Review on Finding Dominance on Incomplete Big Data

Abstract

Big Data is a term used to represent huge size of data and still growing exponentially with time. In short, all data sets are large and complex. The existing traditional data management tools are not able to store and process the large data sets effectively. In Data sets which contains incomplete data and they having random-distributed missing nodes in its dimensions. It is very hard to get back datas from this type of data set when it is large. Dominance value is the most influential value in the data set. A deep analysis is need to identify top-k dominance value in the data set. Some of the existing methods to find the top-k dominant values are Pair wise comparison, Skyline based algorithm, Upper bound based algorithm, Bitmap index guided algorithm. But the major problems of these methods are mainly applicable only to small data sets, complexity increases with increasing data, require numerous comparisons between values, slower data processing respectively. In this review discuss in detail the existing methods to find the dominance values on incomplete data set.