顾及信息熵构造判定树的网络数据库搜索算法  

Network Database Search Algorithm Putting Information Entropy and Constructing Decision Tree into Account

作　　者：胡六四[1] HU Liusi(College of Software,Anhui Vocational College of Electronics ＆ Information Technology,Bengbu 233000,Anhu)

机构地区：[1]安徽电子信息职业技术学院软件学院,安徽蚌埠233000

出　　处：《攀枝花学院学报》2018年第5期79-82,共4页Journal of Panzhihua University

摘　　要：以顾及信息熵构造判定树为核心,在此基础上提出了顾及信息熵构造判定树(Information entropy construction decision tree,IECDT)的网络数据库搜索算法。借助于信息熵构造判定树构建了对应的抽象模型,之后在该数据基础上分析得到了网络数据库搜索算法。实验表明:与典型DS-means相比,文中所提的网络数据库搜索算法不仅能大幅度地减少网络数据间的通讯代价,还能提升平均10%左右的网络数据库搜索效率。This paper centers on information entropy construction decision tree（ Information entropy construction decision tree,IECDT） and proposes a network database search algorithm. It constructs the corresponding abstract model with the aid of information entropy construction decision tree. The experiment shows that in comparison with the typical DS-means,the proposed network database search algorithm can not only greatly reduce the communication cost between the network data,but also improve the efficiency of the network database search with an average of about 10%.

关 键 词：网络数据库 搜索算法 信息熵构造判定树 数据模型 

分 类 号：TP391.3[自动化与计算机技术—计算机应用技术]