{"title":"Enhancing the page ranking for search engine optimization based on weightage of in-linked web pages","authors":"Rekha Singhal, S. Srivastava","doi":"10.1109/ICRAIE.2016.7939544","DOIUrl":null,"url":null,"abstract":"The current information age has witnessed massive increase in the number of web based documents and services. Due to this explosive growth of online content, automated search engine programs are used to search and categorize billions of webpages and show only the most relevant pages for the search query submitted by the user. Search engines employ combination of automated algorithms, manually edited directories and advertisements to generate results for users' queries. In this paper, we propose and implement an augmented version of the standard PageRank algorithm [1] by using ‘weight’ of in-linked web pages. Rather than evenly dividing the weight of an in-linked webpage, our technique distributes it to all the out linked pages on the basis of their popularity. We name this enhanced page ranking algorithm as WIL (Weightage In-Link) PageRank algorithm. WIL uses the weights of in-linked webpages to calculate a new score of every individual webpage called WIL-score. Later the webpages can be ranked according to this WIL-score.","PeriodicalId":400935,"journal":{"name":"2016 International Conference on Recent Advances and Innovations in Engineering (ICRAIE)","volume":"100 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Conference on Recent Advances and Innovations in Engineering (ICRAIE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICRAIE.2016.7939544","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
The current information age has witnessed massive increase in the number of web based documents and services. Due to this explosive growth of online content, automated search engine programs are used to search and categorize billions of webpages and show only the most relevant pages for the search query submitted by the user. Search engines employ combination of automated algorithms, manually edited directories and advertisements to generate results for users' queries. In this paper, we propose and implement an augmented version of the standard PageRank algorithm [1] by using ‘weight’ of in-linked web pages. Rather than evenly dividing the weight of an in-linked webpage, our technique distributes it to all the out linked pages on the basis of their popularity. We name this enhanced page ranking algorithm as WIL (Weightage In-Link) PageRank algorithm. WIL uses the weights of in-linked webpages to calculate a new score of every individual webpage called WIL-score. Later the webpages can be ranked according to this WIL-score.