抽象的な

NOVEL APPROCH FOR OFT BASED WEB DOMAIN PREDICTION

A. Niky Singhai , B. Prof Rajesh Kumar Nigam

In this paper, we present a complete framework and predict the Web page usage patterns from Web log files of a real Web site that has all the challenging aspects of real-life Web usage predict, including evolving user profiles and external data describing ontology of the Web content. Our Studies have been conducted on pre-fetching models based on Decision trees, Markov chains, and path analysis. However, the increased uses of dynamic pages, frequent changes in site structure and user access patterns have limited the efficacy of these static techniques. One of the techniques that are used for improving user latency is Caching and another is Web pre-fetching. Approaches that bank solely on caching offer limited performance improvement because it is difficult for caching to handle the large number of increasingly diverse files. For perform successful perfecting, we must be able to predict the next set of pages that will be accessed by users. The OFT Page Rank algorithm used by Google is able to compute the popularity of a set of Web pages based on their link structure. In this paper, a novel OFT Page Rank-like algorithm is proposed for conducting Web page prediction.. As the tool for the algorithm implementations we chose the ?language of choice in industrial world? – MATLAB.