复杂属性环境下NoSQL分布式大数据挖掘方法研究

由于复杂属性环境下的大数据挖掘工作需要涉及到对大数据的分析、清理、转换和集成等一系列操作,导致以往提出的复杂属性环境下大数据挖掘方法无法同时拥有较强的准确性、稳定性和实用性,故提出复杂属性环境下NoSQL分布式大数据挖掘方法。所提方法利用NoSQL数据库的物理分散逻辑,在复杂属性环境下构建NoS QL数据库,给出挖掘条件,对数据库中大数据的特征、位置、方向和长度属性的关联性进行分布式挖掘,经由挖掘公式给出挖掘结果。利用挖掘聚类公式对大数据的特征、位置、方向和长度属性的关联性挖掘结果进行聚类,获取所提方法的最终挖掘结果。经实验分析可知,所提方法在挖掘工作中具有较强的准确性、稳定性和实用性。

Research on NoSQL distributed big data mining method in complex attribute environment

Due to the complex attribute environment of data mining work need to involve the analysis of data, cleaning, conversion and integration of a series of operation, resulting in past the complex nature of environmental data mining methods can''t have good accuracy, stability and practicability, therefore, the property of the complex environment NoSQL distributed data mining method. Method using NoSQL database physical distributed logic, build NoSQL database under the complex nature of the environment, the characteristics of database data, location, direction and length property of the association mining and distributed, through mining formula is given for the mining results. Using clustering formula for large data feature mining, position, direction and length property of the association mining results are clustered to obtain the final mining results. The experimental results show that the proposed method is of high accuracy, stability and practicability.