High performance elimination method for redundant data under massive data interference
RU Bei
LI Hong
Abstract：Aiming at the problem that in the data treatment process of massive data, a lot of similar characteristics can bring the redundant interference to the data classification, and cause such drawbacks as multiple check and repetition during the determination with the classification center, a high performance elimination method for redundant data under the massive data interference was proposed. With the active sampling method, the redundancy data feature under the massive data interference was extracted and classified. In addition, the mean shift transfer function was introduced to perform the classification of redundant data, obtain the redundant data activity and realize the high performance elimination of redundancy data. The results show that compared with the traditional method, the high performance elimination method has good properties, short processed time and certain superiority.
Keywords：massive datainterferenceredundant datahigh performanceelimination methodimprovementmean valuetransfer function
Publication Date：2017-11-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 686-690 )