Title: Personalised recommendation method of English micro-lectures teaching resources based on internet of things platform

Authors: Zhengui Zhang

Addresses: School of Humanities and Foreign Languages, Xi'an University of Posts and Telecommunications, Xi'an 710121, China

Abstract: In order to overcome the problems of low accuracy and long time-consuming in traditional teaching resource recommendation methods, a personalised recommendation method of English micro course teaching resources based on internet of things platform is proposed. Collect the internet of things platform server agent, server and client for user interest resource data, preprocess user interest resource data. The user interest model is constructed by using the obtained user interest resource data, and the English micro class teaching resource model is constructed by vector space model. This paper combines the user interest model with the English micro class teaching resource model, and makes personalised recommendation of English micro class teaching resources. The experimental results show that: the accuracy rate of the proposed method is as high as 98%, and the recommendation time is less than 6 s, which can realise the personalised recommendation of English micro class teaching resources.

Keywords: internet of things platform; English micro-lectures; teaching resources; personalised recommendation; vector space model; recommendation algorithm.

DOI: 10.1504/IJICT.2022.120632

International Journal of Information and Communication Technology, 2022 Vol.20 No.2, pp.115 - 132

Received: 20 May 2020
Accepted: 31 Jul 2020
Published online: 31 Jan 2022 *

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