Predictive and descriptive analysis on relations graphs with heterogeneous entities
US9406021B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 13, 2013 |
| Grant date | Aug 2, 2016 |
| Priority date | — |
| Expiry date | Feb 26, 2035 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N7/01
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method provides a random walk model with heterogeneous graphs to leverage multiple source data and accomplish prediction tasks. The system and method components include: 1) A heterogeneous graph formulation including heterogeneous instances of abstract objects as graph nodes and multiple relations as edges connecting those nodes. The different types of relations, such as client-vendor relation and client-product relation, are often quantified as the weights of edges connecting those entities; 2) To accomplish prediction tasks with such information, launching a multi-stage random walk model over the heterogeneous graph. The random walk within a subgraph with homogenous nodes usually produces the relevance between entities of the same type. The random walk across different type of nodes provides the prediction of decisions, such as a client purchasing a product.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.