Offline geographic searches
US-2019005055-A1 · Jan 3, 2019 · US
US12033256B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-12033256-B2 |
| Application number | US-202217851484-A |
| Country | US |
| Kind code | B2 |
| Filing date | Jun 28, 2022 |
| Priority date | Dec 13, 2021 |
| Publication date | Jul 9, 2024 |
| Grant date | Jul 9, 2024 |
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Official abstract text for this publication.
The present disclosure provides a map data processing method, an electronic device and a storage medium, relates to a technical field of data processing, and in particular to the field of map data processing. A specific implementation solution is as follows: receiving first data encapsulated in a form of offline data, the first data being used to characterize low-frequency data in the map data; obtaining second data after initiating a first online request, the second data being used to characterize high-frequency data in the map data; and performing merging processing on the first data and the second data to obtain target data to be displayed in a map. By adopting the present disclosure, the timeliness of map data display may be improved.
Opening claim text (preview).
What is claimed is: 1. A map data processing method, comprising: receiving first data encapsulated in a form of offline data, the first data being used to characterize low-frequency data in map data; obtaining second data after initiating a first online request, the second data being used to characterize high-frequency data in the map data; and performing merging processing on the first data and the second data, to obtain target data to be displayed in a map; wherein the first data and the second data are obtained by a background server by layering the map data based on an update frequency of different geographic information elements and/or importance of the different geographic information elements according to a layering model, the layering model is obtained by training a model after performing feature extraction on training data, and a data source of the training data comprises a plurality of data sources with a different confidence level. 2. The method of claim 1 , wherein the first data comprises non-point-of-interest (POI) data, and the second data comprises POI data. 3. The method of claim 1 , wherein performing merging processing on the first data and the second data, to obtain the target data to be displayed in the map, comprises: reading, from the first data, a first geographic information element pertaining to a first layer; reading, from the second data, a second geographic information element pertaining to the first layer; performing merging processing on the first geographic information element and the second geographic information element in the first layer; and continuing to perform merging processing on geographic information elements belonging to a same layer in the first data and the second data, until data of each layer is merged, to obtain the target data to be displayed in the map. 4. The method of claim 1 , further comprising: initiating a second online request, in response to an emergency intervention event; and receiving requested updated first data, the updated first data being indicated by a replacement identifier. 5. The method of claim 4 , wherein performing merging processing on the first data and the second data, to obtain the target data to be displayed in the map, comprises: reading, from the updated first data, a third geographic information element pertaining to a corresponding target layer; replacing a first geographic information element pertaining to the corresponding target layer in the first data with the third geographic information element; reading, from the second data, a fourth geographic information element pertaining to the target layer; and performing merging processing on the third geographic information element and the fourth geographic information element in the target layer, to obtain the target data to be displayed in the map. 6. A map data processing method, comprising: layering map data, to obtain first data and second data, comprising: layering the map data based on an update frequency of different geographic information elements and/or importance of the different geographic information elements, according to a layering model, to obtain the first data and the second data; wherein the layering model is obtained by training a model after performing feature extraction on training data, and a data source of the training data comprises a plurality of data sources with a different confidence level; wherein the first data is used to characterize low-frequency data in the map data, and the second data is used to characterize high-frequency data in the map data; sending the first data encapsulated in a form of offline data; and sending the second data, in response to receiving a first online request. 7. The method of claim 6 , further comprising: predicting and evaluating a layering processing capability of the layering model through test data, to obtain an effect feedback file; and modifying the training data according to the effect feedback file. 8. The method of claim 6 , further comprising: layering the map data, based on a drawing attribute of different geographic information elements and/or a drawing order of the different geographic information elements. 9. The method of claim 6 , further comprising: receiving a second online request, in response to initiating an emergency intervention event; and sending requested updated first data, the updated first data being indicated by a replacement identifier. 10. An electronic device, comprising: at least one processor; and a memory connected in communication with the at least one processor, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the method of claim 1 . 11. The electronic device of claim 10 , wherein the first data comprises non-point-of-interest (POI) data, and the second data comprises POI data. 12. The electronic device of claim 10 , wherein the instructions are executed by the at least one processor to enable the at least one processor to further execute: reading, from the first data, a first geographic information element pertaining to a first layer; reading, from the second data, a second geographic information element pertaining to the first layer; performing merging processing on the first geographic information element and the second geographic information element in the first layer; and continuing to perform merging processing on geographic information elements belonging to a same layer in the first data and the second data, until data of each layer is merged, to obtain the target data to be displayed in the map. 13. An electronic device, comprising: at least one processor; and a memory connected in communication with the at least one processor, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the method of claim 6 . 14. The electronic device of claim 13 , wherein the instructions are executed by the at least one processor to enable the at least one processor to further execute: predicting and evaluating a layering processing capability of the layering model through test data, to obtain an effect feedback file; and modifying the training data according to the effect feedback file. 15. A non-transitory computer-readable storage medium storing computer instructions thereon, wherein the computer instructions are used to enable a computer to execute the method of claim 1 . 16. A non-transitory computer-readable storage medium storing computer instructions thereon, wherein the computer instructions are used to enable a computer to execute the method of claim 6 .
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