Recommendations with consequences exploration

1. A method implemented by at least one processor comprising hardware, the method comprising:

receiving a user input including a recommendation topic;

presenting, via a display interface, an exploration structure including a node corresponding to the recommendation topic;

receiving data corresponding to the node from a knowledge repository;

analyzing the received data to determine at least one follow-on recommendation based on the node, said follow-on recommendation being a follow-on action to be pursued by the user, said follow-on recommendation determined to be positively correlated to said node; and

presenting, via the display interface, each determined follow-on action recommendation in the exploration structure as additional child nodes of the node corresponding to the recommendation topic; and

receiving, via the display interface, user input selections of one or more said additional child nodes that traverse a path of potential recommended follow-on actions for determining a subsequent impact on the user based on the user pursuing the follow-on actions, said method further comprising:

obtaining contextual information regarding the user and a history of prior user transactions;

analyzing said contextual information and prior user interactions history;

comparing said contextual information and history to other users to determine a set of similar users; and

generating follow-on recommendations comprising follow-on actions the similar users have taken in view of the actions that the user has taken.

2. The method of claim 1 , further comprising:

receiving a further user input including a selection of the node, wherein the receiving of the data, analyzing the received data, and presenting each determined follow-on recommendation action in the exploration structure are performed in response to receiving the further user input.

3. The method of claim 1 , further comprising:

receiving a further user input including a selection of one of the child nodes; and

in response to receiving the further user input:

receiving data corresponding to the selected one of the child nodes from the knowledge repository;

analyzing the received data corresponding to the selected one of the child nodes to determine at least one follow-on recommendation based on the selected one of the child nodes; and

presenting each follow-on recommendation that is determined based on the selected one of the child nodes in the exploration structure as a child node of the selected one of the child nodes.

4. The method of claim 1 , further comprising:

receiving a further user input specifying a period of time;

comparing the specified period of time to a time component associated with each of the determined follow-on recommendations; and

determining that the time component of one or more of the determined follow-on recommendations meets the specified period of time,

wherein presenting each determined follow-on recommendation in the exploration structure as a child node of the node corresponding to the recommendation topic comprises presenting only the one or more of the determined follow-on recommendations having time components that meet the specified period of time in the exploration structure.

5. The method of claim 1 , further comprising:

receiving a further user input specifying a location;

comparing the specified location to a location component of each of the determined follow-on recommendations; and

determining that the location component of one or more of the determined follow-on recommendations meets the specified location,

wherein presenting each determined follow-on recommendation in the exploration structure as a child node of the node corresponding to the recommendation topic comprises presenting only the one or more of the determined follow-on recommendations having location components that meet the specified location in the exploration structure.

6. The method of claim 1 , wherein analyzing the received data to determine at least one follow-on recommendation based on the node comprises analyzing at least one action taken by another individual as follow-on to taking an action based on the node.

7. A system comprising:

a display; and

at least one processor comprising hardware, the at least one processor configured to:

receive a first user input including a recommendation topic;

present, via a display, an exploration structure including a node corresponding to the recommendation topic;

receive data corresponding to the node from a knowledge repository;

analyze the received data to determine at least one follow-on recommendation based on the node, said follow-on recommendation being a follow-on action to be pursued by the first user, said follow-on recommendation determined to be positively correlated to said node; and

present, via the display, each determined follow-on action recommendation in the exploration structure as additional child nodes of the node corresponding to the recommendation topic; and

receive, via the display, user input selections of one or more said additional child nodes that traverse a path of potential recommended follow-on actions for determining a subsequent impact on the user based on the user pursuing the follow-on actions, wherein the at least one processor is further configured to:

obtain contextual information regarding the user and a history of prior user transactions;

analyze said contextual information and prior user interactions history;

compare said contextual information and history to other users to determine a set of similar users; and

generate follow-on recommendations comprising follow-on actions the similar users have taken in view of the actions that the user has taken.

8. The system of claim 7 , the at least one processor further configured to:

receive a second user input including a selection of the node, wherein the receiving of the data, analyzing the received data, and presenting each determined follow-on recommendation in the exploration structure are performed in response to receiving the second user input.

