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Machine Learning in Search Engines

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dc.contributor.author Mrs.Neenu Ann Sunny
dc.date.accessioned 2020-07-01T11:59:26Z
dc.date.available 2020-07-01T11:59:26Z
dc.date.issued 2020
dc.identifier.issn 2321-9939
dc.identifier.uri http://202.88.229.59:8080/xmlui/handle/123456789/2577
dc.description.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. en_US
dc.language.iso en en_US
dc.subject Search Engines, expertise, machine learning, web pages, automated en_US
dc.title Machine Learning in Search Engines en_US
dc.type Article en_US


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