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Identifying Cyclic Words with the Help of Google Books N-grams Corpus

Authors:
Costin – Gabriel Chiru
Vladimir – Nicolae Dinu

Keywords: cyclicity detection; dynamic time warping; autocorrelation; Google Books N-grams Corpus; WordNet

Abstract:
In this paper, we present an application for identifying English words whose use is cyclic or regularly varies in time. The purpose of the developed application was to build a cross-platform system for indexing and analyzing the graphs of words usage over time. For words indexing, we used the data provided by the Google Books N-grams Corpus, which was afterwards filtered using the WordNet lexical database. For identifying the cyclic or regularly varying words, we used two different algorithms: autocorrelation and dynamic time warping. The results of the analysis can be visualized using a web interface. The application also offers the possibility to view the evolution of the use frequency of different words in time.

Pages: 34 to 39

Copyright: Copyright (c) IARIA, 2017

Publication date: June 25, 2017

Published in: conference

ISSN: 2308-3972

ISBN: 978-1-61208-563-0

Location: Venice, Italy

Dates: from June 25, 2017 to June 29, 2017