Abstract
In the era of knowledge economy, Knowledge has become the main means of production and the core source for value creation. However, especially tacit knowledge acquisition, knowledge acquisition is bottleneck in all kinds of knowledge system, cutting down the benefit of knowledge sharing, application and innovation. In view of this, in this paper, the main ideas and deficiencies of the existing methods of knowledge acquisition are generalized. And then, the basic principles, characteristics and the integrated advantage of gray theory and RBF neural networks are analyzed. On this basis, three kinds of models are designed and discussed, which is able to obtain tacit rule set by using gray theory integrated with RBF neural network. Simultaneously, an empirical analysis is carried out to analyze application results of tacit knowledge acquisition, which includes five kinds of models using independent and integrated strategies.
Highlights
Knowledge Acquisition connotationThe academic world on the "knowledge acquisition" of the understanding there are multiple versions, representative are: Breuker suggested that knowledge acquisition is to obtain useful knowledge from a specific source to solve the problem of knowledge or experience, it is the foundation for people to understand and transform the the world [1];Cassiman and Veugelers argue that knowledge acquisition is the fundamental activity that underpins the organization to achieve knowledge innovation [2];In China, Wu Quan-yuan and Liu Jiang-ning pointed out that knowledge acquisition is the process of extracting knowledge from external knowledge sources into the computer system [3].In view of the foregoing, we believe that knowledge acquisition refers to the analysis and extraction of problem-solving knowledge from knowledge sources, formats and codes them by appropriate knowledge representation methods stored in the system knowledge base
Manual knowledge acquisition,semi-automatic knowledge acquisition and automatic knowledge acquisition are the main methods of tacit knowledge acquisition [6,7].Manual knowledge acquisition through face-to-face communication with domain experts and experts, which is very inefficient.Compared with manual knowledge acquisition,Semiautomatic knowledge acquisition improves the efficiency of knowledge acquisition to a certain extent
The gray RBF neural network model, which combines the RBF neural network model with the gray model, has the characteristics of small sample data modeling for gray system, and has the advantages of neural network model with adaptive ability to nonlinear and inexact laws ; The model reduces the demand for raw data and the training time consumption of automatic knowledge acquisition to a certain extent
Summary
The academic world on the "knowledge acquisition" of the understanding there are multiple versions, representative are: Breuker suggested that knowledge acquisition is to obtain useful knowledge from a specific source to solve the problem of knowledge or experience, it is the foundation for people to understand and transform the the world [1];Cassiman and Veugelers argue that knowledge acquisition is the fundamental activity that underpins the organization to achieve knowledge innovation [2];In China, Wu Quan-yuan and Liu Jiang-ning pointed out that knowledge acquisition is the process of extracting knowledge from external knowledge sources into the computer system [3].In view of the foregoing, we believe that knowledge acquisition refers to the analysis and extraction of problem-solving knowledge from knowledge sources, formats and codes them by appropriate knowledge representation methods stored in the system knowledge base
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