System and method for hierarchical category classification of products

US11481602B2 · kind B2 · utility

Assignee

• Tata Consultancy Services Limited · IN

Inventors

• Ganesh Prasath Ramani · Chennai, IN
• Aashish Chandra · Bhangrola, IN
• Guruswaminathan Adimurthy · Bhangrola, IN
• Jayanth Shenai · Naperville, US
• Tharun Job · Westchase, US
• Saravanan Mohan · Chennai, IN

Key dates

• Filing date: Jun 2, 2020
• Grant date: Oct 25, 2022
• Expiry date: May 8, 2041

Classification

• Technology area (CPC G): Physics
• CPC primary: G06N3/048
• WIPO field: Computer technology
• WIPO sector: Electrical engineering

Abstract

This disclosure relates generally to system and method for hierarchical category classification of products. Generally in supervised hierarchical classification, the hierarchy structure is predefined. However, majority of the current machine learning methods either expect the model to learn the hierarchy from the data or requires separate models trained at each level taking the prediction of previous level as an additional input, thereby increasing latency in achieving training accuracy and/or requiring an explicit maintenance module to orchestrate inference and retrain multiple models (corresponding to the number of levels in the hierarchy). The disclosed method and system allows the predefined knowledge about hierarchy drive the learning process of a single model, which predicts all levels of the hierarchy. The disclosed multi-layer network model arrives at a consensus based on prediction at each level, thereby increasing the accuracy of prediction and reducing the training time.