System and method for using a knowledge representation to provide information based on environmental inputs

Patent metadata

Field	Value
Publication number	US-10867133-B2
Application number	US-201113341896-A
Country	US
Kind code	B2
Filing date	Dec 30, 2011
Priority date	May 1, 2008
Publication date	Dec 15, 2020
Grant date	Dec 15, 2020

Abstract

There is disclosed a system and method for using a knowledge representation to provide relevant information based on environmental inputs. In an embodiment, the system and method considers environmental information from members in a crowd to generate a pool of interests based on the semantic relevance concepts associated with those interests. The most prominent concepts of interest may then be the basis for presenting content to the crowd as a whole. In another embodiment, environmental inputs and other surrounding inputs are considered as a user context. The concepts may be identified as relevant from the environmental context and used to present information relevant to the user given his or her surroundings.

First claim

The invention claimed is:

1. A computer-implemented method for using a knowledge representation to provide advertising or promotional content, the method comprising:
receiving, from a sensing device detecting at least one physical property, at least one environmental input as a user-context information associated with one or more users, wherein at least one of the environmental inputs is an environmental input other than a location, wherein the sensing device is one or more of a humidity sensor, a vapor sensor, and/or a chemical sensor;
identifying, by at least one processor, at least one context based on the at least one environmental input received as the user-context information;
identifying, by the at least one processor, at least one concept in the knowledge representation as being semantically relevant to the at least one context, wherein the at least one concept is not recited in the at least one environmental input received as the user-context information, and wherein identifying the at least one concept comprises calculating a measure of coherence between the at least one context and the at least one concept by using the graph of the knowledge representation, wherein calculating the measure of coherence comprises:
calculating the measure of coherence based on whether a number of concepts within a predetermined distance of the at least one context in a reference knowledge representation and a number of concepts within a predetermined distance of the at least one concept share at least a predetermined number of concepts;

constructing, by the at least one processor, a search query using one or more labels of the identified at least one concept semantically relevant to the at least one context identified based on the at least one environmental input; and
running, by the at least one processor, the constructed search query on a data set containing advertising or promotional content to obtain advertising or promotional content relevant to the at least one context identified based on the at least one environmental input; and
transmitting the obtained advertising or promotional content relevant to the at least one context identified based on the at least one environmental input to at least one computing device associated with one or more users,
wherein the at least one concept is represented by a data structure storing data associated with the knowledge representation.

2. The computer-implemented method of claim 1 , wherein the knowledge representation comprises a semantic network and the data structure representing the at least one concept stores data associated with a node in the semantic network.

3. The computer-implemented method of claim 1 , wherein obtaining the at least one concept comprises obtaining the at least one concept in the knowledge representation based at least in part on the structure of the knowledge representation.

4. The computer-implemented method of claim 1 , wherein the sensing device utilizes one or more sensors to sense the at least one environmental input for the one or more users.

5. The computer-implemented method of claim 4 , wherein the one or more sensors comprise one or more in-range wireless devices associated with the one or more users.

6. The computer-implemented method of claim 5 , wherein the one or more in-range wireless devices comprise one or more of mobile phones, smart phones, touch pads, net books, laptops, or any other wireless device incorporating wireless technology and adapted to store information about one or more individuals in a crowd.

7. The computer-implemented method of claim 1 , wherein the data from the sensing device comprises at least one of audio data, video data, light data, geo-location data, motion data, or some combination thereof.

8. A system for using a knowledge representation to provide advertising or promotional content, the system comprising:
one or more processors;
a sensing device configured to detect at least one physical property, wherein the sensing device is one or more of a humidity sensor, a vapor sensor, and/or a chemical sensor; and
at least one memory unit configured to store processor-executable instructions which, when executed by the one or more processors, cause the one or more processors to:
receive, from the sensing device, at least one environmental input as a user-context information associated with one or more users, wherein at least one of the environmental inputs is an environmental input other than a location;
identify at least one context based on the at least one environmental input received as the user-context information;
identify at least one concept in the knowledge representation as being semantically relevant to the at least one context, wherein the at least one concept is not recited in the at least one environmental input received as the user-context information, and wherein identifying the at least one concept comprises calculating a measure of coherence between the at least one context and the at least one concept by using the graph of the knowledge representation, wherein calculating the measure of coherence comprises:
calculating the measure of coherence based on whether a number of concepts in a reference knowledge representation within a predetermined distance of the at least one context and a number of concepts in the knowledge representation within a predetermined distance of the at least one concept share at least a predetermined number of concepts; and

constructing a search query using one or more labels of the identified at least one concept semantically relevant to the at least one context identified based on the at least one environmental input;
running the constructed search query on a data set containing advertising or promotional content to obtain advertising or promotional content relevant to the at least one context identified based on the at least one environmental input; and
transmit the obtained advertising or promotional content relevant to the at least one context identified based on the at least one environmental input to at least one computing device associated with one or more users, wherein the at least one concept is represented by a data structure storing data associated with the knowledge representation.

9. The system of claim 8 , wherein the knowledge representation comprises a semantic network and the data structure representing the at least one concept stores data associated with a node in the semantic network.

10. The system of claim 8 , wherein instructions further cause the one or more processors to obtain the at least one concept in the knowledge representation based at least in part on the structure of the knowledge representation.

11. The system of claim 8 , wherein instructions further cause the one or more processors to utilize one or more sensors via the sensing device to sense the at least one environmental input for the one or more users.

12. The system of claim 11 , wherein the one or more sensors comprise one or more in-range wireless devices associated with the one or more users.

13. The system of claim 12 , wherein the one or more in-range wireless devices comprise one or more of mobile phones, smart phones, touch pads, net books, laptops, or any other wireless device incorporating wireless technology and adapted to store information about one or more individuals in a crowd.

14. The system of claim 8 , wherein the data from the sensing device comprises at least one of audio data, video data, light data, geo-location data, motion data or some combination thereof.

15. A non-transitory computer-readable medium storing computer code that when executed on a comput

Assignees

• Sweeney Peter
• Ilyas Ihab Francis
• Khan Naim
• Hunt Anne Jude
• Primal Fusion Inc

Inventors

• Sweeney Peter
• Ilyas Ihab Francis
• Khan Naim
• Hunt Anne Jude

Classifications

• G06F16/38 Primary

  Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually · CPC title

• G06F40/30 Primary

  Semantic analysis · CPC title

• G06F16/367

  Ontology · CPC title

• G06F16/3334

  Selection or weighting of terms from queries, including natural language queries · CPC title