Extracting and leveraging knowledge from unstructured data

• US 9,858,332 B1
• Filed: 01/26/2016
• Issued: 01/02/2018
• Est. Priority Date: 11/02/2011
• Status: Active Grant

• Current Assignee: SRI International, Inc.
• Original Assignee: SRI International, Inc.
• Inventors: Donneau-Golencer, Thierry, Nitz, Kenneth C.
• Primary Examiner(s): CHEEMA, AZAM M
• Application Number:
  US15/006,946
• Time in Patent Office: 707 Days
• CPC Class Codes: G06F 16/22 Indexing; Data structures therefor; Storage structures
• CPC Class Codes: G06F 16/245 Query processing
• CPC Class Codes: G06F 16/285 Clustering or classification
• CPC Class Codes: G06F 16/337 Profile generation, learning or modification
• CPC Class Codes: G06F 40/30 Semantic analysis

Abstract

A system may include a machine-implemented data extractor and correlator configured to retrieve data from at least one data source. The data extractor and correlator may extract information from unstructured data within the retrieved data and correlate the extracted information with previously stored structured data to generate additional structured data. The system may also include a storage device configured to store the previously stored structured data and the additional structured data.

Claims

1. A computer-implemented method comprising:

determining, by a feedback module of a computing device, that unstructured data associated with a public data source on a network has been changed, wherein the change was broadcast using the public data source, and wherein the computing device is on the network;

extracting information from the unstructured data, wherein the extracted information is associated with the change, wherein extracting includes breaking the unstructured data into one or more parts, wherein the one or more parts include a type of information associated with a feature, and wherein the type of information is in close proximity to the feature;

determining that the extracted information is related to user profiles, wherein a user profile is associated with a use of the network, wherein determining includes correlating the type of information associated with the feature to structured data associated with the user profiles;

generating, by a user profile module of the computing device, new structured data using the type of information associated with the feature; and

modifying the user profiles, wherein modifying includes using the new structured data, and wherein modifying a user profile modifies a use of the network associated with the user profile.

2. The computer-implemented method of claim 1, wherein a user profile directs an application on the network to proactively provide information associated with the application.

3. The computer-implemented method of claim 1, wherein the user profile directs an application on the network to proactively provide information stored in a knowledge store.

4. The computer-implemented method of claim 1, further comprising:

detecting an update of information in a user application; and

modifying the user profiles to include the updated information.

5. The computer-implemented method of claim 1, further comprising:

generating a new user profile, wherein the new user profile is generated using previously stored structured data.

6. The computer-implemented method of claim 1, further comprising:

tagging the feature, wherein the tag is used to correlate the type of information associated with the feature to the structured data associated with the user profiles.

7. The computer-implemented method of claim 1, further comprising:

determining a pattern associated with previously stored structured data; and

using the pattern to identify a similar pattern in the unstructured data.

8. The computer-implemented method of claim 1, wherein the type of information includes a word, a phrase, a trend, an attribute, a statistic, a reference, a network identifier, an account identifier, a time, metadata, or an access list.

9. A computing device, comprising:

one or more processors; and

a non-transitory computer-readable medium including instructions that, when executed by the one or more processors, cause the one or more processors to perform operations including;

determining, by a feedback module of the computing device, that unstructured data associated with a public data source on a network has been changed, wherein the change was broadcast using the public data source, and wherein the computing device is on the network;

extracting information from the unstructured data, wherein the extracted information is associated with the change, wherein extracting includes breaking the unstructured data into one or more parts, wherein the one or more parts include a word associated with a feature, and wherein the word is in close proximity to the feature;

determining that the extracted information is related to user profiles, wherein a user profile is associated with a use of the network, wherein determining includes correlating the word associated with the feature to structured data associated with the user profiles;

generating, by a user profile module of the computing device, new structured data using the word associated with the feature; and

modifying the user profiles, wherein modifying includes using the new structured data, and wherein modifying a user profile modifies a use of the network associated with the user profile.

10. The computing device of claim 9, wherein a user profile directs an application on the network to proactively provide information associated with the application.

11. The computing device of claim 9, wherein the user profile directs an application on the network to proactively provide information stored in a knowledge store.

12. The computing device of claim 9, wherein the non-transitory computer-readable medium further includes instructions that, when executed by the one or more processors, cause the one or more processors to perform operations including:

detecting an update of information in a user application; and

modifying the user profiles to include the updated information.

13. The computing device of claim 9, wherein the non-transitory computer-readable medium further includes instructions that, when executed by the one or more processors, cause the one or more processors to perform operations including:

generating a new user profile, wherein the new user profile is generated using previously stored structured data.

14. The computing device of claim 9, wherein the non-transitory computer-readable medium further includes instructions that, when executed by the one or more processors, cause the one or more processors to perform operations including:

tagging the feature, wherein the tag is used to correlate the word associated with the feature to the structured data associated with the user profiles.

15. The computing device of claim 9, wherein the non-transitory computer-readable medium further includes instructions that, when executed by the one or more processors, cause the one or more processors to perform operations including:

determining a pattern associated with previously stored structured data; and

using the pattern to identify a similar pattern in the unstructured data.

16. The computing device of claim 9, wherein the type of information includes a word, a phrase, a trend, an attribute, a statistic, a reference, a network identifier, an account identifier, a time, metadata, or an access list.

17. A computer-program product tangibly embodied in a non-transitory machine-readable storage medium, including instructions that, when executed by one or more processors, cause the one or more processors to:

determine, by a feedback module of a computing device, that unstructured data associated with a public data source on a network has been changed, wherein the change was broadcast using the public data source, and wherein the computing device is on the network;

extract information from the unstructured data, wherein the extracted information is associated with the change, wherein extracting includes breaking the unstructured data into one or more parts, wherein the one or more parts include a word associated with a feature, and wherein the word is in close proximity to the feature;

determine that the extracted information is related to user profiles, wherein a user profile is associated with a use of the network, wherein determining includes correlating the word associated with the feature to structured data associated with the user profiles;

generate, by a user profile module of the computing device, new structured data using the word associated with the feature; and

modify the user profiles, wherein modifying includes using the new structured data, and wherein modifying a user profile modifies a use of the network associated with the user profile.

18. The computer-program product of claim 17, wherein a user profile directs an application on the network to proactively provide information associated with the application.

19. The computer-program product of claim 17, wherein the user profile directs an application on the network to proactively provide information stored in a knowledge store.

20. The computer-program product of claim 17, further comprising instructions that, when executed by the one or more processors, cause the one or more processors to:

detect an update of information in a user application; and

modify the user profiles to include the updated information.

21. The computer-program product of claim 17, further comprising instructions that, when executed by the one or more processors, cause the one or more processors to:

generate a new user profile, wherein the new user profile is generated using previously stored structured data.

22. The computer-program product of claim 17, further comprising instructions that, when executed by the one or more processors, cause the one or more processors to:

tag the feature, wherein the tag is used to correlate the word associated with the feature to the structured data associated with the user profiles.

23. The computer-program product of claim 17, further comprising instructions that, when executed by the one or more processors, cause the one or more processors to:

determine a pattern associated with previously stored structured data; and

use the pattern to identify a similar pattern in the unstructured data.

24. The computer-program product of claim 17, wherein the type of information includes a word, a phrase, a trend, an attribute, a statistic, a reference, a network identifier, an account identifier, a time, metadata, or an access list.