Research Article
Extracting Academic Subjects Semantic Relations Using Collocations
@ARTICLE{10.4108/eai.4-10-2017.153161, author={Velislava Stoykova}, title={Extracting Academic Subjects Semantic Relations Using Collocations}, journal={EAI Endorsed Transactions on Energy Web and Information Technologies}, volume={4}, number={14}, publisher={EAI}, journal_a={EW}, year={2017}, month={10}, keywords={Data mining, Big data, Knowledge discovery}, doi={10.4108/eai.4-10-2017.153161} }- Velislava Stoykova
Year: 2017
Extracting Academic Subjects Semantic Relations Using Collocations
EW
EAI
DOI: 10.4108/eai.4-10-2017.153161
Abstract
The paper presents approach to analyze semantic content of academic subjects and its internal relations using statistically-based techniques for collocation extraction from large electronic educational text corpus. It offers a survey and analysis of some related corpus-based approaches to extract conceptual relations used for educational purpose and presents a technique for semantic search of collocations. The results of extended keyword search from British Academic Spoken English corpus using Sketch Engine searching software are presented. They are analysed with respect to types of generated keyword’s collocations and semantic relations which they assign.
Copyright © 2017 Velislava Stoykova, licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.
