Refine your search
Collections
Co-Authors
Year
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Sangeetha, R.
- A Novel Approach to Identify the Promotion of Sales in Supermarkets using Machine Learning Algorithms
Abstract Views :166 |
PDF Views:0
Authors
G. Sujatha
1,
R. Sangeetha
2
Affiliations
1 PG and Research Department of Computer Science, Sri Meenakshi Government Arts College for Women (A), Madurai, Tamil Nadu, IN
2 Department of Computer Science, Lady Doak College, Madurai, Tamil Nadu, IN
1 PG and Research Department of Computer Science, Sri Meenakshi Government Arts College for Women (A), Madurai, Tamil Nadu, IN
2 Department of Computer Science, Lady Doak College, Madurai, Tamil Nadu, IN
Source
International Journal of Business Analytics and Intelligence, Vol 9, No 1&2 (2021), Pagination: 41-46Abstract
Prediction of sales promotion is a significant method to attract customers and enable retailers in successful planning and forecasting. The core objectives of this paper are to introduce a novel interpretable machine language algorithm to enhance the sales in supermarkets based on the buying behaviour of the customers, and to find the factor of sensitivity that stimulates, satisfies, and builds loyalty among the customers. Decision tree, gradient boosted trees, and support vector machine learning algorithms will be mainly used to compare the accuracy level and to analyse the promotion of sales in supermarkets based on the buying behaviour of customers, and also to find factors influencing customer retention.Keywords
Supermarket, Sales Promotion, Customers, Decision Tree, Gradient Boosted Tree, Support Vector.
References
- Bajaj, P., Ray, R., Shedge, S., Vidhate, S., & Shardoor, N. (2020). Sales prediction using machine learning algorithms. International Research Journal of Engineering and Technology (IRJET), 7(6), 3619-3625.
- Carreira-Perpinan, M. A. (2016, November 28). Merced, Introduction to Machine Learning. EECS, University of California.
- Odegua, R. (2020, January). Applied machine learning for supermarket sales prediction.
- Paták, M., Branská, L., & Pecinova, Z. (2015, August). Demand forecasting in retail grocery stores in the Czech Republic. 2nd International Multidisciplinary Scientific Conference on Social Sciences and Arts SGEM2015.
- Ramesh, K., Mathew, J. J., & Hemalatha, N. (2017). Machine learning approach for the predictive analysis of sales in grocery store. International Journal of Latest Trends in Engineering and Technology, Special Issue, 95-98. e-ISSN: 2278-621X.
- Ray, S. (2017, September 13). Understanding support vector, machine (SVM) algorithm from examples (along with code).
- Singh, M. (2017). Walmart’s sales data analysis – A big data analytics perspective. 2017 4th Asia-Pacific World Congress on Computer Science and Engineering (APWC on CSE).
- Tarallo, E., Akabane, G. K., Shimabukuro, C. I., Mello, J., & Amancio, D. (2019). Machine learning in predicting demand for fast-moving consumer goods: An exploratory research. IFAC-PapersOnLine, 52(13), 737-742.
- Tarallo, E. A., Akabane, G., Shimabukuro, C. I., Mello, J., & Amancio, D. (2019, August). Machine learning in predicting demand for fast-moving consumer goods: An exploratory research. Elsevier, 9th IFAC Conference on Manufacturing Modeling, Management and Control MIM 2019, Berlin, Germany.
- Tsoumakas, G. (2018, June 14). A survey of machine learning techniques for food sales prediction. Artificial Intelligence Review, 52(1), 441-447. Retrieved from https://doi.org/10.1007/s10462-018-9637-z
- Zuo, Y., Yada, K., & Shawkat Ali, A. B. M. (2016, December). Prediction of consumer purchasing in a grocery store using machine learning techniques. IEEE, 3rd Asia-Pacific World Congress on Computer Science and Engineering (APWC on CSE).