Granted Patent B2

US 9,781,228 · App. 14/582,109 · Granted Oct 3, 2017

Inventor: Michael Roberts (Los Gatos, CA)

Assignee: PALO ALTO RESEARCH CENTER INCORPORATED

H04L67/306G06F17/30038G06F17/30867G06F17/30958G06Q50/00G06Q50/10

Abstract

Claims (75)

1. A system for providing contextual media tagging for selective media exposure with the aid of a digital computer, comprising:

a non-transitory computer readable storage medium comprising program code and further comprising:

a database configured to maintain a media file; and

a set of transformation rules for a user semantic graph;

a computer processor and memory with the computer processor coupled to the storage medium, wherein the computer processor is configured to execute the program code to perform steps to:

generate with the computer processor contextual information for and collect with the computer processor contextual data regarding a user;

associate with the computer processor the media file with the user contextual information;

identify with the computer processor insights of the contextual data of the user;

generate with the computer processor a semantic graph for the user with the user contextual information comprising a plurality of nodes and edges that create graph structures;

match with the computer processor each transformation rule with each graph structure of the user semantic graph;

transform with the computer processor the matched graph structure into a single node in the user semantic graph; and

share with the computer processor the media file to other computer processors of individuals who belong to a social network of the user over a network to which the computer processor is connected to the other computer processors based on the user contextual information in the user semantic graph.

2. A system according to claim 1 , wherein the computer processor is further configured to execute the program code to perform steps to:

generate with the computer processor a semantic graph for each individual in the social network;

the non-transitory computer readable storage medium further comprising:

a set of graph production rules with the computer processor for the user semantic graph, each graph production rule applying for a relationship between the user and one individual in the social network;

wherein the computer processor is still further configured to execute the program code to perform steps to

match with the computer processor each graph production rule to each graph structure of the user semantic graph; and

copy with the computer processor the matched graph structure of the user semantic graph to the semantic graph for the individual.

3. A system according to claim 1 , further comprising:

the non-transitory computer readable storage medium further comprising:

a hierarchy of node categories comprised in the database comprising high level node categories and low level node categories corresponding to each high level node category as sub node categories;

wherein the computer processor is further configured to execute the program code to perform steps to:

define with the computer processor the transformation rules as replacing the low level node categories with the high level node category corresponding to the low level node categories;

apply with the computer processor the transformation rules to each graph structure of the user semantic graph; and

replace with the computer processor the graph structure as the low level node categories to the single node which is a high level node category corresponding to the low level node categories.

4. A system according to claim 2 , wherein the computer processor is further configured to execute the program code to perform steps to:

serialize with the computer processor the nodes of the semantic graph; and

embed with the computer processor the serialized nodes of the semantic graph into a metadata of the media file.

5. A system according to claim 1 , wherein the computer processor is further configured to execute the program code to perform steps to:

compute with the computer processor a fingerprint of the semantic graph; and

embed with the computer processor the fingerprint of the semantic graph into the media file.

6. A system according to claim 1 , wherein the computer processor is further configured to execute the program code to perform steps to:

identify with the computer processor a link of the database to the user contextual information; and

embed with the computer processor the link to the media file into the media file.

7. A system according to claim 1 , wherein the computer processor is further configured to execute the program code to perform steps to:

determine with the computer processor an association of the media file with the contextual information and store the association in the database; and

embed with the computer processor the association into the media file.

8. A system according to claim 1 , wherein the computer processor is further configured to execute the program code to perform steps to:

recognize with the computer processor incoming new contextual data regarding the user; and

update with the computer processor the user contextual information based on the incoming new contextual data.

9. A method for providing contextual media tagging for selective media exposure with the aid of a digital computer, comprising:

maintaining a media file in a database and a set of transformation rules for a user semantic graph comprised in a storage medium;

generating contextual information with a computer processor and memory with the computer processor coupled to the non-transitory computer readable storage medium and collecting with the computer processor contextual data regarding for a user;

associating with the computer processor the media file with the user contextual information;

identifying with the computer processor insights of the contextual data of the user;

generating with the computer processor a semantic graph for the user with the user contextual information comprising a plurality of nodes and edges that create graph structures;

matching with the computer processor each transformation rule with each graph structure of the user semantic graph;

transforming with the computer processor the matched graph structure into a single node in the user semantic graph; and

sharing with the computer processor the media file to other computer processors of individuals who belong to a social network of the user over a network to which the computer processor is connected to the other computer processors based on the user contextual information in the user semantic graph.

10. A method according to claim 9 , further comprising:

generating with the computer processor a semantic graph for each individual in the social network;

defining a set of graph production rules with the computer processor for the user semantic graph, each graph production rule applying for a relationship between the user and one individual in the social network;

matching with the computer processor each graph production rule to each graph structure of the user semantic graph; and

copying with the computer processor the matched graph structure of the user semantic graph to the semantic graph for the individual.

11. A method according to claim 9 , further comprising:

maintaining a hierarchy of node categories comprised in the database comprising high level node categories and low level node categories corresponding to each high level node category as sub node categories;

defining with the computer processor the transformation rules as replacing the low level node categories with the high level node category corresponding to the low level node categories;

applying with the computer processor the transformation rules to each graph structure of the user semantic graph; and

replacing with the computer processor the graph structure as the low level node categories to the single node which is a high level node category corresponding to the low level node categories.

12. A method according to claim 9 , further comprising:

serializing with the computer processor the nodes of the semantic graph; and

embedding with the computer processor the serialized nodes of the semantic graph into a metadata of the media file.

13. A method according to claim 9 , further comprising:

computing with the computer processor a fingerprint of the semantic graph; and

embedding with the computer processor the fingerprint of the semantic graph into the media file.

14. A method according to claim 9 , further comprising:

identifying with the computer processor a link of the database to the user contextual information; and

embedding with the computer processor the link to the media file into the media file.

15. A method according to claim 9 , further comprising:

determining with the computer processor an association of the media file with the contextual information and storing the association in the database; and

embedding with the computer processor the association into the media file.

16. A method according to claim 9 , further comprising:

recognizing with the computer processor incoming new contextual data regarding the user; and

updating with the computer processor the user contextual information based on the incoming new contextual data.

Assignments (10)

Continuity (1)