Abstract—We propose an approach of recommendation based
on purchase patterns. The purchase history of users is analyzed
to find their purchase patterns related to user behavior. These
patterns are then used to predict the category of next possible
purchase in a particular location. The proposed approach is
experimented on real transaction data. Synthetic and simulation
tests are conducted to evaluate the performance. Results show
that it performs better than the baseline sequential pattern
Index Terms—Recommendation systems, purchase patterns, sequential pattern analysis.
Haiyun Lu is with SAP Research & Innovation, Singapore (e-mail: hai.yun.lu@ sap.com).
Cite: Haiyun Lu, "Recommendations Based on Purchase Patterns," International Journal of Machine Learning and Computing vol. 4, no. 6, pp. 501-504, 2014.