基于相似度的粗关系数据库的近似查询

基于数据库理论和粗集方法研究了粗关系数据库中不确定数据的存储、索引和检索。提出了分别采用邻接表和十字链表实现粗关系数据库中属性值等价类和元组数据的存储；借助汉明距离和聚类方法，提出了实现粗关系数据库索引的方法；提出一种基于Rough集中的上、下近似计算数据间的相似度，并基于相似度给出了对粗关系数据库进行查询的模型，设计了相应的查询算法。最后，通过一个具体实例说明了查询算法的可行性和有效性。

Approximate query based on similarity degree in rough relation ratabases

In this paper,the storage,index and search of uncertain data in a rough relational database(RRDB) are studied by combining database theory and rough sets.First,two storing techniques are proposed.One is to store equivalence classes with regard to the values of attributes by using an adjacency list.The other is to store records of RRDB by using an orthogonal list.Secondly,based on Hamming distance and the given clustering method,one way to index uncertain data in RRDB is put forward.Thirdly,an approach to calculating the similarity between the data entered by users and the data being queried in RRDB based on the concepts of upper and lower approximation of rough sets is presented.Fourthly,a querying model of RRDB is constructed and an algorithm for querying uncertain data in RRDB is presented.Finally,a real world example is illustrated and results shows that the proposed algorithm is useful and effective.