Data Forgetting System
A system and method for forgetting data in a navigation system is disclosed. The system comprises a monitor module, a determination module and a delete module. The monitor module detects a trigger event. The determination module determines a classification for the trigger event. The determination module determines a set of learning parameters to delete from a memory associated with a navigation system based at least in part on detection of the trigger event and the classification of the trigger event. The delete module deletes the determined set of learning parameters.
1 . A method comprising:
detecting a trigger event;
determining a classification for the trigger event;
determining a set of learning parameters to delete from a memory associated with a navigation system based at least in part on detection of the trigger event and the classification of the trigger event; and
deleting the determined set of learning parameters.
2 . The method of claim 1 further comprising interrogating the memory associated with the navigation system to determine whether the available memory is below a predetermined threshold and wherein determining the set of learning parameters to delete is based at least in part on whether the available memory is below the predetermined threshold.
3 . The method of claim 2 , wherein no learning parameters are deleted from the memory responsive to determining that the available memory is not below the predetermined threshold.
4 . The method of claim 1 , wherein the classification of the trigger event is a factory reset input and all the learning parameters stored in the memory are deleted responsive to the trigger event.
5 . The method of claim 1 , wherein the learning parameters include converted driver history data that describes the one or more past journeys.
6 . The method of claim 1 , wherein the set of learning parameters are arranged in a learning table.
7 . The method of claim 1 , wherein the trigger event is one or more of:
a user request to delete one or more destinations;
a lapse of a predetermined period of time since a last trigger event;
a number of destinations stored in the memory that exceed a predetermined threshold; and
a predetermined number of journeys that have occurred since a last trigger event.
8 . The method of claim 1 , wherein the learning parameters to be deleted are one or more of:
destination data stored in a learning table and describing entries for a destination, and wherein the entries include (1) timestamp data describing a day of week and time of day for a journey to the destination and (2) direction data describing a direction to the destination.
9 . A computer program product comprising a non-transitory computer readable medium encoding instructions that, in response to execution by a computing device, cause the computing device to perform operations comprising:
detecting a trigger event;
determining a classification for the trigger event;
determining a set of learning parameters to delete from a memory associated with a navigation system based at least in part on detection of the trigger event and the classification of the trigger event; and
deleting the determined set of learning parameters.
10 . The computer program product of claim 9 , wherein the instructions cause the computing device to perform operations further comprising interrogating the memory associated with the navigation system to determine whether the available memory is below a predetermined threshold and wherein determining the set of learning parameters to delete is based at least in part on whether the available memory is below the predetermined threshold.
11 . The computer program product of claim 10 , wherein no learning parameters are deleted from the memory responsive to determining that the available memory is not below the predetermined threshold.
12 . The computer program product of claim 9 , wherein the classification of the trigger event is a factory reset input and all the learning parameters stored in the memory are deleted responsive to the trigger event.
13 . The computer program product of claim 9 , wherein the learning parameters include converted driver history data that describes the one or more past journeys.
14 . The computer program product of claim 9 , wherein the set of learning parameters are arranged in a learning table.
15 . The computer program product of claim 9 , wherein the trigger event is one or more of:
a user request to delete one or more destinations;
a lapse of a predetermined period of time since a last trigger event;
a number of destinations stored in the memory that exceed a predetermined threshold; and
a predetermined number of journeys that have occurred since a last trigger event.
16 . The computer program product of claim 9 , wherein the learning parameters to be deleted are one or more of:
destination data stored in a learning table and describing entries for a destination, and wherein the entries include (1) timestamp data describing a day of week and time of day for a journey to the destination and (2) direction data describing a direction to the destination.
17 . A system comprising:
a monitor module detecting a trigger event;
a determination module communicatively coupled to the monitor module, the determination module determining a classification for the trigger event, the determination module determining a set of learning parameters to delete from a memory associated with a navigation system based at least in part on detection of the trigger event and the classification of the trigger event; and
a delete module communicatively coupled to the determination module, the delete module deleting the determined set of learning parameters.
18 . The system of claim 17 , wherein the determination module is further configured to:
interrogate the memory associated with the navigation system to determine whether the available memory is below a predetermined threshold; and
determine the set of learning parameters to delete based at least in part on whether the available memory is below the predetermined threshold.
19 . The system of claim 18 , wherein no learning parameters are deleted from the memory responsive to determining that the available memory is not below the predetermined threshold.
20 . The system of claim 17 , wherein the classification of the trigger event is a factory reset input and all the learning parameters stored in the memory are deleted responsive to the trigger event.
21 . The system of claim 17 , wherein the learning parameters include converted driver history data that describes the one or more past journeys.
22 . The system of claim 17 , wherein the set of learning parameters are arranged in a learning table.
23 . The system of claim 17 , wherein the trigger event is one or more of:
a user request to delete one or more destinations;
a lapse of a predetermined period of time since a last trigger event;
a number of destinations stored in the memory that exceed a predetermined threshold; and
a predetermined number of journeys that have occurred since a last trigger event.
24 . The system of claim 17 , wherein the learning parameters to be deleted are one or more of:
destination data stored in a learning table and describing entries for a destination, and wherein the entries include (1) timestamp data describing a day of week and time of day for a journey to the destination and (2) direction data describing a direction to the destination.