基于粒度原理的知识组织模型构建

Building Knowledge Organization's Model by Means of Granularity Principle

大数据环境下信息爆炸式增长,由于数据量大、分散、混沌和无序,导致难以利用已有信息有效和快速地解决用户的问题,文章试图对复杂问题求解过程进行规划和设计,对求解所需知识进行组织,分析问题、知识和求解过程之间关系,借助粒度原理来描述知识及其相互关联度,以解决用户问题的目标,先对问题求解所需静态知识进行粒度化,然后基于问题进行任务分解动态的关联知识,同时动态调整知识粒度,形成静态知识组织——动态知识组织两级粒度知识组织模型,建立基于粒度知识的综合求解方法,最终实现用户问题的求解,从而为用户提供高效的知识服务。

Under the circumstance of big data explosion, because the data is scattered, chaotic and unordered, it is very difficult for the effective and quick resolution of the user＇s problems by means of the existing information. This paper intends to formulate the solving process of complex problems, organize the knowledge needed, analyze the connection between problem, knowledge and solving process. Knowledge and the correlation is described between different knowledge with the aid of granularity principle. In order to resolve the problems of users, at first, static knowledge is organizated on the process of granularity, secondly, related dynamic knowledge is decomposed, knowledge granularity can be adjusted, the model is built on two-type knowledge granularity, the dynamic and the static knowledge organization are established, hence the user＇s problems is solved, the high efficiency knowledge service is provided for the user.