Determining relationships between data items and individuals, and dynamically calculating a metric score based on groups of characteristics

• US 8,341,101 B1
• Filed: 05/01/2012
• Issued: 12/25/2012
• Est. Priority Date: 02/08/2012
• Status: Active Grant

• Current Assignee: Gatsby Technologies, LLC
• Original Assignee: Adam Treiser
• Inventors: Treiser, Adam
• Primary Examiner(s): VINCENT, DAVID ROBERT
• Application Number:
  US13/461,670
• Time in Patent Office: 238 Days
• Field of Search: 706/12, 706/45, 706/62, 705/7.29, 705/7.37, 705/14.4
• US Class Current: 706/45
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising

Abstract

Systems, apparatus, and methods for correlating two items of interest, based on a plurality of data items and characteristics. The data items may include objective and quantitative data, as well as subjective and qualitative data. In one implementation, the relationship of an individual to a metric is determined. The system, apparatus, and methods may store characteristics describing individuals generally, along with metrics relevant to an organization; receive a plurality of data items; extract information associated with the individual from the data items; determine a number of relationships between the data items, individuals, metric, and characteristics; and use the relationships to determine an overall relationship between the individual and the metric, based on the data and characteristics. In addition, related groups of characteristics may be identified. Similarly, the relationships between any individual, metric, sub-metric, group of characteristics, data item, data source, characteristic, or groups thereof may also be determined.

Claims

1. A method of identifying groups of related characteristics, comprising:

receiving, at a computer;

a plurality of data items, related to individuals;

a plurality of descriptors, identifying the individuals;

a plurality of characteristics, defining categories of the individuals; and

a metric;

calculating a first set of relationships between the data items and one or more of the individuals identified by the plurality of descriptors, wherein each relationship comprises a magnitude and direction;

calculating a second set of relationships between the characteristics and the data items, wherein each relationship comprises a magnitude and direction;

calculating a third set of relationships between the metric and the characteristics, wherein each relationship comprises a magnitude and direction;

identifying groups of one or more of the characteristics based on the second set of relationships and the third set of relationships;

dynamically calculating a metric score based on the identified groups; and

outputting the metric score.

2. The method of claim 1, comprising:

calculating a fourth set of relationships between the groups and the characteristics, wherein each relationship comprises a magnitude and direction;

calculating a fifth set of relationships between the groups and the metric, based on the third and fourth relationships, wherein each relationship comprises a magnitude and direction;

representing each relationship of the fifth set of relationships with a single descriptor; and

outputting (i) the fifth set of relationships and (ii) the descriptors.

3. The method of claim 1, comprising:

calculating a fourth set of relationships between the groups and the characteristics, wherein each relationship comprises a magnitude and direction;

calculating a sixth set of relationships between the individuals identified by the plurality of descriptors and the characteristics, based on one or more of the first set of relationships and one or more of the second set of relationships, wherein each relationship comprises a magnitude and direction;

calculating a seventh set of relationships between the individuals identified by the plurality of descriptors and the groups, based on one or more of the fourth set of relationships and one or more of the sixth set of relationships, wherein each relationship comprises a magnitude and direction;

representing the relationships of the seventh set of relationships with single descriptors; and

outputting (i) the seventh set of relationships and (ii) the descriptors.

4. The method of claim 1, wherein the data items comprise both structured and unstructured information.

5. The method of claim 4, wherein the structured information comprises quantitative information and the unstructured information comprises qualitative information.

6. The method of claim 1, comprising:

calculating an eighth set of relationships between one or more of the plurality of groups, wherein each relationship comprises a magnitude and direction; and

outputting the eighth set of relationships.

7. The method of claim 1, comprising:

calculating a fourth set of relationships between the groups and the characteristics, wherein each relationship comprises a magnitude and direction;

identifying new characteristics based on;

the groups;

one or more of the fourth set of relationships between the groups and the characteristics; and

one or more of the second set of relationships between the existing characteristics and the data items; and

outputting the new characteristics.

