Processing transactions using a semantic network

• US 20050010428A1
• Filed: 09/05/2003
• Published: 01/13/2005
• Est. Priority Date: 07/27/2000
• Status: Abandoned Application

• Current Assignee: HealthEdge, Inc.
• Original Assignee: HealthEdge, Inc.
• Inventors: Sprecher, Benjamin, Jhaveri, Kunjan, Morris, John, Easton, Chris, Kennedy, James, Trustman, John, Krylov, Eugene, Yoshida, Andre, Bergeron, Heather Ellen, Pringle, Simone Lemos
• Application Number:
  US10/656,933
• Publication Number:
  US 20050010428A1
• Time in Patent Office: Days
• US Class Current: 705/7
• CPC Class Codes: G06F 40/30 Semantic analysis
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 30/0601 Electronic shopping [e-shopping]

Abstract

The disclosed technology can identify indicia associated with different entity types that interact within an industry, identify one or more relationships (e.g., contractual provisions) that can affect interactions between such entity types, and identify transactions associated with one or more of the interactions. Further, the identified transactions can be organized into one or more transaction sequences. The identified indicia, the one or more identified relationships, and the one or more transaction sequences can then be associated to form a semantic network. An instance of the semantic network can be formed in response to the execution of at least some of the transaction sequence and can serve, at least in part, as the basis for processing requests associated with the entities. The requests can correspond to interactions associated with the entities and may be represented in a natural language format, exhibiting a fixed context and a fixed grammar.

Claims

1. A method, comprising:

receiving a request associated with a plurality of entities;

identifying a sequence of transactions associated with the request;

executing at least some of the transaction sequence to form an instance of a semantic network, the semantic network instance including at least one relationship between the plurality of entities; and

processing the request based, at least in part, on the semantic network.

2. The method of claim 1, wherein the plurality of entities correspond to at least two different entity types interacting in an industry.

3. The method of claim 2, wherein the industry is a service-based industry and the at least two different entity types correspond to at least two of a service provider, a service implementer, a service purchaser, a service beneficiary, a service maintainer, and a service regulator.

4. The method of claim 2, wherein the industry relates to a health care industry and the at least two different entity types correspond to at least two of a health care subscriber, a health care provider, a health care practitioner, a health care beneficiary, and a health care company.

5. The method of claim 2, wherein the industry is a product-based industry and the at least two different entity types correspond to at least two of a product manufacturer, a product distributor, a product reseller, a product marketer, a product seller, a product purchaser, a product maintainer, and a product regulator.

6. The method of claim 1, further comprising:

storing indicia associated with the request in a data structure; and

assigning a version number to the data structure.

7. The method of claim 6, further comprising:

based, at least in part, on the version number of the data structure, re-executing at least some of the transaction sequence to reprocess the request.

8. The method of claim 1, wherein the request is received from an electronic data interchange system.

9. The method of claim 1, wherein the request is received from at least one of an application program interface, a user interface, and a software editing tool.

10. The method of claim 1, further comprising:

representing the request in a natural language format exhibiting a fixed context and a fixed grammar.

11. The method of claim 10, wherein the fixed grammar exhibits a Backus-Naur format.

12. The method of claim 10, wherein the fixed context is based, at least in part, on an industry-specific data structure, the industry-specific data structure being used to identify operations associated with the transaction sequence.

13. The method of claim 10, further comprising:

parsing the natural language representation of the request into a plurality of fields; and

mapping at least some of the fields into at least one data structure.

14. The method of claim 13, further comprising:

assigning a version number to the at least one data structure.

15. The method of claim 1, wherein the at least one relationship corresponds to at least one contractual provision associated with the plurality of entities.

16. The method of claim 1, wherein the request corresponds to at least one of a request for payment of services performed, a request to authorize proposed services, a request to enroll a service provider, a request to enroll a service purchaser, a request to enroll a service beneficiary, and an adoption of a new contract.

17. The method of claim 1, further comprising:

forming an electronic message in response to detecting an error during the execution of the transaction sequence.

18. The method of claim 1, wherein indicia associated with the plurality of entities correspond to a plurality of nodes in the semantic network and the at least one relationship corresponds to at least one link interconnecting at least some of the plurality of nodes in the semantic network.

19. The method of claim 1, further comprising:

querying data structures associated with the semantic network; and

in response to the query, forming an electronic document containing indicia associated with the plurality of entities and the at least one relationship, wherein the electronic document is viewable in a natural language format exhibiting a fixed context and a fixed grammar.