数据库模糊查询结果自动排序方法

数据库模糊查询会产生多个查询结果,因此有必要将查询结果按照用户需求进行排序.首先根据元组对模糊查询的隶属度,将查询结果中具有不同隶属度的元组分开.然后,利用PIR改进模型和历史查询记录来分析元组中被查询指定的属性值与未指定的属性值之间的关联程度,从而获得用户偏好并以此对具有相同隶属度的元组进行排序.在此基础上,提出了模糊查询下的DPR自动排序方法.实验及分析证明,提出的模糊查询结果自动排序方法能够极大地提高排序质量.

Automated Ranking of Database Fuzzy Query Results

There may be too many tuples in an answer after fuzzy query based on relational database.So,it is necessary to rank query results in accordance to user's needs.The ranking process is as follows.According to the degree of membership between tuple and fuzzy query,the tuples with different degree of membership in query results are differentiated from each other to form several membership classes.Then,the improved PIR(probability information retrieval) model and database workload are used to analyze the degree of correlation between the attribute values specified and unspecified in queries,thus ranking the tuples with the same degree of membership due to users' preferences.As a result,the DPR(degree of membership and probability ranking) process is proposed as an automated ranking approach for fuzzy query results,which has been proved to improve greatly the ranking quality of fuzzy query results through experiments and analysis.