Application of Cloud Storage Technology in the Management of Massive Digital Teaching Resources Based on HDFS

Cao, Hui

doi:10.3923/jse.2015.797.807

Cited by 1 publication

(1 citation statement)

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“…Knowledge network can well describe the knowledge development progress during teaching process and the relations of teaching resources. Therefore, managing the virtual simulation teaching resources based on knowledge network technology and arranging the scattered resources around each teaching point are very important for teachers to form a complete teaching system [26][27][28].…”

Section: Introductionmentioning

confidence: 99%

Use of a Knowledge Network for Management and Sharing of Teaching Resources for Building Construction Simulations

Tan¹,

Yang²

2023

Int. J. Emerg. Technol. Learn.

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A Knowledge network can well describe the knowledge development progress during teaching process and the relations of teaching resources. Managing the virtual simulation teaching resources based on knowledge network technology and arranging the scattered resources around each teaching point are very important for teachers to form a complete teaching system. However, there are many problems pending for solutions in research fields such as the construction of Chinese knowledge network and the text management based on knowledge network technology. For this reason, this paper aims to study the management and sharing of building construction virtual simulation teaching resources based on knowledge network analysis. At first, this paper elaborated on the construction process of the knowledge network of teaching resources, and introduced in detail a few steps during the construction process, including the entity/attribute extraction, coreference resolution, and relation extraction, etc. Then, this paper proposed an improved spectral clustering algorithm for the management and sharing of the said teaching resources, and realized the resource management and sharing works on a platform. At last, experimental results verified the validity of the proposed algorithm and the constructed model.

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Section: Introductionmentioning

confidence: 99%