Selective sharing of user information based on contextual relationship information, such as to crowd-source gifts of interest to recipient
Selective/controlled disclosure of user information to private workspaces of other users/invitees based on context/contextual relations, and a shared workspace or market to collaborate amongst the other users (e.g., to crowd-source gifts of interest to the recipient). Contextual disclosure may be ba...
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Main Authors | , , , , , , , |
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Format | Patent |
Language | English |
Published |
13.01.2016
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Subjects | |
Online Access | Get full text |
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Abstract | Selective/controlled disclosure of user information to private workspaces of other users/invitees based on context/contextual relations, and a shared workspace or market to collaborate amongst the other users (e.g., to crowd-source gifts of interest to the recipient). Contextual disclosure may be based on common context or commonality under a set of conditions, such as a topic, which may include known topics of relationships amongst the users and/or undiscovered contexts. As an example, items of interest to each user are identified and clustered, keywords are assigned to the clusters indicative of topics/subjects of interests to the respective users, recipient keywords are compared to keywords of an invitee to identify common keywords as shared interests, and items of interest to the recipient that relate to the common keywords are disclosed to the invitee as a personalized wish-list. Keyword weighting and/or keyword/item level privacy designations may be provided to further control disclosure. |
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AbstractList | Selective/controlled disclosure of user information to private workspaces of other users/invitees based on context/contextual relations, and a shared workspace or market to collaborate amongst the other users (e.g., to crowd-source gifts of interest to the recipient). Contextual disclosure may be based on common context or commonality under a set of conditions, such as a topic, which may include known topics of relationships amongst the users and/or undiscovered contexts. As an example, items of interest to each user are identified and clustered, keywords are assigned to the clusters indicative of topics/subjects of interests to the respective users, recipient keywords are compared to keywords of an invitee to identify common keywords as shared interests, and items of interest to the recipient that relate to the common keywords are disclosed to the invitee as a personalized wish-list. Keyword weighting and/or keyword/item level privacy designations may be provided to further control disclosure. |
Author | SIA JOSE K JR BECKWITH RICHARD T PHEGADE VINAY LEMAY MICHAEL WOUHAYBI RITA H ROBINSON SCOTT H COPPERNOLL TIMOTHY G BEZAITIS MARIA |
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SubjectTerms | CALCULATING COMPUTING COUNTING DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES PHYSICS SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR |
Title | Selective sharing of user information based on contextual relationship information, such as to crowd-source gifts of interest to recipient |
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