Methods In Latin Computational Linguistics


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Methods in Latin Computational Linguistics


Methods in Latin Computational Linguistics

Author: Barbara McGillivray

language: en

Publisher: BRILL

Release Date: 2013-11-29


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In Methods in Latin Computational Linguistics, Barbara McGillivray presents some of the most significant methodological foundations of the emerging field of Latin Computational Linguistics. The reader will find an overview of the computational resources and tools available for Latin and three corpus case studies covering morpho-syntactic and lexical-semantic aspects of Latin verb valency, as well as quantitative diachronic explorations of the argument realization of Latin prefixed verbs. The computational models and the multivariate data analysis techniques employed are explained with a detailed but accessible language. Barbara McGillivray convincingly shows the challenges and opportunities of combining computational methods and historical language data, and contributes to driving the technological change that is affecting Historical Linguistics and the Humanities.

Computational Linguistics and Intelligent Text Processing


Computational Linguistics and Intelligent Text Processing

Author: Alexander Gelbukh

language: en

Publisher: Springer

Release Date: 2018-10-09


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The two-volume set LNCS 10761 + 10762 constitutes revised selected papers from the CICLing 2017 conference which took place in Budapest, Hungary, in April 2017. The total of 90 papers presented in the two volumes was carefully reviewed and selected from numerous submissions. In addition, the proceedings contain 4 invited papers. The papers are organized in the following topical sections: Part I: general; morphology and text segmentation; syntax and parsing; word sense disambiguation; reference and coreference resolution; named entity recognition; semantics and text similarity; information extraction; speech recognition; applications to linguistics and the humanities. Part II: sentiment analysis; opinion mining; author profiling and authorship attribution; social network analysis; machine translation; text summarization; information retrieval and text classification; practical applications.

Quantitative Historical Linguistics


Quantitative Historical Linguistics

Author: Gard B. Jenset

language: en

Publisher: Oxford University Press

Release Date: 2017


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This book is an innovative guide to quantitative, corpus-based research in historical and diachronic linguistics. Gard B. Jenset and Barbara McGillivray argue that, although historical linguistics has been successful in using the comparative method, the field lags behind other branches of linguistics with respect to adopting quantitative methods. Here they provide a theoretically agnostic description of a new framework for quantitatively assessing models and hypotheses in historical linguistics, based on corpus data and using case studies to illustrate how this framework can answer research questions in historical linguistics. The authors offer an in-depth explanation and discussion of the benefits of working with quantitative methods, corpus data, and corpus annotation, and the advantages of open and reproducible research. The book will be a valuable resource for graduate students and researchers in historical linguistics, as well as for all those working with linguistic corpora.