Methods and apparatus for providing information of interest to one or more users

• US 9,792,550 B2
• Filed: 05/26/2016
• Issued: 10/17/2017
• Est. Priority Date: 05/01/2008
• Status: Active Grant

• Current Assignee: Primal Fusion Inc.
• Original Assignee: Primal Fusion Inc.
• Inventors: Sweeney, Peter Joseph, Ilyas, Ihab Francis, Dupuis, Jean-Paul, Yampolska, Nadiya
• Primary Examiner(s): Smith, Paulinho E
• Assistant Examiner(s): BUSS, BENJAMIN J
• Application Number:
  US15/164,952
• Publication Number:
  US 20160342896A1
• Time in Patent Office: 509 Days
• Field of Search: None
• 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

Methods and system for providing information selected from a large set of digital content to at least one user. One such method comprises receiving user context information associated with the at least one user and identifying or generating, using at least one processor executing stored program instructions, a first concept in a semantic network, the first concept representing at least a portion of the user context information. The method further comprises obtaining at least one concept, including a second concept, semantically relevant to the first concept at least in part, by synthesizing the second concept based on the first concept and at least one other concept in the semantic network; and providing information to the at least one user, wherein the information is selected by using the first concept and the at least one obtained concept semantically relevant to the first concept, wherein the first concept in a semantic network is represented by a data structure storing any data associated with a node in the semantic network.

Claims

1. A method for providing textual information that is personalized to at least one user, the method comprising:

using at least one computer hardware processor to perform;

receiving user context information including textual information indicative of an interest associated with the at least one user;

identifying or generating an active concept in a semantic network, the active concept representing at least a portion of the user context information, wherein, after performance of the identifying or generating, the semantic network comprises a first node representing the active concept;

synthesizing, in response to the received user context information, a new concept that is semantically relevant to the active concept and that was not in the semantic network prior to receiving the user context information, the synthesizing based on the active concept and at least one other concept in the semantic network and comprising augmenting the semantic network with a second node representing the new concept, the second node being different from the first node; and

providing the textual information that is personalized to the at least one user, wherein the textual information is selected based on the recitation in the textual information of the new concept semantically relevant to the active concept.

2. The method of claim 1, wherein synthesizing the new concept comprises:

identifying in the semantic network a third concept that, together with the active concept or a parent or sibling concept of the active concept, co-defines a fourth concept in the semantic network, and combining the active concept and the third concept to synthesize the new concept.

3. The method of claim 1, wherein synthesizing the second new comprises:

identifying a set of one or more attributes of the active concept;

identifying in the semantic network a third concept having an attribute included in the set of one or more attributes of the active concept or connected to an attribute included in the set of one or more attributes of the active concept by an is-a relationship; and

combining the active concept and the third concept to synthesize the new concept.

4. The method of claim 1, wherein synthesizing the new concept comprises:

identifying a set of one or more attributes of the active concept; and

replacing a first attribute in the set of one or more attributes of the first concept with a third concept from the semantic network to synthesize the new concept.

5. The method of claim 1, wherein the user-specific context information comprises at least one of a search query provided by the user, demographic information associated with the user, information from the user'"'"'s browsing history, information typed by the user, and/or information highlighted by the user.

6. The method of claim 1, wherein the information comprises one or more advertisements and/or one or more product recommendations from one or more other users.

7. The method of claim 1, wherein the information comprises content appearing on or accessible through a website.

8. A system for providing textual information that is personalized to at least one user, the system comprising:

at least one computer hardware processor; and

at least one non-transitory computer-readable storage medium storing processor-executable instructions that, when executed by the at least one computer hardware processor, cause the at least one computer hardware processor to perform;

receiving user context information including textual information indicative of an interest associated with the at least one user;

identifying or generating an active concept in a semantic network, the active concept representing at least a portion of the user context information, wherein, after performance of the identifying or generating, the semantic network comprises a first node representing the active concept;

synthesizing, in response to the received user context information, a new concept that semantically relevant to the active concept and that was not in the semantic network prior to receiving the user context information, the synthesizing based on the active concept and at least one other concept in the semantic network and comprising augmenting the semantic network with a second node representing the new concept, the second node being different from the first node; and

providing textual information that is personalized to the at least one user, wherein the textual information is selected based on the recitation in the textual information of the new concept semantically relevant to the active concept.

9. The system of claim 8, wherein synthesizing the new concept comprises:

identifying in the semantic network a third concept that, together with the active concept or a parent or sibling concept of the active concept, co-defines a fourth concept in the semantic network, and combining the active concept and the third concept to synthesize the new concept.

10. The system of claim 9, wherein synthesizing the new concept comprises:

identifying a set of one or more attributes of the active concept;

identifying in the semantic network a third concept having an attribute included in the set of one or more attributes of the active concept or connected to an attribute included in the set of one or more attributes of the active concept by an is-a relationship; and

combining the active concept and the third concept to synthesize the new concept.

11. The system of claim 8, wherein synthesizing the new concept comprises:

identifying a set of one or more attributes of the active concept; and

replacing a first attribute in the set of one or more attributes of the active concept with a third concept from the semantic network to synthesize the new concept.

12. The system of claim 8, wherein the user-specific context information comprises at least one of a search query provided by the user, demographic information associated with the user, information from the user'"'"'s browsing history, information typed by the user, and/or information highlighted by the user.

13. The system of claim 8, wherein the information comprises one or more advertisements and/or one or more product recommendations from one or more other users.

14. The system of claim 8, wherein the information comprises content appearing on or accessible through a website.

15. At least one non-transitory computer-readable storage medium storing processor-executable instructions that, when executed by at least one computer hardware processor, cause the at least one computer hardware processor to perform:

receiving user context information including textual information indicative of an interest associated with the at least one user;

identifying or generating an active concept in a semantic network, the active concept representing at least a portion of the user context information, wherein, after performance of the identifying or generating, the semantic network comprises a first node representing the active concept;

synthesizing, in response to the received user context information, a new concept that is semantically relevant to the active concept and that was not in the semantic network prior to receiving the user context information, the synthesizing based on the active concept and at least one other concept in the semantic network and comprising augmenting the semantic network with a second node representing the new concept, the second node being different from the first node; and

providing textual information that is personalized to the at least one user, wherein the textual information is selected based on the recitation in the textual information of the new concept semantically relevant to the active concept.

16. The at least one non-transitory computer-readable storage medium of claim 15, wherein synthesizing the new concept comprises:

identifying in the semantic network a third concept that, together with the active concept or a parent or sibling concept of the active concept, co-defines a fourth concept in the semantic network, and combining the active concept and the third concept to synthesize the new concept.

17. The at least one non-transitory computer-readable storage medium of claim 15, wherein synthesizing the new concept comprises:

identifying a set of one or more attributes of the active concept;

identifying in the semantic network a third concept having an attribute included in the set of one or more attributes of the active concept or connected to an attribute included in the set of one or more attributes of the active concept by an is-a relationship; and

combining the active concept and the third concept to synthesize the new concept.

18. The at least one non-transitory computer-readable storage medium of claim 15, wherein synthesizing the new concept comprises:

identifying a set of one or more attributes of the active concept; and

replacing a first attribute in the set of one or more attributes of the active concept with a third concept from the semantic network to synthesize the new concept.

19. The at least one non-transitory computer-readable storage medium of claim 15, wherein the information comprises one or more advertisements and/or one or more product recommendations from one or more other users.

20. The at least one non-transitory computer-readable storage medium of claim 15, wherein the information comprises content appearing on or accessible through a website.