Performance Evaluation of Page Ranking Algorithm Based on Counting of Link Visits (PRCLV) for Effective Information Retrieval on World Wide Web

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Zaved Akhtar, Ravindra Kumar, Umesh Chandra Jaiswal Mahesh Kumar Singh


Due to an increasing number of web users and traffic, knowledge investigators rely greatly on engines for searching to extract useful information. The availability of innumerable textual, video, audio, and different kinds of content has raised the duty of search engines. The searching engine delivers relevant data about Internet users' queries based on interest, link order, and so on. It does not, however, ensure the accuracy of the data. The position module is a significant variable that decides the efficiently the search engine operates. Getting valuable information has demonstrated to be a debilitating undertaking. Site page ranker, a part that is professed to have been the vital game changer in Google's accomplishment, is quite possibly of the main component that solid the reception of page search administration. This article explains page ranking systems for internet mining that are based on content, structure, and usage mining. The suggested Page Ranking Algorithms is based on the number of link hits. Because each product has its own webpage dedicated to decryption, the top traffic links may be utilized to build a list of ideas for someone carrying out an online information search as well  may use for develop web based recommendation system on the basis of users behaviors .

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