Recommendation system with dual collaborative filter usage matrix
US9348898B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 27, 2014 |
| Grant date | May 24, 2016 |
| Priority date | — |
| Expiry date | Nov 2, 2034 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06Q30/0631
- WIPO fieldIT methods for management
- WIPO sectorElectrical engineering
Abstract
Example apparatus and methods perform matrix factorization (MF) on a usage matrix to create a latent space that describes similarities between users and items and between items and items in the usage matrix. The usage matrix relates users to items according to a collaborative filtering approach. A cell in the usage matrix may store a value that describes whether a user has acquired an item and the strength with which the user likes an item that has been acquired. The latent item space may reflect true relationships between items represented in the usage matrix and those relationships may be proportional to the strength in the usage matrix. The strength of the relationship may be encoded using continuous data that measures, for example, the amount of time a video game has been played, the amount of time content has been viewed, or other continuous or cumulative engagement measurements.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.