Lexical Collocation Analysis: Advances and Applications (Quantitative Methods in the Humanities and Social Sciences) - Tapa dura

Acerca del autor

Pascual Cantos-Gómez is Full Professor in the Department of English Language and Literature at the University of Murcia (Spain). He earned his BA and PhD at the University of Murcia; his MA in Computational Linguistics at the University of Essex (UK); and his PGDip in Multivariate Statistics at the UNED (Spain). His main research interests are in Corpus Linguistics, Quantitative Linguistics and Computational Lexicography. He has (co-)authored numerous articles, papers and various books one corpus linguistics, computational lexicography and statistics in linguistics research; his most recent book is Statistical Methods in Language and Linguistic Research (Equinox Publishing). He is the founder and co-editor-in-chief of the international peer-reviewed Journal of Research Design and Statistics in Linguistics and Communication Science (Equinox) and was also editor-in-chief of International Journal of English Studies (Editum). Presently, he is the Dean of the Faculty of Humanities(University of Murcia), Head of the LACELL (Applied Computational Linguistics, Second Language Learning and Lexicography) Research Group and President of the Spanish Association of Corpus Linguistics (AELINCO). 

Moisés Almela is Tenured Assistant Professor in the Department of English Language and Literature at the University of Murcia (Spain). He holds a BA in German Studies from the Complutense University (Spain), a BA in English Studies from the National University of Distance Education (Spain), an MA in Translation and Interpreting from the University of Murcia (Spain) and a PhD in English Studies from the University of Murcia. His main research interests are in Corpus Linguistics and Corpus-based Lexicography. He has authored numerous articles and papers on collocation analysis. Presently, he is the Chair of the Corpus Linguistics, Computational and Language Engineering Panel of the Spanish Association of Applied Linguistics (AESLA), and of the Corpus-based Lexicology and Lexicography Panel of the Spanish Association of Corpus Linguistics (AELINCO).

De la contraportada

This book re-examines the notion of word associations, more precisely collocations. It attempts to come to a potentially more generally applicable definition of collocation and how to best extract, identify and measure collocations. The book highlights the role played by (i) automatic linguistic annotation (part-of-speech tagging, syntactic parsing, etc.), (ii) using semantic criteria to facilitate the identification of collocations, (iii) multi-word structured, instead of the widespread assumption of bipartite collocational structures, for capturing the intricacies of the phenomenon of syntagmatic attraction, (iv) considering collocation and valency as near neighbours in the lexis-grammar continuum and (v) the mathematical properties of statistical association measures in the automatic extraction of collocations from corpora. This book is an ideal guide to the use of statistics in collocation analysis and lexicography, as well as a practical text to the development of skills in the application of computational lexicography.

 

Lexical Collocation Analysis: Advances and Applications begins with a proposal for integrating both collocational and valency phenomena within the overarching theoretical framework of construction grammar. Next the book makes the case for integrating advances in syntactic parsing and in collocational analysis. Chapter 3 offers an innovative look at complementing corpus data and dictionaries in the identification of specific types of collocations consisting of restricted predicate-argument combinations. This strategy complements corpus collocational data with network analysis techniques applied to dictionary entries. Chapter 4 explains the potential of collocational graphs and networks both as a visualization tool and as an analytical technique. Chapter 5 introduces MERGE (Multi-word Expressions from the Recursive Grouping of Elements), a data-driven approach to the identification and extraction of multi-word expressions from corpora. Finally the book concludes with an analysis and evaluation of factors influencing the performance of collocation extraction methods in parsed corpora.