Please use this identifier to cite or link to this item:
http://202.88.229.59:8080/xmlui/handle/123456789/2577
Title: | Machine Learning in Search Engines |
Authors: | Mrs.Neenu Ann Sunny |
Keywords: | Search Engines, expertise, machine learning, web pages, automated |
Issue Date: | 2020 |
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. |
URI: | http://202.88.229.59:8080/xmlui/handle/123456789/2577 |
ISSN: | 2321-9939 |
Appears in Collections: | Mrs.Neenu Ann Sunny |
Files in This Item:
File | Description | Size | Format | |
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Neenu Ann Sunni-IJEDR.pdf | 316.72 kB | Adobe PDF | View/Open |
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