METHOD FOR ANALYZING DEMOGRAPHIC DATA

• US 20100185620A1
• Filed: 03/10/2010
• Published: 07/22/2010
• Est. Priority Date: 12/21/2001
• Status: Active Grant

• Current Assignee: Location Incorporated Group Corporation (CoreLogic Incorporated)
• Original Assignee: Location Incorporated Group Corporation (CoreLogic Incorporated)
• Inventors: Schiller, Andrew
• Granted Patent: US 8,849,808 B2
• Time in Patent Office: Days
• US Class Current: 707/738
• CPC Class Codes: G06F 16/29 Geographical information databases
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 16/9537 Spatial or temporal dependent retrieval, e.g. spatiotemporal queries
• CPC Class Codes: G06F 3/04842 Selection of displayed objects or displayed text elements G06F3/0482 takes precedence
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: Y10S 707/918 Location
• CPC Class Codes: Y10S 707/919 Geographic

Abstract

A computer implemented method of generating an ordered list of geographical locations having similarities in preselected categories relative to a first geographical location.

Claims

1. A computer-implemented method of creating a listing of a plurality of locations in rank order from greatest to least similarity in at least one user identified characteristic, the method comprising the steps of:

calculating a numeric value that represents a relative measure at which said at least one characteristic exists in each of said plurality of locations and associating said value with each of said plurality of locations within a database;

allowing a user to select at least one characteristic associated with the locations within the database;

automatically comparing the numeric value associated with each of the plurality of locations in the database to determine the overall dissimilarities between each of said numeric values based on said user selected characteristic; and

automatically generating an ordered list of locations from greatest to least similarity in said at least one user identified characteristic based on the smallest dissimilarities in said numeric values.

2. A method according to claim 1 wherein the step of automatically comparing the user selected characteristic in the data base with the plurality of locations in the data base and generating an ordered list of other locations most similar to the user selected characteristic comprises generating a dissimilarity matrix in which an overall dissimilarity value is assigned to each of the plurality of locations relative to the level at which said user selected characteristic exists within the location, and generating an ordered list of the other locations therefrom.

3. A method according to claim 2 wherein the step of generating a dissimilarity matrix comprises the step of applying an extraction method to the raw data, the extraction method including a factor analysis to extract factors from the data base, and applying a squared Euclidian distance measure to the extracted factors.

4. The method of claim 1, wherein said step of allowing a user to select at least one characteristic associated with the locations within the database further comprises:

allowing a user to select at least one location from the locations within the database wherein at least one characteristic associated with the selected location becomes the user selected characteristic.

5. The method according to claim 4, wherein said step of comparing the numeric value associated with each of the plurality of locations in the database to determine the overall dissimilarities between each of said numeric values based on said user selected characteristic further comprises:

calculating a squared difference between a numeric value associated with a first chosen characteristic of each location to a numeric value associated with said first user selected characteristic;

repeating said step of calculating a squared difference using each respective identifiable characteristic associated with each respective location; and

adding each squared difference that is calculated to create a cumulative dissimilarity value between each of said plurality of locations.

6. A computer-implemented method of identifying a plurality of locations that have the greatest similarity to another user selected location as modified by at least one user selected characteristic, the method comprising the steps of:

calculating a numeric value that represents a relative measure at which said at least one characteristic exists in each of said plurality of locations and associating said value with each of said plurality of locations within a database;

allowing a user to select a first location from the database;

allowing said user to modify at least one of said characteristics associated with said locations;

automatically recalculating said numeric value based on said user modification of said characteristics;

automatically comparing the recalculated numeric value associated with said modified set of characteristics with the numeric values associated with the other locations in the data base to determine the overall dissimilarities in said numeric values; and

automatically generating an ordered list of locations that are most similar to said user selected location as modified by said user based on the smallest dissimilarities in said numeric values.

7. A method according to claim 6 wherein the step of automatically comparing the numeric values associated with said user selected location as modified by said user with the numeric values associated with the other locations in the data base and automatically generating an ordered list of other locations most similar to the modified set of characteristics further comprises:

automatically generating a dissimilarity matrix in which an overall dissimilarity value is assigned to each of the other locations relative to the numeric value of said set of characteristics of said user selected location as modified by said user through selection of said keyword descriptors, and generating an ordered list based on the smallest dissimilarity between the user modified search and all of the locations within the data base.