Discrete Characteristic Probability Distribution Theorem

Adib Kabir Chowdhury

ISBN 10: 3639515706 / ISBN 13: 9783639515701

Published by Scholars' Press Jan 2015, 2015

About this Item

Neuware -As internet has become a crucial element of Information Technology in our daily lives, so has the web search engine. Web search engines are formed with the reason to search information from the World Wide Web (WWW). This work proposes a new approach to rank web pages for search engines. This new method is an alternative to PageRank algorithm. It starts off by discussing in brief about the algorithm of PageRank, the mathematical background of PageRank and its role to rank web pages. Next, the book introduces a new method and formula to find the probability that can be used to rank web pages efficiently. The derivation of formula and how it is found is explained in details. The proposed methodology shows how it is not only dependent on backward link while ranking webpages. It also considers other entities of a webpage to rank a webpage. The data and results for this research are presented to prove how the new probability formula derived is efficient to overcome the backward overloading problem of PageRank.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 72 pp. Englisch.

Seller Inventory # 9783639515701

Bibliographic Details

• Title: Discrete Characteristic Probability Distribution Theorem
• Publisher: Scholars' Press Jan 2015
• Publication Date: 2015
• Language: English
• ISBN 10: 3639515706
• ISBN 13: 9783639515701
• Binding: Taschenbuch
• Condition: Neu

About this title

Synopsis

As internet has become a crucial element of Information Technology in our daily lives, so has the web search engine. Web search engines are formed with the reason to search information from the World Wide Web (WWW). This work proposes a new approach to rank web pages for search engines. This new method is an alternative to PageRank algorithm. It starts off by discussing in brief about the algorithm of PageRank, the mathematical background of PageRank and its role to rank web pages. Next, the book introduces a new method and formula to find the probability that can be used to rank web pages efficiently. The derivation of formula and how it is found is explained in details. The proposed methodology shows how it is not only dependent on backward link while ranking webpages. It also considers other entities of a webpage to rank a webpage. The data and results for this research are presented to prove how the new probability formula derived is efficient to overcome the backward overloading problem of PageRank.