FINDING BUSINESS SIMILARITIES BETWEEN ENTITIES USING MACHINE LEARNING

A method identifies a plurality of product categories by applying a categorization model to product data that includes product names and product descriptions. The product data is obtained from internal sources and external sources. The method creates a knowledge graph for a plurality of business entities from inputs that include the plurality of product categories, published data that includes merchant categorizations, and geographical data. The method generates cohort clusters of similar business entities by applying a clustering algorithm to the knowledge graph. The method uses the cohort clusters to learn a first extrapolation model for predicting inventory. And the method provides access to the first extrapolation model to predict inventory level at a specific point in time. The access is provided via a merchant application that runs on an online merchant platform.