Systems and methods for resolving points of interest on maps

Patent metadata

Field	Value
Publication number	US-2020300656-A1
Application number	US-202016828929-A
Country	US
Kind code	A1
Filing date	Mar 24, 2020
Priority date	Mar 24, 2019
Publication date	Sep 24, 2020
Grant date	—

Abstract

The present technology improves points-of-interest (POIs) in applications by the gathering and use of data available from various sources to improve metadata of POIs in applications (e.g., map applications) or any other metadata or information that may be of interest to a user regarding any given POI. The present technology resolves transactions to POIs or Brands (in a map application, for example) and improves, updates, creates, and removes POIs/Brands. The present technology can also gain a clear name, granular and correct categorization, a URL, phone/chat contact info, etc. of the transactions.

First claim

1 . A non-transitory computer-readable medium comprising computer-executable instructions stored thereon, when executed the computer-executable instructions are effective to causing a computing system to:
receive a notification of a transaction using an account associated with a mobile device, the notification also including transaction metadata; receive a current location from the mobile device and mobile device metadata; determine at least one point-of-interest based on the transaction metadata and mobile device metadata; and store the at least one point-of-interest, transaction, transaction metadata and mobile device metadata in a database.

2 . The non-transitory computer-readable medium of claim 1 , further comprising instructions which when executed, causes the computing system to:
update metadata associated with the at least one point-of-interest, wherein the metadata associated with the at least one point-of-interest is stored at an application server.

3 . The non-transitory computer-readable medium of claim 1 , further comprising instructions which when executed, causes the computing system to:
validate metadata associated with the at least one point-of-interest based on the transaction metadata, wherein the metadata associated with the at least one point-of-interest is stored at an application server.

4 . The non-transitory computer-readable medium of claim 1 , further comprising instructions which when executed, causes the computing system to:
receive a plurality of transactions and associated transaction metadata, including the transaction using the account associated with the mobile device; cluster the plurality of transactions into one or more subset clusters; identify a center point transaction for each of the one or more subset clusters; reduce the one or more subset clusters based on a comparison of metadata of the center point transaction and transaction metadata of the subset of the plurality of transactions; and transmit one or more matches of the comparison.

5 . The non-transitory computer-readable medium of claim 4 , wherein the plurality of transactions are clustered by location.

6 . The non-transitory computer-readable medium of claim 4 , wherein the one or more matches are transmitted to a machine learning environment for training or validation.

7 . The non-transitory computer-readable medium of claim 4 , further comprising instructions which when executed, causes the computing system to:
subsequent to the clustering, geo-hash the plurality of transactions based on the respective associated transaction metadata.

8 . A system comprising:
at least one processor; and at least one memory storing instructions which, when executed by the at least one processor, cause the at least one processor to:
receive a notification of a transaction using an account associated with a mobile device, the notification also including transaction metadata;
receive a current location from the mobile device and mobile device metadata;
determine at least one point-of-interest based on the transaction metadata and mobile device metadata; and
store the at least one point-of-interest, transaction, transaction metadata and mobile device metadata in a database.

9 . The system of claim 8 , wherein the memory further comprising instructions which when executed, causes the at least one processor to:
update metadata associated with the at least one point-of-interest, wherein the metadata associated with the at least one point-of-interest is stored at an application server.

10 . The system of claim 8 , wherein the memory further comprising instructions which when executed, causes the at least one processor to:
validate metadata associated with the at least one point-of-interest based on the transaction metadata, wherein the metadata associated with the at least one point-of-interest is stored at an application server.

11 . The system of claim 8 , wherein the memory further comprising instructions which when executed, causes the at least one processor to:
receive a plurality of transactions and associated transaction metadata, including the transaction using the account associated with the mobile device; cluster the plurality of transactions into one or more subset clusters; identify a center point transaction for each of the one or more subset clusters; reduce the one or more subset clusters based on a comparison of metadata of the center point transaction and transaction metadata of the subset of the plurality of transactions; and transmit one or more matches of the comparison.

12 . The system of claim 11 , wherein the plurality of transactions are clustered by location.

13 . The system of claim 11 , wherein the one or more matches are transmitted to a machine learning environment for training or validation.

14 . The system of claim 8 , wherein the memory further comprising instructions which when executed, causes the at least one processor to:
subsequent to the clustering, geo-hash the plurality of transactions based on the respective associated transaction metadata.

15 . A method comprising:
receiving a notification of a transaction using an account associated with a mobile device, the notification also including transaction metadata; receiving a current location from the mobile device and mobile device metadata; determining at least one point-of-interest based on the transaction metadata and mobile device metadata; and storing the at least one point-of-interest, transaction, transaction metadata and mobile device metadata in a database.

16 . The method of claim 15 , further comprising:
updating metadata associated with the at least one point-of-interest, wherein the metadata associated with the at least one point-of-interest is stored at an application server.

17 . The method of claim 15 , further comprising:
validating metadata associated with the at least one point-of-interest based on the transaction metadata, wherein the metadata associated with the at least one point-of-interest is stored at an application server.

18 . The method of claim 15 , further comprising:
receiving a plurality of transactions and associated transaction metadata, including the transaction using the account associated with the mobile device; clustering the plurality of transactions into one or more subset clusters; identifying a center point transaction for each of the one or more subset clusters; reducing the one or more subset clusters based on a comparison of metadata of the center point transaction and transaction metadata of the subset of the plurality of transactions; and transmitting one or more matches of the comparison.

19 . The method of claim 16 , wherein the plurality of transactions are clustered by location.

20 . The method of claim 16 , wherein the one or more matches are transmitted to a machine learning environment for training or validation.

Assignees

• Apple Inc

Inventors

• Weilert Shanni
• Studelska Ryan
• Wang Ren
• Gutenko Ievgeniia
• Ji Fang
• Makhanov Andrei
• Rane Aditya
• Fisher Jarad M
• SURESH Akila
• Nagre Ashish C
• Williams Andrew
• Hugaev Victor

Classifications

• G01C21/3811

  Point data, e.g. Point of Interest [POI] · CPC title

• G01C21/32

  Structuring or formatting of map data · CPC title

• G01C21/3679 Primary

  Retrieval, searching and output of POI information, e.g. hotels, restaurants, shops, filling stations, parking facilities (G01C21/3611 takes precedence) · CPC title

• G06Q30/016

  After-sales · CPC title

• G06Q30/0201

  Market modelling; Market analysis; Collecting market data · CPC title