Point-of-interest recommendation method based on temporal knowledge graph
US12254420B1 · kind B1 · utility
Assignees
Inventors
Key dates
| Filing date | Nov 12, 2024 |
| Grant date | Mar 18, 2025 |
| Priority date | — |
| Expiry date | Nov 12, 2044 |
Classification
- Technology area (CPC Y)Emerging Cross-Sectional Technologies
- CPC primaryY02D10/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The disclosure discloses a point-of-interest recommendation method based on a temporal knowledge graph. Based on the historical behavior trajectory of the user and multimodal information, the disclosure constructs a dynamic temporal knowledge graph and a static group knowledge graph, which are used to learn interest preferences of the user that change over time and stable features that do not change over time, respectively. At the same time, the disclosure uses deep learning methods to build a point-of-interest recommendation model, which can extract a point-of-interest fusion feature representation and a user fusion feature representation from the two knowledge graphs in combination with a user review sentiment embedding sequence to accurately predict a point of interest most likely to be visited by the target user at a next moment. The disclosure has the characteristics of high precision and strong scalability, and can provide support for personalized user behavior trajectory prediction.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.