Micro-geographic aggregation system

Patent metadata

Field	Value
Publication number	US-10102536-B1
Application number	US-201414244186-A
Country	US
Kind code	B1
Filing date	Apr 3, 2014
Priority date	Nov 15, 2013
Publication date	Oct 16, 2018
Grant date	Oct 16, 2018

Abstract

The present disclosure describes systems and methods for automatically rolling-up data associated with one or more geographic units, such as ZIP+4 codes, such that the rollup comprises a minimum number of households to protect anonymity and ensure compliance with privacy regulations, while preserving variance of the underlying data associated with the geographic regions. Data attributes may include demographic data, socio-economic data, lifestyle segmentation, psychographic data, behavioral data, credit data, and other data. The rollup process may involve identifying one or more geographic units with a number of households below a minimum or threshold amount, applying filters to find candidate geographic units for rollup, scoring candidate geographic units to select best pairings for rollup, and repeating until the rollup group has at least the minimum number of households. The process may make trades off between granularity (e.g., number of households), proximity, and similarity of data attributes associated with each geographic unit.

First claim

What is claimed is:

1. A computer-implemented method of displaying household information relating to and facilitating presentation of the information in a way that satisfies a minimum threshold of household granularity on a graphical user interface, the method comprising:
under control of a computing device configured with specific computer-executable instructions:
receiving, from a requesting entity, at least one indication associated with a geographic area;
displaying a map of the geographic area based on the at least one indication;
receiving, from the requesting entity, a minimum threshold indicating a quantity of households required in aggregated groups of households, the minimum threshold indicating the minimum number of individual households included in the aggregated groups;
accessing a list of one or more target geographic units and related attribute data, wherein each of the target geographic units includes one or more households associated with a location on the displayed map;
determining one or more combinable geographic units within a particular geographic distance of a target geographic unit, the target geographic unit having a target number of households within the target geographic unit;
identifying one or more candidate geographic units for potential aggregation with the target geographic unit;
applying one or more filter criteria to the one or more candidate geographic units to remove candidate geographic units that do not meet the one or more filter criteria;
determining, for each remaining candidate geographic unit after application of the filter:
a score based at least in part on similarity of a household data attribute associated with the remaining candidate geographic unit and the target geographic unit;

determining a best candidate number of households associated with a best candidate geographic unit having a highest score;
updating an aggregated group to include the best candidate geographic unit and the target geographic unit;
determining an aggregated group sum as a sum of the best candidate number of households and the target number of households;
determining whether the aggregated group sum is below the minimum threshold; and
automatically repeating until the aggregated group sum is not below the minimum threshold:
determining a best candidate geographic unit for aggregation into the aggregated group, the best candidate geographic unit having a best score;
updating the aggregated group sum to include a best candidate number of households;
determining whether the aggregated group sum is below the minimum threshold; or
in response to determining that the aggregated group sum is not below the minimum threshold:
determining an aggregated value of household data attributes of households within the aggregated group;

associating the aggregated group with a distinct visual indicator;
determining locations of each of the geographic units within the aggregated group on the map; and
updating the map to depict the distinct visual indicator at each of the determined locations on the map,
wherein the individually identifiable household data attributes of the individual households in the aggregated group are concealed.

2. The computer-implemented method of claim 1 , wherein identifying one or more candidate geographic units for potential aggregation with the target geographic unit comprises:
accessing geographic attribute data associated with a target geographic unit and one or more candidate geographic units, the geographic attribute data accessed from a physical data store storing geographic data that includes household data attributes associated with respective geographic units, the household data attributes indicating at least a number of households associated with respective geographic units;
determining a geographic location for the target geographic unit, based at least in part on accessed geographic unit attribute data; and
identifying the one or more candidate geographic units, wherein each candidate geographic unit is within a radial distance of the geographic location, based at least in part on geographic data associated with the respective candidate geographic unit.

3. The computer-implemented method of claim 1 , wherein the predetermined geographic distance comprises a latitude longitude bounded area.

4. The computer-implemented method of claim 1 , wherein the household data attributes include one or more socio-economic and/or lifestyle segment attributes.

5. The computer-implemented method of claim 4 , wherein the socio-economic attributes include an average asset value per household within the respective geographic unit.

6. The computer-implemented method of claim 1 , wherein each candidate geographic unit is a ZIP+4 code.

7. The computer-implemented method of claim 1 , further comprising:
receiving one or more additional filter criteria from the requesting entity.

8. The computer-implemented method of claim 1 , wherein the one or more additional filter criteria are received from the requesting entity via a web user interface, and wherein the web user interface provides one or more input fields enabling the requesting entity to configure custom filter criteria for identifying the aggregated group.

9. The computer-implemented method of claim 1 , wherein determining the score for each remaining candidate geographic unit further comprises:
identifying one or more target attributes on which to analyze the similarity of each remaining candidate geographic unit to the target geographic unit, wherein the target attributes are selected from the household data attributes;
calculating, for each remaining candidate geographic unit, a weighted similarity of the remaining candidate geographic unit to the target geographic unit based on a comparison of the target attributes; and
determining the score based at least in part on the weighted similarity.

10. The computer-implemented method of claim 9 , wherein the weighted similarity is calculated based at least in part on a calculated geographic distance between the remaining candidate geographic unit and the target geographic unit.

11. A computer system for displaying household information relating to and facilitating presentation of the information in a way that satisfies a minimum threshold of household granularity on a graphical user interface, the system comprising:
an electronic data store configured to at least store geographic data associated with each of a plurality of geographic units; and
a computing system comprising one or more hardware computing devices, said computing system in communication with the electronic data store and configured to at least:
receive, from a requesting entity, at least one indication associated with a geographic area;
display a map of the geographic area based on the at least one indication;
receive, from the requesting entity, a minimum threshold indicating a quantity of households required in aggregated groups of households, the minimum threshold indicating the minimum number of individual households included in the aggregated groups;
determine one or more combinable geographic units within a particular geographic distance of a target geographic unit, the target geographic unit having a target number of households within the target geographic unit;
identify one or more candidate geographic units for potential aggregation with the target geographic unit;
apply one or more filter criteria to the one or more candidate geographic units to remove candidate geographic units that do not meet the one or more filter criteria;
determine, for each remaining candidate geographic unit after application of the filter:
a score based at least in part on simi

Assignees

• Experian Inf Solutions Inc

Inventors

• Hickman Andrew John
• Tsang Alan
• Tao Yaqi
• Pan Shengjun

Classifications

• G06Q30/0201

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

• G06Q30/0205 Primary

  based on location or geographical consideration · CPC title