A Novel Page Ranking Algorithm Based on Social Annotations

2010 ◽  
Vol 33 (6) ◽  
pp. 1014-1023 ◽  
Author(s):  
Kai-Peng LIU ◽  
Bin-Xing FANG
Keyword(s):  
Ranking Algorithm ◽  
Page Ranking ◽  
Social Annotations

Web Page Ranking Algorithm Based on the Meta-Information

2014 ◽  
Vol 596 ◽  
pp. 292-296
Author(s):  
Xin Li Li
Keyword(s):  
Experimental Results ◽  
High Rank ◽  
Ranking Algorithm ◽  
Web Page ◽  
Page Ranking ◽  
Two Factors ◽  
Meta Information ◽  
The Web

PageRank algorithms only consider hyperlink information, without other page information such as page hits frequency, page update time and web page category. Therefore, the algorithms rank a lot of advertising pages and old pages pretty high and can’t meet the users' needs. This paper further studies the page meta-information such as category, page hits frequency and page update time. The Web page with high hits frequency and with smaller age should get a high rank, while the above two factors are more or less dependent on page category. Experimental results show that the algorithm has good results.

scholarly journals Improved Weighted Page Ranking Algorithm Based on Principal Component Analysis and Map Reduce Frame work for Web Access

2019 ◽  
Vol 8 (2) ◽  
pp. 32-39
Author(s):  
T. Mylsami ◽  
B. L. Shivakumar
Keyword(s):  
Data Mining ◽  
Principal Component Analysis ◽  
Web Mining ◽  
Principal Component ◽  
Component Analysis ◽  
Mean Value ◽  
Ranking Algorithm ◽  
Mean Values ◽  
Page Ranking ◽  
The Web

In general the World Wide Web become the most useful information resource used for information retrievals and knowledge discoveries. But the Information on Web to be expand in size and density. The retrieval of the required information on the web is efficiently and effectively to be challenge one. For the tremendous growth of the web has created challenges for the search engine technology. Web mining is an area in which applies data mining techniques to deal the requirements. The following are the popular Web Mining algorithms, such as PageRanking (PR), Weighted PageRanking (WPR) and Hyperlink-Induced Topic Search (HITS), are quite commonly used algorithm to sort out and rank the search results. In among the page ranking algorithm uses web structure mining and web content mining to estimate the relevancy of a web site and not to deal the scalability problem and also visits of inlinks and outlinks of the pages. In recent days to access fast and efficient page ranking algorithm for webpage retrieval remains as a challenging. This paper proposed a new improved WPR algorithm which uses a Principal Component Analysis technique called (PWPR) based on mean value of page ranks. The proposed PWPR algorithm takes into account the importance of both the number of visits of inlinks and outlinks of the pages and distributes rank scores based on the popularity of the pages. The weight values of the pages is computed from the inlinks and outlinks with their mean values. But in PWPR method new data and updates are constantly arriving, the results of data mining applications become stale and obsolete over time. To solve this problem is a MapReduce (MR) framework is promising approach to refreshing mining results for mining big data .The proposed MR algorithm reduces the time complexity of the PWPR algorithm by reducing the number of iterations to reach a convergence point.

Analysis on Natural Language Processing Using Page Ranking Algorithm on YouTube Videos

2021 ◽  
Author(s):  
Jefferson A. Costales ◽  
Janice A. Abellana ◽  
Joel S. Gracia ◽  
Madhavi Devaraj
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Ranking Algorithm ◽  
Page Ranking ◽  
Youtube Videos

scholarly journals An Efficient User Preference and Page Relevance based Page Ranking Algorithm

2017 ◽  
Vol 10 (37) ◽  
pp. 1-7 ◽  
Author(s):  
Ashlesha Gupta ◽  
Ashutosh Dixit ◽  
A. K. Sharma ◽  
◽  
◽  
...  
Keyword(s):  
User Preference ◽  
Ranking Algorithm ◽  
Page Ranking

Rank algorithm of web English educational resources based on fuzzy sets and RSS

2021 ◽  
pp. 1-11
Author(s):  
Haijun Chen ◽  
Weichao Yang
Keyword(s):  
Fuzzy Sets ◽  
English Education ◽  
Educational Resources ◽  
Damping Factor ◽  
Ranking Algorithm ◽  
User Interest ◽  
Basic Principles ◽  
Education Resources ◽  
Page Ranking ◽  
Browsing Behavior

In order to improve the acquisition and recommendation effect of English education resources, this paper proposes a Rank algorithm of web English educational resources based on fuzzy sets and RSS, and deeply studies the basic principles of the algorithm and introduces several keyword extraction techniques. The user’s browsing behavior and user interest acquisition methods are classified. Researchers can plan to further explore the page ranking algorithm to improve the performance of the scheme based on the damping factor. In addition, this paper uses Web technology to acquire English education resources and build a recommendation model, and uses crawler technology to build an overall system model. Finally, this paper designs experiments to verify the performance of the algorithm model constructed in this paper, and analyses the experimental results by mathematical statistics. The research results show that the algorithm model proposed in this paper has significant effects and is of great significance to the acquisition and recommendation of English education resources.

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