Optimization of Algorithm of Similarity Measurement in High-Dimensional Data
Limin Yan · Computer Technology and Development · 2011
The problem of similarity measurement between high dimensional data is one of the problems high-dimensional data mining faces.In order to solve the problems of high-dimensional similarity measurement,analysis of traditional algorithms are made at first to obtain limitation.A new function Close() is presented based on the improvement of traditional algorithm to make up for the inadequate of traditional algorithm used in high-dimensional space.Advantages of the new function are obvious in high-dimensional similarity measurement after the comparison between Close() and tradition algorithms are made.Quantitative analysis of function Close() is made with Matlab and experiments prove that this function can avoid the affects of noise and the curse of high-dimension.