8. The method of claim 1, wherein dynamically calculating the metric score based on the identified groups further comprises:

calculating a fourth set of relationships between the groups and the characteristics, wherein each relationship comprises a magnitude and direction;

calculating a fifth set of relationships between the groups and the metric, based on one or more of the third set of relationships and one or more of the fourth set of relationships, wherein each relationship comprises a magnitude and direction;

receiving a plurality of sub-metrics;

calculating a ninth set of relationships between the groups and the sub-metrics, wherein each relationship comprises a magnitude and direction;

calculating a tenth set of relationships between the sub-metrics and the metrics, wherein each relationship comprises a magnitude and direction;

calculating a set of metric sub-scores based on one or more of the fifth set of relationships and one or more of the tenth set of relationships, wherein each relationship comprises a magnitude and direction;

dynamically calculating a metric score based on one or more of the set of metric sub-scores;

representing the metric score with a single descriptor; and

outputting the descriptor.

9. The method of claim 1, wherein dynamically calculating the metric score based on the identified groups further comprises:

receiving data items comprising both qualitative and structured information and quantitative and unstructured information;

identifying new characteristics based on;

the groups;

the relationships between the groups and the data items; and

the relationships between existing characteristics and the data items;

calculating a fourth set of relationships between the groups and the characteristics, wherein each relationship comprises a magnitude and direction;

calculating a fifth set of relationships between the groups and the metric based on (i) one or more or the third set of relationships and (ii) one or more of the fourth set of relationships, wherein each relationship comprises a magnitude and direction;

calculating a sixth set of relationships between the individuals identified by the plurality of descriptors and the characteristics, based on one or more of the first set of relationships and one or more of the second set of relationships, wherein each relationship comprises a magnitude and direction;

calculating a seventh set of relationships between the individuals identified by the plurality of descriptors and the groups based on one or more of the fourth set of relationships and one or more of the sixth set of relationships, wherein each relationship comprises a magnitude and direction;

receiving a plurality of sub-metrics;

calculating a ninth set of relationships between the groups and the sub-metrics, wherein each relationship comprises a magnitude and direction;

calculating a tenth set of relationships between the sub-metrics and the metrics, wherein each relationship comprises a magnitude and direction;

calculating a set of metric sub-scores, based on one or more of the fifth set of relationships and one or more of the tenth set of relationships;

dynamically calculating a metric score based on one or more of the set of metric sub-scores;

representing the metric score with a single descriptor; and

outputting the descriptor.

10. The method of claim 9, wherein members of the first through tenth sets of relationships comprise a direction that may be positive, neutral, or negative.

11. A non-transitory computer-readable storage medium encoded with instructions which, when executed on a processor, perform a method of identifying groups of related characteristics, the method comprising:

receiving, at a computer;

a plurality of data items, related to individuals;

a plurality of descriptors, identifying the individuals;

a plurality of characteristics, defining categories of individuals; and

a metric;

calculating a first set of relationships between data items and specific ones of the individuals identified by the plurality of descriptors;

calculating second set of relationships between characteristics and data items, wherein each relationship comprises a magnitude and direction;

calculating a third set of relationships between the metric and the characteristics, wherein each relationship comprises a magnitude and direction;

identifying groups of one or more characteristics based on the second set of relationships and the third set of relationships;

dynamically calculating a metric score based on the identified groups; and

outputting the metric score.

12. The storage medium of claim 11, wherein the method comprises:

calculating a fourth set of relationships between the groups and the characteristics, wherein each relationship comprises a magnitude and direction;

calculating a fifth set of relationships between the groups and the metric based on one or more of the third set of relationships and one or more of the fourth set of relationships, wherein each relationship comprises a magnitude and direction;

representing the relationships of the fifth set of relationships with single descriptors; and

outputting the fifth set of relationships and descriptors.

13. The storage medium of claim 11, wherein the method comprises:

calculating a fourth set of relationships between the groups and the characteristics, wherein each relationship comprises a magnitude and direction;

calculating a sixth set of relationships between the individuals identified by the plurality of descriptors and the characteristics, based on one or more of the first set of relationships and one or more of the second set of relationships, wherein each relationship comprises a magnitude and direction;

calculating a seventh set of relationships between specific ones of the individuals identified by the plurality of descriptors and the groups based on one or more of the fourth set of relationships and one or more of the sixth set of relationships, wherein each relationship comprises a magnitude and direction;

representing the relationships in the seventh set of relationships with single descriptors; and

outputting the seventh set of relationships and descriptors.

