System and method for applying tracing tools for network locations

Abstract

A method is disclosed for enabling a network location to provide an ordering process for data relevant to connected network devices' activities. The method includes assembling the data, utilizing the activity data, and associating the data, such that information is derived to enable a desired expansion of at least one designated activity. Another method is disclosed for managing an object assignment broadcast operations for a network location based on a network device's previous activities. This second method includes tracing a network device's conduct to determine that a network device prefers a particular class of content. The method also includes tagging a network device's profile with the respective observation and deciding by a network location as to the classification factor for a network device to be targeted for an object assignment broadcast.

1 . (canceled) 
     
     
         2 . A computer-implemented method comprising:
 constructing an activity correlation model that correlates one or more content objects to activity by one or more network devices in a network;   receiving real-time information regarding one or more network devices connected to the network, wherein the real-time information includes one or more of the content objects associated with a level of activity;   updating the activity correlation model based on the real-time information, wherein the updated activity correlation model identifies one or more connections between the level of the activity and a contribution by the one or more content objects;   determining a set of the content objects to display to a first user device based on rankings of the contributions of the content objects; and   generating an individualized user interface unique to the first user device, wherein the individualized user interface includes the determined set of the content objects.   
     
     
         3 . The method of  claim 2 , wherein the level of activity is associated with the first user device, and further comprising determining a different set of the content objects to display to a second user device based on rankings of the contributions of the content objects associated with activity data associated with the second user device. 
     
     
         4 . The method of  claim 2 , further comprising generating an individualized user interface unique to a second user device, wherein the individualized user interface for the second user device includes a different set of the content objects. 
     
     
         5 . The method of  claim 2 , further comprising determining that the first user device is associated with one or more preferences based on the updated activity correlation model. 
     
     
         6 . The method of  claim 5 , further comprising tagging the first user device based on the determined preferences. 
     
     
         7 . The method of  claim 5 , further comprising determining a classification factor to add to a profile of the first user device, and targeting the first user device for one or more object assignment broadcasts based on the determined classification factor. 
     
     
         8 . The method of  claim 7 , further comprising generating an object assignment broadcast to the network, wherein one or more of the network devices associated with a profile that includes the classification factor are provided with a display of the object assignment broadcast. 
     
     
         9 . The method of  claim 2 , further comprising identifying an activity that needs to be improved based on a deviation in the level of activity, and generating an actionable report based on the updated activity correlation model for one or more of the content objects associated with improving the identified activity. 
     
     
         10 . A system comprising:
 memory that stores a constructed activity correlation model that correlates one or more content objects to activity by one or more network devices in a network;   a communication interface that receives real-time information regarding one or more network devices connected to the network, wherein the real-time information includes one or more of the content objects associated with a level of activity; and   a processor that executes instructions stored in memory to:
 update the activity correlation model based on the real-time information, wherein the updated activity correlation model identifies one or more connections between the level of the activity and a contribution by the one or more content objects; 
 determine a set of the content objects to display to a first user device based on rankings of the contributions of the content objects; and 
 generate an individualized user interface unique to the first user device, wherein the individualized user interface includes the determined set of the content objects. 
   
     
     
         11 . The system of  claim 10 , wherein the level of activity is associated with the first user device, and wherein the processor executes further instructions to determine a different set of the content objects to display to a second user device based on rankings of the contributions of the content objects associated with activity data associated with the second user device. 
     
     
         12 . The system of  claim 10 , wherein the processor executes further instructions to generate an individualized user interface unique to a second user device, wherein the individualized user interface for the second user device includes a different set of the content objects. 
     
     
         13 . The system of  claim 10 , wherein the processor executes further instructions to determine that the first user device is associated with one or more preferences based on the updated activity correlation model. 
     
     
         14 . The system of  claim 13 , wherein the processor executes further instructions to tag the first user device based on the determined preferences. 
     
     
         15 . The system of  claim 13 , wherein the processor executes further instructions to determine a classification factor to add to a profile of the first user device, and targeting the first user device for one or more object assignment broadcasts based on the determined classification factor. 
     
     
         16 . The system of  claim 15 , wherein the processor executes further instructions to generate an object assignment broadcast to the network, wherein one or more of the network devices associated with a profile that includes the classification factor are provided with a display of the object assignment broadcast. 
     
     
         17 . The system of  claim 10 , wherein the processor executes further instructions to identify an activity that needs to be improved based on a deviation in the level of activity, and generating an actionable report based on the updated activity correlation model for one or more of the content objects associated with improving the identified activity. 
     
     
         18 . A non-transitory, computer-readable storage medium, having embodied thereon a program executable by a processor to perform a method comprising:
 constructing an activity correlation model that correlates one or more content objects to activity by one or more network devices in a network;   receiving real-time information regarding one or more network devices connected to the network, wherein the real-time information includes one or more of the content objects associated with a level of activity;   updating the activity correlation model based on the real-time information, wherein the updated activity correlation model identifies one or more connections between the level of the activity and a contribution by the one or more content objects;   determining a set of the content objects to display to a first user device based on rankings of the contributions of the content objects; and   generating an individualized user interface unique to the first user device, wherein the individualized user interface includes the determined set of the content objects.   
     
     
         19 . The non-transitory, computer-readable storage medium of  claim 18 , wherein the level of activity is associated with the first user device, and further comprising instructions executable to determine a different set of the content objects to display to a second user device based on rankings of the contributions of the content objects associated with activity data associated with the second user device. 
     
     
         20 . The non-transitory, computer-readable storage medium of  claim 18 , further comprising instructions executable to generate an individualized user interface unique to a second user device, wherein the individualized user interface for the second user device includes a different set of the content objects. 
     
     
         21 . The non-transitory, computer-readable storage medium of  claim 18 , further comprising instructions executable to determine that the first user device is associated with one or more preferences based on the updated activity correlation model. 
     
     
         22 . The non-transitory, computer-readable storage medium of  claim 21 , further comprising instructions executable to tag the first user device based on the determined preferences. 
     
     
         23 . The non-transitory, computer-readable storage medium of  claim 21 , further comprising instructions executable to determine a classification factor to add to a profile of the first user device, and targeting the first user device for one or more object assignment broadcasts based on the determined classification factor. 
     
     
         24 . The non-transitory, computer-readable storage medium of  claim 23 , further comprising instructions executable to generate an object assignment broadcast to the network, wherein one or more of the network devices associated with a profile that includes the classification factor are provided with a display of the object assignment broadcast. 
     
     
         25 . The non-transitory, computer-readable storage medium of  claim 18 , further comprising instructions executable to identify an activity that needs to be improved based on a deviation in the level of activity, and generating an actionable report based on the updated activity correlation model for one or more of the content objects associated with improving the identified activity.