Deep Data Anaylizing Method Based on Scale Space Theory

Scale space theory has been introduced into the field of big data, but its research is still not deep enough and perfect because of the lack of universal theory and method. With deepening of big data processing applications, the research becomes more and more urgent. In view of the above question, this paper studies pervasive multi-scale data analysis theory and method. On one hand, we give the definition and partition of data scale as well as the relationship of multi-scale data set between the upper scale and lower scale based on concept hierarchy theory. On the other hand, we clarify the definition of multi-scale data analysis, study essence and classification method. Previous studies show that the proposed method has high coverage rate, high accuracy rate, lower error rate of support estimation degree and greater improvement the efficiency than the traditional algorithm.