linguistics and Linguistics. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-45327-4.

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Przepiórkowski, Adam, Maciej Piasecki, Krzysztof Jassem, and Piotr Fuglewicz, eds. Computational Linguistics. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-34399-5.

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Hasida, Kôiti, and Ayu Purwarianti, eds. Computational Linguistics. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-0515-2.

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Hasida, Kôiti, and Win Pa Pa, eds. Computational Linguistics. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-8438-6.

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Nguyen, Le-Minh, Xuan-Hieu Phan, Kôiti Hasida, and Satoshi Tojo, eds. Computational Linguistics. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-6168-9.

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Eva, Ejerhed, ed. Computational linguistics. Oslo: Norwegian University Press, 1988.

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Gazdar, Gerald. Computational linguistics. Brighton: Cognitive Studies Programme, The University of Sussex, 1986.

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Bátori, István S., Winfried Lenders, and Wolfgang Putschke, eds. Computational Linguistics / Computerlinguistik. Berlin • New York: Walter de Gruyter, 1989. http://dx.doi.org/10.1515/9783110203325.

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Li, Sheng, Maosong Sun, Yang Liu, Hua Wu, Liu Kang, Wanxiang Che, Shizhu He, and Gaoqi Rao, eds. Chinese Computational Linguistics. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-84186-7.

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Sun, Maosong, Yang Liu, Wanxiang Che, Yang Feng, Xipeng Qiu, Gaoqi Rao, and Yubo Chen, eds. Chinese Computational Linguistics. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-18315-7.

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Book chapters on the topic "Computational linguistics"

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Brown, Georgina. "Computational linguistics." In Introducing Linguistics, 339–51. London: Routledge, 2022. http://dx.doi.org/10.4324/9781003045571-21.

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De Roeck, Anne. "Computational linguistics." In Handbook of Pragmatics, 154–64. Amsterdam: John Benjamins Publishing Company, 1995. http://dx.doi.org/10.1075/hop.m.comm2.

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De Roeck, Anne. "Computational linguistics." In Handbook of Pragmatics, 238–49. Amsterdam: John Benjamins Publishing Company, 2022. http://dx.doi.org/10.1075/hop.m2.comm2.

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Matthiessen, Christian M. I. M., Bo Wang, Yuanyi Ma, and Isaac N. Mwinlaaru. "Computational Linguistics." In Systemic Functional Insights on Language and Linguistics, 125–45. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-8713-6_5.

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Trujillo, Arturo. "Computational Linguistics Techniques." In Translation Engines: Techniques for Machine Translation, 85–119. London: Springer London, 1999. http://dx.doi.org/10.1007/978-1-4471-0587-9_5.

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Woolls, David. "Computational forensic linguistics." In The Routledge Handbook of Forensic Linguistics, 593–607. Title: The Routledge handbook of forensic linguistics / edited by Malcolm Coulthard, Alison May, Rui Sousa-Silva. Description: Second edition. | London ; New York : Routledge, 2020. | Series: Routledge handbooks in applied linguistics: Routledge, 2020. http://dx.doi.org/10.4324/9780429030581-45.

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Ionkina, Karina, Suraj Sood, Monte Hancock, Charlotte Walker, and Raman Kannan. "Kantian Computational Linguistics." In Augmented Cognition, 237–49. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-78114-9_17.

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Munaro, Nicola. "Computational puzzles of conditional clause preposing." In Linguistik Aktuell/Linguistics Today, 73–94. Amsterdam: John Benjamins Publishing Company, 2005. http://dx.doi.org/10.1075/la.75.06mun.

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Patricia, Friedrich. "Combining corpus linguistics and computational linguistics." In Applied Linguistics In The Real World, 90–102. Title: Applied linguistics in the real world/Patricia Friedrich. Description: London; New York, NY: Routledge, 2019.: Routledge, 2019. http://dx.doi.org/10.4324/9780429032219-7.

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Lindén, Krister, Erik Axelson, Senka Drobac, Sam Hardwick, Miikka Silfverberg, and Tommi A. Pirinen. "Using HFST for Creating Computational Linguistic Applications." In Computational Linguistics, 3–25. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-34399-5_1.

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Conference papers on the topic "Computational linguistics"

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Uszkoreit, Hans. "Linguistics in computational linguistics." In the EACL 2009 Workshop. Morristown, NJ, USA: Association for Computational Linguistics, 2009. http://dx.doi.org/10.3115/1642038.1642043.

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Erbach, Gregor. "Computational linguistics and linguistics." In the EACL 2009 Workshop. Morristown, NJ, USA: Association for Computational Linguistics, 2009. http://dx.doi.org/10.3115/1642038.1642046.

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"Computational linguistics." In 2016 Third International Conference on Information Retrieval and Knowledge Management (CAMP). IEEE, 2016. http://dx.doi.org/10.1109/infrkm.2016.7806324.

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Pullum, Geoffrey K. "Computational linguistics and generative linguistics." In the EACL 2009 Workshop. Morristown, NJ, USA: Association for Computational Linguistics, 2009. http://dx.doi.org/10.3115/1642038.1642042.

