A detection algorithm of customer outlier data based on data mining technology
Available Online October 2017.
- https://doi.org/10.2991/febm-17.2017.35How to use a DOI?
- outlier membership data; dempster/shafer evidence theory; algorithm; data fusion
- For the outlier data detection problem of customer transactional retail data in a large-scale chain supermarket, customer transaction data are detected by data mining technology and database technology, the sample data of abnormal customer behavior have been chosen in the customer transaction database, the abnormal customer behavior will be found out for outlier samples data fusion by the Dempster/Shafer evidence theory. The experimental result shows that the algorithm is more accurate and efficient than other algorithms to detect abnormal customer transactional retail behavior by the Dempster/Shafer evidence theory.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Jia Ren PY - 2017/10 DA - 2017/10 TI - A detection algorithm of customer outlier data based on data mining technology BT - Second International Conference On Economic and Business Management (FEBM 2017) PB - Atlantis Press SP - 272 EP - 278 SN - 2352-5428 UR - https://doi.org/10.2991/febm-17.2017.35 DO - https://doi.org/10.2991/febm-17.2017.35 ID - Ren2017/10 ER -