使用机器学习方法的网页排名

Vijay Chauhan, Arunima Jaiswal, Junaid Khan
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引用次数: 11

摘要

本文概述了目前可用的关于使用机器学习的网页排名算法的文献。网页排名算法是一种众所周知的对网络世界中可用网页进行排名的方法。它帮助我们了解——搜索引擎是如何工作的,机器是如何在优先考虑页面的同时学习自己的,哪些页面对成功满足用户的查询需求是重要的,哪些页面价值较低。机器学习方法也帮助我们理解最流行的搜索引擎中页面优先级标准的复杂部分,如Google, yahoo, AltaVista, dog pile和许多类似的搜索引擎。网页排名主要不揭示网页的结构。本文概述了网页排名算法领域的现有文献,并重点介绍了基于机器学习方法的网页排名算法的要点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Web Page Ranking Using Machine Learning Approach
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.
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