【摘要】 为深度挖掘企业级信息系统用户群的多样化信息需求,通过宏观和微观的粒计算理论模型的对比分析,提出了一种融合粗糙集和商空间理论的企业级信息系统日志挖掘方法。首先以用户在一定时间内对企业级信息系统不同功能模块的使用频次和岗位角色来构建用户特征属性表;然后采用商空间理论的投影划分法进行用户群的层次化划分,得到两个不同用户粒度空间下的决策表;再利用基于粗糙集理论的知识获取方法,在两个用户粒度空间上分别导出相应的用户群识别规则;最终从不同角度综合分析用户群信息需求的一致性和差异性。应用实例验证了该方法的可行性和有效性。更多还原

【Abstract】 To realize the deep mining of diversification in information requirements among different user groups of enterprise information system,a log mining method by combining the theory of rough set and quotient space was put forward through comparison and analysis of the macrocosmic and microcosmic theoretical models of granular computing.Firstly,the users’ characteristic attributes table was established in terms of their use frequencies for different function modules of enterprise information system in a certain period and their working roles.Secondly,the decision tables in two user granular spaces were built by hierarchical division of user groups based on projection division method of quotient space theory.Furthermore,the corresponding user identification rules in two user granular spaces were respectively derived by means of applying knowledge acquisition method of rough set theory.Finally,the consistency and discrepancy of information requirements among different user groups was comprehensively analyzed from different angles.The application case shows the feasibility and effectiveness of the proposed method.更多还原