Title: Analysis of word vector combined with group intelligence perception based on STEM concept for ELT word recommendation strategy

Authors: Ke Qin; Yang Zhou; Daniel Kvitrud

Addresses: School of Foreign Languages, Guizhou University of Finance and Economics, Guiyang, 550000, China ' Guizhou University of Finance and Economics, Guiyang, 550000, China ' Athletic Department, Saint John's University, Collegeville, 56321, USA

Abstract: With the rapid development of China's education concept, the mode of English learning has produced great changes, and the learning methods of ELT words have gradually developed towards intelligence. For the problem of ELT word recommendation strategy, an optimised CWSAR algorithm model based on STEM concept, combining collaborative filtering algorithm, word vector semantic perception, context perception and crowdsensing is proposed. The optimal parameter experiments and comparison experiments are conducted for this algorithm model. The experimental results show that CWSAR algorithm is better than the two CF algorithms in the experiment of ordinary data sets. The CWSAR algorithm can better complete the work of English teaching word recommendation and provide effective help for English teaching.

Keywords: word recommendation; collaborative filtering; word vector; group wisdom perception.

DOI: 10.1504/IJCSYSE.2024.137451

International Journal of Computational Systems Engineering, 2024 Vol.8 No.1/2, pp.30 - 39

Received: 09 Aug 2022
Accepted: 27 Dec 2022
Published online: 19 Mar 2024 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article