Title :
Web Page Ranking Using Machine Learning Approach
Author :
Chauhan, Vijay ; Jaiswal, Arunima ; Khan, Junaid
Abstract :
This article gives an overview of the currently available literature on web page ranking algorithm using machine learning. Web page ranking algorithm, a well-known approach to rank the web pages available on cyber world. It helps us to know - how the search engine exactly works and how a machine learn itself while giving priority to the page that which page is important to successfully fulfills the user query need and which page is worth less. Machine learning approach also helps us in understanding the complex part of page priority criteria in most popular search engines like Google, yahoo, AltaVista, dog pile and many more search engines like that. Page ranking mainly unrevealed the structure of web. This article gives an overview of available literature in the field of web page ranking algorithm and it also highlights the main point based on machine leaning approach in web page ranking algorithm.
Keywords :
Internet; learning (artificial intelligence); query processing; search engines; AltaVista; Dogpile; Google; Web page ranking algorithm; Yahoo; cyber world; machine learning approach; search engine; user query; Algorithm design and analysis; Crawlers; Engines; Google; Machine learning algorithms; Search engines; Web pages; CRAWLER; INDEXER; SEACH ENGINE; Web page ranking using machine learning approach;
Conference_Titel :
Advanced Computing & Communication Technologies (ACCT), 2015 Fifth International Conference on
Conference_Location :
Haryana
Print_ISBN :
978-1-4799-8487-9
DOI :
10.1109/ACCT.2015.56