14. The storage medium of claim 11, wherein the method comprises:

calculating an eighth set of relationships between each of the plurality of groups, wherein each relationship comprises a magnitude and direction; and

outputting the eighth set of relationships.

15. The storage medium of claim 11, wherein the method comprises:

calculating a fourth set of relationships between the groups and the characteristics, wherein each relationship comprises a magnitude and direction;

identifying new characteristics based on;

the groups;

one or more of the fourth set of relationships between the groups and the characteristics; and

one or more of the second set of relationships between the existing characteristics and the data items; and

outputting the new characteristics.

16. The storage medium of claim 11, wherein dynamically calculating a metric score based on the identified groups comprises:

calculating a fourth set of relationships between the groups and the characteristics, wherein each relationship comprises a magnitude and direction;

calculating a fifth set of relationships between the groups and the metric based on one or more of the third set of relationships and one or more of the fourth set of relationships, wherein each relationship comprises a magnitude and direction;

receiving a plurality of sub-metrics;

calculating a ninth set of relationships between the groups and the sub-metrics, wherein each relationship comprises a magnitude and direction;

calculating a tenth set of relationships between the sub-metrics and the metrics, wherein each relationship comprises a magnitude and direction;

calculating a set metric sub-scores, based on one or more of the fifth set of relationships and one or more of the tenth set of relationships;

dynamically calculating a metric score based on one or more of the set of metric sub-scores;

representing the metric score with a single descriptor; and

outputting the descriptor.

17. The storage medium of claim 11, wherein dynamically calculating a metric score based on the identified groups comprises:

receiving data items comprising both qualitative and structured information and quantitative and unstructured information;

calculating a fourth set of relationships between the groups and the characteristics, wherein each relationship comprises a magnitude and direction;

identifying new characteristics based on;

the groups;

one or more of the fourth set of relationships between the groups and the characteristics; and

one or more of the second set of relationships between existing characteristics and the data items;

calculating a fifth set of relationships between the groups and the metric based on one or more of the third set of relationships and one or more of the fourth set of relationships, wherein each relationship comprises a magnitude and direction;

calculating a sixth set of relationships between the individuals identified by the plurality of descriptors and characteristics, based on one or more of the first set of relationships and one or more of the second set of relationships, wherein each relationship comprises a magnitude and direction;

calculating a seventh set of relationships between specific ones of the individuals identified by the plurality of descriptors and the groups based on one or more of the fourth set of relationships and one or more of the sixth set of relationships, wherein each relationship comprises a magnitude and direction;

receiving a plurality of sub-metrics;

calculating a ninth set of relationships between the groups and the sub-metrics, wherein each relationship comprises a magnitude and direction;

calculating a tenth set of relationships between the sub-metrics and the metrics, wherein each relationship comprises a magnitude and direction;

calculating a set of metric sub-scores, based on one or more of the fifth set of relationships and one or more of the tenth set of relationships, wherein each relationship comprises a magnitude and direction;

dynamically calculating a metric score, based on one or more of the set of metric sub-scores, wherein each relationship comprises a magnitude and direction;

representing the metric score with a single descriptor; and

outputting the descriptor.

18. The storage medium of claim 17, wherein members of the first through tenth sets of relationships comprise a direction that may be positive, neutral, or negative.

19. A characteristic-based server to identify groups of related characteristics of individuals, the server comprising;

a data collection module to gather data items from a plurality of data sources;

a relationship analysis module to;

calculate a first set of relationships between data items and specific ones of the individuals identified by the plurality of descriptors, wherein each relationship comprises a magnitude and direction;

calculate a second set of relationships between the characteristics and data items, wherein each relationship comprises a magnitude and direction;

calculate a sixth set of relationships between the individuals identified by the plurality of descriptors and the characteristics, based on one or more of the first set of relationships and one or more of the second set of relationships, wherein each relationship comprises a magnitude and direction;

calculate a third set of relationships between the metric and the characteristics, wherein each relationship comprises a magnitude and direction; and

dynamically calculate a metric score based on groups of characteristics; and

a grouping module to identify groups of related characteristics based on one or more of the second set of relationships and one or more of the third set of relationships.

