{"title":"基于遗传和蚁群算法的聚焦爬虫设计","authors":"Song Zheng","doi":"10.1109/IBICA.2011.98","DOIUrl":null,"url":null,"abstract":"A novel design of the focused crawler based on the genetic and ant algorithms is proposed in this paper. The genetic and ant algorithms are combined together to improve the performance of focused crawler. The selection operator, crossover and mutation operator are optimized. The whole improved frame is funded on the new URL analysis model. And experimental results show the new algorithm's efficiency.","PeriodicalId":158080,"journal":{"name":"2011 Second International Conference on Innovations in Bio-inspired Computing and Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Genetic and Ant Algorithms Based Focused Crawler Design\",\"authors\":\"Song Zheng\",\"doi\":\"10.1109/IBICA.2011.98\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A novel design of the focused crawler based on the genetic and ant algorithms is proposed in this paper. The genetic and ant algorithms are combined together to improve the performance of focused crawler. The selection operator, crossover and mutation operator are optimized. The whole improved frame is funded on the new URL analysis model. And experimental results show the new algorithm's efficiency.\",\"PeriodicalId\":158080,\"journal\":{\"name\":\"2011 Second International Conference on Innovations in Bio-inspired Computing and Applications\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-12-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 Second International Conference on Innovations in Bio-inspired Computing and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IBICA.2011.98\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 Second International Conference on Innovations in Bio-inspired Computing and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IBICA.2011.98","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Genetic and Ant Algorithms Based Focused Crawler Design
A novel design of the focused crawler based on the genetic and ant algorithms is proposed in this paper. The genetic and ant algorithms are combined together to improve the performance of focused crawler. The selection operator, crossover and mutation operator are optimized. The whole improved frame is funded on the new URL analysis model. And experimental results show the new algorithm's efficiency.