System and methods thereof for generation of taxonomies based on an analysis of multimedia content elements

Abstract

A method and system for generating concept structures and taxonomies based on received multimedia data elements (MMDEs) are provided. The method comprises receiving at least one MMDE; generating at least one signature for the at least one received MMDE; matching the at least one generated signature to a plurality of clusters to find at least one matching cluster; associating the at least one generated signature with each of the at least one matching cluster; and analyzing the at least one generated signature with respect to a signature reduced cluster (SRC) of each of the at least one matching cluster to generate a taxonomy, wherein the taxonomy relates to the at least one received MMDE and an MMDE respective of each of the at least one matching cluster.

What is claimed is: 
     
         1 . A method for generating a taxonomy of a plurality of multimedia data elements (MMDEs) based on at least one multimedia data element (MMDE), comprising:
 receiving the at least one MMDE;   generating at least one signature for the at least one received MMDE;   matching the at least one generated signature to a plurality of clusters, each cluster representing a compressed number of signatures, wherein each cluster is created based on inter-matching among a plurality of signatures, to find at least one matching cluster;   
       associating the at least one generated signature with each of the at least one matching cluster;
 analyzing the at least one generated signature with respect to a signature reduced cluster (SRC) of each of the at least one matching cluster to generate a taxonomy, wherein the taxonomy relates to the at least one received MMDE and an MMDE respective of each of the at least one matching cluster. 
 
     
     
         2 . The method of  claim 1 , further comprising:
 when at least one matching cluster is not found, performing an inter-matching process between the plurality of signatures stored in a database and the at least one generated signatures, wherein the plurality of signatures are generated for previously received MMDEs;   generating at least one cluster respective of the inter-matching results; and   analyzing the at least one generated signature with respect to a SRC of each the at least one generated cluster to produce the taxonomy.   
     
     
         3 . The method of  claim 2 , wherein the method is performed by a Deep Content Classification (DCC) system. 
     
     
         4 . The method of  claim 3 , further comprising: saving the generated new data structure in a database communicatively connected to the deep-content-classification (DCC) system. 
     
     
         5 . The method of  claim 3 , wherein the DCC system includes: an attention processor (AP) for generating a plurality of items from the at least one MMDE; a signature generator (SG) for generating at least one signature responsive to at least one MMDE; and a concept generator (CG) for matching the at least one generated signature to a plurality of clusters to find at least one matching cluster. 
     
     
         6 . The method of  claim 1 , wherein the at least one MMDE is at least one of: graphics, a video stream, a video clip, an audio stream, an audio clip, a video frame, a photograph, and images of signals. 
     
     
         7 . The method of  claim 6 , wherein the images of signals are one of: medical signals, geophysical signals, subsonic signals, supersonic signals, electromagnetic signals, and infrared signals. 
     
     
         8 . A non-transitory computer readable medium containing instructions that, when executed, perform a process comprising:
 receiving the at least one multimedia data element (MMDE);   generating at least one signature for the at least one received MMDE;   matching the at least one generated signature to a plurality of clusters, each cluster representing a compressed number of signatures, wherein each cluster is created based on inter-matching among a plurality of signatures, to find at least one matching cluster;   
       associating the at least one generated signature with each of the at least one matching cluster;
 analyzing the at least one generated signature with respect to a signature reduced cluster (SRC) of each of the at least one matching cluster to generate a taxonomy, wherein the taxonomy relates to the at least one received MMDE and an MMDE respective of each of the at least one matching cluster. 
 
     
     
         9 . A system for generating concept structures, comprising:
 an interface to a network for receiving a request to create a new concept structure, wherein the request includes at least a multimedia data element (MMDE) related to the new concept structure;   a processor; and   a memory connected to the processor, the memory contains instructions that when executed by the processor, configure the system to:   receive the at least one MMDE;   generate at least one signature for the at least one received MMDE;   match the at least one generated signature to a plurality of clusters, each cluster representing a compressed number of signatures, wherein each cluster is created based on inter-matching among a plurality of signatures, to find at least one matching cluster;   associate the at least one generated signature with each of the at least one matching cluster; and   analyze the at least one generated signature with respect to a signature reduced cluster (SRC) of each of the at least one matching cluster to generate a taxonomy, wherein the taxonomy relates to the at least one received MMDE and an MMDE respective of each of the at least one matching cluster.   
     
     
         10 . The system of  claim 9 , further configured to:
 when at least one matching cluster is not found, perform an inter-matching process between the plurality of signatures stored in a database and the at least one generated signatures, wherein the plurality of signatures are generated for previously received MMDEs;   generate at least one cluster respective of the inter-matching results; and   analyze the at least one generated signature with respect to a SRC of each the at least one generated cluster to produce the taxonomy.   
     
     
         11 . The system of  claim 10 , wherein the system further includes:
 an attention processor (AP) for generating a plurality of items from the at least one MMDE;   a signature generator (SG) for generating at least one signature responsive to at least one at least one MMDE; and   a concept generator (CG) for matching the at least one generated signature to a plurality of clusters to find at least one matching cluster.   
     
     
         12 . The system of  claim 10 , wherein the at least one MMDE is at least one of: graphics, a video stream, a video clip, an audio stream, an audio clip, a video frame, a photograph, and images of signals. 
     
     
         13 . The system of  claim 13 , wherein the images of signals are one of: medical signals, geophysical signals, subsonic signals, supersonic signals, electromagnetic signals, and infrared signals. 
     
     
         14 . The method according to  claim 1  wherein the matching of the at least one generated signature to the plurality of clusters comprises matching the at least one generated signature to signatures of concept structures; wherein each concept structure comprises clusters that are associated with each other. 
     
     
         15 . The method according to  claim 14  wherein clusters of a concept structure are associated to each other when an overlap between metadata associated with the clusters exceeds a threshold. 
     
     
         16 . The method according to  claim 14  wherein the taxonomy comprises concept structures that are related to each other. 
     
     
         17 . The method according to  claim 16  wherein concept structures are related to each other when at least a predefined number of signatures that belong to the concept structures match each other. 
     
     
         18 . The method according to  claim 1  comprising generating the concept structures in an unsupervised manner. 
     
     
         19 . The method according to  claim 1 , comprising generating the at least one signature for the at least one received MMDE by independent computational cores. 
     
     
         20 . The method according to  claim 1 , wherein the at least one signature for the at least one received MMDE are at least one response of one or more neural networks to the received multimedia content element. 
     
     
         21 . The method according to  claim 1  comprising calculating entropy of multiple patches of each MMDE of the at least one MMDE; and wherein the at least one signature for the at least one received MMDE comprises at least one signature of at least one patch that has an entropy that exceeds a threshold.