Access Optimization of Teaching Resource Management Database Based on Semantic Association Mining

Due to the rapidly increasing use of information and communications technology, Semantic Web technology is being increasingly applied in a large spectrum of applications in which domain knowledge is represented by means of an ontology in order to support reasoning performed by a machine. A semantic association (SA) is a set of relationships between two entities in knowledge base represented as graph paths consisting of a sequence of links. Because the number of relationships between entities in a knowledge base might be much greater than the number of entities, it is recommended to develop tools and invent methods to discover new unexpected links and relevant semantic associations in the large store of the preliminary extracted semantic association. Semantic association mining is a rapidly growing field of research, which studies these issues in order to create efficient methods and tools to help us filter the overwhelming flow of information and extract the knowledge that reflect the user need. The authors present, in this work, an approach which allows the extraction of association rules (SWARM: Semantic Web Association Rule Mining) from a structured semantic association store. Then, present a new method which allows the discovery of relevant semantic associations between a preliminary extracted SA and predefined features, specified by user, with the use of Hyperclique Pattern (HP) approach. In addition, the authors present an approach which allows the extraction of hidden entities in knowledge base. The experimental results applied to synthetic and real world data show the benefit of the proposed methods and demonstrate their promising effectiveness.

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Design and Implementation of Campus Network Based Teaching Resource Management

2010 International Conference on E-Product E-Service and E-Entertainment ◽

10.1109/iceee.2010.5661588 ◽

2010 ◽

Author(s):

Hongyan Wang

Keyword(s):

Resource Management ◽

Campus Network ◽

Design And Implementation ◽

Teaching Resource

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Design of Online and Offline Integration Teaching System for Body Sense Dance Based on Cloud Computing

Journal of Interconnection Networks ◽

10.1142/s0219265921470010 ◽

2021 ◽

Author(s):

Yun He

Keyword(s):

Cloud Computing ◽

Resource Management ◽

Data Storage ◽

Data File ◽

Media Management ◽

Teaching Resources ◽

Teaching Management ◽

Module Design ◽

Teaching Resource ◽

Teaching Content

Traditional teaching methods are limited to time and place, and the performance of dance teaching resource management is poor. This paper designs a dance teaching resource management system based on cloud computing. The functional structure of the system includes the core cloud computing teaching and teaching management application. The data management module is used to store the processed data in the data file, and respond to the retrieval request of dance teaching content publishing module and the remote image resource positioning request of multi-media management module. Design user courseware on demand process, using the existing dance teaching resources to learn. The experimental results show that the designed system has good performance, high stability and compatibility, and strong data storage capacity of teaching resources.

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Construction of Multimedia Teaching Resource Management Evaluation Model in the Big Data Environment

International Journal of Emerging Technologies in Learning (iJET) ◽

10.3991/ijet.v13i03.8365 ◽

2018 ◽

Vol 13 (03) ◽

pp. 4

Author(s):

Wei Bian

Keyword(s):

Big Data ◽

Resource Management ◽

Evaluation Method ◽

Evaluation Model ◽

Management Evaluation ◽

Teaching Resource ◽

Multimedia Teaching ◽

Proposed Model ◽

Multi Media ◽

Data Environment

In view of the deficiencies in the studies of the multi-media teaching resource management method and resource management evaluation model, a multi-media teaching resource management evaluation model in the big data environment is proposed in this paper based on the existing work. The teaching resource management evaluation method of the proposed model is further studied based on the elaboration of the component elements of the model. Guided by the multimedia teaching resource management evaluation model, the construction method for the multimedia teaching resource management evaluation model is studied in the open big data environment. And the multimedia remote teaching data of 360 encyclopedia and news web pages are used as the basis for experimental verification. The results show that the proposed model and method can effectively evaluate the multimedia teaching resource management.

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