基于错误逻辑相似变换构建网购用户评价有效集模型

Building Effective Set of User Evaluation in Network Shopping Model Based on Error Logic Similarity Transformation

基于错误逻辑相似转化联结词,给出了错误逻辑命题的论域、事物、空间、特征、量值、错误值、规则、错误函数、时间等参数的相似变换矩阵定义.文中给出了形式上为T(C_1)=C_2的相似变换错误矩阵方程模型.针对电子商务网购用户评价的网上抓取数据,定义了从包含若干无效评价的大集合向有效小集合变换的错误矩阵模型.模型是基于错误逻辑理论,从已知转化系数矩阵T,以及初始错误矩阵,向未知目标集合进行相似变换的知识推理探索.

Based on error logic similarity connective, the definitions of similarity transformation matrix about these parameters such as domain, things, space, characteristics, value of characteristic, error function, decision rules, error functions and time are proposed in this paper. The paper builds a similarity transformation matrix equation like T（C1 ） = C2. It uses the data from network shopping platform to construct a model from big set that conclude many invalid evaluation to effective small set. This model is an exploration of knowledge reasoning that from transformation coefficient matrix and initial matrix known to objective set unknown based on error logic.