WhatNext: A Prediction System for Web Requests using N-gram Sequence Models
WISE '00 Proceedings of the First International Conference on Web Information Systems Engineering (WISE'00)-Volume 1 - Volume 1
Analysis and improvement of HITS algorithm for detecting Web communities
Systems and Computers in Japan
USITS'99 Proceedings of the 2nd conference on USENIX Symposium on Internet Technologies and Systems - Volume 2
Mining longest repeating subsequences to predict world wide web surfing
USITS'99 Proceedings of the 2nd conference on USENIX Symposium on Internet Technologies and Systems - Volume 2
Exploring the bounds of web latency reduction from caching and prefetching
USITS'97 Proceedings of the USENIX Symposium on Internet Technologies and Systems on USENIX Symposium on Internet Technologies and Systems
ICIT '07 Proceedings of the 10th International Conference on Information Technology
Proceedings of the CUBE International Information Technology Conference
The changing nature of Spam 2.0
Proceedings of the CUBE International Information Technology Conference
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Web page prediction plays an important role by predicting and fetching probable web page of next request in advance, resulting in reducing the user latency. The users surf the internet either by entering URL or search for some topic or through link of same topic. For searching and for link prediction, clustering plays an important role. Besides the topic, navigational behaviour is not ignored. This paper proposes a web page prediction model giving significant importance to the user's interest using the clustering technique and the navigational behaviour of the user through Markov model. The clustering technique is used for the accumulation of the similar web pages. Similar web pages of same type reside in the same cluster, the cluster containing web pages have the similarity with respect to topic of the session. The clustering algorithms considered are K-means and K-mediods, where K is determined by HITS algorithm. Finally, the predicted web pages are stored in form of cellular automata to make the system more memory efficient.