An IMPROVED PAGERANK ALGORITHM BASED ON A HYBRID APPROACH
Fares Hasan, Koo Kwong Ze, Rozilawati Razali, Abudhahir Buhari, Elisha Tadiwa · Science Proceedings Series · 2020
PageRank is an algorithm that brings an order to the Internet by returning the best result to the users corresponding to a search query. The algorithm returns the result by calculating the outgoing links that a webpage has thus reflecting whether the webpage is relevant or not. However, there are still problems existing which relate to the time needed to calculate the page rank of all the webpages. The turnaround time is long as the webpages in the Internet are a lot and keep increasing. Secondly, the results returned by the algorithm are biased towards mainly old webpages resulting in newly created webpages having lower page rankings compared to old webpages even though new pages might have comparatively more relevant information. To overcome these setbacks, this research proposes an alternative hybrid algorithm based on an optimized normalization technique and content-based approach. The proposed algorithm reduces the number of iterations required to calculate the page rank hence improving efficiency by calculating the mean of all page rank values and normalising the page rank value through the use of the mean. This is complemented by calculating the valid links of web pages based on the validity of the links rather than the conventional popularity.