DYNAMIC GENERATION OF PRODUCTS FOR ONLINE RECOMMENDATION

• US 20110307294A1
• Filed: 06/10/2010
• Published: 12/15/2011
• Est. Priority Date: 06/10/2010
• Status: Abandoned Application

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Barkai, Gilad, Har'El, Nadav, Roitman, Haggai, Shmueli-Scheuer, Michal
• Application Number:
  US12/797,621
• Publication Number:
  US 20110307294A1
• Time in Patent Office: Days
• US Class Current: 705/7.29
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 30/0282 Rating or review of business operators or products
• CPC Class Codes: G06Q 30/0621 Item configuration or customization
• CPC Class Codes: G06Q 30/0631 Item recommendations
• CPC Class Codes: G06Q 30/0641 Shopping interfaces

Abstract

A method, system, and computer program product for dynamic generation of products for online recommendation. The method includes receiving a signal and processing the signal to extract one to many features and locating baseline products and embeddable items relating to the features a baseline product is dynamically matched with one or more embeddable items to generate a combined product and a representation of the combined product is provided as an online recommendation for a product;

Claims

1. A method for dynamic generation of products for online recommendation, comprising:

receiving a signal and processing the signal to extract one to many features;

locating baseline products and embeddable items relating to the features;

dynamically matching a baseline product with one or more embeddable items to generate a combined product;

providing a representation of the combined product as an online recommendation for a product;

wherein said steps are implemented in either;

computer hardware configured to perform said identifying, tracing, and providing steps, or

computer software embodied in a non-transitory, tangible, computer-readable storage medium.

2. The method as claimed in claim 1, including ranking the generated combined product representations based on the signal, the baseline products, the embeddable items, and the deployment of the embeddable items in the products.

3. The method as claimed in claim 1, including receiving a user or segment of users profile and customizing the product generation based on the profile.

4. The method as claimed in claim 1, including suggesting feature enhancements to the combined product based on features available for the baseline products.

5. The method as claimed in claim 1, including evaluating a price for the combined product based on the baseline product cost, enhanced features cost, production cost and shipment cost.

6. The method as claimed in claim 1, wherein the signal is an external signal generated online including one of the group of:

an emerging trend, a social media buzz, an external event including quotes, a microblogging trend, social media, and popular advertisement.

7. The method as claimed in claim 1, wherein the signal is input by a user including one of the group of:

search keywords, browsing history, user'"'"'s profile, user bookmarks, comments, blog postings.

8. The method as claimed in claim 1, wherein an embeddable item includes royalty-free content.

9. The method as claimed in claim 1, including independently ranking located baseline products and ranking embeddable items.

10. The method as claimed in claim 1, wherein the combined products do not pre-exist.

11. The method as claimed in claim 1, including mapping a baseline product of a combined product to suppliers of the product.

12. A computer program product for dynamic generation of products for online recommendation, the computer program product comprising:

a computer readable storage medium having computer readable program code embodied therewith, the computer readable program code comprising;

computer readable program code configured to;

receive a signal and processing the signal to extract one to many features;

locate baseline products and embeddable items relating to the features;

dynamically match a baseline product with one or more embeddable items to generate a combined product; and

provide a representation of the combined product as an online recommendation for a product.

13. A system for dynamic generation of products for online recommendation, comprising:

a processor;

an incoming signal processing component for receiving a signal and processing the signal to extract one to many features;

a retrieving component for locating and retrieving baseline products and embeddable items relating to the features;

a matching component for dynamically matching a baseline product with one or more embeddable items to generate a combined product; and

a recommendation output component for providing a representation of the combined product as an online recommendation for a product.

14. The system as claimed in claim 13, wherein the retrieving component retrieves baseline products from multiple sources mapped to suppliers of the baseline products.

15. The system as claimed in claim 13, wherein the retrieving component retrieves embeddable items from multiple third party sources wherein the embeddable items include royalty-free content.

16. The system as claimed in claim 13, including a ranking component for ranking the generated combined product representations based on the signal, the baseline products, the embeddable items, and the deployment of the embeddable items in the products.

17. The system as claimed in claim 13, including a profile determining component for determining a user or segment of users profile and a personalization component for personalizing the combined product based on the user or segment of users profile.

18. The system as claimed in claim 13, including a feature enhancement component for adding feature enhancements to the combined product based on features available for the baseline products.

19. The system as claimed in claim 13, including a price evaluation component for evaluating a price for the combined product based on the baseline product cost, enhanced features cost, production cost and shipment cost.

20. The system as claimed in claim 13, wherein the signal is an external signal generated online including one of the group of:

an emerging trend, a social media buzz, an external event including quotes, a microblogging trend, social media, and popular advertisement.

21. The system as claimed in claim 13, wherein the signal is input by a user including one of the group of:

search keywords, browsing history, user'"'"'s profile, user bookmarks, comments, blog postings.

22. The system as claimed in claim 13, wherein the combined products do not pre-exist in the system.

23. The system as claimed in claim 13, including a supplier component ordering a combined product from a supplier.

24. A method for providing a service to a customer over a network for dynamic generation of products for online recommendation, comprising:

receiving a signal and processing the signal to extract one to many features;

locating baseline products and embeddable items relating to the feature;

dynamically matching a baseline product with one or more embeddable items to generate a combined product;

providing a representation of the combined product as an online recommendation for a product;

wherein said steps are implemented in either;

computer hardware configured to perform said identifying, tracing, and providing steps, or

computer software embodied in a non-transitory, tangible, computer-readable storage medium.