SYSTEMS AND METHODS FOR PREDICTIVE MODELS USING GEOGRAPHIC TEXT SEARCH

• US 20080140348A1
• Filed: 10/31/2007
• Published: 06/12/2008
• Est. Priority Date: 10/31/2006
• Status: Abandoned Application

• Current Assignee: Nokia Corporation
• Original Assignee: Metacarta, Inc.
• Inventors: FRANK, John R.
• Application Number:
  US11/932,438
• Publication Number:
  US 20080140348A1
• Time in Patent Office: Days
• US Class Current: 702/181
• CPC Class Codes: G06F 16/30 of unstructured textual data document management systems G06F16/93
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/10 Office automation; Time management

Abstract

Under one aspect, a computer-implemented method of generating a predictive model includes accepting search criteria from a user, the search criteria including information identifying a past event, a domain identifier identifying a domain in which the past event occurred, and a time identifier identifying a time period preceding the past event; obtaining a plurality of sets of document-location-time tuples based on the domain identifier and the time identifier; statistically analyzing the sets of document-location-time tuples; comparing results of the statistical analysis of the sets of document-location-time tuples to identify information that precedes and statistically correlates with the past event; and displaying information associated with the identified information on a display device.

Claims

1. A computer-implemented method of generating a predictive model, the method comprising:

accepting search criteria from a user, the search criteria including information identifying a past event, a domain identifier identifying a domain in which the past event occurred, and a time identifier identifying a time period preceding the past event;

obtaining a plurality of sets of document-location-time tuples based on the domain identifier and the time identifier;

statistically analyzing the sets of document-location-time tuples;

comparing results of the statistical analysis of the sets of document-location-time tuples to identify information that precedes and statistically correlates with the past event; and

displaying information associated with the identified information on a display device.

2. The method of claim 1, further comprising labeling the identified information according to an event type, and storing the labeled identified information on a computer-readable medium.

3. The method of claim 1, wherein obtaining the plurality of sets of document-location-time tuples comprises obtaining a first set of tuples that includes information about the domain, and obtaining a second set of tuples that includes information about a region that excludes the domain.

4. The method of claim 1, wherein obtaining a plurality of sets of document-location-time tuples comprises obtaining a first set of tuples that includes information about a time period preceding the past event, and obtaining a second set of tuples that includes information about a time period that excludes the time period preceding the past event.

5. The method of claim 1, further comprising automatically refining the identified information based on at least some document-location-time tuples in response to user input.

6. The method of claim 5, wherein said refining comprises at least one of accepting user input scoring at least some of the document-location-time tuples and entering a feedback loop;

accepting user input truthing at least some of the document-location-time tuples and entering a feedback loop;

using blind relevance feedback in response to a user instruction; and

accepting user input modifying the identified information.

7. The method of claim 1, wherein the information associated with the identified information comprises a model of an event of the same type as the past event.

8. The method of claim 1, wherein the information associated with the identified information comprises an abstraction of the identified information.

9. The method of claim 1, wherein the identified information comprises at least one of a statistically interesting phrase and statistically interesting information.

10. An interface program stored on a computer-readable medium for causing a computer system with a display device to perform the functions of:

accepting search criteria from a user, the search criteria including information identifying a past event, a domain identifier identifying a domain in which the past event occurred, and a time identifier identifying a time period preceding the past event;

obtaining a plurality of sets of document-location-time tuples based on the domain identifier and the time identifier;

statistically analyzing the sets of document-location-time tuples;

comparing results of the statistical analysis of the sets of document-location-time tuples to identify information that precedes and statistically correlates with the past event; and

displaying information associated with the identified information on a display device.

11. The interface program of claim 10, wherein the program further causes the computer system to perform the functions of labeling the identified information according to an event type, and storing the labeled identified information on a computer-readable medium.

12. The interface program of claim 10, wherein obtaining the plurality of sets of document-location-time tuples comprises obtaining a first set of tuples that includes information about the domain, and obtaining a second set of tuples that includes information about a region that excludes the domain.

13. The interface program of claim 10, wherein obtaining a plurality of sets of document-location-time tuples comprises obtaining a first set of tuples that includes information about a time period preceding the past event, and obtaining a second set of tuples that includes information about a time period that excludes the time period preceding the past event.