20. The server of claim 19, wherein the relationship module is further operative to calculate:

a fourth set of relationships between the groups and the characteristics, wherein each relationship comprises a magnitude and direction;

a fifth set of relationships between the groups and the metric based on one or more of the third set of relationships and one or more of the fourth set of relationships, wherein each relationship comprises a magnitude and direction; and

descriptors representing the relationships of the fifth set of relationships.

21. The server of claim 19, wherein the relationship module is further operative to calculate:

a fourth set of relationships between the groups and the characteristics, wherein each relationship comprises a magnitude and direction;

a sixth set of relationships between the individuals identified by the plurality of descriptors and the characteristics, based on one or more of the first set of relationships and one or more of the second set of relationships, wherein each relationship comprises a magnitude and direction;

a seventh set of relationships between specific ones of the individuals identified by the plurality of descriptors and the groups based on one or more of the fourth relationships and one or more of the sixth relationships, wherein each relationship comprises a magnitude and direction; and

descriptors representing the relationships of the seventh set of relationships.

22. The server of claim 19, wherein the relationship module is further operative to calculate an eighth set of relationships between each of the plurality of groups and output the relationships, wherein each relationship comprises a magnitude and direction.

23. The server of claim 22, wherein the characteristic-based server further comprises:

a pattern recognition module to recognize new characteristics based on;

the groups;

one or more of the fourth set of relationships between the groups and the characteristics; and

one or more of the second set of relationships between the existing characteristics and the data items.

24. The server of claim 19, wherein the relationship module is further operative to;

calculate a fourth set of relationships between the groups and the characteristics, wherein each relationship comprises a magnitude and direction;

calculate a fifth set of relationships between the groups and the metric based on one or more of the third set of relationships and one or more of the fourth set of relationships, wherein each relationship comprises a magnitude and direction;

receive a plurality of sub-metrics;

calculate a ninth set of relationships between the groups and the sub-metrics, wherein each relationship comprises a magnitude and direction;

calculate a tenth set of relationships between the sub-metrics and the metrics, wherein each relationship comprises a magnitude and direction;

calculate a set of metric sub-scores, based on one or more of the fifth set of relationships and one or more of the tenth set of relationships;

dynamically calculate an overall metric score based on one or more of the set of metric sub-scores;

represent the overall metric score with a single descriptor; and

output the descriptor.

25. The server of claim 19, wherein;

the data items comprise both qualitative and structured information and quantitative and unstructured information;

the relationship module is further operative to;

calculate a fourth set of relationships between the groups and the characteristics, wherein each relationship comprises a magnitude and direction;

calculate a fifth set of relationships between the groups and the metric, based on one or more of the third set of relationships and one or more of the fourth set of relationships, wherein each relationship comprises a magnitude and direction;

calculate a sixth set of relationships between the individuals identified by the plurality of descriptors and the characteristics, based on one or more of the first set of relationships and one or more of the second set of relationships, wherein each relationship comprises a magnitude and direction;

calculate a seventh set of relationships between specific ones of the individuals identified by the plurality of descriptors and the groups, based on one or more of the fourth set of relationships and one or more of the sixth set of relationships, wherein each relationship comprises a magnitude and direction;

receive a plurality of sub-metrics;

calculate a ninth set of relationships between the groups and the sub-metrics, wherein each relationship comprises a magnitude and direction;

calculate a tenth set of relationships between the sub-metrics and the metrics, wherein each relationship comprises a magnitude and direction;

calculate a set of metric sub-scores, based on one or more of the fifth set of relationships and one or more of the tenth set of relationships;

dynamically calculate a metric score, based on one or more of the set of metric sub-scores;

represent the metric score with a single descriptor; and

output the descriptor; and

the pattern recognition module is further operative to identify new characteristics based on;

the groups;

one or more of the fourth relationships between the groups and the characteristics; and

one or more of the second relationships between existing characteristics and the data items.

26. The server of claim 25, wherein members of the first through tenth sets of relationships comprise a direction that may be positive, neutral, or negative.