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New Language Technologies and Linguistic Research
This book is a collection of the papers presented and discussed at the 11th Corpus Linguistics Symposium (ELC 2012), held at the Instituto de Ciências Matemáticas e de Computação (Institute of Mathematics and Computer Science) of the University of São Paulo, at São Carlos, Brazil. The sessions addressed the following six topics: Corpus Linguistics and Language Description; Translation, Terminology and Corpora; Spoken Language and Corpora; Natural Language Processing and Corpora; Corpus Annotation; and Corpora and Multiple Documents. These unique studies will inspire readers with an interest in Linguistics, and will provide motivation for conducting further research in the interdisciplinary area of Language Technologies and Linguistic Research.
Working with Portuguese Corpora
Although Portuguese is one of the main world languages and researchers have been working on Portuguese electronic text collections for decades (e.g. Kelly, 1970; Biderman, 1978; Bacelar do Nascimento et al., 1984; see Berber Sardinha, 2005), this is the first volume in English that encapsulates the exciting and cutting-edge corpus linguistic work being done with Portuguese language corpora on different continents. The book includes chapters by leading corpus linguists dealing with Portuguese corpora across the world, and their contributions explore various methods and how they are applicable to a wide range of language issues. The book is divided into six sections, each covering a key issue in Corpus Linguistics: lexis and grammar, lexicography, language teaching and terminology, translation, corpus building and sharing, and parsing and annotation. Together these sections present the reader with a broad picture of the field.
Computational Processing of the Portuguese Language
This book constitutes the proceedings of the 14th International Conference on Computational Processing of the Portuguese Language, PROPOR 2020, held in Evora, Portugal, in March 2020. The 36 full papers presented together with 5 short papers were carefully reviewed and selected from 70 submissions. They are grouped in topical sections on speech processing; resources and evaluation; natural language processing applications; semantics; natural language processing tasks; and multilinguality.
Computational Processing of the Portuguese Language
This book constitutes the refereed proceedings of the 12th International Conference on Computational Processing of the Portuguese Language, PROPOR 2016, held in Tomar, Portugal, in July 2016. The 23 full papers and 14 short papers presented in this volume were carefully reviewed and selected from 52 submissions. The papers are organized in topical sections named: language applications, language processing, and language resources.
The Oxford Handbook of Computational Linguistics
Ruslan Mitkov's highly successful Oxford Handbook of Computational Linguistics has been substantially revised and expanded in this second edition. Alongside updated accounts of the topics covered in the first edition, it includes 17 new chapters on subjects such as semantic role-labelling, text-to-speech synthesis, translation technology, opinion mining and sentiment analysis, and the application of Natural Language Processing in educational and biomedical contexts, among many others. The volume is divided into four parts that examine, respectively: the linguistic fundamentals of computational linguistics; the methods and resources used, such as statistical modelling, machine learning, and corpus annotation; key language processing tasks including text segmentation, anaphora resolution, and speech recognition; and the major applications of Natural Language Processing, from machine translation to author profiling. The book will be an essential reference for researchers and students in computational linguistics and Natural Language Processing, as well as those working in related industries.
A resource-light approach to morpho-syntactic tagging
While supervised corpus-based methods are highly accurate for different NLP tasks, including morphological tagging, they are difficult to port to other languages because they require resources that are expensive to create. As a result, many languages have no realistic prospect for morpho-syntactic annotation in the foreseeable future. The method presented in this book aims to overcome this problem by significantly limiting the necessary data and instead extrapolating the relevant information from another, related language. The approach has been tested on Catalan, Portuguese, and Russian. Although these languages are only relatively resource-poor, the same method can be in principle applied t...
Intelligent Tutoring Systems
This book constitutes the refereed proceedings of the 7th International Conference on Intelligent Tutoring Systems, ITS 2004, held in Maceió, Alagoas, Brazil in August/September 2004. The 73 revised full papers and 39 poster papers presented together with abstracts of invited talks, panels, and workshops were carefully reviewed and selected from over 180 submissions. The papers are organized in topical sections on adaptive testing, affect, architectures for ITS, authoring systems, cognitive modeling, collaborative learning, natural language dialogue and discourse, evaluation, machine learning in ITS, pedagogical agents, student modeling, and teaching and learning strategies.
Natural Language Processing for Historical Texts
More and more historical texts are becoming available in digital form. Digitization of paper documents is motivated by the aim of preserving cultural heritage and making it more accessible, both to laypeople and scholars. As digital images cannot be searched for text, digitization projects increasingly strive to create digital text, which can be searched and otherwise automatically processed, in addition to facsimiles. Indeed, the emerging field of digital humanities heavily relies on the availability of digital text for its studies. Together with the increasing availability of historical texts in digital form, there is a growing interest in applying natural language processing (NLP) methods...
