Research on Applied-Information Technology with Application of Data Mining in Analysis of Consumer Behavior

Abstract:

With the development of computer technology, especially the rapid development and extensive application of database technology and computer network technology, the data quantity increases sharply, the accumulation of a large number of data in various fields, and rising fast. Enterprise database or data warehouse has stored a large number of customer data, these data include many aspects of the information of customers, but also contains the advantages and disadvantages of the enterprise operation. If we can use these data quickly, efficiently in-depth analysis and research, to find the rules and modes, to obtain the necessary knowledge from it, will help enterprises to better decision making. The system can successfully excavate students and staff of the tendency of consumption and consumption habits, analyze their satisfaction with each restaurant. The results of system analysis to a certain role for school students and teachers to understand and analyze the condition of daily consumption, so the establishment of this system has great practical value.

• Periodical: Advanced Materials Research (Volume 1003)
• Pages: 230-234
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.1003.230
• Online since: July 2014
• Authors: Feng Long Fan*, Xu Li, Xu Sheng Yu, Li Wang
• Keywords: Association Rule, Consumer Behavior, Customer Relationship Management, Data Mining (DM)

References

[1] Li JianZhong, Li JinBao, Shi ShengFei, Concepts, Issues and Advance of Sensor Networks and Data Management of Sensor Networks, Journal of Software, vol. 14, no. 10, pp.1717-1727, (2003).

[2] D. Abbott, S. Cunningham, G. Daniels, B. Doyle, J. Dumlop, D. Economo, T. Farmer, D. Farrant, C. Foley, B. Fox, M. Hedley, J. Herrmann, C. Jacka, Development and Evaluation of Sensor Concepts for Ageless Aerospace Vehicles – Threats and Measurands, NASA, vo. 2, no. 11, pp.68-77, (2002).

[3] Tilak S, Abu-Ghazaleh NB, Heinzelman W, A Taxonomy of Wireless Micro-sensor Network models, Mobile Computing and Commuications Review, vo. 1, no. 2, pp.1-8, (2002).

DOI: 10.1145/565702.565708

[4] David Culler, Deborah Estrin, Mani Srivastava, Overview of Sensor Networks, IEEE Computer Society Officers, vol. 11, no. 10, pp.15-25, (2005).

[5] T. Matsuo, Y. Kaneko, M. Matano, Introduction of Intelligent Vehicle Detection Sensors, IEEE/IEEJ/JSAI International Conference on Intelligent Transportation Systems, vol. 5, no. 12, pp.709-713, (1999).

DOI: 10.1109/itsc.1999.821148

[6] Zhao Wei, Mao Shiyi, A pixel-level multisensor image fusion algorithm based on false color, Chinese Journal of Electronics, vol. 3, no. 31, pp.368-371, (2003).