Updating point of interest data using georeferenced transaction data
Georeferenced transaction data is harvested (“crowd-sourced”) from client devices and sent to a network-based map service. The map service performs cluster analysis on location data points in the harvested data, resulting in one or more clusters representing local densities of transaction occurrences. Data vectors including supplemental data are obtained from one or more vendors. Location data points included in the data vectors are compared to center coordinates of the one or more clusters and the closest matching cluster/vector pair provides a mapping to POI data in a POI database. The mapped POI data is updated with the supplemental data. In some implementations, transaction timestamps in the harvested data are used to estimate the business hours of a business POI.
1. A method comprising:
determining, at a user device, one or more timestamps of one or more transaction events and a respective location of the user device at each timestamp;
converting, by one or more hardware processors, the one or more timestamps into one or more time windows;
submitting, by the user device to a network-based service, georeferenced transaction data, the georeferenced transaction data including the one or more converted timestamps and one or more locations of the user device corresponding to the one or more converted timestamps;
receiving, from the network-based service, point of interest (POI) data, the POI data including information on an attribute of a POI in the georeferenced transaction data;
updating, by the one or more hardware processors, the georeferenced transaction data in a database, including supplementing the georeferenced transaction data with the information on the attribute of the POI; and
providing the supplemented georeferenced transaction data for display on the user device.
2. The method of claim 1 , wherein the POI data is mapped to a location of the POI based on clustering of the one or more locations.
3. The method of claim 1 , wherein the georeferenced transaction data includes a transaction description and geographic coordinates of the user device.
4. The method of claim 1 , wherein the attribute of the POI includes business hours of the POI.
5. The method of claim 1 , wherein the supplemented georeferenced transaction data is stored in a database table including a first column and a second column, the first column storing a transaction description, the second column storing a name of the POI and a street address of the POI.
6. The method of claim 1 , wherein the georeferenced transaction data includes one or more transaction descriptions and are clustered based on a common transaction description.
7. The method of claim 1 , wherein the information on the attribute of the POI includes at least one of a business name or street address.
8. The method of claim 1 , wherein the transaction event is a Near Field Communication (NFC) transaction.
9. The method of claim 1 , further comprising:
adding a new POI to a POI database.
10. The method of claim 1 , further comprising:
correcting POI locations using address information included in supplemental data.
11. The method of claim 1 , further comprising performing a cluster analysis on the georeferenced transaction data, wherein the cluster analysis results in two or more clusters associated with the georeferenced transaction data and the POI data is mapped to one of the two or more clusters.
12. A system comprising:
one or more processors;
memory coupled to the one or more processors and configured to store instructions, which, when executed by the one or more processors, causes the one or more processors to perform operations comprising:
determining, at a user device, one or more timestamps of one or more transaction events and a respective location of the user device at each timestamp;
converting the one or more timestamps into one or more time windows;
submitting, by the user device to a network-based service, georeferenced transaction data, the georeferenced transaction data including the one or more converted timestamps and one or more locations of the user device corresponding to the one or more converted timestamps;
receiving, from the network-based service, point of interest (POI) data, the POI data including information on an attribute of a POI in the georeferenced transaction data, the attribute being present for the POI during the one or more time windows;
updating the georeferenced transaction data in a database, including supplementing the georeferenced transaction data with the information on the attribute of the POI; and
providing the supplemented georeferenced transaction data for display on the user device.
13. The system of claim 12 , wherein the POI data is mapped to a location of the POI based on clustering of the one or more locations.
14. The system of claim 12 , wherein the georeferenced transaction data includes a transaction description and geographic coordinates of the user device.
15. The system of claim 14 , wherein the attribute of the POI includes business hours of the POI.
16. The system of claim 15 , wherein the supplemented georeferenced transaction data is stored in a database table including a first column and a second column, the first column storing the transaction description, the second column storing a name of the POI and a street address of the POI.
17. The system of claim 12 , wherein the georeferenced transaction data includes one or more transaction descriptions and are clustered based on a common transaction description.
18. The system of claim 12 , wherein the information on the attribute of the POI includes at least one of a business name or street address.
19. The system of claim 12 , wherein the transaction event is a Near Field Communication (NFC) transaction.
20. The system of claim 12 , further comprising:
adding a new POI to a POI database.
21. The system of claim 12 , further comprising:
correcting POI locations using address information included in supplemental data.
22. The system of claim 12 , further comprising performing a cluster analysis on the georeferenced transaction data, wherein the cluster analysis results in two or more clusters associated with the georeferenced transaction data and the POI data is mapped to one of the two or more clusters.