Analysis of Metacrawler approach for URL based DUST removal by knowledge engineering systems

Priti Chittekar, Smita Deshmukh
{"title":"Analysis of Metacrawler approach for URL based DUST removal by knowledge engineering systems","authors":"Priti Chittekar, Smita Deshmukh","doi":"10.1109/ICCMC.2019.8819753","DOIUrl":null,"url":null,"abstract":"Multiple copies of URLs gathered by the web crawlers responsible for pages with similar or near about to similar content. Few pages combined by the web crawlers consist of similar content. Different URLs with Similar Text are generally known as DUST. Result of this is crawl data, to store the data and use such duplicated data results in building of less quality marking, waste of resources and destitute naive user experiences.To study with such problem, multiple studies have been observed. Previous studies focus only on URL based DUST removal .The proposed method removes content depended DUST and URL based DUST. To crawl the documents we are using a new method of metacrawler which fetches results from three Search engine. We are going to compare each website content with the other linked content to remove duplicates using k- gram paraphrased technique.","PeriodicalId":232624,"journal":{"name":"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)","volume":"161 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCMC.2019.8819753","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Multiple copies of URLs gathered by the web crawlers responsible for pages with similar or near about to similar content. Few pages combined by the web crawlers consist of similar content. Different URLs with Similar Text are generally known as DUST. Result of this is crawl data, to store the data and use such duplicated data results in building of less quality marking, waste of resources and destitute naive user experiences.To study with such problem, multiple studies have been observed. Previous studies focus only on URL based DUST removal .The proposed method removes content depended DUST and URL based DUST. To crawl the documents we are using a new method of metacrawler which fetches results from three Search engine. We are going to compare each website content with the other linked content to remove duplicates using k- gram paraphrased technique.
知识工程系统中基于URL的元爬虫除尘方法分析
由网络爬虫收集的多个url副本,这些网页具有相似或接近相似的内容。由网络爬虫组合的页面很少包含相似的内容。具有相似文本的不同url通常被称为DUST。这样做的结果是抓取数据,存储数据并使用这种重复的数据会导致构建质量较低的标记,浪费资源,缺乏幼稚的用户体验。为了研究这一问题,已经进行了多项研究。以往的研究主要集中在基于URL的粉尘去除上,本文提出了基于URL和基于内容的粉尘去除方法。为了抓取文档,我们使用了一种新的metcrawler方法,它从三个搜索引擎中获取结果。我们将比较每个网站的内容与其他链接的内容,以消除重复使用k- gram意译技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信