Recommendation system using improved neural network
US10635973B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 28, 2016 |
| Grant date | Apr 28, 2020 |
| Priority date | — |
| Expiry date | Jan 12, 2039 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L67/55
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Techniques described herein are directed to improved artificial neural network machine learning techniques that may be employed with a recommendation system to provide predictions with improved accuracy. In some embodiments, item consumption events may be identified for a plurality of users. From these item consumption events, a set of inputs and a set of outputs may be generated according to a data split. In some embodiments, the set of outputs (and potentially the set of inputs) may include item consumption events that are weighted according to a time-decay function. Once a set of inputs and a set of outputs are identified, they may be used to train a prediction model using an artificial neural network. The prediction model may then be used to identify predictions for a specific user based on user-specific item consumption event data.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.