14. The interface program of claim 10, wherein the program further causes the computer system to perform the functions of automatically refining the identified information based on at least some document-location-time tuples in response to user input.

15. The interface program of claim 10, wherein said refining comprises at least one of accepting user input scoring at least some of the document-location-time tuples and entering a feedback loop;

accepting user input truthing at least some of the document-location-time tuples and entering a feedback loop;

using blind relevance feedback in response to a user instruction; and

accepting user input modifying the identified information.

16. The interface program of claim 10, wherein the information associated with the identified information comprises a model of an event of the same type as the past event.

17. The interface program of claim 10, wherein the information associated with the identified information comprises an abstraction of the identified information.

18. The interface program of claim 10, wherein the identified information comprises at least one of a statistically interesting phrase and statistically interesting information.

19. A computer-implemented method of using a model to predict an event, the method comprising:

accepting search criteria from a user, the search criteria including information identifying a type of event the user would like to predict, a domain identifier identifying a domain, and a time identifier identifying a time period;

obtaining a model based on the type of event the user would like to predict, the model including information that was previously identified as being predictive of the type of event;

obtaining a set of document-location-time tuples based on the domain identifier and the time identifier, each of the document-location-time tuples including at least some of the information that was previously identified as being predictive of the type of event;

based on the set of document-location-time tuples, estimating a probability that the type of event will occur in the domain; and

if the estimate of the probability exceeds a predefined threshold, alerting the user.

20. The method of claim 19, wherein alerting the user comprises at least one of displaying information about the estimated probability of the event to the user;

emailing a notification to the user;

displaying a visual representation of the domain identified by the domain identifier; and

displaying at least one of the document-location-time-tuples to the user.

21. The method of claim 19, further comprising providing an interface allowing a user to request additional information related to the estimate of the probability.

22. The method of claim 21, wherein the request for additional information includes a free text query string, and wherein the method further comprises displaying to the user a visual representation of locations identified in document-location-time tuples responsive to the free text query.

23. The method of claim 21, wherein the request for additional information includes a spatial domain identifier identifying a domain, and wherein the method further comprises displaying to the user a visual representation of the identified domain and a listing of documents containing spatial identifiers that identify locations within the domain.

24. The method of claim 19, further comprising providing an interface for the user to modify the model.

25. The method of claim 24, wherein the interface allows the user to provide a set of training document-location-time tuples that include information about the type of event.

26. An interface program stored on a computer-readable medium for causing a computer system with a display device to perform the functions of:

accepting search criteria from a user, the search criteria including information identifying a type of event the user would like to predict, a domain identifier identifying a domain, and a time identifier identifying a time period;

obtaining a model based on the type of event the user would like to predict, the model including information that was previously identified as being predictive of the type of event;

obtaining a set of document-location-time tuples based on the domain identifier and the time identifier, each of the document-location-time tuples including at least some of the information that was previously identified as being predictive of the type of event;

based on the set of document-location-time tuples, estimating a probability that the type of event will occur in the domain; and

if the estimate of the probability exceeds a predefined threshold, alerting the user on a display device.

27. The interface program of claim 26, wherein alerting the user comprises at least one of displaying information about the estimated probability of the event to the user on the display device;

emailing a notification to the user;

displaying a visual representation of the domain identified by the domain identifier on the display device; and

displaying at least one of the document-location-time-tuples to the user on the display device.

28. The interface program of claim 26, wherein the program further causes the computer system to perform the functions of providing an interface allowing a user to request additional information related to the estimate of the probability.

29. The interface program of claim 28, wherein the request for additional information includes a free text query string, and wherein the program further causes the computer system to perform the functions of displaying to the user a visual representation of locations identified in document-location-time tuples responsive to the free text query.

30. The interface program of claim 28, wherein the request for additional information includes a spatial domain identifier identifying a domain, and wherein the program further causes the computer system to perform the functions of displaying to the user a visual representation of the identified domain and a listing of documents containing spatial identifiers that identify locations within the domain.

31. The interface program of claim 26, wherein the program further causes the computer system to perform the functions of providing an interface for the user to modify the model.

32. The interface program of claim 31, wherein the interface allows the user to provide a set of training document-location-time tuples that include information about the type of event.