Extracting and leveraging knowledge from unstructured data

• US 9,245,010 B1
• Filed: 11/02/2011
• Issued: 01/26/2016
• 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
• Application Number:
  US13/287,985
• Time in Patent Office: 1,546 Days
• US Class Current: 1/1
• 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 system, comprising:

a processor configured to operate a machine-implemented data extractor and correlator configured to retrieve public data from at least one of a plurality of public data sources, extract information from unstructured data within the retrieved public data, and correlate the information extracted from the unstructured data with previously stored structured data to generate additional structured data by building at least one semantic relationship between the extracted information and the previously stored structured data based at least in part on semantic information, the data extractor and correlator comprising a semantic analysis module configured to determine the semantic information based on the unstructured data, wherein the data extractor and correlator is further configured to extract information from the unstructured data by performing;

breaking at least one sentence into subject, verb, and object;

extracting phrases that link a subject to an object;

extracting at least one word in close proximity to an identified feature; and

extracting at least one word in close proximity to a known quality; and

a storage device configured to store the previously stored structured data and the additional structured data.

2. The system of claim 1, wherein the plurality of public data sources comprises at least two of a group comprising:

a website, a blog entry, a shared folder, a shared directory, and a shared file.

3. The system of claim 1, wherein the retrieved public data comprises supplemental structured data.

4. The system of claim 3, wherein the data extractor and correlator is further configured to correlate the supplemental structured data with one or both of the previously stored structured data and the additional structured data to generate further structured data.

5. The system of claim 1, wherein the data extractor and correlator is further configured to correlate the semantic information with one or both of the previously stored structured data and the additional structured data to generate further structured data.

6. The system of claim 1, wherein the processor is further configured to operate a machine-implemented user profile module configured to update a user profile based at least in part on one or both of the previously stored structured data and the additional structured data.

7. The system of claim 6, wherein the user profile module is further configured to generate a new user profile based at least in part on one or both of the previously stored structured data and the additional structured data.

8. The system of claim 6, further comprising at least one user application configured to provide user interaction based at least in part on the user profile.

9. The system of claim 8, wherein the feedback module is further configured to update the user profile responsive to the public data retrieved from the at least one of the plurality of public data sources.

10. The system of claim 6, wherein the processor is further configured to operate a feedback module configured to update the user profile responsive to one or both of the previously stored structured data and the additional structured data.

11. The system of claim 1, wherein the processor is further configured to operate a machine-implemented document harvester configured to retrieve a document from at least one of the plurality of public data sources.

12. The system of claim 11, wherein the processor is further configured to operate a machine-implemented document indexer configured to index a plurality of documents harvested by the document harvester.

13. The system of claim 1, wherein the data extractor and correlator is further configured to build the at least one relationship between the extracted information and the previously stored structured data by tagging a feature identified in the extracted information.

14. A machine-implemented method, comprising:

a device retrieving public data from at least one of a plurality of public data sources;

a processor extracting information from unstructured data within the retrieved public data by performing;

breaking at least one sentence into subject, verb, and object;

extracting phrases that link a subject to an object;

extracting at least one word in close proximity to an identified feature; and

extracting at least one word in close proximity to a known quality;

the processor determining semantic information based on the unstructured data and correlating the information extracted from the unstructured data with previously stored structured data to generate additional structured data by building at least one semantic relationship between the information extracted and the previously stored structured data based at least in part on the semantic information; and

a storage device storing the previously stored structured data and the additional structured data.

15. The machine-implemented method of claim 14, further comprising:

generating a user profile based at least in part on one or both of the previously stored structured data and the additional structured data.

16. The machine-implemented method of claim 14, further comprising:

updating a previously generated user profile based at least in part on one or both of the previously stored structured data and the additional structured data.