Investigating the Effect of Duration, Page Size and Frequency on Next Page Recommendation with Page Rank Algorithm

In this paper, we extend the use of page rank algorithm for next page prediction with several navigational attributes, which are size of the page, duration time of the page and duration of transition (two page visits sequentially), frequency of page and transition. In our model, we define popularity of transitions and pages by using duration information and use it in relation to page size and visit frequency factors. By using the popularity value of pages we bias conventional Page Rank algorithm and model a next page prediction system that produces page predictions under given top-n value. Actually we devise Duration Based Rank (DPR), which focuses on page duration with size proportion and Popularity Based Page Rank (PPR) ranking model, which focuses on both page duration with size proportion and frequency value of page visits. In addition to this, we investigate the effect of global and local ranking on PPR and DPR.