Abstract
Web page prediction plays a vital role in anticipation and pre-fetching webpage in advance earlier than the user accesses that webpage in future, resulting in reducing the user latency and efficiently utilize the minimum bandwidth of the network. Process of accessing any information on the internet, clustering plays an important role. But clustering is done only by using the navigational behavior of the user. The clustering technique is done for the purpose of making certain groups of similar web pages. The whole process of anticipation of web page tries to use the pre-fetching techniques and Markov and hidden Markov model. On the basis of the similar behavior of web pages they are divided into various clusters and with the help of using the prediction algorithm we are able to anticipate the next most probable web page by using the user’s current accessible web page.
Highlights
Owing t o t he e normous growth o f W orld W ide Web, congestion and overloading of server occurs
F or im plementing t his web p age a nticipation m odel, na vigational be havior of th e current users is stored in the web log files
Markov m odel prediction a ccuracy was computed considering the transaction as a test set and only the c luster t hat the t ransaction be longs toasat raining s et
Summary
Owing t o t he e normous growth o f W orld W ide Web, congestion and overloading of server occurs. V arious techniques for latency reduction are web catching, pre-fetching and preopening. Need of this web page anticipation system is required i n t he er a o f e-commerce digital w orld w here ev ery transaction is d epended o nly o n the efficiency o f how fast we are able to accesses the required web page within the particular time s lot. R esearchers us e different ki nd of t echniques comprising M arkov M odel f or ne xt w eb pa ge anticipation, clustering and prediction A rchitecture. F or im plementing t his web p age a nticipation m odel, na vigational be havior of th e current users is stored in the web log files
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