9. The system of claim 7 , the at least one processor further configured to:

receive a second user input including a selection of one of the child nodes; and

in response to receiving the second user input:

receive data corresponding to the selected one of the child nodes from the knowledge repository;

analyze the received data corresponding to the selected one of the child nodes to determine at least one follow-on recommendation based on the selected one of the child nodes; and

present each follow-on recommendation that is determined based on the selected one of the child nodes in the exploration structure as a child node of the selected one of the child nodes.

10. The system of claim 7 , the at least one processor further configured to:

receive a second user input specifying a period of time;

compare the specified period of time to a time component of each of the determined follow-on recommendations; and

determine that the time component of one or more of the determined follow-on recommendations meets the specified period of time,

wherein only the one or more of the determined follow-on recommendations having time components that meet the specified period of time are presented in the exploration structure.

11. The system of claim 7 , the at least one processor further configured to:

receive a second user input specifying a location;

compare the specified location to a location component of each of the determined follow-on recommendations; and

determine that the location component of one or more of the determined follow-on recommendations meets the specified location,

wherein only the one or more of the determined follow-on recommendations having location components that meet the specified location are presented in the exploration structure.

12. The system of claim 7 , wherein analyzing the received data to determine at least one follow-on recommendation based on the node comprises analyzing at least one action taken by another individual as follow-on to taking an action based on the node.

13. A computer readable medium comprising instructions that, when executed by at least one processor comprising hardware, configure the at least one hardware processor to:

receive a first user input including a recommendation topic;

present, via a display, an exploration structure including a node corresponding to the recommendation topic;

receive data corresponding to the node from a knowledge repository;

analyze the received data to determine at least one follow-on recommendation based on the node, said follow-on recommendation being a follow-on action to be pursued by the user, said follow-on recommendation determined to be positively correlated to said node; and

present, via the display, each determined follow-on action recommendation in the exploration structure as additional child nodes of the node corresponding to the recommendation topic; and

receive, via the display, user input selections of one or more said additional child nodes that traverse a path of potential recommended follow-on actions for determining a subsequent impact on the user based on the user pursuing the follow-on actions, wherein the instructions further configuring the at least one processor to:

obtain contextual information regarding the user and a history of prior user transactions;

analyze said contextual information and prior user interactions history;

compare said contextual information and history to other users to determine a set of similar users; and

generate follow-on recommendations comprising follow-on actions the similar users have taken in view of the actions that the user has taken.

14. The computer readable medium of claim 13 , the instructions further configuring the at least one processor to:

receive a second user input including a selection of the node, wherein the receiving of the data, analyzing the received data, and presenting each determined follow-on recommendation in the exploration structure are performed in response to receiving the second user input.

15. The computer readable medium of claim 13 , the instructions further configuring the at least one processor to:

receive a second user input including a selection of one of the child nodes; and

in response to receiving the second user input:

receive data corresponding to the selected one of the child nodes from the knowledge repository;

analyze the received data corresponding to the selected one of the child nodes to determine at least one follow-on recommendation based on the selected one of the child nodes; and

present each follow-on recommendation that is determined based on the selected one of the child nodes in the exploration structure as a child node of the selected one of the child nodes.

16. The computer readable medium of claim 13 , the at least one processor further configured to:

receive a second user input specifying a period of time;

compare the specified period of time to a time component of each of the determined follow-on recommendations; and

determine that the time component of one or more of the determined follow-on recommendations meets the specified period of time,

wherein only the one or more of the determined follow-on recommendations having time components that meet the specified period of time are presented in the exploration structure.

17. The computer readable medium of claim 13 , the at least one processor further configured to:

receive a second user input specifying a location;

compare the specified location to a location component of each of the determined follow-on recommendations; and

determine that the location component of one or more of the determined follow-on recommendations meets the specified location,

wherein only the one or more of the determined follow-on recommendations having location components that meet the specified location are presented in the exploration structure.