System and method for recommending trending content based on context

Patent metadata

Field	Value
Publication number	US-2017192973-A1
Application number	US-201715463414-A
Country	US
Kind code	A1
Filing date	Mar 20, 2017
Priority date	Oct 26, 2005
Publication date	Jul 6, 2017
Grant date	—

Abstract

A system and method for recommending trending content based on context. The method includes receiving a query, wherein the query indicates a user intent; searching in at least one data source for a plurality of multimedia content elements related to the user intent; generating at least one signature for each of the plurality of multimedia content elements, wherein each signature represents a concept, wherein each concept is a collection of signatures and metadata describing the concept; correlating the concepts of the generated signatures to determine at least one context of each multimedia content element, wherein each context represents a sentiment; and generating, based on the determined contexts, a recommendation of at least one multimedia content element from among the plurality of multimedia content elements.

First claim

What is claimed is:

1 . A method for recommending trending content based on context, comprising:
receiving a query, wherein the query indicates a user intent; searching in at least one data source for a plurality of multimedia content elements related to the user intent; generating at least one signature for each of the plurality of multimedia content elements, wherein each signature represents a concept, wherein each concept is a collection of signatures and metadata describing the concept; correlating the concepts of the generated signatures to determine at least one context of each multimedia content element, wherein each context represents a sentiment; and generating, based on the determined contexts, a recommendation of at least one multimedia content element from among the plurality of multimedia content elements.

2 . The method of claim 1 , wherein generating the at least one signature for each multimedia content element related to the user intent further comprises:
generating a plurality of signatures to metadata associated with the multimedia content element, wherein the concepts are correlated among the plurality of signatures generated to the metadata of each multimedia content element.

3 . The method of claim 2 , wherein the metadata includes at least one of: a number of likes, a number of dislikes, a number of upvotes, a number of downvotes, at least one comment, a number of comments, at least one rating value, a number of viewers, a number of views, a number of clicks, and a number of downloads.

4 . The method of claim 1 , wherein generating the at least one signature for each multimedia content element related to the user intent further comprises:
generating a signature to the multimedia content element, wherein the concepts are correlated between signatures generated to the plurality of multimedia content elements.

5 . The method of claim 1 , further comprising:
determining, based on the at least one context of each multimedia content element, a sentiment value of each multimedia content element, wherein each recommended multimedia content element has a sentiment value matching a predetermined recommended sentiment value.

6 . The method of claim 5 , further comprising:
identifying, based on the correlation, a strong context of each multimedia content element, wherein the sentiment value for each multimedia content element is determined based further on the identified strong context for the multimedia content element.

7 . The method of claim 6 , wherein a context is identified as a strong context when a predetermined threshold of concept correlated to determine the context each satisfy a predetermined condition.

8 . The method of claim 1 , wherein each signature is robust to noise and distortions.

9 . The method of claim 1 , wherein each signature is generated by a signature generator system, wherein the signature generator system includes a plurality of computational cores configured to receive a plurality of unstructured data elements, each computational core of the plurality of computational cores having properties that are at least partly statistically independent of other of the computational cores, wherein the properties of each core are set independently of each other core.

10 . A non-transitory computer readable medium having stored thereon instructions for causing a processing circuitry to perform a process, the process comprising:
receiving a query, wherein the query indicates a user intent; searching in at least one data source for a plurality of multimedia content elements related to the user intent; generating at least one signature for each of the plurality of multimedia content elements, wherein each signature represents a concept, wherein each concept is a collection of signatures and metadata describing the concept; correlating the concepts of the generated signatures to determine at least one context of each multimedia content element, wherein each context represents a sentiment; and generating, based on the determined contexts, a recommendation of at least one multimedia content element from among the plurality of multimedia content elements.

11 . A system for recommending trending content based on context, comprising:
a processing circuitry; and a memory, the memory containing instructions that, when executed by the processing circuitry, configure the processing circuitry to: receive a query, wherein the query indicates a user intent; search in at least one data source for a plurality of multimedia content elements related to the user intent; generate at least one signature for each of the plurality of multimedia content elements, wherein each signature represents a concept, wherein each concept is a collection of signatures and metadata describing the concept; correlate the concepts of the generated signatures to determine at least one context of each multimedia content element, wherein each context represents a sentiment; and generate, based on the determined contexts, a recommendation of at least one multimedia content element from among the plurality of multimedia content elements.

12 . The system of claim 11 , wherein the system is further configured to:
generate a plurality of signatures to metadata associated with the multimedia content element, wherein the concepts are correlated among the plurality of signatures generated to the metadata of each multimedia content element.

13 . The system of claim 12 , wherein the metadata includes at least one of: a number of likes, a number of dislikes, a number of upvotes, a number of downvotes, at least one comment, a number of comments, at least one rating value, a number of viewers, a number of views, a number of clicks, and a number of downloads.

14 . The system of claim 11 , wherein the system is further configured to:
generate a signature to the multimedia content element, wherein the concepts are correlated between signatures generated to the plurality of multimedia content elements.

15 . The system of claim 11 , wherein the system is further configured to:
determine, based on the at least one context of each multimedia content element, a sentiment value of each multimedia content element, wherein each recommended multimedia content element has a sentiment value matching a predetermined recommended sentiment value.

16 . The system of claim 15 , wherein the system is further configured to:
identify, based on the correlation, a strong context of each multimedia content element, wherein the sentiment value for each multimedia content element is determined based further on the identified strong context for the multimedia content element.

17 . The system of claim 16 , wherein a context is identified as a strong context when a predetermined threshold of concept correlated to determine the context each satisfy a predetermined condition.

18 . The system of claim 11 , wherein each signature is robust to noise and distortions.

19 . The system of claim 1 , further comprising:
a signature generator system, wherein each signature is generated by the signature generator system, wherein the signature generator system includes a plurality of computational cores configured to receive a plurality of unstructured data elements, each computational core of the plurality of computational cores having properties that are at least partly statistically independent of other of the computational cores, wherein the properties of each core are set independently of each other core.

Assignees

• Cortica Ltd

Inventors

• Raichelgauz Igal
• Odinaev Karina
• Zeevi Yehoshua Y

Classifications

• G06F17/30873

  Physics · mapped topic

• G06F17/30867

  Physics · mapped topic

• G06F17/30038 Primary

  Physics · mapped topic

• G06N5/00

  Computing arrangements using knowledge-based models · CPC title

• H04H60/73

  using meta-information · CPC title