SYSTEM AND METHOD FOR ECONOMICAL REPRESENTATION OF PRODUCTS USING INTELLIGENCE CLUSTERING

• US 20080275727A1
• Filed: 12/14/2007
• Published: 11/06/2008
• Est. Priority Date: 05/01/2007
• Status: Abandoned Application

• Current Assignee: Evincii, Inc.
• Original Assignee: Evincii, Inc.
• Inventors: Lai, Peter, Koo, Charles C., Wu, Dennis
• Application Number:
  US11/957,400
• Publication Number:
  US 20080275727A1
• Time in Patent Office: Days
• US Class Current: 705/2
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G16H 20/00 ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance

Abstract

A system includes a recommendation engine, product database and interface. The recommendation engine determines one or more recommended product clusters from the product database based on a request for a healthcare product recommendation based on a symptom. The interface, which is communicatively coupled to the engine, displays the one or more recommended product clusters. The product clusters are organized based on at least one common attribute, such as active ingredient.

Claims

1. A method, comprising:

receiving a request for a healthcare product recommendation based on a symptom;

determining one or more recommended product clusters based on the request; and

displaying the one or more recommended product clusters.

2. The method of claim 1, wherein each product cluster includes at least one common attribute.

3. The method of claim 2, wherein the at least one common attribute includes active ingredient and intended use.

4. The method of claim 3, wherein the at least one common attribute further includes brand, active ingredient dosage, and intended age group.

5. The method of claim 1, wherein the determining uses an ontological method based on the request.

6. The method of claim 1, further comprising:

receiving a user selection of the one or more clusters; and

displaying products in the selected cluster.

7. The method of claim 1, further comprising:

receiving a selection of one of the product clusters; and

displaying sub-clusters of the selected product cluster.

8. The method of claim 7, wherein the sub-clusters are based on product size.

9. A system, comprising:

means for receiving a request for a healthcare product recommendation based on a symptom;

means for determining one or more recommended product clusters based on the request; and

means for displaying the one or more recommended product clusters.

10. A computer-readable medium having stored thereon instructions to cause a computer to execute a method, the method comprising:

receiving a request for a healthcare product recommendation based on a symptom;

determining one or more recommended product clusters based on the request; and

displaying the one or more recommended product clusters.

11. A system, comprising:

a recommendation engine, for determining one or more recommended product clusters from a product database based on a request for a healthcare product recommendation based on a symptom; and

an interface, communicatively coupled to the engine, for displaying the one or more recommended product clusters.

12. The system of claim 11, wherein each product cluster includes at least one common attribute.

13. The system of claim 12, wherein the at least one common attribute includes active ingredient and intended use.

14. The system of claim 13, wherein the at least one common attribute further includes brand, active ingredient dosage, and intended age group.

15. The system of claim 11, wherein the recommendation engine uses an ontological method based on the request.

16. The system of claim 11, wherein the interface further receives a user selection of the one or more clusters;

and displays products in the selected cluster.

17. The system of claim 11, wherein the interface receives a selection of one of the product clusters;

and displays sub-clusters of the selected product cluster.

18. The system of claim 17, wherein the sub-clusters are based on product size.