Systems and Methods for Identifying Content Based on User Interactions

Abstract

Disclosed is an intelligent recommendation system for identifying and/or providing personalized one or more independent applications and/or healthcare related media content (e.g., multimedia content and applications involved in healthcare or the treatment of various health conditions of a user) to a plurality of user devices and/or client devices.

What is claimed is: 
     
         1 . A system comprising:
 one or more computer readable storage media; and   a recommendation application comprising instructions stored on the one or more computer readable media, wherein the instructions, when executed by one or more computing devices, cause the one or more computing devices to:
 obtain data defining user interactions of a user occurring at a plurality of independent applications included in a platform, wherein each application of the plurality of applications corresponds to a health condition of the user; 
 based on the user interactions, identify a pattern of engagement defining the user's engagement with at least one independent application of the plurality of independent applications during a specific period of time; and 
 identify an independent application for integration into the platform, based on the pattern of engagement. 
   
     
     
         2 . The system of  claim 1 , wherein the platform, when executed by the one or more computing devices, generates a graphical user-interface providing access to each independent application of the plurality of independent applications included in the platform and the independent application. 
     
     
         3 . The system of  claim 1 , wherein the pattern of engagement identifies that the user interacts with the at least one independent application most often relative to other independent applications of the plurality of independent applications included in the platform. 
     
     
         4 . The system of  claim 1 , wherein the pattern of engagement comprises at least one feature that corresponds to an aspect of the user's health. 
     
     
         5 . The system of  claim 4 , wherein the instructions further cause the one or more computing devices to execute an automated learning algorithm to combine the at least one feature with similar features of an overall user-population. 
     
     
         6 . The system of  claim 1 , wherein the independent application maximizes the expected outcome of user interactions with the independent application. 
     
     
         7 . The system of  claim 1 , wherein the instructions further cause the one or more computing devices to:
 access one or more portions of health care information associated with the user;   determine from the accessed health care information, one or more health care concerns associated with the user; and   include the plurality of independent applications in the platform based on the determined one or more health care concerns.   
     
     
         8 . A method comprising:
 obtaining, using one or more computing devices, data defining user interactions of a user occurring at a plurality of independent applications included in a platform, wherein each application of the plurality of applications corresponds to a health condition of the user;   based on the user interactions, using the one or more computing devices, identifying a pattern of engagement defining the user's engagement with at least one independent application of the plurality of independent applications included in the platform, during a specific period of time; and   identifying, using the one or more computing devices, an independent application for integration into the platform, based on the pattern of engagement.   
     
     
         9 . The method of  claim 8 , further comprising generating a graphical user-interface providing access to each independent application of the plurality of independent applications included in the platform and the independent application. 
     
     
         10 . The method of  claim 8 , wherein the pattern of engagement identifies that the user interacts with the at least one independent application most often relative to other independent applications in the plurality of independent applications included in the platform. 
     
     
         11 . The method of  claim 8 , wherein the pattern of engagement comprises at least one feature that corresponds to an aspect of the user's health. 
     
     
         12 . The method of  claim 11 , further comprising executing an automated learning algorithm to combine the at least one feature with similar features of an overall user-population. 
     
     
         13 . The method of  claim 8 , wherein the application maximize the expected outcome of user interactions with the independent application. 
     
     
         14 . The method of  claim 8 , further comprising:
 accessing one or more portions of health care information associated with the user;   determining from the accessed health care information, one or more health care concerns associated with the user; and   including the plurality of independent applications in the platform based on the determined one or more health care concerns.   
     
     
         15 . A non-transitory computer readable medium encoded with instructions, the instructions, executable by one or more computing devices, comprising:
 obtaining data defining user interactions of a user occurring at a plurality of independent applications included in a platform, wherein each application of the plurality of applications corresponds to a health condition of the user;   based on the user interactions, using the one or more computing devices, identifying a pattern of engagement defining the user's engagement with at least one independent application of the plurality of independent applications included in the platform, during a specific period of time; and   identifying, using the one or more computing devices, an independent application for integration into the platform, based on the pattern of engagement.   
     
     
         16 . The non-transitory computer readable medium of  claim 15 , further comprising generating a graphical user-interface providing access to each independent application of the plurality of independent applications included in the platform and the independent application. 
     
     
         17 . The non-transitory computer readable medium of  claim 15 , wherein the pattern of engagement identifies that the user interacts with the at least one independent application most often relative to other independent applications in the plurality of independent applications included in the platform. 
     
     
         18 . The non-transitory computer readable medium of  claim 15 , wherein the pattern of engagement comprises at least one feature that corresponds to an aspect of the user's health. 
     
     
         19 . The non-transitory computer readable medium of  claim 18 , further comprising executing an automated learning algorithm to combine the at least one feature with similar features of an overall user-population. 
     
     
         20 . The non-transitory computer readable medium of  claim 15 , wherein the application maximize the expected outcome of user interactions with the independent application. 
     
     
         21 . The non-transitory computer readable medium of  claim 15 , further comprising:
 accessing one or more portions of health care information associated with the user;   determining from the accessed health care information, one or more health care concerns associated with the user; and   including the plurality of independent applications in the platform based on the determined one or more health care concerns.