一种基于关联度的Skyline多目标优化文献检索方法设计与测试

Design and Experiment of a Skyline Multi-objective Optimization Literature Retrieval Method Based on Correlation Degree

查询与结果排序是文献检索系统的两个重要指标,直接影响着用户对文献资源的利用率。针对目前文献检索排序策略上存在的不足,从用户检索文献的需求出发,在Skyline算法的基础上提出一种基于Skyline关联度的多目标优化文献检索排序方法,将文献之间的关联程度作为查询算法的主要条件进行检索和排序,从而将有价值的资源挖掘出来。最后,基于CNKI数据库平台对相关文献进行检索,并应用所设计模型对检索结果进行重新排序。结果表明,该方法可有效优化排序结果,将关联度较高的文献信息挖掘出来,满足用户对期望资源的检索要求,提高了文献的利用率,具有一定的参考价值。

The querying and sorting the results are two important indexes of literature retrieval system,they directly affect the utilization of literature resources. In view of the current literature retrieval sequencing strategy,this study started from the user retrieval information needs,and was based on Skyline algorithm to propose a multi-objective optimization literature retrieval ranking method. The degree of correlation of the literature was the main condition and used to retrieving and ranking information,so that it could have the value of resource mining. Based on the CNKI database,relevant literature was retrieved,and application design model of search results was established. Results showed that the method could effectively optimize the ranking results,and mine associative information with a higher degree of correlation to meet the user expectations of resource retrieval requirements. The method improved the utilization rate of literature,and had a certain reference value.