Enhancing Privacy and Security in Personalized Web Search
A. G. Priyanka, D. Satpalsing · International Journal of Computer Applications · 2016
Personalized Web Search is a promising way to improve the accuracy of web search and has been attracting much attention recently.Data classification and prediction using searching are used for many purposes.Privacy and security of Personal information has the more challenging task in web mining.In existing system greedy algorithm is used and it generates decision tree which stores split pattern.If split pattern is disclose then complete tree data can be retrieved.So this can compromise privacy due to which it is unsecured.In proposed system train the system with dataset and calculate the probability of output classes.The probability calculation is personalized to the training dataset and output is secured by providing enhanced privacy.In Proposed Approach, System improve the relevancy and prediction of the information in order to get more accurate result for effective personalized web search.Experimental evaluation shows that, Results obtained by using proposed approach are more precise and relevant than existing approach.