We apologize for a recent technical issue with our email system, which temporarily affected account activations. Accounts have now been activated. Authors may proceed with paper submissions. PhDFocusTM
CFP last date
20 December 2024
Reseach Article

InfoHRDS: Information Domain Linked With Hypertext Resource Discovery System

Published on May 2012 by Rajni Mehta, Upasana
National Workshop-Cum-Conference on Recent Trends in Mathematics and Computing 2011
Foundation of Computer Science USA
RTMC - Number 5
May 2012
Authors: Rajni Mehta, Upasana
c5e89816-be46-4548-8a71-c3feb70e4fd6

Rajni Mehta, Upasana . InfoHRDS: Information Domain Linked With Hypertext Resource Discovery System. National Workshop-Cum-Conference on Recent Trends in Mathematics and Computing 2011. RTMC, 5 (May 2012), 1-5.

@article{
author = { Rajni Mehta, Upasana },
title = { InfoHRDS: Information Domain Linked With Hypertext Resource Discovery System },
journal = { National Workshop-Cum-Conference on Recent Trends in Mathematics and Computing 2011 },
issue_date = { May 2012 },
volume = { RTMC },
number = { 5 },
month = { May },
year = { 2012 },
issn = 0975-8887,
pages = { 1-5 },
numpages = 5,
url = { /proceedings/rtmc/number5/6650-1033/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Workshop-Cum-Conference on Recent Trends in Mathematics and Computing 2011
%A Rajni Mehta
%A Upasana
%T InfoHRDS: Information Domain Linked With Hypertext Resource Discovery System
%J National Workshop-Cum-Conference on Recent Trends in Mathematics and Computing 2011
%@ 0975-8887
%V RTMC
%N 5
%P 1-5
%D 2012
%I International Journal of Computer Applications
Abstract

The world wide web is a system of interlinked hypertext documents contained on the Internet, these web page may contain text, images, videos, and other multimedia and navigate between them by using hyperlink. About million new pages go online each day. It is impossible for major search engines to update their collections to meet such rapid growth. Web mining is the application of data mining techniques to extract knowledge from web data, including web documents, hyperlinks between documents. To address the above problems, domain-specific search engines were introduced, which keep their Web collections for one or several related domains. Focused crawlers were used by the domain-specific search engines to selectively retrieve Web pages relevant to particular domains to build special Web collections, which have smaller size and provide search results with high precision. In this paper, we are introducing a global focused crawling approach which is beneficial in extracting more relevant data.

References
  1. Jin Xu Yingping Huang Gregory Madey ?A RESEARCH SUPPORT SYSTEM FRAMEWORK FOR WEB DATA MINING?.
  2. Subhendu kumar pani Deepak Mohapatra Bikram Keshari Ratha ?Integration of Web mining and web crawler: Relevance and State of Art? (IJCSE) International Journal on Computer Science and Engineering Vol. 02, No. 03, 2010, 772-776.
  3. Jaideep Srivastava. et . al "Web Mining— Concepts, Applications, and Research Directions? Chapter 21.
  4. Arvind Arasu,Junghoo Cho, Hector Garcia-Molina, Andreas Paepcke. Sriram Raghavan "Searching The Web". Computer Science Department, Stanford University.
  5. Raymond Kosala et. Al ?Web Mining Research: A Survey?.
  6. Dr. A. C. Mondal, Sourav Maitra ?A Study of Web Mining Research – Last few years and the Road Ahead? ICCS 2010, Burdwan University.
  7. Ying Wang, Wanli Zuo, Tao Peng, Fengling He "Domain-Specific Deep Web Sources Discovery" Fourth International Conference on Natural Computation.
  8. Zhaoqiong Gao, Yajun Du, Liangzhong Yi, Qiangqiang Peng, Yuekui Yan "Incrementally Updating Concept Context Graph(CCG) for Focused Web Crawling Based on FCA" 2009 .
  9. Michelangelo Diligenti, Frans Coetzee, Steve Lawrence, C. Lee Giles, Marco Gori, " Focused Crawling using Context Graphs," Proceedings of the 26th VLDB Conference, Cairo, p. 527–534, 2000.
  10. Qu Cheng, Wang Beizhan, Wei Pianpian" Efficient Focused Crawling Strategy Using Combination of Link Structure and Content Similarity" Proceedings of 2008 IEEE International Symposium on IT in Medicine and Education.
  11. Chau, M. and Chen, H. (2003). "Comparison of Three Vertical Search Spiders," IEEE Computer, 36(5), 56-62.
  12. Chen, H. , Chung, Y. , Ramsey, M. and Yang, C. (1998). "A Smart Itsy-Bitsy Spider for the Web," JASIS, 49(7), 604-618.
  13. Z. Michalewicz, Genetic algorithms + data structures = evolution Programs, Springer-Verlag, 1992.
  14. H. Chen, Y. Chung, M. Ramsey, and C. Yang, "A Smart Itsy-Bitsy Spider for the Web," JASIS, 49(7), pp. 604-618, 1998.
  15. Milad shokouhi, Pirooz Chubak, Zaynab Raeesy," Enhancing Focused Crawling with Genetic Algorithms," Information Technology: Coding and Computing, Volume 2, Issue, 4-6 April P. 503 – 508, 2005.
Index Terms

Computer Science
Information Sciences

Keywords

Www Web Mining Crawling Focused Crawling.