US Patent Application 18319096. HYPERGRAPH-BASED COLLABORATIVE FILTERING RECOMMENDATIONS simplified abstract
Contents
HYPERGRAPH-BASED COLLABORATIVE FILTERING RECOMMENDATIONS
Organization Name
Inventor(s)
PROSENJIT Biswas of BENGALURU (IN)
BRIJRAJ Singh of BENGALURU (IN)
RAKSHA Jalan of BENGALURU (IN)
HYPERGRAPH-BASED COLLABORATIVE FILTERING RECOMMENDATIONS - A simplified explanation of the abstract
This abstract first appeared for US patent application 18319096 titled 'HYPERGRAPH-BASED COLLABORATIVE FILTERING RECOMMENDATIONS
Simplified Explanation
- The patent application describes an electronic device and a method for implementing hypergraph-based collaborative filtering recommendations. - The device receives a collaborative filtering graph that represents a group of users and a set of items. - It determines user embeddings and item embeddings, which are representations of users and items in a mathematical space. - A semantic clustering model is applied to further refine these embeddings. - A hypergraph is constructed to capture relationships between users and items. - The device calculates contrastive losses, which are measures of the difference between embeddings, to determine a collaborative filtering score. - Based on this score, the device recommends an item to a user. - The recommended item is then displayed on a display device.
Original Abstract Submitted
An electronic device and a method for implementation of hypergraph-based collaborative filtering recommendations. The electronic device receives a collaborative filtering graph corresponding to a set of users and a set of items. The electronic device determines a first set of user embeddings and a first set of item embeddings. The electronic device applies a semantic clustering model to determine a second set of user embeddings and a second set of item embeddings. The electronic device constructs a hypergraph to determine a third set of user embeddings and a third set of item embeddings. The electronic device determines a first contrastive loss and a second contrastive loss to determine a collaborative filtering score. The electronic device determines a recommendation of an item for a user based on the determined collaborative filtering score. The electronic device renders the determined recommended item on a display device.
