A new computing method for extracting contiguous phraseological sequences from academic text corpora

Bibliographic Data

ID12621700
AuthorsNaixing Wei (Beihang University, corresponding author), Jingjie Li (0009-0004-2847-4184, Donghua University)
Year2013
Volume18
Issue4
Pages506-535
Publication date2013-12-05
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueInternational Journal of Corpus Linguistics (JOURNAL)
Journal identifiersISSN: 1384-6655 • E-ISSN: 1569-9811
PublisherJohn Benjamins Publishing Company (PUBLISHER • NL)
DOI10.1075/ijcl.18.4.03wei
OpenAlexW1990242677
LanguageEN
Citations received7

This study aims to develop a new computing method for extracting contiguous phraseological sequences (PSs) of various lengths from academic text corpora by measuring internal associations of n-grams. We construct a new normalizing algorithm of probability-weighted average for refining the MI measure and enhancing precision in extracting PSs from corpora. This computing method is applied to the data in a medium-sized text corpus of academic English. Results indicate that the resultant new MI measure can provide statistics which better reveal internal associations within an n-gram, regardless of size. Lexico-grammatical sequences extracted with this method are more complete and less arbitrary in terms of grammar and semantics. The method can be applied to treating a variety of linguistic phenomenon, ranging from well-established phrases to likely phrasal entities, thus having potentially practical applications in corpus-based studies of phraseology and natural language processing

Construct (python library · Corpus linguistics · Data mining · Grammar · Linguistics · Measure (data warehouse · Natural language processing · Phraseology · Programming language · Semantics (computer science · Variety (cybernetics · Advanced Text Analysis Techniques · Computer Science · Natural Language Processing Techniques · Topic Modeling · Artificial Intelligence

Tools

Open DOISci-Hub