隱性知識外顯案例之多案例誘導(dǎo)型適配研究

摘要： [目的/意義]知識經(jīng)濟時代知識成為核心資源,隱性知識是組織創(chuàng)造價值的源泉。文章設(shè)計了一套隱性知識外顯案例的多案例誘導(dǎo)型適配方法,對知識用戶提供過程輔助,以此提高組織隱性知識的應(yīng)用效益。[方法/過程]采用熵權(quán)法確定案例條件方面權(quán)重,利用向量相似度算法計算待解問題與案例庫中既有歷史案例之間的視圖相似度,從而確定待解問題的多案例適配集;針對適配案例集中存在的冗余方面不利于挖掘出案例條件空間對決策空間的決定關(guān)系問題,采用遺傳算法簡化待解問題的適配案例集,并基于簡化的適配案例集,利用C4. 5決策樹算法求解待解問題誘導(dǎo)型適配的解軌跡。[結(jié)果/結(jié)論]算例表明,與業(yè)內(nèi)既有適配方法相比,文章提出的多案例誘導(dǎo)型適配方法合理、有效,具有相對優(yōu)勢。
[Purpose/significance] Knowledge is the core resource in the era of knowledge economy,and tacit knowledge is the source of organizational value creation. This paper designs a multi-case derivation adaptation method for tacit knowledge's explicit cases,so as to provide process assistance to knowledge users,and improve the application efficiency of organizational tacit knowledge. [Method/process] Entropy weight method is used to determine the weight of the case condition,and the vector similarity algorithm is used to calculate the view similarity between the case to be solved and the existing historical case in the case library,thereby the multi-case adaptation set of the problem is determined; the redundancy aspect in the case set is not conducive to mine the decision relationship of the case condition space to the decision space. Therefore,the genetic algorithm is used to simplify the set of adaptation cases for the problem in this paper. Based on the simplified adaptation case set,the C4. 5 decision tree algorithm is used to solve the solution trajectory of the induced adaptation of the problem. [Result/conclusion] The example shows that the multi-case induction adaptation method proposed in this paper is more reasonable and more effective compared with the existing adaptation methods in the industry. So this method has a comparative advantage.