IP Library Patent Application 19323886
Patent Application
App. No. 19/323,886

SYSTEM AND METHOD FOR AGGREGATION AND GRADUATED VISUALIZATION OF USER GENERATED SOCIAL POST ON A SOCIAL MAPPING NETWORK

Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US None
App. No.
19/323,886
Abstract

A system and method for location-based social networking, including: a social mapping module executing on a computer processor and configured to enable the computer processor to receive, from a client device, a request for social media posts, wherein the request comprises location information and screen attribute information associated with a display of the client device; identify a candidate set of social media posts based at least on the location information; determine a graduated visualization level from a plurality of predetermined graduated visualization levels based on the screen attribute information, wherein each graduated visualization level corresponds to a different aggregation density and symbol representation type; generate an aggregated group comprising a subset of the candidate set of social media posts using grouping criteria that varies based on the determined graduated visualization level; and provide an aggregated graphical symbol to the client device for display.

Claims (82)

1 . A system for location-based social networking, comprising:

a computer processor; and

a social mapping module executing on the computer processor and configured to enable the computer processor to:

receive, from a client device, a request for social media posts, wherein the request comprises location information and screen attribute information associated with a display of the client device;

identify a candidate set of social media posts based at least on the location information;

determine a graduated visualization level from a plurality of predetermined graduated visualization levels based on the screen attribute information, wherein each graduated visualization level corresponds to a different aggregation density and symbol representation type;

generate an aggregated group comprising a subset of the candidate set of social media posts using grouping criteria that varies based on the determined graduated visualization level;

generate an aggregated graphical symbol based on the aggregated group, wherein the aggregated graphical symbol represents the aggregated group and corresponds to the determined graduated visualization level; and

provide the aggregated graphical symbol to the client device for display, wherein the aggregated graphical symbol dynamically transforms between different symbol representation types as the screen attribute information changes across predetermined transformation thresholds.

2 . The system of claim 1 , wherein the social mapping module is further configured to enable the computer processor to:

process the screen attribute information comprising at least one selected from a group consisting of a current zoom level, a pan location, an availability of screen space, and an amount of screen space; and

determine the graduated visualization level by comparing the screen attribute information against predetermined threshold values corresponding to each of the plurality of predetermined graduated visualization levels.

3 . The system of claim 1 , wherein the plurality of predetermined graduated visualization levels comprises:

a low zoom graduated level configured to generate aggregated graphical symbols as dot symbols representing aggregated groups with high aggregation density;

a medium zoom graduated level configured to generate aggregated graphical symbols as emoji symbols representing aggregated groups with medium aggregation density; and

a high zoom graduated level configured to generate aggregated graphical symbols as individual post symbols representing single posts or aggregated groups with low aggregation density.

4 . The system of claim 1 , wherein the social mapping module is further configured to enable the computer processor to:

detect a change in the screen attribute information that crosses one of the predetermined transformation thresholds;

automatically transition between graduated visualization levels by transforming the aggregated graphical symbol from a first symbol representation type to a second symbol representation type; and

wherein the transforming comprises at least one selected from a group consisting of converting a single aggregated symbol into multiple individual symbols, and converting multiple individual symbols into a single aggregated symbol.

5 . The system of claim 1 , wherein generating the aggregated group further comprises:

calculating available screen real estate based on the screen attribute information and positions of other aggregated graphical symbols;

determining a maximum symbol density for the determined graduated visualization level to prevent symbol overlap; and

conditionally excluding social media posts with lower relevancy rankings from the aggregated group when the maximum symbol density would be exceeded.

6 . The system of claim 1 , wherein the social mapping module is further configured to enable the computer processor to:

maintain a relevancy ranking for each social media post in the candidate set;

implement relevancy-based cycling within the determined graduated visualization level by prioritizing display of social media posts with higher relevancy rankings; and

cycle through display of social media posts with lower relevancy rankings based on available screen space and the aggregation density of the determined graduated visualization level.

7 . The system of claim 1 , wherein generating the aggregated graphical symbol comprises:

determining attributes of social media posts included in the aggregated group; and

selecting the aggregated graphical symbol based on at least one selected from a group consisting of an average of graphical symbols selected by authors of the social media posts, a median of graphical symbols selected by authors of the social media posts, emotional states selected by authors of the social media posts, and colors selected by authors of the social media posts.

8 . The system of claim 1 , wherein the social mapping module is further configured to enable the computer processor to:

maintain persistent tracking of individual relevancy rankings for each social media post across all of the plurality of predetermined graduated visualization levels; and

dynamically adjust which social media posts are included in aggregated groups at each graduated visualization level based on changes in the screen attribute information while preserving the individual relevancy rankings.

9 . The system of claim 1 , wherein the social mapping module is further configured to enable the computer processor to:

detect a zoom-out condition based on the screen attribute information; and

implement reverse graduated visualization by progressively re-aggregating individual post symbols into larger aggregated symbols and increasing aggregation density as the graduated visualization level transitions from higher zoom levels to lower zoom levels.

