{"title":"深层网站的智能爬虫实现","authors":"Ewit","doi":"10.30534/ijccn/2018/30722018","DOIUrl":null,"url":null,"abstract":"Deep web is termed as data present on web but inaccessible to search engine. Due to the large volume of web resources and the dynamic nature of deep web, achieving wide coverage and high efficiency is a challenging issue. Smart crawler for hidden web interfaces consist of mainly two stages, first is site locating another is in-site exploring. Site locating starts from seed sites and obtains relevant websites through reverse searching and obtains relevant sites through feature space of URL, anchor and text around URL. Second stage takes input from site locating and goes to find relevant link from those sites. The adaptive link learner is used to find out relevant links with help of link priority and link rank.. To eliminate bias on visiting some highly relevant links in hidden web directories, we design a link tree data structure to achieve wider coverage for a website.","PeriodicalId":313852,"journal":{"name":"International Journal of Computing, Communications and Networking","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"IMPLEMENTATION OF SMARTCRAWLER FOR DEEP-WEB SITES\",\"authors\":\"Ewit\",\"doi\":\"10.30534/ijccn/2018/30722018\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Deep web is termed as data present on web but inaccessible to search engine. Due to the large volume of web resources and the dynamic nature of deep web, achieving wide coverage and high efficiency is a challenging issue. Smart crawler for hidden web interfaces consist of mainly two stages, first is site locating another is in-site exploring. Site locating starts from seed sites and obtains relevant websites through reverse searching and obtains relevant sites through feature space of URL, anchor and text around URL. Second stage takes input from site locating and goes to find relevant link from those sites. The adaptive link learner is used to find out relevant links with help of link priority and link rank.. To eliminate bias on visiting some highly relevant links in hidden web directories, we design a link tree data structure to achieve wider coverage for a website.\",\"PeriodicalId\":313852,\"journal\":{\"name\":\"International Journal of Computing, Communications and Networking\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-06-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Computing, Communications and Networking\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.30534/ijccn/2018/30722018\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Computing, Communications and Networking","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.30534/ijccn/2018/30722018","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

深网是指存在于网络上但搜索引擎无法访问的数据。由于网络资源的巨大容量和深网的动态性,实现广覆盖和高效率是一个具有挑战性的问题。隐藏界面智能爬虫主要包括两个阶段,一是站点定位阶段,二是站点内探索阶段。网站定位从种子网站开始,通过反向搜索获得相关网站,通过URL、锚点、URL周围文字的特征空间获得相关网站。第二阶段从站点定位输入,并从这些站点找到相关链接。自适应链接学习器通过链接优先级和链接等级来寻找相关链接。为了消除访问隐藏网络目录中一些高度相关链接的偏见,我们设计了一个链接树数据结构,以实现网站的更广泛覆盖。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
IMPLEMENTATION OF SMARTCRAWLER FOR DEEP-WEB SITES
Deep web is termed as data present on web but inaccessible to search engine. Due to the large volume of web resources and the dynamic nature of deep web, achieving wide coverage and high efficiency is a challenging issue. Smart crawler for hidden web interfaces consist of mainly two stages, first is site locating another is in-site exploring. Site locating starts from seed sites and obtains relevant websites through reverse searching and obtains relevant sites through feature space of URL, anchor and text around URL. Second stage takes input from site locating and goes to find relevant link from those sites. The adaptive link learner is used to find out relevant links with help of link priority and link rank.. To eliminate bias on visiting some highly relevant links in hidden web directories, we design a link tree data structure to achieve wider coverage for a website.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Comparative Analysis of Deadlock Detection Algorithm based on Blockchain A Framework for Meta-Learning in Dynamic Adaptive Streaming over HTTP OnionAider: A Model Driven Decision Support System for Weather and Pest-Occurrence Prediction in Onion Cultivation Digital Citizenship and its Role in Achieving the Vision of Kingdom of Saudi Arabia 2030 The Effective Role of using Kahoot Application in Supporting University Education in Saudi Universities: Case Study on King Abdulaziz University Jeddah, Saudi Arabia
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1