Deriving and Verifying Statistical Distribution of a Hyperlink-Based Web Page Quality Metric

Dhyani, Devanshu; Bhowmick, Sourav S.; Ng, Wee Keong

doi:10.1007/3-540-46146-9_3

Cited by 5 publications

(2 citation statements)

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“…Among thousands of web search engines based on various algorithms that have emerged in recent years, Google has become the most popular and successful one. Google's success should largely be attributed to its simple but elegant algorithm: PageRank [1]. The core of the PageRank algorithm involves computing the PageRank vector, which is the stationary distribution of the so-called Google matrix and a measurement of the importance of the web pages.…”

Section: Introductionmentioning

confidence: 99%

A Novel Heuristic PageRank Algorithm in Web Search

He¹

2011

AMR

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With the booming development of the Internet, web search engines have become the most important Internet tools for retrieving information. PageRank computes the principal eigenvector of the matrix describing the hyperlinks in the web using the famous power method. Based on empirical distributions of Web page degrees, we derived analytically the probability distribution for the PageRank metric. We found out that it follows the familiar inverse polynomial law reported for Web page degrees.

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Section: Introductionmentioning

confidence: 99%

A Novel Heuristic PageRank Algorithm in Web Search

He¹

2011

AMR

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“…Therefore, most of the improved HITS algorithm can not effectively avoid topic drift. People like Chen H. proposed designing client-side intelligent search engine [3] . The Spider information search method, similar to our method, introduced genetic algorithm into search algorithm.…”

Section: Introductionmentioning

confidence: 99%

A Improved Topics Search Algorithm Based on PSO Strategy for Web Mining

Zhan

2010

KEM

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HITS algorithm assigns same weight to links between Web pages,which results in topic drift. In this paper,a new focused crawling approach based on PSO Algorithm is proposed（PSOHITS）. The method electively seeks out pages that are relevant to a pre-defined set of topics using PSO Algorithm,increases the crawling chance of the web page following the web page with the low content-relevance,and broadens the relevant-searching scope of crawlers.Meanwhile,the hyperlink metadata is used to predict the topic-relevance of the web page pointed and quickens the information crawling. Experiments show that the proposed algorithm can improve relevance ratio by 15%~36%.Furthermore,it can well avoid topic drift and improve the accuracy of information collection. It has important theoretical and practical values for search engines research.

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A Case Study for Ranking of Relevant Search Results

Balabantaray

Ghosh

2017

Advances in Intelligent Systems and Computing

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Deriving and Verifying Statistical Distribution of a Hyperlink-Based Web Page Quality Metric

Cited by 5 publications

References 4 publications

A Novel Heuristic PageRank Algorithm in Web Search

A Novel Heuristic PageRank Algorithm in Web Search

A Improved Topics Search Algorithm Based on PSO Strategy for Web Mining

A Case Study for Ranking of Relevant Search Results

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