Collaborative Group Decision Making Process using Air Traffic-Flow Management

Initially linear dataset is formed for efficient retrieval of data from a huge database. Before undergoing the process of knowledge discovery feature reduction process is implemented. This reduces the dimensionality and increases the space of data storage. Hence the map reduce is processed for the next step in knowledge discovering process to remove unwanted and irrelevant data from the database. The Support Vector Machine is one of the classifications technique is used. This overcome the problem of k Means disadvantage, it does not support effectively for both linear and nonlinear format of data. Map Reduce method to add privacy to a huge database can be obtained by adding dual authentication technique which ensures the privacy of the user without over heading the process. This overcomes the overlapping issue caused by the k means algorithm and it also reduces the issue of finding the distance between the record and cluster.