Calculating representative location information for network addresses

Patent metadata

Field	Value
Publication number	US-10762103-B2
Application number	US-201715856008-A
Country	US
Kind code	B2
Filing date	Dec 27, 2017
Priority date	Dec 27, 2017
Publication date	Sep 1, 2020
Grant date	Sep 1, 2020

Abstract

A method is provided that includes accessing, by a server provider server of a service provider, a database storing associations between network addresses and locations. Additionally, the method includes determining a subset of the database corresponding to a first network address, each association included in the subset corresponding to an association between the first network address and a respective location. The method also includes in response to determining that the subset of the database satisfies one or more clustering criteria, calculating a representative location corresponding to the first network address, and storing an association between the first network address and the representative location in a second database.

First claim

What is claimed is:

1. A system, comprising:
one or more hardware processors; and
a memory storing computer-executable instructions, that in response to execution by the one or more hardware processors, causes the system to perform operations comprising:
accessing a database storing a set of database entries, each database entry of the set of database entries storing an association between a network address and a coordinate location corresponding to the network address;
determining a first subset of the set of database entries by filtering out database entries of the database that store network addresses that correspond to cellular data connections;
identifying a first network address for which a second subset of the set of database entries stores respective associations between the first network address and respective coordinate locations corresponding to the first network address, the second subset being a subset of the first subset;
determining a number of database entries in the second subset;
determining a cluster density corresponding to the respective coordinate locations in the second subset, wherein the determining the cluster density comprises:
determining a centroid of the database entries of the second subset; and
determining respective distances between the centroid and the respective coordinate locations of the database entries of the second subset;

in response to determining that the number of database entries satisfies a number threshold, and determining that the cluster density satisfies a density threshold, calculating a representative coordinate location corresponding to the first network address;
adding a new database entry to a second database, the new database entry storing an association between the first network address and the representative coordinate location; and
generating an accuracy measure corresponding to the representative coordinate location based on applying a mathematical operation to an average distance of the representative coordinate location from two or more coordinate locations of the respective coordinate locations in the second subset.

2. The system of claim 1 , wherein the first subset of the set of database entries correspond to Wi-Fi connections.

3. The system of claim 1 , wherein the operations further comprise:
identifying a third subset of the set of database entries, the third subset storing associations between the first network address and other respective coordinate locations that satisfy the density threshold, and wherein a number of database entries in the third subset satisfies the number threshold; and
based on determining that the number of database entries in the third subset is less than the number of database entries in the first subset, selecting the first subset over the third subset for the calculating of the representative coordinate location corresponding to the first network address.

4. The system of claim 1 , wherein the operations further comprise:
identifying a third subset of the set of database entries, the third subset storing associations between a second network address and other respective coordinate locations corresponding to the second network address; and
in response to determining that a number of database entries in the third subset fails to satisfy the number threshold or determining that a cluster density corresponding to the other respective coordinate locations in the third subset fails to satisfy the density threshold:
accessing an open-source database having an open-source database entry storing an association between the second network address and a particular coordinate location; and
adding the open-source database entry of the open-source database to the second database.

5. The system of claim 1 , wherein the set of database entries in the database correspond to payment transactions processed over an electronic network.

6. The system of claim 1 , wherein the generating the accuracy measure further comprises: calculating the accuracy measure as 1/(1+avg_dist), wherein the avg_dist is an average distance between a plurality of nearest distance neighbor locations and the representative coordinate location.

7. The system of claim 1 , wherein the operations further comprise:
accessing a third database using a key that is determined based on the representative coordinate location; and
determining, based on the accessing the third database, additional geographic information corresponding to the first network address.

8. The system of claim 1 , wherein the calculating the representative coordinate location further comprises:
averaging respective latitude coordinates corresponding to the respective coordinate locations included the second subset; and
averaging respective longitude coordinates corresponding to the respective coordinate locations included in the second subset.

9. The system of claim 1 , wherein the operations further comprise:
receiving a request for a payment transaction, the request associated with a requestor network address and a requestor coordinate location;
determining that the requestor network address is the same as the first network address; and
determining a risk level corresponding to the request for the payment transaction based on a comparison between the representative coordinate location and the requestor coordinate location.

10. A method, comprising:
accessing, by a server provider server of a service provider, a database storing associations between network addresses and locations;
determining a subset of the database corresponding to a first network address, each association included in the subset corresponding to an association between the first network address and a respective location;
calculating a cluster density corresponding to the subset of the database;
determining that the cluster density satisfies a density threshold by:
determining a centroid corresponding to the locations included the subset of the database;
calculating respective distances between the centroid and the locations included in the subset; and
identifying a largest distance from the respective distances;

in response to determining that the cluster density satisfies the density threshold, calculating a representative location corresponding to the first network address;
storing an association between the first network address and the representative location in a second database;
applying a mathematical operation to an average distance of the representative location from two or more coordinate locations of the respective locations in the subset; and
generating an accuracy measure corresponding to the representative location based on a result of the applying.

11. The method of claim 10 , wherein the determining the subset of the database further comprises:
filtering associations stored by the database that correspond to cellular data connections.

12. The method of claim 10 , wherein the determining that the subset of the database satisfies the one or more clustering criteria further comprises:
determining that a number of associations included in the subset satisfies a number threshold.

13. The method of claim 10 , wherein the locations included in the subset of the database correspond to Global Positioning Satellite coordinates.

14. The method of claim 10 , wherein the generating the accuracy measure is further based on: calculating the accuracy measure as 1/(1+avg_dist), wherein the avg_dist is an average distance between a plurality of nearest distance neighbor locations and the representative location.

15. The method of claim 10 , further comprising:
accessing a third d

Assignees

• Paypal Inc

Inventors

• Meron Avishay
• Livshits-Rozenman Anna
• Cohen Adam
• Nathan Avihay
• Ben Haim Oded
• Alon Raz

Classifications

• G06F16/9537 Primary

  Spatial or temporal dependent retrieval, e.g. spatiotemporal queries · CPC title

• H04L2101/69

  using geographic information, e.g. room number · CPC title

• H04L61/45

  Network directories; Name-to-address mapping · CPC title

• G06F16/27 Primary

  Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor · CPC title

• G06Q20/4016

  involving fraud or risk level assessment in transaction processing · CPC title