METHODS AND SYSTEMS FOR AUTO-GENERATING MODELS OF NETWORKS FOR NETWORK MANAGEMENT PURPOSES

• US 20100241698A1
• Filed: 03/18/2010
• Published: 09/23/2010
• Est. Priority Date: 03/18/2009
• Status: Abandoned Application

• Current Assignee: Talk3, Inc.
• Original Assignee: Talk3, Inc.
• Inventors: Hillerbrand, Eric Thomas
• Application Number:
  US12/726,460
• Publication Number:
  US 20100241698A1
• Time in Patent Office: Days
• US Class Current: 709/203
• CPC Class Codes: G06F 16/13 File access structures, e.g. distributed indices arrangements of input from, or output to, record carriers G06F3/06
• CPC Class Codes: G06F 16/20 of structured data, e.g. relational data
• CPC Class Codes: G06F 40/205 Parsing
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: H04L 41/00 Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
• CPC Class Codes: H04L 41/0893 Assignment of logical groups to network elements
• CPC Class Codes: H04L 41/0894 Policy-based network configuration management
• CPC Class Codes: H04L 41/16 using machine learning or artificial intelligence
• CPC Class Codes: H04L 67/01 Protocols

Abstract

A system and method for modeling networks by auto-generation. The system generally comprises methods and systems for enabling the extraction, management and merging of models of networks and creating models of networks that can dynamically respond to changing context and computer requirements. The method includes ways of creating network models, maintaining n-dimensional graphs of networks; using adaptive and evolutionary algorithms for result emergence, using training and feedback to tune adaptive algorithms for solution optimization, and transformation of results into ontological and or data models.

Claims

1. A computer system comprising:

at least one server computer; and

,

at least one client computer coupled to the at least one server computer through a network;

wherein the at least one server computer includes at least one program stored thereon, said at least one program being capable of performing the following steps;

processing information relating to at least one artifact;

establishing at least one relationship between the processed information and information contained in a first datastore;

establishing the degree to which the processed information and the at least one relationship conform to at least one predetermined pattern; and

,

forming a network model based on the at least one relationship and the at least one predetermined pattern.

2. The computer system of claim 1, wherein said at least one program is capable of performing the further step of:

establishing one or more connection weights based on the at least one relationship, the at least one predetermined pattern, and at least one computational algorithm.

3. The computer system of claim 1, wherein said at least one relationship is measured across a plurality of dimensions.

4. The computer system of claim 2, wherein said at least one program is capable of performing the further steps of:

providing feedback regarding at least one of the one or more connection weights, the at least one relationship, and the at least one predetermine pattern;

altering one or more of the at least one connection weight, the at least one relationship, and the at least one predetermine pattern depending upon the feedback.

5. The computer system of claim 1, wherein said step of processing information relating to at least one artifact comprises:

parsing the information; and

,

generating at least one token corresponding to the parsed information.

6. The computer system of claim 5, wherein said step of processing information relating to at least one artifact further comprises:

generating at least one n-gram for the at least one token; and

,

creating at least one first association between the at least one token and another token using the at least one n-gram.

7. The computer system of claim 1, wherein said step of establishing at least one relationship between the processed information and information contained in a first datastore comprises:

creating at least one association between the processed information and information contained in the first datastore; and

storing information relating to the at least one association in the first datastore.

8. The computer system of claim 1, wherein said step of establishing the degree to which the processed information and the at least one relationship conform to at least one predetermined pattern comprises:

implementing one or more algorithms to determine the dimensions of an initial network model representing the processed information and the at least one relationship;

permitting a user to assert context information;

establishing one or more distances between nodes of the initial network model;

establishing one or more distances between dimensions of the initial network model; and

,

determining the degree to which the initial network model conforms to at least one predetermined pattern, the predetermined pattern being stored in the first datastore.

9. The computer system of claim 1, wherein said step of establishing the degree to which the processed information and the at least one relationship conform to at least one predetermined pattern further comprises:

implementing at least one algorithm to determine the applicability of the initial network model;

measuring feedback; and

,

modifying the at least one algorithm based on the feedback; and

,

altering at least one connection weight within the initial network model based on the feedback.

10. The computer system of claim 1, wherein said step of processing information relating to at least one artifact comprises generating a plurality of tokens corresponding to the information processed.

11. The computer system of claim 10, wherein said step of establishing at least one relationship between the processed information and information contained in a first datastore comprises generating at least one relationship between one or more of the plurality of tokens, and a plurality of tokens stored in the first datastore.

12. The computer system of claim 11, wherein said step of establishing the degree to which the processed information and the at least one relationship conform to at least one predetermined pattern comprises generating a token graph representative of the plurality of tokens and the at least one relationship.

13. The computer system of claim 12, wherein said step of forming a network model based on the at least one relationship and the at least one predetermined pattern comprises associating the token graph with a specific context.

14. The computer system of claim 13, wherein said step of forming a network model based on the at least one relationship and the at least one predetermined pattern further comprises associating the token graph with an algorithm graph.

15. The computer system of claim 14, wherein algorithm graph is created by the steps of:

implementing a neuro-cognitive model comprised of a plurality of algorithms;

generating at least one relationship between the two or more of the plurality of algorithms; and

,

generating an algorithm graph representative of the plurality of algorithms and the at least one relationship.

16. The computer system of claim 13, wherein said step of forming a network model based on the at least one relationship and the at least one predetermined pattern further comprises measuring changes in the token and algorithm graphs over time.

17. The computer system of claim 16, wherein said step of forming a network model based on the at least one relationship and the at least one predetermined pattern further comprises changing one or more weightings for the token graph or the algorithm graph based on the changes in the token and algorithm graphs over time, feedback information, or context information.

18. A computer system for auto-generation of network models comprising:

a processing component;

an affinity generation component;

an adaptation manager; and

a datastore.

19. The computer system of claim 18, wherein the processing component further comprises:

a garbage eater component;

a garbage churning component;

a garbage consolidation component; and

a garbage dumping component,

wherein information output from garbage dumping component is transmitted to the datastore.

20. The computer system of claim 18, wherein the processing component parses information and creates at least one token corresponding to the information.

21. The computer system of claim 20, wherein the processing component disambiguates the information.

22. The computer system of claim 18, wherein the affinity generation component executes at least one algorithm to establish at least one connection between the at least one token and one or more tokens in the datastore.

23. The computer system of claim 18, wherein the adaptation manager component executes at least one algorithm to establish at least one pattern.

24. A computer readable medium having embodied therein a computer program for processing by a machine, the computer program comprising:

a first code segment for processing information relating to at least one artifact;

a second code segment for establishing at least one relationship between the processed information and information contained in a first datastore;

a third code segment for establishing the degree to which the processed information and the at least one relationship conform to at least one predetermined pattern; and

,

a fourth code segment for forming a network model based on the at least one relationship and the at least one predetermined pattern.