构建模糊检索的数学模型

Research on How to Construct Math Models for Fuzzy Retrieves

为了提高系统处理非精确信息的能力,模糊检索是不可缺少的。而构建模糊检索所用模糊语言的数学模型又是其成败的关键所在。对于数值型属性的语言变量使用隶属函数以及一些模糊算子,能够较准确表达模糊语言变量的含义;对于字符型属性的数据检索,当模糊性只存在字型和字音两个方面时,建立匹配函数更能体现模糊检索的优越性,从而帮助用户在信息模糊的情况下检索出所需信息。

Fuzzy is indispensable to improve the ability of dealing with the inaccurate information and the math models are key points in success. Membership functions are constructed to retrieve the information used language variables of numerical attributes. Matching function is constructed to retrieve the information of string attributes. It is proved that the methods are efficient for fuzzy retrieves. 