{"title":"用于PageRank计算的分布式随机方法:第2部分","authors":"H. Ishii, R. Tempo","doi":"10.1109/CDC.2008.4739022","DOIUrl":null,"url":null,"abstract":"In the search engine of Google, the PageRank algorithm plays a crucial role in ranking the obtained results. The algorithm determines the importance of each web page based on the link structure of the web. In this two-part paper, we propose a distributed randomized approach for the PageRank computation, where the pages locally update their values by communicating with linked pages. This paper is the second part, and we develop two enhanced distributed schemes which deal with simultaneous updates and update termination of the computations, respectively.","PeriodicalId":411031,"journal":{"name":"IEEE Conference on Decision and Control","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"A distributed randomized approach for the PageRank computation: Part 2\",\"authors\":\"H. Ishii, R. Tempo\",\"doi\":\"10.1109/CDC.2008.4739022\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the search engine of Google, the PageRank algorithm plays a crucial role in ranking the obtained results. The algorithm determines the importance of each web page based on the link structure of the web. In this two-part paper, we propose a distributed randomized approach for the PageRank computation, where the pages locally update their values by communicating with linked pages. This paper is the second part, and we develop two enhanced distributed schemes which deal with simultaneous updates and update termination of the computations, respectively.\",\"PeriodicalId\":411031,\"journal\":{\"name\":\"IEEE Conference on Decision and Control\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Conference on Decision and Control\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CDC.2008.4739022\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Conference on Decision and Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CDC.2008.4739022","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A distributed randomized approach for the PageRank computation: Part 2
In the search engine of Google, the PageRank algorithm plays a crucial role in ranking the obtained results. The algorithm determines the importance of each web page based on the link structure of the web. In this two-part paper, we propose a distributed randomized approach for the PageRank computation, where the pages locally update their values by communicating with linked pages. This paper is the second part, and we develop two enhanced distributed schemes which deal with simultaneous updates and update termination of the computations, respectively.