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PageRank Algorithm and HITS Algorithm in Web Page Ranking

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Application of Intelligent Systems in Multi-modal Information Analytics (MMIA 2021)

Abstract

This paper takes web page ranking as the theoretical basis of the research, uses PageRank algorithm and HITS algorithm as auxiliary research, and integrates their important content to analyze and research the algorithm optimization of improving web page ranking. This paper takes the classic algorithms PageRank algorithm and HITS algorithm as the research objects, and optimizes and improves the ranking of web pages respectively. Through the ranking of web pages in search engines, the PageRank algorithm and the HITS algorithm can be regarded as a kind of node ranking algorithm, so they can be used to construct selective web page ranking strategies; in addition, these two algorithms have fast calculation speed and are suitable for large networks. Features, suitable for large-scale web page sorting. This article introduces the PageRank algorithm and the HITS algorithm into the web page ranking strategy. On this basis, it deeply discusses the applicability and ranking efficiency of these two algorithms in the ranking of complex web pages, and provides better for the future practice of complex web page ranking. The experimental results show that this research has made breakthrough optimizations for the algorithm design of web page ranking selection in the current Internet era, improved the use of PageRank algorithm and HITS algorithm in web page ranking, and arranged the rationality of web page ranking in search engines in a more reasonable manner. The development of page ranking is of great significance.

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Acknowledgements

This work was supported by Anhui quality engineering project: Large scale online open Courses (MOOC) (Fund number: 2019mooc381).

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Correspondence to Huilin Wu .

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Zhang, X., Wu, H. (2021). PageRank Algorithm and HITS Algorithm in Web Page Ranking. In: Sugumaran, V., Xu, Z., Zhou, H. (eds) Application of Intelligent Systems in Multi-modal Information Analytics. MMIA 2021. Advances in Intelligent Systems and Computing, vol 1384. Springer, Cham. https://doi.org/10.1007/978-3-030-74811-1_56

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