Systems and methods for identifying and selecting personalized waypoints for presentation on a map

• US 9,234,763 B1
• Filed: 08/14/2013
• Issued: 01/12/2016
• Est. Priority Date: 08/14/2013
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Savvopoulos, Christos, Seyboth, Stephan
• Primary Examiner(s): Dager, Jonathan M
• Application Number:
  US13/966,424
• Time in Patent Office: 881 Days
• US Class Current: 1/1
• CPC Class Codes: G01C 21/3484 Personalized, e.g. from learned user behaviour or user-defined profiles
• CPC Class Codes: G01C 21/3682 output of POI information on a road map G01C21/3614, G01C21/3685 take precedence

Abstract

Systems and methods for identifying and selecting personalized waypoints for presentation on a map are provided. In particular, a user'"'"'s data can be analyzed to identify a plurality of candidate waypoints. The candidate waypoints can correspond to locations at which the user has a scheduled event, reservation, or appointment. When the user performs a search query in a mapping application or geographic information system, the plurality of candidate waypoints can be obtained and scored according to a scoring formula. One or more candidate waypoints can be selected based on the determined scores and presented on a personalized map in addition to the result of the search query. An exemplary scoring formula takes a candidate waypoint and a point of interest search result as inputs and analyzes a distance between the two locations and a likelihood that a user wants directions between the two locations.

Claims

1. A host server for providing geographic information comprising:

one or more computing devices associated with the host server, the one or more computing devices being configured to perform operations comprising;

receiving a search query from a client device, the client device having been associated with user account;

in response to the received search query, identifying a point of interest for display on a map; and

obtaining a plurality of candidate waypoints from a database, each of the candidate waypoints having been identified by analyzing data associated with the user account;

determining a score for each of the candidate waypoints using a scoring formula, wherein the scoring formula includes scoring components that are based at least in part on a first category defining the type of entity of each candidate waypoint being scored and a second category defining the type of entity of the point of interest, and wherein the scoring formula includes a distance scaling component, the distance scaling component comprising a weighted distance divided by a distance between the candidate waypoint being scored and the point of interest, the weighted distance providing a number based on the second category associated with the point of interest; and

selecting, based on the determined scores, at least one of the candidate waypoints for presentation on the map displaying the point of interest.

2. The host server of claim 1, wherein the client device is signed into the user account.

3. The host server of claim 1, wherein the data associated with the user account comprises email data.

4. The host server of claim 3, wherein the candidate waypoints are identified by comparing the email data to a plurality of templates.

5. The host server of claim 1, wherein the data associated with the user account comprises calendar entry data.

6. The host server of claim 1, wherein each of the candidate waypoints comprises a location at which an event is scheduled to occur.

7. The host server of claim 1, wherein the scoring formula provides the score for each candidate waypoint based at least in part on a distance between the candidate waypoint being scored and the point of interest.

8. The host server of claim 7, wherein the distance between the candidate waypoint being scored and the point of interest comprises a driving distance between the candidate waypoint being scored and the point of interest.

9. The host server of claim 1, wherein the scoring formula includes a suitability component, the suitability component providing a likelihood that directions between the candidate waypoint being scored and the point of interest are desired by a user.

10. The host server of claim 9, wherein the suitability component provides the likelihood by comparing the first category associated with the candidate waypoint being scored with the second category associated with the point of interest.

11. The host server of claim 1, wherein the scoring formula includes a distance scaling component, the distance scaling component comprising a weighted distance divided by a distance between the candidate waypoint being scored and the point of interest, the weighted distance providing a number based on the first category associated with the candidate waypoint being scored.

12. A computer-implemented method for providing a personalized map, the method comprising:

receiving, by one or more computing devices, from a client device associated with a user account, a request for geographic information;

identifying, by the one or more computing devices, based on the request for geographic information, a point of interest;

obtaining, by the one or more computing devices, from a database a plurality of candidate reference locations associated with the user account, wherein the plurality of candidate reference locations are culled from user data comprising email data or calendar data;

assigning, by the one or more computing devices, each of the plurality of candidate reference locations to one of a plurality of first categories;

assigning, by the one or more computing devices, the point of interest to one of a plurality of second categories;

determining, by the one or more computing devices, a score for each of the plurality of candidate reference locations using a scoring formula, the scoring formula receiving the point of interest as an input and including scoring components that are based at least in part on a first category defining the type of entity of each candidate reference location being scored and a second category defining the type of entity of the point of interest, wherein the scoring formula further includes a suitability component that references a look-up table providing a suitability score for each combination of the first and second categories; and

selecting, by the one or more computing devices, based on the determined scores, at least one of the plurality of candidate reference locations for presentation on the personalized map.

13. A computing system for providing personalized maps, the computing system being configured to perform operations comprising:

analyzing data associated with a user account to identify a plurality of locations the user is expecting to visit;

storing the plurality of locations in a database;

identifying a point of interest in response to a search request received from the user;

determining, for each of the plurality of locations, a score based at least in part on a distance between the location and the point of interest and a likelihood that the user desires directions between the location and the point of interest, the likelihood based at least in part on a first category defining the type of entity of each location being scored and a second category defining the type of entity of the point of interest;

wherein determining, for each of the plurality of locations, a score based at least in part on a distance between the location and the point of interest and a likelihood that the user desires directions between the location and the point of interest comprises, for each of the plurality of locations;

determining a first distance scaling component;

determining a second distance scaling component; and

determining a suitability component; and

selecting, based on the plurality of scores, one or more of the plurality of locations for presentation on a map alongside the point of interest.

14. The computing system of claim 13, wherein analyzing data associated with a user account to identify a plurality of locations the user is expecting to visit comprises:

parsing textual information to identify a plurality of scheduled events; and

respectively generating a plurality of geocodes for the plurality of scheduled events, the plurality of locations comprising the plurality of geocodes.

15. The computing system of claim 13, wherein:

the first distance scaling component scales the distance between the location and the point of interest based on the first category assigned to the location;

the second distance scaling component scales the distance between the location and the point of interest based on the second category assigned to the point of interest; and

the suitability component provides the likelihood that the user desires directions between the location and the point of interest based on the first category and the second category.

16. The computing system of claim 15, wherein determining, for each of the plurality of locations, a score based at least in part on a distance between the location and the point of interest and a likelihood that the user desires directions between the location and the point of interest further comprises, for each of the plurality of locations, summing the first distance scaling component, the second distance scaling component, and the suitability component.