An Improved Model for the Evaluation of Search Engine Result Pages Using Hybridized Evaluation Techniques

In this paper, the hybridised ranking system was developed by utilising WPR to evaluate the structural importance of web pages by assigning values to both the incoming and outgoing links and also other web pages it is connected to while incorporating CTR metrics to account for user activities and TF-IDF to reduce the weight of commonly used words by assigning lower values to words that appear in many documents hence combining both to measure content relevance. The hybridised approach is compared with the standard PageRank (PR) using the sum of WPR, CTR and TF-IDF metrics for position ranking with 50 randomly selected query datasets which were ranked into less relevant (LR) and most relevant (MR) positions. The hybridised approach reduced irrelevant pages by reshuffling the less relevant pages to the bottom of the list of web pages found while moving the more relevant pages to the top for the given queries, thereby improving the ranking efficiency of the search engine result pages. In Table 4.1, the process of ranking the 1st, 2nd,7th and 8th document for the PageRank is moved to the 23rd 24th 25th and 26th position based on their relevance to the queried data while the 3rd, 4th,5th and 6th document maintained a high position based on their relevance. In Table 4.2, the 1st 2nd 3rd and 4th documents were reshuffled to the 7th 8th 9th and 10th positions while the 6th 7th and 8th documentsmaintained a high-ranked position due to their relevance.This study has provided a scalable framework that enhances user experience by minimising irrelevant search results and prioritising pages of higher relevance.