Research on Fuzzy Mining Algorithm for Massive Text Data Under Uncertain Noise

According to the traditional data mining methods have been mining of low precision, long running time, the wavelet transform and the uncertain fuzzy association rules data text data mining algorithm based on noise, firstly using wavelet transform for uncertain fuzzy data of massive text data noise preprocessing, fuzzy time massive text data sequence conversion to spectrum space, get the distance transform based clustering coefficient, the maximum of the minimum inter class spectrum space, and as a massive text data feature data using fuzzy coefficient, calculate the feature coefficients from membership belonging to the respective categories, determine the fuzzy association rules text data sets, interval division basis the multidimensional degree between the massive data sets, thus the uncertainty of effective mining of massive text data noise. The experimental results show that the proposed algorithm can effectively improve the accuracy of massive text data mining, and the mining efficiency is high.