Abstract: In certain implementations, a system may receive attribute data corresponding to attributes of a plurality of users and to one or more venues for which the plurality of users has an affinity. A user personality matrix may be calculated for one or more of the plurality of users based on interrelational nodal link strengths between the one or more users and the venues. The user personality matrices may be merged to calculate a combined personality matrix representing a unified taste profile for the one or more users. A candidate list of venues having the highest link strength with the combined personality matrix may be determined. One or more recommended venues from the candidate list of venues that have the strongest links to the combined personality matrix may be determined, and recommendation data corresponding to the recommended venues may be output.
Type:
Grant
Filed:
April 17, 2014
Date of Patent:
April 14, 2015
Assignee:
Nara Logics, Inc.
Inventors:
Nathan R. Wilson, Luyao Li, Emily A. Hueske, Eleanor C. Kenyon, Thomas C. Copeman
Abstract: In selected embodiments a recommendation generator builds a network of interrelationships between venues, reviewers and users based on their attributes and reviewer and user reviews of the venues. Each interrelationship or link may be positive or negative and may accumulate with other links (or anti-links) to provide nodal links the strength of which are based on commonality of attributes among the linked nodes and/or common preferences that one node, such as a reviewer, expresses for other nodes, such as venues. The links may be first order (based on a direct relationship between, for instance, a reviewer and a venue) or higher order (based on, for instance, the fact that two venue are both liked by a given reviewer). The recommendation engine in certain embodiments determines recommended venues based on user attributes and venue preferences by aggregating the link matrices and determining the venues which are most strongly coupled to the user.
Type:
Application
Filed:
November 10, 2014
Publication date:
March 5, 2015
Applicant:
NARA LOGICS, INC.
Inventors:
Nathan R. WILSON, Emily A. Hueske, Thomas C. Copeman
Abstract: In selected embodiments a recommendation generator builds a network of interrelationships between venues, reviewers and users based on their attributes and reviewer and user reviews of the venues. Each interrelationship or link may be positive or negative and may accumulate with other links (or anti-links) to provide nodal links the strength of which are based on commonality of attributes among the linked nodes and/or common preferences that one node, such as a reviewer, expresses for other nodes, such as venues. The links may be first order (based on a direct relationship between, for instance, a reviewer and a venue) or higher order (based on, for instance, the fact that two venue are both liked by a given reviewer). The recommendation engine in certain embodiments determines recommended venues based on user attributes and venue preferences by aggregating the link matrices and determining the venues which are most strongly coupled to the user.
Type:
Grant
Filed:
May 1, 2014
Date of Patent:
December 9, 2014
Assignee:
Nara Logics, Inc.
Inventors:
Nathan R. Wilson, Emily A. Hueske, Thomas C. Copeman
Abstract: In certain implementations, a system may receive attribute data corresponding to attributes of a plurality of users and to one or more venues for which the plurality of users has an affinity. A user personality matrix may be calculated for one or more of the plurality of users based on interrelational nodal link strengths between the one or more users and the venues. The user personality matrices may be merged to calculate a combined personality matrix representing a unified taste profile for the one or more users. A candidate list of venues having the highest link strength with the combined personality matrix may be determined. One or more recommended venues from the candidate list of venues that have the strongest links to the combined personality matrix may be determined, and recommendation data corresponding to the recommended venues may be output.
Type:
Application
Filed:
April 17, 2014
Publication date:
September 18, 2014
Applicant:
NARA LOGICS, INC.
Inventors:
Nathan R. WILSON, Luyao Li, Emily A. Hueske, Eleanor C. Kenyon, Thomas C. Copeman
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.
Type:
Application
Filed:
March 15, 2013
Publication date:
September 18, 2014
Applicant:
Nara Logics, Inc.
Inventors:
Nathan R. WILSON, Michael D. Houle, Joakim A. Sternberg, Thomas C. Copeman
Abstract: In selected embodiments a recommendation generator builds a network of interrelationships between venues, reviewers and users based on their attributes and reviewer and user reviews of the venues. Each interrelationship or link may be positive or negative and may accumulate with other links (or anti-links) to provide nodal links the strength of which are based on commonality of attributes among the linked nodes and/or common preferences that one node, such as a reviewer, expresses for other nodes, such as venues. The links may be first order (based on a direct relationship between, for instance, a reviewer and a venue) or higher order (based on, for instance, the fact that two venue are both liked by a given reviewer). The recommendation engine in certain embodiments determines recommended venues based on user attributes and venue preferences by aggregating the link matrices and determining the venues which are most strongly coupled to the user.
Type:
Application
Filed:
May 1, 2014
Publication date:
August 28, 2014
Applicant:
NARA LOGICS, INC.
Inventors:
Nathan R. WILSON, Emily A. HUESKE, Thomas C. COPEMAN
Abstract: In selected embodiments a recommendation generator builds a network of interrelationships between venues, reviewers and users based on their attributes and reviewer and user reviews of the venues. Each interrelationship or link may be positive or negative and may accumulate with other links (or anti-links) to provide nodal links the strength of which are based on commonality of attributes among the linked nodes and/or common preferences that one node, such as a reviewer, expresses for other nodes, such as venues. The links may be first order (based on a direct relationship between, for instance, a reviewer and a venue) or higher order (based on, for instance, the fact that two venue are both liked by a given reviewer). The recommendation engine in certain embodiments determines recommended venues based on user attributes and venue preferences by aggregating the link matrices and determining the venues which are most strongly coupled to the user.
Type:
Grant
Filed:
June 17, 2013
Date of Patent:
June 17, 2014
Assignee:
Nara Logics, Inc.
Inventors:
Nathan R. Wilson, Emily A. Hueske, Thomas C. Copeman
Abstract: In certain implementations, a system may receive attribute data corresponding to attributes of a plurality of users and to one or more venues for which the plurality of users has an affinity. A user personality matrix may be calculated for one or more of the plurality of users based on interrelational nodal link strengths between the one or more users and the venues. The user personality matrices may be merged to calculate a combined personality matrix representing a unified taste profile for the one or more users. A candidate list of venues having the highest link strength with the combined personality matrix may be determined. One or more recommended venues from the candidate list of venues that have the strongest links to the combined personality matrix may be determined, and recommendation data corresponding to the recommended venues may be output.
Type:
Grant
Filed:
March 15, 2013
Date of Patent:
May 20, 2014
Assignee:
Nara Logics, Inc.
Inventors:
Nathan R. Wilson, Luyao Li, Emily A. Hueske, Eleanor C. Kenyon, Thomas C. Copeman
Abstract: In selected embodiments a recommendation generator builds a network of interrelationships between venues, reviewers and users based on their attributes and reviewer and user reviews of the venues. Each interrelationship or link may be positive or negative and may accumulate with other links to provide nodal links the strength of which are based on commonality of attributes among the linked nodes and/or common preferences that one node, such as a reviewer, expresses for other nodes, such as venues. The links may be first order (based on a direct relationship between, for instance, a reviewer and a venue) or higher order (based on, for instance, the fact that two venue are both liked by a given reviewer). The recommendation engine in certain embodiments determines recommended venues based on user attributes and venue preferences by aggregating the link matrices and determining the venues which are most strongly coupled to the user.
Type:
Grant
Filed:
March 9, 2012
Date of Patent:
August 20, 2013
Assignee:
Nara Logics, Inc.
Inventors:
Nathan R. Wilson, Emily A. Hueske, Thomas C. Copeman