CFP last date
20 June 2024
Reseach Article

Performance Evaluation of Web Crawler

Published on None 2011 by Sandhya, M. Q. Rafiq
International Conference on Emerging Technology Trends
Foundation of Computer Science USA
ICETT2011 - Number 1
None 2011
Authors: Sandhya, M. Q. Rafiq
05c41b2a-90bb-44c8-a7fc-59010431f188

Sandhya, M. Q. Rafiq . Performance Evaluation of Web Crawler. International Conference on Emerging Technology Trends. ICETT2011, 1 (None 2011), 43-46.

@article{
author = { Sandhya, M. Q. Rafiq },
title = { Performance Evaluation of Web Crawler },
journal = { International Conference on Emerging Technology Trends },
issue_date = { None 2011 },
volume = { ICETT2011 },
number = { 1 },
month = { None },
year = { 2011 },
issn = 0975-8887,
pages = { 43-46 },
numpages = 4,
url = { /proceedings/icett2011/number1/4361-icett025/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Emerging Technology Trends
%A Sandhya
%A M. Q. Rafiq
%T Performance Evaluation of Web Crawler
%J International Conference on Emerging Technology Trends
%@ 0975-8887
%V ICETT2011
%N 1
%P 43-46
%D 2011
%I International Journal of Computer Applications
Abstract

important and popular. To find Web pages one typically uses search engines that are based on the web crawling framework. A web crawler is a software module that fetches data from various servers. The quality of a crawler directly affects the searching quality. So the time to time performance evaluation of the web crawler is needed. This paper proposes a new URL ordering algorithm .It covers major factors that a good ranking algorithm should have. It also overcomes limitation of PAGERANK. It uses all three web mining technique to obtain a score with its parameters relevance .It is expected to get better result than PAGERANK, as implementation of it in a web crawler is still under progress.

References
  1. Bhaskar Reddy,Kethi Reddy,” Improving efficiency of web crawler algorithm using parametric variations“ Ph.d thesis submitted in June 2010 at Thapar University India.
  2. Arvind chandramouli ,Susan gauch andJosua eno ”A popularity-based URL ordering Algorithm for Crawlers”, Rzesow ,Poland may 13-15 2010 IEEE
  3. Shaojie Qiao ,Tianni Li, Jiangtao Qiu,” SimRank: A Page Rank Approach based on Similarity Measure “ 2010 IEEE.
  4. Dilip Kumar Sharma, A.K.Sharma “A Comparative Analysis of Web Page Ranking Algorithms “(IJCSE) International Journal on Computer Science and Engineering Vol. 02, No. 08, 2010, 2670-2676
  5. Hongzhi Guo, Qingcai Chen, Xiaolong Wang, Zhiyong Wang, Yonghui Wu,” STRank: A SiteRank Algorithm using Semantic Relevance and Time Frequency “Proceedings of the 2009 IEEE International Conference on Systems, Man, and Cybernetics .
  6. Components of Googles Ranking Algorithm in 2010- Linking Still King, available at http://palatnikfactor.com/2010/05/18/components-of-googles-ranking-algorithm-in-2010-linking-still-king/
  7. Yi Zhang,Lei Zhang,Yan zhang,Xiaoming Li,”XRrank;Learning More from Web User Behaviors”2006 IEEE
  8. Qiancheng jiang,Yan Zhang,”SiteRank-Based crawling Ordering Strategy for Search Engine” 2007IEEE
  9. Neelam Duhan, A. K. Sharma, Komal Kumar Bhatia,” Page Ranking Algorithms: A Survey”, 2009 IEEE International Advance Computing Conference (IACC 2009).
  10. Apostolos Kritikopoulos, Martha Sideri, Iraklis Varlamis,” Wordrank: A Method for Ranking Web Pages Based on Content Similarity “2007 IEEE.
Index Terms

Computer Science
Information Sciences

Keywords

Web crawler URL Web Pages