Data Disambiguation Systems and Methods

• US 20080005158A1
• Filed: 09/04/2007
• Published: 01/03/2008
• Est. Priority Date: 05/04/2004
• Status: Abandoned Application

• Current Assignee: Mark Zartler, Robert Hust
• Original Assignee: Mark Zartler, Robert Hust
• Inventors: Hust, Robert, Zartler, Mark
• Application Number:
  US11/849,876
• Publication Number:
  US 20080005158A1
• Time in Patent Office: Days
• US Class Current: 707/102
• CPC Class Codes: G06F 16/3329 Natural language query formulation or dialogue systems
• CPC Class Codes: G06F 16/3344 using natural language analysis
• CPC Class Codes: G06F 40/284 Lexical analysis, e.g. tokenisation or collocates
• CPC Class Codes: Y10S 707/99943 Generating database or data structure, e.g. via user interface
• CPC Class Codes: Y10S 707/99944 Object-oriented database structure

Abstract

Various embodiments provide a state-based, regular expression parser in which data, such as generally unstructured text, is received into the system and undergoes a tokenization process which permits structure to be imparted to the data. Tokenization of the data effectively enables various patterns in the data to be identified. In some embodiments, one or more components can utilize stimulus/response paradigms to recognize and react to patterns in the data.

Claims

1. A system comprising:

one or more computer-readable media;

a dynamic agent server embodied on the one or more computer-readable media and configured to manage deployable agents;

one or more deployable agents embodied on the one or more computer-readable media and configured to be deployed by the dynamic agent server;

one or more knowledge base objects embodied on the one or more computer-readable media and associated with and useable by the one or more deployable agents, the knowledge base objects being associated with one or more files that define cases of text that can be matched by a functional presence engine configured as a probabilistic parser, to text obtained from one or more data origination entities, the one or more files being defined in a hierarchical tag-based language.

2. The system of claim 1, wherein the hierarchical tag-based language comprises an extensible markup language.

3. The system of claim 1, wherein an agent comprises a data source that provides a pipeline through which data travels and a runtime object that is configured to receive and process data in the form of text that travels through the pipeline.

4. The system of claim 1, wherein an agent comprises a data source that provides a pipeline through which data travels and a runtime object that is configured to receive and process data in the form of text that travels through the pipeline, and wherein the system comprises a plurality of agents, and wherein data sources can comprise different types of data sources.

5. The system of claim 4, wherein at least one data source comprises an IRC data source.

6. The system of claim 4, wherein at least one data source comprises a TCP/IP data source.

7. The system of claim 4, wherein at least one data source comprises a POP 3 data source.

8. The system of claim 1, wherein said one or more deployable agents comprises agents of a first type and agents of a second different type.

9. The system of claim 1, wherein said one or more deployable agents comprises agents of a first type and agents of a second different type, wherein a first type of agent is a passive agent that listens to one or more data origination entities.

10. The system of claim 1, wherein said one or more deployable agents comprises agents of a first type and agents of a second different type, wherein a first type of agent is a passive agent that listens to one or more data origination entities, and wherein a second type of agent is an active agent that is configured to interact with a data origination entity.

11. A method comprising:

providing a dynamic agent server configured to manage deployable agents;

deploying one or more deployable agents that are configured to receive data;

with the one or more deployable agents, using one or more knowledge base objects to process the data using a functional presence engine configured as a probabilistic parser, the knowledge base objects being associated with one or more files that define cases of text that can be matched to text obtained from one or more data origination entities, the one or more files being defined in a hierarchical tag-based language.

12. The method of claim 11, wherein the hierarchical tag-based language comprises an extensible markup language.

13. The method of claim 11, wherein an agent comprises a data source that provides a pipeline through which data travels and a runtime object that is configured to receive and process data in the form of text that travels through the pipeline.

14. The method of claim 11, wherein an agent comprises a data source that provides a pipeline through which data travels and a runtime object that is configured to receive and process data in the form of text that travels through the pipeline, and wherein the system comprises a plurality of agents, and wherein data sources can comprise different types of data sources.

15. The method of claim 11, wherein said one or more deployable agents comprises agents of a first type and agents of a second different type.

16. The method of claim 11, wherein said one or more deployable agents comprises agents of a first type and agents of a second different type, and wherein a first type of agent is a passive agent that listens to one or more data origination entities.

17. The method of claim 11, wherein said one or more deployable agents comprises agents of a first type and agents of a second different type, and wherein a first type of agent is a passive agent that listens to one or more data origination entities, and wherein a second type of agent is an active agent that is configured to interact with a data origination entity.