Survey on Parallel Comparison of Text Document with Input Data Mining and VizSFP

Nowadays, the usage of world wide web is growing tremendously. The corpuses available on this world wide web is not structured or scattered data, due to this wide availability of huge amounts of corpuses there is a need for turning such data into useful information and knowledge. Therefore, data mining algorithm get used. In this work, various data is taken as input and mining algorithm get apply on this data for getting frequent pattern. After this, Parallel comparator get used to detect the similar pattern from the corpuses. Then the data get arrange into different groups of similar type by using clustering algorithm. To overcome the problem of representing this large amount of data, data mining and clustering results we are using information visualization techniques for visualizing similar frequent patterns.