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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Zeraatkar, A.: Improvement of page ranking algorithm by negative score of spam pages. Webology 16(2), 43–56 (2019)
Sharma, P.S., Yadav, D.: Incremental refinement of page ranking of web pages. Int. J. Inf. Retrieval Res. 10(3), 57–73 (2020)
Пaвeл Пecтepeв, Pesterev P., Aннa Янишeвcкaя, et al.: Simulator and algorithm for page index definition for ranking in results of multi-agent search system issue. Bull. Bryansk State Tech. Univ. 2018(9), 47–55 (2018)
Bhawsar, M., Kumar, S.: Improved weight based web page ranking algorithm. Int. J. Comput. Appl. 182(29), 1–5 (2018)
Zhao, C., Li, N., Fang, D.: Criticality assessment of urban interdependent lifeline systems using a biased PageRank algorithm and a multilayer weighted directed network model. Int. J. Crit. Infrastr. Protect. 22(SEP.), 100–112 (2018)
Agryzkov, T., Curado, M., Pedroche, F., et al.: Extending the adapted PageRank algorithm centrality to multiplex networks with data using the pagerank two-layer approach. Symmetry 11(2), 284 (2019)
Zhou, H., Zhao, Y., Xu, G., et al.: Chip-scale optical matrix computation for pagerank algorithm. IEEE J. Sel. Top. Quantum Electron. PP(99), 1 (2019)
Hemangini, S., Apurva, A.: An improvement of link analysis algorithm to mine pertinent links: weighted HITS algorithm based on additive fusion of graphs by query similarity. Int. J. Comput. Appl. 176(24), 21–27 (2020)
Giannoulakis, S., Tsapatsoulis, N.: Filtering instagram hashtags through crowdtagging and the HITS algorithm. IEEE Trans. Comput. Soc. Syst. 6(3), 592–603 (2019)
Goel, S., Kumar, R., Kumar, M., et al.: An efficient page ranking approach based on vector norms using sNorm(p) algorithm. Inf. Process. Manage. 56(3), 1053–1066 (2019)
Acknowledgements
This work was supported by Anhui quality engineering project: Large scale online open Courses (MOOC) (Fund number: 2019mooc381).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
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
Download citation
DOI: https://doi.org/10.1007/978-3-030-74811-1_56
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-74810-4
Online ISBN: 978-3-030-74811-1
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)