Theoretical Approach of Search of Missing Values in Data Set using Data Mining

Abstract

The uncontrollable expansion of the information over the internet creates a critical job to discover which information is supportive or useful for a particular user. This paper proposes a new filtering technique using rough set and clustering technique to seek out the nearest neighbor, So that the user can get the right choice for the collection of the objects which are appropriate for them. In this paper, we are going to find out missing values in data set by using data mining specifically with the help of filtering technique that uses a membership function which is a unique suggesting approach by combining the marking, trait, likes and features of user’s information about items. Our approach moves towards the state of the art suggesting system, and reduce the recorded problems. Filtering technique suggest items by taking in to order of the taste of users, under the supposition that users will be attracted by a particular item that users alike to them have rated highly. To our best information, this is the unique study of integrating traits and likes of user’s information converted into a missing value for the development of suggesting manager..