The Web Server Acceleration Technology Research Based on Web Site Structure and Content

Lei Zhou; Jing Fen Du; Yu Qiang Sun; Yu Wan Gu

doi:10.4028/www.scientific.net/AMR.271-273.775

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 271-273The Web Server Acceleration Technology Research...

The Web Server Acceleration Technology Research Based on Web Site Structure and Content

Abstract:

How to speed up Web Server is one important problem to increase the speed of accessing information and knowledge effectively. Through analyzing the structure and content of the website, using User Browse Trend (referred to as UBT) algorithm, predicting the webpage most likely to be visited in next step by users, combining webpage pre-delivery technology, the web sever acceleration technique is implemented.

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Periodical:

Advanced Materials Research (Volumes 271-273)

Pages:

775-779

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.271-273.775

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Online since:

July 2011

Authors:

Lei Zhou, Jing Fen Du, Yu Qiang Sun, Yu Wan Gu

Keywords:

Algorithm (GA), Web Server Acceleration, Webpage Pre-Delivery

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References

[1] Shan Songwei, Feng Shicong, Li Xiaoming. The Effect of Typical Feature Selection Method on the Chinese Webpage Classification [J]. Computer Engineering and Applications, 2003, 39 (22) : 146—148.

Google Scholar

[2] Zhang Peiying. Personalized Web Page Recommend System Based on Web Content and Log Mining [J]. Application of computer systems, 2008, 17 (9) : 9—11.

Google Scholar

[3] Ching-I Teng, Fan-Chen Tseng, David M. Chiang. The way to replace existing technologycharacterized by network effects. TECHNOVATION. 26 (2006): 1384–1389.

DOI: 10.1016/j.technovation.2005.08.005

Google Scholar

[4] Xu Huanqing, Wang yongcheng. Web Page Prefetching Model Based on User Access Path Analysis [J]. Journal of software, 2003, 14(06): 1142—1147.

Google Scholar

[5] Yang Li, Li Guo, Zhi-Hong Tian, Tian-Bo Lu. A lightweight web server anomaly detection method based on transductive scheme and genetic algorithms[J]. Computer Communications, 31(2008): 4018—4025.

DOI: 10.1016/j.comcom.2008.08.009

Google Scholar