SYSTEM AND METHODS FOR PROVIDING SPATIALLY SEGMENTED RECOMMENDATIONS

• US 20140279196A1
• Filed: 03/15/2013
• Published: 09/18/2014
• Est. Priority Date: 03/15/2013
• Status: Abandoned Application

• Current Assignee: Nara Logics, Inc.
• Original Assignee: Nara Logics, Inc.
• Inventors: Copeman, Thomas C., Houle, Michael D., Sternberg, Joakim A., WILSON, Nathan R.
• Application Number:
  US13/842,165
• Publication Number:
  US 20140279196A1
• Time in Patent Office: Days
• US Class Current: 705/26.7
• CPC Class Codes: G06Q 30/0631 Item recommendations

Abstract

In certain implementations, data is spatially segmented into a variety of grids having particular keyed location data. Items of interest located within the boundaries of each grid are identified and stored in association with the grid location information. Data with respect to venue attributes is encoded and stored in association with corresponding grid location data. The system will identify a grid location based on a recommendation request or based on the user location and will generate a list of items of interest in that location and neighboring locations. This information is filtered based on the particularities of the user request to form a final filter set. User attribute weights are then applied to the final filter set to determine an overall score for each item of interest. Items of interest are then recommended to the user based on their overall score.

Claims

1. A method comprising:

receiving, at least one server, attribute data for a plurality of users and location data, the attribute data relating to a plurality of attributes of a user, user affinity data, and to at least a first venue for which the user has an affinity;

receiving, at the at least one server, venue data for a plurality of venues, the venue data relating to a plurality of attributes of the venues;

receiving, at the at least one server, review data for the plurality of venues, the review data reflecting the affinity of a plurality of reviewers for the plurality of venues;

encoding, at the server, the venue data of at least one venue as an encoded item of data containing at least one predetermined value for each venue attribute;

identifying, at the server, one or more local venues based on the location data;

comparing encoded venue data for each identified local venue to the user affinity data to generate a filtered set of venues;

accessing, via the at least one server, a data network comprising nodes corresponding at least to the plurality of venues and the plurality of reviewers and further comprising links between said nodes, each link reflecting a strength of an interrelationship between at least two nodes, wherein at least a plurality of the link strengths are a function of at least the review data and the venue data and are further a function of both content-based and collaborative interrelationships;

determining, at the at least one server and based on the link strengths and at least one venue parameter, a plurality of recommended venues from the filtered set of venues which have the strongest links to a user;

generating, at the at least one server, recommendation data comprising at least one recommended venue; and

serving to a client device the recommendation data for display on a screen of the client device.

2. The method according to claim 1, wherein the plurality of venues include at least one of restaurants, hotels and theaters.

3. The method according to claim 1, wherein the location data includes at least one of a location of a user or a location received from the user.

4. The method according to claim 1, wherein the plurality of attributes of the venues includes at least venue location data.

5. The method according to claim 1, further comprising:

spatially segmenting geographic data into a plurality of grids;

storing at least one venue in association with a grid in which the at least one venue is located; and

storing encoded venue data of at least one venue in association with a grid in which the venue is located.

6. The method according to claim 5, wherein the one or more local venues are identified by determining which venues of the plurality of venues are located in a grid corresponding to the location data.

7. The method according to claim 5, wherein at least one grid is stored in association with at least one other grid based on a location of the grids with respect to each other.

8. The method according to claim 7, wherein the one or more local venues are identified by determining which venues of the plurality of venues are located in a grid corresponding to the location data and any grids stored in association with the grid.

9. The method according to claim 1, further comprising:

applying weights corresponding to the user affinity data to each venue attribute of each venue of the filtered set of venues to determine an overall score for each venue; and

modifying the filter set based on the overall score of each venue.

10. The method according to claim 1, wherein the data network is accessed to provide a recommendation after performing the encoding, identifying and comparing.

11. The method according to claim 1, wherein the encoded item of data is a string containing the values in a predetermined order.

12. The method according to claim 11, wherein each value contained within the encoded item of data is separated by a predetermined character to distinguish values from each other.

13. The method according to claim 1, wherein the values contained within the encoded item of data are ordered in a sequence based on a quality level of each attribute.

14. A method for providing venue recommendations on a client device, comprising:

transmitting, from the client device to at least one server device, attribute data for a user and location data, the attribute data relating to a plurality of attributes of a user, user affinity data, and to at least a first venue for which the user has an affinity;

transmitting, from the client device to the at least one server device, a recommendation request including at least one venue attribute;

receiving, from the at least one server device, data identifying a plurality of recommended venues, each recommended venue being selected from a filtered set of venues based on the strength of a nodal interrelationship between the venue and the user within a data network comprising nodes corresponding at least to a plurality of venues and a plurality of reviewers and further comprising links between said nodes, each link reflecting a strength of an interrelationship between at least two nodes, wherein at least a plurality of the link strengths are a function of venue data relating to a plurality of attributes of the venues and review data reflecting the affinity of a plurality of reviewers for the plurality of venues, and are further a function of both content-based and collaborative interrelationships, and wherein the venue data of at least one venue is encoded as an encoded item of data containing predetermined values for each venue attribute, one or more local venues from the data network are identified based on the location data, and the filtered set of venues is generated by comparing encoded venue data for each identified local venue to the user affinity data; and

displaying, on a screen of the client device, data identifying the plurality of recommended venues.

15. The method according to claim 14, wherein the at least one server device

spatially segments geographic data into a plurality of grids,

stores at least one venue in association with a grid in which the venue is located, and

stores encoded venue data of at least one venue in association with a grid in which the venue is located.

16. The method according to claim 15, wherein the one or more local venues are identified by determining which venues of the plurality of venues are located in a grid corresponding to the location data.

17. The method according to claim 15, wherein the at least one server device

applies weights corresponding to the user affinity data to each venue attribute of each venue of the filtered set of venues to determine an overall score for each venue, and

modifies the filter set based on the overall score of each venue.

18. The method according to claim 15, wherein the data network is accessed to provide a recommendation after performing the encoding, identifying and comparing.

19. The method according to claim 15, wherein the encoded item of data is a string containing the values in a predetermined order.

20. The method according to claim 19, wherein each value contained within the encoded item of data is separated by a predetermined character to distinguish values from each other.