# US 2013/0159230 A1 · Data Forgetting System > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2013/0159230 A1 - Document ID: US20130159230A1 - Status: Published application - Kind: A1 - Application number: 13/327,617 - Filed: 2011-12-15 - Published: 2013-06-20 - Earliest claimed: 2011-12-15 - Assignees: Toyota Infotechnology Center Co., Ltd.; Toyota Jidosha Kabushiki Kaisha - Inventors: David Frank Russell Weir - Web page: https://patentgrep.com/patent/US20130159230A1 ## CPC - G01C 21/3617: {using user history, behaviour, conditions or preferences, e.g. predicted or inferred from previous use or current movement} - G01C: MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY (measuring liquid level G01F; radio navigation, determining distance or velocity by use of propagation effects, e.g. Doppler effects, propagation time, of radio waves, analogous arrangements using other waves G01S) ## Abstract 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. ## Claims ### Claim 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. ### Claim 2 (depends on 1) 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. ### Claim 3 (depends on 2) 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. ### Claim 4 (depends on 1) 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. ### Claim 5 (depends on 1) The method of claim 1, wherein the learning parameters include converted driver history data that describes the one or more past journeys. ### Claim 6 (depends on 1) The method of claim 1, wherein the set of learning parameters are arranged in a learning table. ### Claim 7 (depends on 1) 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. ### Claim 8 (depends on 1) 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. ### Claim 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. ### Claim 10 (depends on 9) 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. ### Claim 11 (depends on 10) 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. ### Claim 12 (depends on 9) 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. ### Claim 13 (depends on 9) The computer program product of claim 9, wherein the learning parameters include converted driver history data that describes the one or more past journeys. ### Claim 14 (depends on 9) The computer program product of claim 9, wherein the set of learning parameters are arranged in a learning table. ### Claim 15 (depends on 9) 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. ### Claim 16 (depends on 9) 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. ### Claim 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. ### Claim 18 (depends on 17) 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. ### Claim 19 (depends on 18) 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. ### Claim 20 (depends on 17) 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. ### Claim 21 (depends on 17) The system of claim 17, wherein the learning parameters include converted driver history data that describes the one or more past journeys. ### Claim 22 (depends on 17) The system of claim 17, wherein the set of learning parameters are arranged in a learning table. ### Claim 23 (depends on 17) 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. ### Claim 24 (depends on 17) 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.