Abstract
Under cloud computing, traditional user browsing behavior data acquisition method cannot optimize data classification, which results in slow and low accuracy of data acquisition. For this reason, a fast method to obtain user browsing behavior data under cloud computing is proposed. Using node processing user browsing behavior data, complete the query the user browsing behavior data collection, provide the conditions for data classification optimization, the data to calculate the similar characteristics after multiple iterations data peak, peak according to complete the user browsing behavior data classification, the classification of output data integration, realize the cloud user browsing behavior fast data acquisition. Compared with the traditional data acquisition method, the data acquisition speed of the design method is increased by 20 min and the accuracy is increased by 45%. The experimental data show that the overall performance of the proposed method is better than the traditional method, and it has strong practicability and high reference value.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Alharbi, S.: An empirical investigation on the impact of trust mediated determinants and moderating factors on the adoption of cloud computing. Int. J. Inf. Technol. Comput. Sci. 9(11), 12–22 (2017)
Gdaniec, N., Szwargulski, P., Knopp, T.: Fast multi-resolution data acquisition for magnetic particle imaging using adaptive feature detection. Med. Phys. 44(12), 6456 (2017)
Gao, C., Wang, H., Wang, J.: An improved CURE algorithm based on the uncertainty of mobile user data clustering. Comput. Eng. Sci. 38(4), 768–774 (2016)
Namasudra, S., Roy, P.: Time saving protocol for data accessing in cloud computing. IET Commun. 11(10), 1558–1565 (2017)
Zhe, D., Zhen, Q., Zheng, W.T., et al.: A recommendation model based on browsing behaviors of mobile users. J. Univ. Electron. Sci. Technol. China 46(6), 907–912 (2017)
Bo, Z., Jin, L.: Research on the acquisition and application of user data in publishing industry against the background of big data. Editors’ Friend 12(8), 26–31 (2017)
Guohua, Y., Jingjing, K., Fang, L.: Data source description approach for deep web based on domain features and user query-based sampling. Libr. Inf. Serv. 1(15), 138–145 (2017)
Taieb, C.: A quick model method for obtaining real-height parameters from routine ionospheric data. Radio Sci. 2(10), 1263–1267 (2016)
Wang, Y.: Accurate detection of user characteristic data in large data network. Comput. Simul. 34(6), 415–418 (2017)
Yang, J., Shi, Z., Liu, Z.: Simulation research on fast acquisition of terminal user information based on big data analysis. Comput. Simul. 1(2), 110–111 (2018)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Shan, J., Guo, H. (2019). Method for Quickly Obtaining User Browsing Behavior Data Under Cloud Computing. In: Liu, S., Yang, G. (eds) Advanced Hybrid Information Processing. ADHIP 2018. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 279. Springer, Cham. https://doi.org/10.1007/978-3-030-19086-6_41
Download citation
DOI: https://doi.org/10.1007/978-3-030-19086-6_41
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-19085-9
Online ISBN: 978-3-030-19086-6
eBook Packages: Computer ScienceComputer Science (R0)