{"title":"判断网页类型的方法","authors":"Xue Hong-Jun, Chen Tao, Xue Li-Min","doi":"10.1109/CIS.2012.28","DOIUrl":null,"url":null,"abstract":"This paper introduces a concept of information entropy to judge web-page types, which associates with the method put forward by Roadrunner that pre-purifying topic pages and then using proportional relation to judge the type of pages. With some typical pages from large website home, the average precision could be reached to 96.7%, which lays foundation for further information extracting work.","PeriodicalId":294394,"journal":{"name":"2012 Eighth International Conference on Computational Intelligence and Security","volume":"500 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Method for Judging Web-page Type\",\"authors\":\"Xue Hong-Jun, Chen Tao, Xue Li-Min\",\"doi\":\"10.1109/CIS.2012.28\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper introduces a concept of information entropy to judge web-page types, which associates with the method put forward by Roadrunner that pre-purifying topic pages and then using proportional relation to judge the type of pages. With some typical pages from large website home, the average precision could be reached to 96.7%, which lays foundation for further information extracting work.\",\"PeriodicalId\":294394,\"journal\":{\"name\":\"2012 Eighth International Conference on Computational Intelligence and Security\",\"volume\":\"500 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-11-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 Eighth International Conference on Computational Intelligence and Security\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIS.2012.28\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 Eighth International Conference on Computational Intelligence and Security","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIS.2012.28","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper introduces a concept of information entropy to judge web-page types, which associates with the method put forward by Roadrunner that pre-purifying topic pages and then using proportional relation to judge the type of pages. With some typical pages from large website home, the average precision could be reached to 96.7%, which lays foundation for further information extracting work.