为了解决知识网库中知识网的选择问题,提出了一种基于信息熵的知识网度量方法.首先,定义了基于信息熵的知识量函数,并证明了知识量函数的单调性.然后,将基于信息熵的知识网度量法用于基于用户功能需求的知识网选择中,并将基于用户功能需求的相似性和知识量作为评价知识网的量化指标.最后,在.NET平台上利用C#语言和数据库管理系统SQL Server2000,开发出基于用户功能需求的知识网选择的使能工具,并通过实例证明,相似性和知识量的结合可以更好地对知识网进行度量.用户功能需求越详细,且知识网库中的知识网相似性值和知识量值越接近目标知识网,则搜索到的知识网越能满足用户的需求.
To solve the selection problem of a knowledge mesh in a knowledge mesh base,an entropy-based measurement method of knowledge mesh is proposed.First,the definition of an entropy-based knowledge amount function is described.The function's monotonic properties are proved.Then,the entropy-based measure method is applied to the selection of the knowledge mesh based on user functional requirements.The similarity and the knowledge amount based on user functional requirements are used to quantitatively evaluate the knowledge mesh.Finally,by means of C# program language and SQL Server 2000 database,a knowledge mesh selection enabling tool is developed on the.NET platform.It is exemplified that the proposed method can precisely measure the knowledge mesh by combining the similarity and the knowledge amount.When the user functional requirements are more detailed and the similarity and the knowledge amount of the knowledge-mesh in the knowledge-mesh database are closer to the destination mesh,the searched knowledge mesh will meet the user requirements better.