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INTERNATIONAL JOURNAL OF ENGINEERING DEVELOPMENT AND RESEARCH
(International Peer Reviewed,Refereed, Indexed, Citation Open Access Journal)
ISSN: 2321-9939 | ESTD Year: 2013

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Paper Details
Paper Title
Machine Learning in Search Engines
Authors
  Neenu Ann Sunny

Abstract
The relevance of a web page is an innately biased matter and based on readers knowledge, interests and attitudes, web page is depended. To say justly about the relative importance of web pages, there is still much. One factor which makes it difficult for search engines to give relevant results to the users within a stipulated time is the explosive growth of internet. Classified directories are used by search engines for storing the webpages and for this process, some search engines even depend on human expertise. Automated methods are used by most of the web pages for classification of web pages. We can infer from experimental results that machine learning techniques for automated classification of the web pages proves to be the best and more relevant method for search engines.

Keywords- for search engines. Keywords— Search Engines, expertise, machine learning, web pages, automated.
Publication Details
Unique Identification Number - IJEDR2002029
Page Number(s) - 155-161
Pubished in - Volume 8 | Issue 2 | April 2020
DOI (Digital Object Identifier) -   
Publisher - IJEDR (ISSN - 2321-9939)
Cite this Article
  Neenu Ann Sunny,   "Machine Learning in Search Engines", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.8, Issue 2, pp.155-161, April 2020, Available at :http://www.ijedr.org/papers/IJEDR2002029.pdf
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