METHOD, SYSTEM, AND COMPUTER PROGRAM FOR USER-DRIVEN DYNAMIC GENERATION OF SEMANTIC NETWORKS AND MEDIA SYNTHESIS

• US 20100235307A1
• Filed: 05/01/2009
• Published: 09/16/2010
• Est. Priority Date: 05/01/2008
• Status: Active Grant

• Current Assignee: Primal Fusion Inc.
• Original Assignee: Primal Fusion Inc.
• Inventors: Good, Robert, Sweeney, Peter, Barlow-Busch, Robert, Black, Alexander David
• Granted Patent: US 8,676,722 B2
• Time in Patent Office: Days
• US Class Current: 706/12
• CPC Class Codes: G06F 16/24575 using context
• CPC Class Codes: G06F 16/3334 Selection or weighting of terms from queries, including natural language queries
• CPC Class Codes: G06F 16/3344 using natural language analysis
• CPC Class Codes: G06F 16/367 Ontology
• CPC Class Codes: G06F 40/30 Semantic analysis
• CPC Class Codes: G06N 5/02 Knowledge representation; Symbolic representation
• CPC Class Codes: G06N 5/022 Knowledge engineering; Knowledge acquisition
• CPC Class Codes: G06Q 30/0241 Advertisements
• CPC Class Codes: G06Q 30/0269 based on user profile or attribute

Abstract

This invention relates generally to classification systems. More particularly this invention relates to a system, method, and computer program to dynamically generate a domain of information synthesized by a classification system or semantic network. The invention discloses a method, system, and computer program providing a means by which an information store comprised of knowledge representations, such as a web site comprised of a plurality of web pages or a database comprised of a plurality of data instances, may be optimally organized and accessed based on relational links between ideas defined by one or more thoughts identified by an agent and one or more ideas embodied by the data instances. Such means is hereinafter referred to as a “thought network”.

Claims

1. A computer implemented method for generating a semantic network characterized in that it comprises the steps of:

(a) providing an information domain;

(b) representing the information domain as a data set, the data set being defined by data entities and one or more relationships between the data entities;

(c) providing, by means of an agent, data representing one or more thoughts; and

(d) synthesizing, or facilitating the synthesizing, by one or more computer processors, a semantic network based on one or more interactions between the data entities and the one or more thoughts.

2. The computer implemented method of claim 1, characterized in that it comprises the further step of enabling one or more of:

(a) interactions between the data entities and the one or more thoughts; and

(b) interactions between the agent and the data entities based on the one or more thoughts,

by one or more synthesis operations.

3. The computer implemented method of claim 1, characterized in that it comprises the further step of integrating the one or more thoughts with the data entities.

4. The computer implemented method of claim 1, characterized in that it comprises the further step of providing the agent with means to traverse the semantic network by selecting data entities related to the one or more thoughts.

5. The computer implemented method of claim 1, characterized in that it comprises the further step of synthesizing the semantic network dynamically upon the agent providing the data representing the one or more thoughts.

6. The computer implemented method of claim 4, characterized in that it comprises the further step of storing one or more aspects of learning derived from the semantic network to a storage means.

7. The computer implemented method of claim 6, characterized in that it comprises the further step of basing the learning on selecting the data entities related to the one or more thoughts.

8. The computer implemented method of claim 6, characterized in that it comprises the further step of storing the one or more aspects of learning, thereby facilitating dynamic generation of one or more other semantic networks.

9. The computer implemented method of claim 6, characterized in that the concepts of the semantic network are stored to the storage means.

10. The computer implemented method of claim 9, characterized in that it comprises the further step of storing relationships between the concepts to the storage means.

11. The computer implemented method of claim 1, characterized in that it comprises the further step of generating the semantic network to include label-to-concept translation.

12. The computer implemented method of claim 11, characterized in that it comprises the further step of defining a label representing a string, and generating from the label a representation of a concept.

13. The computer implemented method of claim 12, characterized in that it comprises one or more of the further steps of:

(a) defining the label by the agent;

or

(b) obtaining the label from another knowledge representation.

14. The computer implemented method of claim 11, characterized in that it comprises the further step of applying the label-to-concept translation to synthesizing the semantic network by:

(a) the one or more thoughts including the label;

(b) separating the label into one or more word components thereof;

(c) obtaining from the information domain a plurality of keywords associated with the one or more word components;

(d) ranking the keywords based on matching of the keywords with the one or more word components; and

(e) creating concept definitions based on the ranking of the keywords.

15. The computer implemented method of claim 1, characterized in that it comprises the further step of the agent specifying parameters to limit the synthesis of the semantic network being generated.

16. The computer implemented method of claim 15, characterized in that it comprises the further step of including one or more of a domain, axis direction, maximum degree(s) of separation, maximum degree(s) of depth, and maximum number of network nodes in the parameters.

17. The computer implemented method of claim 1, characterized in that it comprises the further step of storing the data set to a storage means, and wherein the data set includes means to create a semantic network.

18. The computer implemented method of claim 17, characterized in that it comprises the further step of first encoding the data entities, the relationships, and the labels, prior to storing the data set to the storage means.

19. The computer implemented method of claim 1, characterized in that it comprises the further step of one or more agents selecting parts of the data set to populate one or more domains.

20. The computer implemented method of claim 1, characterized in that it comprises the further step of synthesizing a second semantic network based on the data entities and relationships in the one or more domains.

21. A computer system for generating a semantic network characterized in that it comprises:

(a) one or more computers configured to provide, or provide access to, an information domain, wherein a data set is operable to represent the information domain, the data set being defined by data entities and one or more relationships between the data entities, and wherein an agent is operable to provide data representing one or more thoughts; and

(b) a thought processor operable to synthesize, or facilitate the synthesis of, by one or more computer processors, a semantic network based on one or more interactions between the data entities and the one or more thoughts.

22. The computer system of claim 21, characterized in that the thought processor is operable to synthesize the semantic network dynamically upon the agent providing the data representing the one or more thoughts to facilitate new mappings.

23. The computer system of claim 22, characterized in that the new mappings provide one or more of the following:

basic lookup functions;

attribute hierarchy;

or concept matching.

24. A computer program product for enabling the generation of a semantic network accessible through a web interface that enables an agent to initiate one or more computers to generate the semantic network, the computer program product characterized in that the computer program product comprises computer instructions and data for configuring one or more computer processors to:

(a) obtain, or obtain access to, an information domain, the information domain being represented by a data set representing the information domain, the data set being defined by data entities and one or more relationships between the data entities, wherein an agent is operable to provide data representing one or more thoughts; and

(b) synthesize, or facilitate the application of, by a thought processor, a semantic network based on one or more interactions between the data entities and the one or more thoughts.

25. The computer program product of claim 24 characterized in that the web interface is provided by a web application.

26. A computer implemented method for synthesizing media utilizing a semantic network characterized in that it comprises the steps of:

(a) generating, or facilitating the generation of by one or more computer processors, a thought network based on one or more interactions between one or more data entities and one or more thoughts; and

(b) transforming the thought network so as to generate and provide one or more forms of synthesized media to a consumer.

27. The computer implemented method of claim 26 characterized in that it comprises the further step of providing client-directed synthesized media based on a consumer-directed interaction whereby the consumer performs one of the following steps:

(a) providing input to direct the generation of the synthesized media;

or

(b) selecting synthesized media from the one or more forms provided.

28. The computer implemented method of claim 26 characterized in that the synthesized media is web-integrable media.

29. The computer implemented method of claim 26 characterized in that it comprises the further step of storing the synthesized media as a content inventory.