An Efficient Data Compress Algorithm and Data Mining

Yang Li

Abstract: LARGE DATA SIZE, BOTTLENECK IN THE SPEED OF THE CLOUD UPLOADS AND PROGRAM LOADS, REDUNDANT DATA, INACCURATE DATA IS THE RESENT BLOCK TOWARDS DATA RESEARCHES. IN THE PAPER, WE PROPOSE A PRACTICAL DATA COMPRESSION ALGORITHM, IN ORDER TO MERGE THE TIME INFORMATION, DELETE REDUNDANT DATA, ROUND THE OVER PRECISION, ETC. AIMING AT THE DIFFICULTY OF DATA MINING, WE PROPOSE APRIORI ALGORITHM AND SUPPORT VECTOR MACHINE (SVM). IN THE LIGHT OF INSUFFICIENT DATA ANALYSES AND MANAGEMENT, THIS PAPER PROPOSES ROUGH SETS THEORY, CONTRIBUTE TO COMPUTING DATA STUDY. THESE NUMERICAL EXPERIMENTS SHOW THAT THE ALGORITHMS BELOW CAN EFFECTIVELY ACCELERATE DATA LOAD SPEED, REDUCE DATA SIZE AND EFFICIENTLY MINING DATA.

Keywords: DATA COMPRESSION, APRIORI, DATA MINING, ROUGH SETS, SUPPORT VECTOR MACHINE