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Author:

Jiang, W. (Jiang, W..) | Ma, Q. (Ma, Q..)

Indexed by:

Scopus

Abstract:

In order to optimize the integration of English multimedia resources and achieve the goal of sharing English teaching resources in education, this article reconstructs the traditional college English curriculum system. It divides professional English into learning modules according to different majors integrating public health teaching resources. How optimize the integration of English multimedia resources and achieving the goal of sharing English teaching resources (ETR) is the main direction of English teaching reform during the current COVID-19 pandemic. An English multimedia teaching resource-sharing platform is designed to extract feature items from multimedia teaching resources using the ID3 information gain method and construct a decision tree for resource push. In resource sharing, a structured peer-to-peer network is used to manage nodes, query location and share multimedia teaching resources. The optimal gateway node is selected by calculating the distance between each gateway node and the fixed node. Finally, a collaborative filtering (CF) algorithm recommends Multimedia ETR to different users. The simulation results show that the platform can improve the sharing speed and utilization rate of teaching resources, with maximum throughput reaching 12 Mb/s and achieve accurate recommendations of ETR. © 2023 Jiang and Ma

Keyword:

ETR ID3 information gain method Multimedia resources Resource sharing platform Hybrid recommendation algorithm

Author Community:

  • [ 1 ] [Jiang W.]Faculty of Humanities and Social Sciences, Beijing University of Technology, Beijing, China
  • [ 2 ] [Ma Q.]Faculty of Department of Foreign Language and Tourism, Hebei Petroleum University of Technology, Hebei, Chengde, China

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Source :

PeerJ Computer Science

ISSN: 2376-5992

Year: 2023

Volume: 9

3 . 8 0 0

JCR@2022

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 5

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