Abstract
To enable the teaching administrator to better obtain effective knowledge from a large amount of information to assist management and improve the efficiency and level of teaching management, a variable precision rough set model for knowledge assisted management of distance education was proposed. First, based on the theory of complete reduction and knowledge extraction, the proposed pedigree ambiguity tree was used as a strategy for obtaining complete reduction. An algorithm for obtaining a complete set of reductions was given. Then, by studying the process of knowledge extraction, a multi-knowledge extraction framework was put forward. The process of data conversion was completely realized. Finally, experimental verification was performed. The results showed that the proposed model overcame the effect of noise data in real data and improved the efficiency of the algorithm. Therefore, the model has high universality.
Highlights
Distance open education is a new form of teaching in the world, and it is receiving increasing attention from the state and society
Dai and Xu [6] proposed a fuzzy gain ratio attribute selection method based on fuzzy rough set theory, and applied this method to gene selection of tumor gene expression
If the equivalence class information of the selected attribute is not retained, and only the reduced distribution table is used for attribute reduction, the necessary reduction information will be lost, which violates the basis of the acceleration mechanism
Summary
Distance open education is a new form of teaching in the world, and it is receiving increasing attention from the state and society. Dai and Xu [6] proposed a fuzzy gain ratio attribute selection method based on fuzzy rough set theory, and applied this method to gene selection of tumor gene expression It provides an alternative strategy for processing tumor data in gene expression or other applications. Liu et al [7] proposed a new method for computing variable-precision rough set model reduction and applied to the evaluation of power production. Aiming at the above research status, a variable precision rough set model for distance education knowledge-assisted management is proposed. It hopes to provide reference and help for knowledge management in distance education
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