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MetaCrawler: A Literature Review

Published on May 2016 by Monali R. Parthe, Sarika Choudhari
journal_cover_thumbnail

National Conference on Advancements in Computer & Information Technology
Foundation of Computer Science USA
NCACIT2016 - Number 3
May 2016
Authors: Monali R. Parthe, Sarika Choudhari
64a2c64a-8cb8-4ce3-812f-965eb79a1b0b

Monali R. Parthe, Sarika Choudhari . MetaCrawler: A Literature Review. National Conference on Advancements in Computer & Information Technology. NCACIT2016, 3 (May 2016), 11-13.

@article{
author = { Monali R. Parthe, Sarika Choudhari },
title = { MetaCrawler: A Literature Review },
journal = { National Conference on Advancements in Computer & Information Technology },
issue_date = { May 2016 },
volume = { NCACIT2016 },
number = { 3 },
month = { May },
year = { 2016 },
issn = 0975-8887,
pages = { 11-13 },
numpages = 3,
url = { /proceedings/ncacit2016/number3/24711-3047/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference on Advancements in Computer & Information Technology
%A Monali R. Parthe
%A Sarika Choudhari
%T MetaCrawler: A Literature Review
%J National Conference on Advancements in Computer & Information Technology
%@ 0975-8887
%V NCACIT2016
%N 3
%P 11-13
%D 2016
%I International Journal of Computer Applications
Abstract

As the world-wide web is increasing quickly, Now a day's searching information on internet, not only the information also find the truth & related data about topic, so It is complicated to find truth details and relevancy. Unluckily, there is no assurance for the exactness of information on the web. Likewise, different websites often provide inconsistent information on a subject, such as different terms for the same product. We design a general structure for the veracity (trueness) problem, and originate an algorithm called Truth Extractor, this operates the associations among web sites and their information, i. e. , a website is truthness if it runs many bits of truth material, and a bit of material is possible to be true if it is provided by many truthness web sites. In this paper we use Truth Extractor to calculate true details among variance information, and identify truthness web sites better than the popular search engines.

References
  1. Design of A MetaCrawler For Web Document Retrieval [ISDA-978-1-4673-5119-5/12/ 2012 IEEE].
  2. An Analysis of Web Document Clustering Algorithms [ISSN-Volume 1, No. 6, December 2011].
  3. Web Crawling Algorithms [International Journal of Computer Science and Artificial Intelligence Sept. 2014, Vol. 4 Issue. 3. ].
  4. Truth Discovery with Multiple Conflicting Information Providers on the Web [IEEE Transactions On Knowledge And Data Engineering, Vol. 20, No. 6, June 2008].
  5. The MetaCrawler Architecture For Resource Aggregation on the Web [November 8, 1996].
  6. An Intelligent Meta Search Engine for Efficient Web Document Retrieval [(IOSR-JCE) e-ISSN: 2278-0661, Volume 17, Issue 2, Ver. V (Mar – Apr. 2015)].
  7. Information retrieval on Internet using meta search engines: A Review [(Journal of Scientific & Industrial Research) Vol. 67,October 2008,pp. 739-746].
  8. String Matching Algorithms and their Applicability in various Applications [(IJSCE) ISSN: 2231-2307, Volume-I, Issue-6, January 2012].
  9. www. metacrawler. com or www. zoo. com.
Index Terms

Computer Science
Information Sciences

Keywords

Search Engine Data Quality Truth Extraction Algorithm Ranking Clustering