Advanced Page Rank Algorithm with Semantics, In Links, Out Links and Google Analytics
This incremental improvement aims to enhance search engine results for users by reducing search space through better ranking.
The authors tackled the problem of improving web search relevance by modifying the PageRank algorithm to incorporate semantics, link analysis, and Google Analytics data, resulting in a system that ranks pages based on search queries and user behavior to display more valuable results at the top.
In this paper we have modified the existing page ranking mechanism as an advanced Page Rank Algorithm based on Semantics Inlinks Outlinks and Google Analytics. We have used Semantics page ranking to rank pages according to the word searched and match it with the metadata of the website and provide a value of rank according to the highest priority.We have also used Google analytics to store the number of hits of a website in a particular variable and add the required percentage amount to the ranking procedure.The proposed algorithm is used to find more relevant information according to users query.So this concept is very useful to display most valuable pages on the top of the result list on the basis of user browsing behaviour which reduce the search space to a large scale.