INVENTORY DATA MINING SYSTEM USING FEDERATED MACHINE LEARNING STRATEGY

Inventory management is a particularly important process for keeping track of levels, orders, and transactions in the inventory retailing industry. A significant quantity data about stocked items generated gathered daily current market. It often job to manage goods effectively due growing volume transaction their related relationships, but it must be conducted, especially when these databases are scattered various places. To collect all from different distributed databases, time consuming, insecure, inaccurate implement intelligent systems; essential investigate underlying dependencies body items. However, systems only have limited ability because they depend on statistical analysis historical data. There has not been much progress made putting place use combined data-driven uncover hidden relationships. In this paper, we computing resources an enormous amount integrate federated learning, one most recent developments mining techniques. Federated Learning offers thorough aid conducting duties, including showing anomalous examining aging inventory. Keywords: Data Mining, Distributed Database, Inventory, Learning, Machine DOI： https://doi.org/10.35741/issn.0258-2724.58.3.51