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Feldman, Jerome A. "Computational cognitive linguistics." In the 20th international conference. Morristown, NJ, USA: Association for Computational Linguistics, 2004. http://dx.doi.org/10.3115/1220355.1220515.

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Moore, Robert C. "What do computational linguists need to know about linguistics?" In the EACL 2009 Workshop. Morristown, NJ, USA: Association for Computational Linguistics, 2009. http://dx.doi.org/10.3115/1642038.1642047.

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"Computational linguistics—applications." In 2008 International Multiconference on Computer Science and Information Technology. IEEE, 2008. http://dx.doi.org/10.1109/imcsit.2008.4747257.

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"Computational linguistics—applications." In 2009 International Multiconference on Computer Science and Information Technology (IMCSIT). IEEE, 2009. http://dx.doi.org/10.1109/imcsit.2009.5352731.

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"Computational Linguistics—Applications." In 2010 International Multiconference on Computer Science and Information Technology (IMCSIT 2010). IEEE, 2010. http://dx.doi.org/10.1109/imcsit.2010.5680067.

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Bharati, Akshar, Vineet Chaitanya, and Rajeev Sangal. "Computational linguistics in India." In the 38th Annual Meeting. Morristown, NJ, USA: Association for Computational Linguistics, 2000. http://dx.doi.org/10.3115/1075218.1075295.

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Reports on the topic "Computational linguistics"

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Taylor, Ronald C. Automated insertion of sequences into a ribosomal RNA alignment: An application of computational linguistics in molecular biology. Office of Scientific and Technical Information (OSTI), November 1991. http://dx.doi.org/10.2172/10108317.

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2

Taylor, R. C. Automated insertion of sequences into a ribosomal RNA alignment: An application of computational linguistics in molecular biology. Office of Scientific and Technical Information (OSTI), November 1991. http://dx.doi.org/10.2172/6057182.

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3

Lutz, Carsten. PDL with Intersection and Converse is Decidable. Technische Universität Dresden, 2005. http://dx.doi.org/10.25368/2022.148.

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In its many guises and variations, propositional dynamic logic (PDL) plays an important role in various areas of computer science such as databases, artificial intelligence, and computer linguistics. One relevant and powerful variation is ICPDL, the extension of PDL with intersection and converse. Although ICPDL has several interesting applications, its computational properties have never been investigated. In this paper, we prove that ICPDL is decidable by developing a translation to the monadic second order logic of infinite trees. Our result has applications in information logic, description logic, and epistemic logic. In particular, we solve a long-standing open problem in information logic. Another virtue of our approach is that it provides a decidability proof that is more transparent than existing ones for PDL with intersection (but without converse).
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4

Jamilov, Rustam, Hélène Rey, and Ahmed Tahoun. The Anatomy of Cyber Risk. Institute for New Economic Thinking Working Paper Series, May 2023. http://dx.doi.org/10.36687/inetwp206.

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This paper employs computational linguistics to introduce a novel text-based measure of firm-level cyber risk exposure based on quarterly earnings conference calls of listed firms. Our quarterly measures are available for more than 13,000 firms from 85 countries over 2002-2021. We document that cyber risk exposure predicts cyber attacks, affects stock returns and profits, and is priced in the equity option market. The cost of option protection against price, variance, and tail risks is greater for more cyber-exposed firms. Cyber risks spill over across firms and persist at the sectoral level. The geography of cyber risk exposure is well approximated by a gravity model extended with cross-border portfolio flows. Back-of-the-envelope calculations suggest that the global cost of cyber risk is over $200 billion per year.
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Jurafsky, Daniel. An On-Line Computational Model of Human Sentence Interpretation: A Theory of the Representation and Use of Linguistic Knowledge. Fort Belvoir, VA: Defense Technical Information Center, March 1992. http://dx.doi.org/10.21236/ada604298.

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6

Moreno Pérez, Carlos, and Marco Minozzo. “Making Text Talk”: The Minutes of the Central Bank of Brazil and the Real Economy. Madrid: Banco de España, November 2022. http://dx.doi.org/10.53479/23646.

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This paper investigates the relationship between the views expressed in the minutes of the meetings of the Central Bank of Brazil’s Monetary Policy Committee (COPOM) and the real economy. It applies various computational linguistic machine learning algorithms to construct measures of the minutes of the COPOM. First, we create measures of the content of the paragraphs of the minutes using Latent Dirichlet Allocation (LDA). Second, we build an uncertainty index for the minutes using Word Embedding and K-Means. Then, we combine these indices to create two topic-uncertainty indices. The first one is constructed from paragraphs with a higher probability of topics related to “general economic conditions”. The second topic-uncertainty index is constructed from paragraphs that have a higher probability of topics related to “inflation” and the “monetary policy discussion”. Finally, we employ a structural VAR model to explore the lasting effects of these uncertainty indices on certain Brazilian macroeconomic variables. Our results show that greater uncertainty leads to a decline in inflation, the exchange rate, industrial production and retail trade in the period from January 2000 to July 2019.
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