COLLECTIVE INTELLIGENCE RECOMMENDER SYSTEM FOR TRAVEL INFORMATION AND TRAVEL INDUSTRY MARKETING PLATFORM

• US 20070179863A1
• Filed: 01/19/2007
• Published: 08/02/2007
• Est. Priority Date: 01/30/2006
• Status: Abandoned Application

• Current Assignee: Goseetell Network Incorporated
• Original Assignee: Goseetell Network Incorporated
• Inventors: Stoll, Martin
• Application Number:
  US11/625,157
• Publication Number:
  US 20070179863A1
• Time in Patent Office: Days
• US Class Current: 705/26
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0254 based on statistics
• CPC Class Codes: G06Q 30/0269 based on user profile or attribute
• CPC Class Codes: G06Q 30/0601 Electronic shopping [e-shopping]
• CPC Class Codes: G06Q 50/14 Travel agencies

Abstract

Embodiments of the present invention provide travelers with the ability to get travel advice and travel related information from other users by using the collective intelligence of a web-based social network as well as using the social network for creating marketing and advertising opportunities for travel suppliers.

Claims

1. A computer implemented method for generating travel recommendations for users, comprising:

registering by a server a new user;

receiving in a database of the server a user profile provided in connection with the user registration;

receiving in a database of the server information about demographic information and/or preferences of the user;

generating a travel recommendation based on at least one of the user profile, demographic information of the user, and preferences of the user.

2. The method of claim 1, further comprising receiving in a database information about reviews and ratings from other users regarding prior experiences and utilizing said information about reviews and ratings from other users regarding prior experiences in combination with said at least one of the user profile, demographic information of the user, and preferences of the user to generate a travel recommendation.

3. The method of claim 2, wherein reviews from other users regarding prior experiences may be further reviewed and rated and said further reviews and ratings may be used to evaluate relative value of the reviews from other users regarding prior experiences.

4. The method of claim 2, wherein each other user providing reviews and ratings regarding prior experiences may be provided a relative score indicative of a value for each other user'"'"'s reviews and ratings, said relative score being based on at least one of the number of reviews or ratings provided by the user and the values of the ratings of the user'"'"'s reviews provided by other users.

5. The method of claim 1, further comprising receiving in a database information from the user regarding prior experiences and utilizing said information from the user regarding prior experiences in combination with said at least one of the user profile, demographic information of the user, and preferences of the user to generate a travel recommendation.

6. The method of claim 5, wherein said information from the user regarding prior experiences comprises reviews, ratings, and/or descriptions of said prior experiences.

7. The method of claim 1, further comprising grouping users into clusters with the grouped users having one or more common characteristics and generating a travel recommendation for a user based on travel recommendations of a cluster of which the user is a member.

8. The method of claim 1, wherein generating a travel recommendation further comprises identifying by the server another user that has one more matching demographic, profile, or preference characteristics with the user and displaying attributes or a profile of the another user so that recommendations of the another user may be used by the user as a travel recommendation.

9. The method of claim 1, further comprising, prior to generating a travel recommendation, receiving in a server a query from the user for a travel recommendation and further basing said travel recommendation on said query.

10. The method of claim 1, wherein generating a travel recommendation further comprises identifying by the server another user that has one more matching demographic, profile, or preference characteristics with the user and has at least one rating for a first prior experience that closely matches a rating provided by the user for the same first prior experience and generating a travel recommendation by identifying the another user'"'"'s rating for a second prior experience responsive to the user'"'"'s query.

11. The method of claim 1, wherein generating a travel recommendation comprises displaying one or more recommended travel options to the user.

12. The method of claim 11, wherein further comprising, prior to displaying said one or more recommended travel options to the user, applying a filter to further qualify generated recommendations.

13. The method of claim 12, wherein said filter allows responsive recommendations based on data added to the database during a predefined time period.

14. The method of claim 12, wherein said filter allows responsive recommendations based on data from other users that share specific similarities with the user, based on data from other users preselected by the user, or based on data from other users that have entered at least a minimum amount of data into the database

15. The method of claim 12, wherein said filter allows responsive recommendations to be limited to recommendations within a defined distance of another location, recommendations for locations or suppliers receiving a minimum rating, or recommendations for locations or suppliers receiving a minimum number of reviews or ratings.

16. The method of claim 1, wherein generating a travel recommendation is further based on a current location of the user as provided by an associated location indication device.

17. The method of claim 15, wherein said location indication device is a global positioning system or a wireless triangulation system.

18. An apparatus, comprising:

a storage medium having stored therein a plurality of programming instructions designed to enable the apparatus to operate or contribute in operating a travel recommendation service when the programming instructions are executed, the travel recommendation service being configured to register by a server a new user;

receive in a database of the server a user profile provided in connection with the user registration;

receive in a database of the server information about demographic information and/or preferences of the user;

receive in a server a query from the user for a travel recommendation; and

generate a travel recommendation based on at least one of the user profile, demographic information of the user, and preferences of the user; and

a processor coupled to the storage medium to execute the plurality of programming instructions.

19. A computer implemented method for providing targeted advertising by a supplier to a user, comprising:

receiving in a database of a server user data for a plurality of users, said user data being directed to one or more characteristics;

selecting by the supplier at least one of said one or more characteristics to target for the advertising;

generating by the supplier an advertisement for display to users having said selected characteristics;

and displaying by the server said advertisement to the users having said selected characteristics.

20. The method of claim 19, wherein the one or more user characteristics are at least one of demographic data of the user, user travel preferences, and user interests.

21. The method of claim 19, wherein said advertisement is one of a plurality of advertisements and said plurality of advertisements are displayed to a user in an order based on a number of users the particular advertisement is targeting, a smaller number of targeted users being ranked higher in priority.