A sentence-wide collocation recommendation system with error detection for academic writing

Yen Lun Chu, Tzone I. Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Collocation plays an important role in English article writing. This research builds a collocation corpus for academic writings in engineering and science fields. Based on the collocation corpus, this research also establishes a sentence-wide collocation recommendation and error detection system for academic writing. The corpus is built from Science Citation Index (SCI) papers and industry field thesis, which are collected and processed by a formal procedure developed in this research. The first step of the procedure uses the Stanford Parser to parse and retrieve collocations sentence by sentence from those papers and thesis. The second step classifies these collected collocations in different types and gathers their information to establish a collocation corpus specifically for academic article writings. The use of the corpus is through a web-based collocation system built in this study. Distinguished from other collocation systems found on the web nowadays, the system can do full sentence collocation error detections and recommendations. After several conducted experiments, the system is proved capable of giving satisfied feedbacks and recommendations for scientific article authors. Although the collocation corpus now is not complete enough to give the most precise results, the formal procedure can still keep enhancing the corpus and improving the system by automatically collecting articles from various fields.

Original languageEnglish
Title of host publicationInnovative Technologies and Learning - First International Conference, ICITL 2018, Proceedings
EditorsLin Lin, Ting-Ting Wu, Yueh-Min Huang, Yueh-Min Huang, Andreja Istenic Starcic, Rustam Shadieva
PublisherSpringer Verlag
Pages307-316
Number of pages10
ISBN (Print)9783319997360
DOIs
Publication statusPublished - 2018 Jan 1
Event1st International Conference on Innovative Technologies and Learning, ICITL 2018 - Portoroz, Slovenia
Duration: 2018 Aug 272018 Aug 30

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11003 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other1st International Conference on Innovative Technologies and Learning, ICITL 2018
CountrySlovenia
CityPortoroz
Period18-08-2718-08-30

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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