{"title":"Application of Page Ranking Algorithm Based on Numbers of Link Visits in Web Recommendation System for Online Business","authors":"M. Singh, O. Rishi, S. Wadhwa","doi":"10.21058/GJECS.2018.32001","DOIUrl":null,"url":null,"abstract":"World Wide Web plays a vital role in global information service center. Online business is growing very rapidly by creating websites. Website is made of number of webpages. Webpage is dynamic collection of hyperlink and usage information, providing rich sources of web data for web mining. Due to exponential growth of dynamic information over the internet, information overload create big challenges for the researchers in this area. One of the key components which ensure the acceptance of web page search service is the web page ranker a component which is said to have been the main contributing factor of Google. This paper discusses the page ranking algorithms based on contents, structures and usages in web mining, proposed page ranking algorithm based on number of links visit. Since every product has its own unique web page for its decryption hence in selection of top most visited links can be applicable to create the recommendation list for the corresponding customer in online business. KeywordsPageRank, Web Mining, Recommendation System, Information retrieval, Web Graph, Online business.","PeriodicalId":365710,"journal":{"name":"Gyancity Journal of Electronics and Computer Science","volume":"121 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Gyancity Journal of Electronics and Computer Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21058/GJECS.2018.32001","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
World Wide Web plays a vital role in global information service center. Online business is growing very rapidly by creating websites. Website is made of number of webpages. Webpage is dynamic collection of hyperlink and usage information, providing rich sources of web data for web mining. Due to exponential growth of dynamic information over the internet, information overload create big challenges for the researchers in this area. One of the key components which ensure the acceptance of web page search service is the web page ranker a component which is said to have been the main contributing factor of Google. This paper discusses the page ranking algorithms based on contents, structures and usages in web mining, proposed page ranking algorithm based on number of links visit. Since every product has its own unique web page for its decryption hence in selection of top most visited links can be applicable to create the recommendation list for the corresponding customer in online business. KeywordsPageRank, Web Mining, Recommendation System, Information retrieval, Web Graph, Online business.