Method and System for Modeling Consumer Behavior Using N-Dimensional Decision Factor Categorization with Quantifiers and Qualifiers

• US 20130332406A1
• Filed: 05/30/2013
• Published: 12/12/2013
• Est. Priority Date: 05/31/2012
• Status: Abandoned Application

• Current Assignee: WUHU, LLC
• Original Assignee: WUHU, LLC
• Inventors: Gilliam, Terry K., Maille, Rob, Oral, Burc
• Application Number:
  US13/905,450
• Publication Number:
  US 20130332406A1
• Time in Patent Office: Days
• US Class Current: 706/52
• CPC Class Codes: G06N 5/02 Knowledge representation; Symbolic representation
• CPC Class Codes: G06Q 30/0202 Market predictions or forecasting for commercial activities
• CPC Class Codes: G06Q 50/40 Business processes related to the transportation industry shipping G06Q10/083

Abstract

The system and method for modeling consumer behavior uses n-dimensional decision factor categorization of travel qualifiers and quantifiers to provide the user with only the most relevant results for each query by matching numerous variables to a user'"'"'s behavior to learn about the user, remember the user, and ultimately predict further behavior of a user.

Claims

1. A system for modeling consumer behavior comprising,

at least one input mechanism configured to receive and send user-related information;

a central processing unit configured to receive and send user-related information and supply data relating to travel and entertainment, wherein the central processing unit comprises a scoring engine and at least one database for storing information relating to travel and entertainment;

a scoring engine configured to categorize user-related information based on decision models and compare the categorized user-related information to the information stored in the at least one database thereby creating a list of results; and

at least one output mechanism configured to receive and display the list of results, wherein the user selects a result to add to a journey.

2. The system for modeling consumer behavior of claim 1, wherein the at least one input mechanism comprises a computing device.

3. The system for modeling consumer behavior of claim 1, wherein the at least one output mechanism comprises a computing device.

4. The system for modeling consumer behavior of claim 1, wherein the central processing unit is configured to update and store the journey and related information from search to purchasing.

5. The system for modeling consumer behavior of claim 4, wherein the central processing unit is configured to notify the user of gaps in the journey via the output mechanism.

6. The system for modeling consumer behavior of claim 5, wherein the central processing unit is configured to provide a list of possible results to fill a gap in the journey.

7. The system for modeling consumer behavior of claim 1, wherein the scoring engine comprises a scoring function selected from the group consisting of a passive decision model approach, an active decision factor approach, and a coordinated multi-factor approach.

8. The system for modeling consumer behavior of claim 1, wherein the scoring function comprises the WUHU score and confidence level.

9. The system for modeling consumer behavior of claim 8, wherein the WUHU score and confidence level uses realized, transient, bootstrapping, rewards, and direct behavior values to evaluate a result.

10. The system for modeling consumer behavior of claim 9, wherein the direct behavior comprises options ranging from like-it, hate-it, exclude-it-forever, make-it-default, hide-it, and the like, wherein the designations map into an importance value scale between −

1 and 1.

11. The system for modeling consumer behavior of claim 1, wherein the decision models are selected from the group consisting of an initial set, C3, T9, B5 and I8.