Method and system for artificial intelligence based content recommendation and provisioning

Abstract

Systems and methods of artificial intelligence based recommendation are disclosed herein. The system can include: a user device including: a network interface; and an I/O subsystem. The system can include an artificial intelligence engine that can provide a remediation dialogue. The system can include a content management server that can: receive a user identification identifying a user from the user device; retrieve user information from a memory; identify and deliver a question to the user device based on the retrieved user information; receive a response to the delivered question from the user device; determine that the received response is incorrect; trigger the launch of the artificial intelligence engine; receive an indication of completion of the dialogue; and provide a second question after receipt of the indication of completion of the dialogue.

What is claimed is: 
     
         1 . An artificial intelligence based recommendation system comprising:
 a user device comprising:
 a network interface configured to exchange data via the communication network; and 
 an I/O subsystem configured to convert electrical signals to user interpretable outputs via a user interface; 
   an artificial intelligence engine configured to receive inputs from at least the user device and to:
 launch a dialogue based on the received inputs; 
 identify remediation dialogue based on received user inputs; and 
 terminate the dialogue based on at least one halting criterion; and 
   a content management server, wherein the content management server is configured to:
 receive a user identification identifying a user from the user device; 
 receive data indicative of a user pattern of interaction; 
 generate a trigger value characterizing the user pattern of interaction; 
 trigger the launch of the artificial intelligence engine; 
 receive an indication of completion of the dialogue; and 
 provide second content after receipt of the indication of completion of the dialogue. 
   
     
     
         2 . The system of  claim 1 , wherein the content management server is further configured to receive an indication of an updated user skill level with the indication of completion of the dialogue. 
     
     
         3 . The system of  claim 2 , wherein the content management server is configured to select the second content based on the user skill level. 
     
     
         4 . The system of  claim 3 , wherein the remediation dialogue comprises multiple levels of interrogation and response. 
     
     
         5 . The system of  claim 4 , wherein at least some of the levels of interrogation comprise a question and delivered content. 
     
     
         6 . The system of  claim 5 , wherein the delivered content corresponds to the user skill level as identified in a user model at the time of selection of the delivered. 
     
     
         7 . The system of  claim 6 , wherein the delivered content corresponds to a request received from the user as part of the remediation dialogue. 
     
     
         8 . The system of  claim 6 , wherein the artificial intelligence engine is configured to reevaluate the user skill level subsequent to each level of interrogation and response. 
     
     
         9 . The system of  claim 8 , wherein the reevaluation of the user skill level comprises application of a natural language processing algorithm to the received response. 
     
     
         10 . The system of  claim 9 , wherein the natural language processing algorithm comprises at least one of: a speech recognition algorithm; and natural language understanding algorithm. 
     
     
         11 . The system of  claim 1 , wherein launching the dialogue comprises launching a user interface on the user device, wherein the user interface is configured to display dialogue content and receive user responses to the displayed dialogue content. 
     
     
         12 . A method for artificial intelligence based content recommendation and provisioning, the method comprising:
 receiving at a content management server a user identification from a user device, wherein the user identification identifies a user;   receiving data indicative of a user pattern of interaction;   generating a trigger value characterizing the user pattern of interaction;   triggering the launch of an artificial intelligence engine;   launching a dialogue based on the received inputs with the artificial intelligence engine;   identifying remediation dialogue with the artificial intelligence engine based on received user inputs;   terminating the dialogue with the artificial intelligence engine;   receiving an indication of completion of the dialogue with the content management server; and   delivering second content to the user device after receipt of the indication of completion of the dialogue.   
     
     
         13 . The method of  claim 12 , wherein the dialogue is terminated based on at least one halting criteria. 
     
     
         14 . The method of  claim 13 , wherein the halting criteria comprises a termination threshold, and wherein terminating the dialogue comprises generating a user performance metric indicative of at least one of: a skill level; a correct response; and an incorrect response; and comparing the user performance metric to the termination threshold. 
     
     
         15 . The method of  claim 12 , further comprising: receiving an indication of an updated user skill level with the indication of completion of the dialogue at the content management server. 
     
     
         16 . The method of  claim 15 , further comprising selecting the second content with the content management server, wherein the second content is selected based on the user skill level. 
     
     
         17 . The method of  claim 16 , wherein the remediation dialogue comprises multiple levels of interrogation and response. 
     
     
         18 . The method of  claim 17 , wherein at least some of the levels of interrogation comprise a question and delivered content, wherein the delivered content corresponds to the user skill level as identified in a user model at the time of selection of the delivered content, and wherein the delivered content corresponds to a request received from the user as part of the remediation dialogue. 
     
     
         19 . The method of  claim 17 , further comprising reevaluating the user skill level subsequent to each level of interrogation and response with the artificial intelligence engine. 
     
     
         20 . The method of  claim 19 , wherein reevaluating the user skill level comprises application of a natural language processing algorithm to the received response. 
     
     
         21 . The method of  claim 20 , wherein the natural language processing algorithm comprises at least one of: a speech recognition algorithm; and natural language understanding algorithm. 
     
     
         22 . The method of  claim 21 , wherein launching the dialogue comprises launching a user interface on the user device, wherein the user interface is configured to display dialogue content and receive user responses to the displayed dialogue content. 
     
     
         23 . The method of  claim 12 , further comprising:
 retrieving with the content management server user information from a memory, wherein the user information identifies progress by the user through a content progression;   identifying and delivering a question to the user device based on the retrieved user information;   receiving a response to the delivered question from the user device;   determining that the received response is incorrect.   
     
     
         24 . The method of  claim 23 , wherein the second content comprises a second question. 
     
     
         25 . The method of  claim 12 , wherein the launch of the artificial intelligence engine is triggered via at least one triggering condition, wherein the triggering condition delineates between patterns of user interaction.