System for automating purchase recommendations

• US 20040230440A1
• Filed: 06/20/2003
• Published: 11/18/2004
• Est. Priority Date: 06/21/2002
• Status: Abandoned Application

• Current Assignee: Anil Malhotra
• Original Assignee: Anil Malhotra
• Inventors: Malhotra, Anil
• Application Number:
  US10/600,283
• Publication Number:
  US 20040230440A1
• Time in Patent Office: Days
• US Class Current: 705/1
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0282 Rating or review of business operators or products
• CPC Class Codes: G06Q 30/0601 Electronic shopping [e-shopping]

Abstract

A purchase recommendation system for selected items by a user via a human speech platform. The human speech platform is in communication with the user via any type of communication media. Further, the human speech platform is in communication with a computer system having stored thereon at least one program to receive, translate and select a recommendation for the purchase of an item based on a correlation of predetermined attributes of selected items for purchase and selected attributes derived from the user at the incident of purchase. The user, after receiving the recommendation for the purchase of an item may, if desired, accept or reject the recommendation. If the user accepts the recommendation, the transaction is complete. If the user rejects the recommendation, the user may, if desired, receive a subsequent recommendation for the purchase of an item via a selected program from the computer system.

Claims

1. ) A purchase recommendation method for items by a user, comprising the steps of:

a) providing predetermined selections of items for purchase;

b) correlating said predetermined selections of items according to a weighted attribute scale;

c) receiving selected attributes of preference from the user;

d) determining a match between said correlated predetermined selections of items and said received selected attributes of preference from the user; and

e) presenting said determined match to the user for purchase.

2. ) A purchase recommendation method for items by a user as recited in claim 1 further comprising the steps of:

f) receiving a rejection of said presented determined match by the user; and

g) presenting a subsequent determined match to the user for purchase.

3. ) A purchase recommendation method for items by a user comprising the steps:

a) providing an event group comprising selected events derived from the user;

b) determining selected recommendations via a preference mapping engine;

c) deriving an event group score from preferences received from the user;

d) organizing said determined selected recommendations according to said event group score; and

e) presenting selected said organized event group to the user for purchase.

4. ) A purchase recommendation method for items by a user as recited in claim 3 wherein said event group consists of at least one event derived from the user.

5. ) A purchase recommendation method for items by a user as recited in claim 3 wherein said preference mapping engine consists of the steps:

f) providing a catalog of selected event attributes stored on a database;

g) deriving selected event preferences from the user;

h) comparing selected event attributes and selected event preferences; and

i) deriving a preference map from said derived selected event preferences from the user and said stored selected event attributes.

6. ) A purchase recommendation method for items by a user as recited in claim 5 wherein said preference map consists of the steps:

j) determining a relevance score denoting selected event attributes;

k) determining a prominence score denoting relative prominence of the selected event attributes;

l) deriving an attribute score, said attribute score defining a quantitative relationship of said relevance score and said prominence score of said selected event attributes stored on said database; and

m) adding said attribute score to said event group score.

7. ) A purchase recommendation method for items by a user recited in claim 6 wherein said quantitative relationship is the product of said prominence score and said attribute score.

8. ) A purchase recommendation method for items by a user as recited in claim 3 wherein said events selected from the group consisting of musical concerts, theatrical productions, opera productions and ballet productions.

9. ) A purchase recommendation method for items by a user as recited in claim 3 wherein said organized selected recommendations are sorted from the highest said event group score to the lowest said event group score.

10. ) A purchase recommendation method for items by a user as recited in claim 3 further comprising the step of accepting for purchase said selected organized event group by the user.

11. ) A purchase recommendation method for items by a user as recited in claim 3 further comprising the step of rejecting said selected organized event group by the user.

12. ) A purchase recommendation method for items by a user as recited in claim 11 wherein the step of rejecting said selected organized event group by the user consists of the steps:

a) presenting a next in sequence of said organized event group to the user;

b) accepting for purchase said next in sequence said organized event group by the user; and

c) terminating the recommendation presentation by the user.

13. ) A purchase recommendation method for items by a user as recited in claim 11 wherein the step of rejecting said selected organized event group by the user consists of the steps:

d) presenting said selected organized event group to the user;

e) accepting for purchase said selected organized event group by the user; and

f) terminating the recommendation presentation by the user.