Improve an Enhanced-Ratio Rank Algorithm based on Reading Time

Web mining is an active research area in the present scenario. Web mining is defined as the application of the data mining techniques on the World Wide Web for finding the hidden information. It can be classified into three categories web content mining, web structure mining, and web usage mining. Page ranking is based on the web structure mining. Page rank is extensively used for rank the webpages using various page ranking algorithms like page ranking algorithm, weighted page ranking algorithm, enhanced-ratio rank algorithm, reading time based page ranking algorithm, page level based algorithm, etc. By Comparison between all these algorithms, conclude that enhanced-ratio rank is better because it use inlinks, outlinks and also visit of links. And my proposed algorithm is adding an average reading time in enhanced ratio rank algorithm for the getting a better results and to reduce the limitation of existing algorithm. In this paper we add the results of enhanced-ratio rank and page ranking algorithm based on reading time and proposed algorithm that is improve an Enhanced-Ratio Rank Algorithm Based on Reading Time. Results shown that proposed algorithm gives the better result because it assign the rank based on the inlinks, outlinks, visit of links of the webpages and use the average reading time of the webpages. Here we use the different webpage on the Book Information and the average reading time of different users.