Real-time autonomous organization

• US 9,667,513 B1
• Filed: 01/24/2013
• Issued: 05/30/2017
• Est. Priority Date: 01/24/2012
• Status: Active Grant

• Current Assignee: Lingo IP Holding, LLC
• Original Assignee: DW Associates LLC
• Inventors: Rehani, Manu, Wolf, Warren L.
• Primary Examiner(s): Eskandarnia, Arvin
• Application Number:
  US13/749,232
• Time in Patent Office: 1,587 Days
• Field of Search: 709203, 709219, 709222, 709224
• CPC Class Codes: G06Q 50/01 Social networking
• CPC Class Codes: H04L 41/509 wherein the managed service relates to media content delivery, e.g. audio, video or TV
• CPC Class Codes: H04L 43/045 for graphical visualisation of monitoring data
• CPC Class Codes: H04L 51/216 Handling conversation history, e.g. grouping of messages in sessions or threads
• CPC Class Codes: H04L 51/52 for supporting social networking services
• CPC Class Codes: H04M 1/7243 with interactive means for internal management of messages
• CPC Class Codes: H04M 3/5307 for recording messages comprising any combination of audio and non-audio components

Abstract

A system can receive content. The content can be analyzed to determine the invested interest of an object in a network, and to determine the strength of a relationship in the network, the network pertaining to a particular setting. The network can then be graphed, and the information produced can be output for later use.

Claims

1. A system, comprising:

a server;

an input port on the server to receive a content regarding at least one of a plurality of objects;

an invested interest analyzer to analyze said content to identify a level of invested interest for each of said objects in a setting;

a relationship analyzer to analyze said content to identify a strength of a relationship for each pair of the objects in said setting; and

an output port on the server to output information regarding said level of invested interest for each of said objects in said setting and said strength of said relationship for each pair of said objects,

wherein the output port is operative to output a network including at least two nodes and at least one edge, wherein each node in said network corresponds to one of said objects, each edge between pairs of nodes represents a relationship between said pair of objects represented by said nodes, a size of said node represents said invested interest of said corresponding object, and a thickness of said edge between pairs of nodes represents said strength of said relationship between said pair of objects represented by said nodes.

2. A system according to claim 1, wherein the plurality of objects is drawn from a set including individuals, groups, and contexts.

3. A system according to claim 1, wherein the setting is drawn from a set including an individual, a group, or a context.

4. A system according to claim 1, wherein:

the input port is operative to receive a new content regarding at least one of said objects;

the invested interest analyzer is operative to analyze said new content to identify a new level of invested interest for each of said objects in said setting;

the relationship analyzer is operative to analyze said new content to identify a new strength of a relationship for each pair of the objects in said setting; and

the output port is operative to output new information regarding said level of invested interest for each of said objects in said setting and said strength of said relationship for each pair of said objects.

5. A system according to claim 1, wherein said content is drawn from a set including documents, e-mails, texts, comments, posts, tweets, and transcribed conversations.

6. A method, comprising:

receiving a content regarding at least one of a plurality of objects;

analyzing the content using a machine to identify a level of invested interest for each of the objects in a setting and to identify a strength of a relationship for each pair of the objects in the setting; and

outputting information regarding the level of invested interest for each of the objects in the setting and the strength of the relationship for each pair of the objects, including graphing a network, wherein the network includes at least two nodes and at least one edge, each node in the network corresponds to one of the objects, each edge between pairs of nodes represents a relationship between the pair of objects represented by the nodes, a size of the node represents the invested interest of the corresponding object, and a thickness of the edge between pairs of nodes represents the strength of the relationship between the pair of objects represented by the nodes.

7. A method according to claim 6, wherein receiving a content includes receiving the content regarding the at least one of the plurality of objects, the plurality of objects drawn from a set including individuals, groups, and contexts.

8. A method according to claim 6, wherein analyzing the content includes analyzing the content to identify the level of invested interest for each of the objects in the setting and to identify the strength of the relationship for each pair of the objects, the setting drawn from a set including an individual, a group, or a context.

9. A method according to claim 6, further comprising:

receiving a second content regarding at least one of a plurality of objects;

analyzing the new content using a machine to identify a new level of invested interest for each of the objects in the setting and to identify a new strength of the relationship for each pair of the objects in the setting; and

outputting new information regarding the new level of invested interest for each of the objects in the setting and the new strength of the relationship for each pair of the objects.

10. A method according to claim 6, wherein receiving a content includes receiving the content regarding at least one of the objects, the content drawn from a set including documents, e-mails, texts, comments, posts, tweets, and transcribed conversations.

11. An article, comprising a non-transitory storage medium, said non-transitory storage medium having stored thereon instructions that, when executed by a machine, result in:

receiving a content regarding at least one of a plurality of objects;

analyzing the content using a machine to identify a level of invested interest for each of the objects in a setting and to identify a strength of a relationship for each pair of the objects in the setting; and

outputting information regarding the level of invested interest for each of the objects in the setting and the strength of the relationship for each pair of the objects, including graphing a network, wherein the network includes at least two nodes and at least one edge, each node in the network corresponds to one of the objects, each edge between pairs of nodes represents a relationship between the pair of objects represented by the nodes, a size of the node represents the invested interest of the corresponding object, and a thickness of the edge between pairs of nodes represents the strength of the relationship between the pair of objects represented by the nodes.

12. An article according to claim 11, wherein receiving a content includes receiving the content regarding the at least one of the plurality of objects, the plurality of objects drawn from a set including individuals, groups, and contexts.

13. An article according to claim 11, wherein analyzing the content includes analyzing the content to identify the level of invested interest for each of the objects in the setting and to identify the strength of the relationship for each pair of the objects, the setting drawn from a set including an individual, a group, or a context.

14. An article according to claim 11, said non-transitory storage medium having stored thereon further instructions that, when executed by a machine, result in:

receiving a second content regarding at least one of a plurality of objects;

analyzing the new content using a machine to identify a new level of invested interest for each of the objects in the setting and to identify a new strength of the relationship for each pair of the objects in the setting; and

outputting new information regarding the new level of invested interest for each of the objects in the setting and the new strength of the relationship for each pair of the objects.

15. An article according to claim 11, wherein receiving a content includes receiving the content regarding at least one of the objects, the content drawn from a set including documents, e-mails, texts, comments, posts, tweets, and transcribed conversations.