Abstract
This paper mainly studies the use of Apache + PHP + MySQL and big data computing technology to design a commodity trading platform based on big data analysis. This commodity trading platform has multi-style data analysis. The front desk has user personal data analysis, including footprint, order analysis, purchase preferences, consumption information, etc. There are various kinds of marketing data analysis of the platform in the background, including sales profile data analysis, peer hot sales data analysis, sales ranking, etc. In addition, big data computing technology is used to analyze user behavior, collect all access ways of user browsing platform, and process the collected data in depth, so as to obtain a real-time dynamic effect map, dynamically display the access amount and proportion of each access way, and extract valuable information from it, so as to develop an effective promotion plan for the platform and achieve precision marketing.
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
Utku, A., Aydogan, E., Mutlu, B., et al.: A new recommender system based on multiple parameters and extended user behavior analysis. In: The 9th International Conference. ACM (2017)
Zeng, Z., Rao, H.K., Liu, A.P.: Research on personalized referral service and big data mining for e-commerce with machine learning. In: 4th International Conference on Computer and Technology Applications (ICCTA). IEEE (2018)
Yan, L.: Personalized recommendation method for e-commerce platform based on data mining technology. In: International Conference on Smart Grid and Electrical Automation (ICSGEA) IEEE Computer Society (2017)
Nixon, R.: Learning PHP, MySQL, and Javascript. Oreilly Media (2018)
Zhao, H.Q.: Best scheme of design dynamic website: Apache + PHP + Mysql. Computer Engineering and Design (2007)
Anderson, D., Hills, M.: Query construction patterns in PHP. In: IEEE 24th International Conference on Software Analysis, Evolution and Reengineering (SANER). IEEE (2017)
Harris, R., Murach, J.: Murach’s PHP and MySQL: Training & reference. Mike Murach & Associates Inc (2017)
Singh, A., Mittal, M., Kapoor, N.: Data processing framework using Apache and Spark technologies in big data. Big Data Processing Using Spark in Cloud (2019)
Han, D., Chen, X., Lei, Y., et al.: Real-time data analysis system based on Spark Streaming and its application. Journal of Computer Applications (2017)
Sunny, B.K., Janardhanan, P.S, Francis, A.B., et al.: Implementation of a self-adaptive real time recommendation system using spark machine learning libraries. In: IEEE International Conference on Signal Processing, Informatics, Communication and Energy Systems (SPICES). IEEE (2017)
Acknowledgements
National Undergraduate Science and technology innovation and entrepreneurship training program.
Fund: National College Students’ science and technology innovation and entrepreneurship training program.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this paper
Cite this paper
Cai, Z., Zhang, J. (2021). Commodity Trading Platform Based on Big Data Analysis. In: Sugumaran, V., Xu, Z., Zhou, H. (eds) Application of Intelligent Systems in Multi-modal Information Analytics. MMIA 2020. Advances in Intelligent Systems and Computing, vol 1233. Springer, Cham. https://doi.org/10.1007/978-3-030-51431-0_112
Download citation
DOI: https://doi.org/10.1007/978-3-030-51431-0_112
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-51430-3
Online ISBN: 978-3-030-51431-0
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)