10 . A method for location-based social networking, comprising:

receiving, from a client device, a request for social media posts, wherein the request comprises location information and screen attribute information associated with a display of the client device;

identifying a candidate set of social media posts based at least on the location information;

determining a graduated visualization level from a plurality of predetermined graduated visualization levels based on the screen attribute information, wherein each graduated visualization level corresponds to a different aggregation density and symbol representation type;

generating, by a computer processor, an aggregated group comprising a subset of the candidate set of social media posts using grouping criteria that varies based on the determined graduated visualization level;

generating an aggregated graphical symbol based on the aggregated group, wherein the aggregated graphical symbol represents the aggregated group and corresponds to the determined graduated visualization level; and

providing the aggregated graphical symbol to the client device for display, wherein the aggregated graphical symbol dynamically transforms between different symbol representation types as the screen attribute information changes across predetermined transformation thresholds.

11 . The method of claim 10 , further comprising:

processing the screen attribute information comprising at least one selected from a group consisting of a current zoom level, a pan location, an availability of screen space, and an amount of screen space; and

determining the graduated visualization level by comparing the screen attribute information against predetermined threshold values corresponding to each of the plurality of predetermined graduated visualization levels.

12 . The method of claim 10 , wherein the plurality of predetermined graduated visualization levels comprises:

a low zoom graduated level configured to generate aggregated graphical symbols as dot symbols representing aggregated groups with high aggregation density;

a medium zoom graduated level configured to generate aggregated graphical symbols as emoji symbols representing aggregated groups with medium aggregation density; and

a high zoom graduated level configured to generate aggregated graphical symbols as individual post symbols representing single posts or aggregated groups with low aggregation density.

13 . The method of claim 10 , further comprising:

detecting a change in the screen attribute information that crosses one of the predetermined transformation thresholds;

automatically transitioning between graduated visualization levels by transforming the aggregated graphical symbol from a first symbol representation type to a second symbol representation type; and

wherein the transforming comprises at least one selected from a group consisting of converting a single aggregated symbol into multiple individual symbols, and converting multiple individual symbols into a single aggregated symbol.

14 . The method of claim 10 , wherein generating the aggregated group further comprises:

calculating available screen real estate based on the screen attribute information and positions of other aggregated graphical symbols;

determining a maximum symbol density for the determined graduated visualization level to prevent symbol overlap; and

conditionally excluding social media posts with lower relevancy rankings from the aggregated group when the maximum symbol density would be exceeded.

15 . The method of claim 10 , further comprising:

maintaining a relevancy ranking for each social media post in the candidate set;

implementing relevancy-based cycling within the determined graduated visualization level by prioritizing display of social media posts with higher relevancy rankings; and

cycling through display of social media posts with lower relevancy rankings based on available screen space and the aggregation density of the determined graduated visualization level.

16 . The method of claim 10 , wherein generating the aggregated graphical symbol comprises:

determining attributes of social media posts included in the aggregated group; and

selecting the aggregated graphical symbol based on at least one selected from a group consisting of an average of graphical symbols selected by authors of the social media posts, a median of graphical symbols selected by authors of the social media posts, emotional states selected by authors of the social media posts, and colors selected by authors of the social media posts.

17 . The method of claim 10 , further comprising:

maintaining persistent tracking of individual relevancy rankings for each social media post across all of the plurality of predetermined graduated visualization levels; and

dynamically adjusting which social media posts are included in aggregated groups at each graduated visualization level based on changes in the screen attribute information while preserving the individual relevancy rankings.

18 . The method of claim 10 , further comprising:

detecting a zoom-out condition based on the screen attribute information; and

implementing reverse graduated visualization by progressively re-aggregating individual post symbols into larger aggregated symbols and increasing aggregation density as the graduated visualization level transitions from higher zoom levels to lower zoom levels.

19 . A non-transitory computer-readable storage medium comprising a plurality of instructions for location-based social networking, the plurality of instructions configured to execute on at least one computer processor to enable the at least one computer processor to:

receive, from a client device, a request for social media posts, wherein the request comprises location information and screen attribute information associated with a display of the client device;

identify a candidate set of social media posts based at least on the location information;

determine a graduated visualization level from a plurality of predetermined graduated visualization levels based on the screen attribute information, wherein each graduated visualization level corresponds to a different aggregation density and symbol representation type;

generate an aggregated group comprising a subset of the candidate set of social media posts using grouping criteria that varies based on the determined graduated visualization level;

generate an aggregated graphical symbol based on the aggregated group, wherein the aggregated graphical symbol represents the aggregated group and corresponds to the determined graduated visualization level; and

provide the aggregated graphical symbol to the client device for display, wherein the aggregated graphical symbol dynamically transforms between different symbol representation types as the screen attribute information changes across predetermined transformation thresholds.

20 . The non-transitory computer-readable storage medium of claim 19 , wherein the plurality of instructions are further configured to execute on the at least one computer processor to enable the at least one computer processor to:

process the screen attribute information comprising at least one selected from a group consisting of a current zoom level, a pan location, an availability of screen space, and an amount of screen space; and

determine the graduated visualization level by comparing the screen attribute information against predetermined threshold values corresponding to each of the plurality of predetermined graduated visualization levels.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 11, 2025
From: CONSTANTINIDES, STEPHEN
To: YOU MAP INC.
Reel/Frame 072228/0848 →