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Web of Proceedings - Francis Academic Press

Machine Learning Based Market Models in Business Operation

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DOI: 10.25236/ISMHI.2019.132


Annie Li

Corresponding Author

Annie Li


Shopping Centers Are Not Only Places for People to Engage in Commercial and Social Activities But Are Also Important Business and Entrepreneur Sites. for These Areas to Maintain High Customer Satisfaction and Maximal Profits, It is Crucial to Operate These Centers Efficiently and with Optimal Performance. However, Making Good Decisions to Improve a Business is a Complex Ordeal. This Project Utilizes Machine Learning to Design and Propose Market Models as a Method to Establish Business Strategies Suitable for Shopping Center Operation and Management. Three Market Models Comprised of Clustering Model, Principal Component Analysis (Pca), and Association Model Are Proposed in This Paper. Clustering Model is Used to Categorize the Different Stores into Multiple Groups. This Allows Us to Provide Specific Business Service for Each Group of Stores. Pca is Utilized to Organize Our Data into a Cleaner and Easier Format. Finally, the Association Model is Used to Find the Relationships between Different Stores and Store Categories, Which Provide Us with Information Regarding Popular Stores, Where Stores Should Be Located, and How to Provide Promotions from the Viewpoint of Business Operations.


Machine Learning; Market Models; Business Operation; Data Visualization