自适应元数据关联与本体学习

Amruta Pawar, Pranali Vethekar, Rupam Bhor, S. Bajpai
{"title":"自适应元数据关联与本体学习","authors":"Amruta Pawar, Pranali Vethekar, Rupam Bhor, S. Bajpai","doi":"10.17148/iarjset.2015.21011","DOIUrl":null,"url":null,"abstract":"A paying attention crawler is a crawler which returns connected web pages on a in traversing the web. Web Crawlers are one of the most vital unit of decisive part of the Search Engines to gather pages from the Web. The necessity of a web crawler that downloads most related web pages from such a large web is still a major challenge in the field of Information Retrieval Systems. Most Web Crawlers use Keywords approach for search the information from Web. But they search many irrelevant pages as well. In this paper, we present the framework of a novel self-adaptive semantic focused crawler – SASF crawler, with the of precisely and finding, and indexing by taking into account the heterogeneous, ubiquitous and ambiguous nature of mining information.The framework the technologies of semantic focused crawling and ontology learning, in order to use this crawler.","PeriodicalId":13360,"journal":{"name":"Imperial journal of interdisciplinary research","volume":"71 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2016-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Self-Adaptive Metadata Association and Ontology Learning\",\"authors\":\"Amruta Pawar, Pranali Vethekar, Rupam Bhor, S. Bajpai\",\"doi\":\"10.17148/iarjset.2015.21011\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A paying attention crawler is a crawler which returns connected web pages on a in traversing the web. Web Crawlers are one of the most vital unit of decisive part of the Search Engines to gather pages from the Web. The necessity of a web crawler that downloads most related web pages from such a large web is still a major challenge in the field of Information Retrieval Systems. Most Web Crawlers use Keywords approach for search the information from Web. But they search many irrelevant pages as well. In this paper, we present the framework of a novel self-adaptive semantic focused crawler – SASF crawler, with the of precisely and finding, and indexing by taking into account the heterogeneous, ubiquitous and ambiguous nature of mining information.The framework the technologies of semantic focused crawling and ontology learning, in order to use this crawler.\",\"PeriodicalId\":13360,\"journal\":{\"name\":\"Imperial journal of interdisciplinary research\",\"volume\":\"71 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Imperial journal of interdisciplinary research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.17148/iarjset.2015.21011\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Imperial journal of interdisciplinary research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.17148/iarjset.2015.21011","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

一个关注爬虫是一个爬虫返回连接的网页在一次遍历网络。网络爬虫是搜索引擎从网络中收集网页的决定性部分中最重要的单元之一。从如此庞大的网络中下载大多数相关网页的网络爬虫的必要性仍然是信息检索系统领域的一个主要挑战。大多数网络爬虫使用关键字方法从网络中搜索信息。但他们也会搜索许多不相关的页面。考虑到挖掘信息的异构性、泛在性和模糊性,本文提出了一种新的自适应语义聚焦爬虫框架——SASF爬虫,该爬虫具有精确查找和索引的特点。该框架采用了语义聚焦爬行技术和本体学习技术,以实现该爬虫的使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Self-Adaptive Metadata Association and Ontology Learning
A paying attention crawler is a crawler which returns connected web pages on a in traversing the web. Web Crawlers are one of the most vital unit of decisive part of the Search Engines to gather pages from the Web. The necessity of a web crawler that downloads most related web pages from such a large web is still a major challenge in the field of Information Retrieval Systems. Most Web Crawlers use Keywords approach for search the information from Web. But they search many irrelevant pages as well. In this paper, we present the framework of a novel self-adaptive semantic focused crawler – SASF crawler, with the of precisely and finding, and indexing by taking into account the heterogeneous, ubiquitous and ambiguous nature of mining information.The framework the technologies of semantic focused crawling and ontology learning, in order to use this crawler.
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
×
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