Open AccessNetwork Big Data Mining Algorithm Based on Association Rules of Computer Technology
Author(s) -
Ya Dong Jiang
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1574/1/012084
Subject(s) - big data , computer science , association rule learning , data mining , generalization , intersection (aeronautics) , process (computing) , data stream mining , cluster analysis , cloud computing , data science , algorithm , machine learning , engineering , mathematics , mathematical analysis , aerospace engineering , operating system
With the development of cloud computing, it has provided a platform for big data presentation and sharing. These data often contain artificially added uncertain factors to prevent privacy leaks. How to perform mining of these big data is a problem to be solved urgently in big data sharing. In the big data for sharing, it is implemented through the generalization process of precise data, with the feature of uniform distribution, which is not conducive to exact query, but it can provide convenience for the mining of association rules. Firstly, based on the possible intersection or inclusion relationship, hierarchical clustering is performed on the generalized values. To save the essential information related to big dataset mining, we proposed an algorithm for building an uncertain frequent pattern tree. An improved algorithm of network big data mining based on association rules of computer technology is proposed in the big data environment, and its application in landslide monitoring and early warning is discussed.