Elimination of backward browsing using decomposition and compression for efficient navigation prediction

摘要

Analysing the user's browsing patterns stored in weblog file can help in providing the personalised environment, improving website structure and recommending the suitable navigation pattern. While browsing the web, the user navigates in a forward direction following the web topology, results in the session having correlated web pages. Backward navigation takes place when the user returns to the previously visited page. This traversal results in increased session length, complexity and reduction in the prediction accuracy. The frequent backward movement also infers that the web community is not well structured. Therefore, to discover the meaningful browsing pattern and improve the website structure, it is essential to filter the repeated web pages from the session. This paper proposes two novel backward elimination techniques: decomposed backward browsing ( BBD~(com) ) and compressed backward browsing ( BB~(Com) ). BB~(Dcom) reduces the length of a session using decomposition. It can restore the original session without losing data. BB~(Com) compresses the session length by eliminating web page(s) lying in between the redundant web pages. The experimental result shows that proposed techniques improve the prediction accuracy and reduces the state-space complexity.