An Efficient Top-K Relevant Data Retrieval Using Catsort Algorithm

Abstract

In the current era of internet world data act as an important source that holds many entity of information about the corporates, Financial Institutions, stock exchanges, IT firms, health organisations etc. The data extraction transforming the data into the required format unloading the data into the system is typically used to retrieve the information created by the organisation. The information act as an asset for the organisation to make for the improvements and enhancements of the business form and act as an asset. The driving the data from the massive storage is an important task. However the volume of data increases its it become difficult progressively to handle the data with current methods. The downside of employing the conventional approach motivated to create a robot model for returning top k search analysis. The proposed approach is focused on creating an efficient top-k relevant data retrieval using Catsort algorithm. From the massive Collection of data the top-K relevant data alone retrieved with reduced frame of time and accuracy of 90%.