Preference setting in a computer system

• US 7,788,219 B2
• Filed: 12/13/2007
• Issued: 08/31/2010
• Est. Priority Date: 12/13/2007
• Status: Expired due to Fees

• Current Assignee: Harris Technology LLC
• Original Assignee: Harris Technology LLC
• Inventors: Harris, Scott C
• Primary Examiner(s): EHICHIOYA, IRETE FRED
• Application Number:
  US11/956,334
• Publication Number:
  US 20090157702A1
• Time in Patent Office: 992 Days
• Field of Search: 707/609, 707/687, 707/705, 707/769, 707/802, 707/821, 709/217, 725/37, 725/46
• US Class Current: 707/609
• CPC Class Codes: G06F 9/4451 User profiles; Roaming

Abstract

A profile of likelihoods of actions that will occur on a computer is stored. The computer may be likely to be off between time periods, e.g., between midnight and 7 am. Some action is taken relative to the actions that are likely to occur, before those actions actually happen.

Claims

1. A method comprising:

in a computer-based device, storing a data structure which includes information about a plurality of specific actions that a user has requested the computer based device to take and a plurality of specific times that the user has taken said actions, said information defining a likelihood that one of said actions will be carried out at one of said times;

using the computer based device for comparing a current time to said times in said data structure;

determining an action which is probabilistically likely to happen in the computer based device at an operation time, where said operation time includes at least one of a current time and times subsequent to said current time; and

taking an action on the computer based device, based on what is most likely to happen at said operation time, prior to said action actually happening, wherein said action comprises determining that a program is likely to be started, and responsive to determining that the program is likely to be started, loading at least some part of said program into a memory prior to the program being actually started.

2. A method as in claim 1, wherein said data structure is a feature vector that stores information indicative of likelihoods of plural different actions at plural different times.

3. A method as in claim 1, further comprising forming an individual data structure for an individual user of the computer-based device and updating said individual data structure based on actions taken by the individual user and times when those actions are taken.

4. A method as in claim 1, further comprising storing sets of information in the data structure that represents generic users and likely actions and times of actions taken by said generic users, and selecting one of said data sets as a set of information to use for the current time.

5. A method as in claim 1, wherein said data structure also includes information indicative of a time between a first action and a second action.

6. A method as in claim 1, wherein said data structure includes times that are spaced by different amounts of granularity depending on time of day, so that a first amount of granularity between times is present at a first time of day, and a second amount of granularity between times is used at a second time of day.

7. A method as in claim 1, wherein said taking an action comprises starting a computer program prior to receiving a request to start the computer program.

8. A method as in claim 1, further comprising increasing a likelihood that the action will be taken at a first time when said user takes the action at the first time, and decreasing the likelihood that the action will be taken at the first time when the user does not take the action at the first time.

9. A method comprising:

in a computer-based device, storing a data structure which includes information about a plurality of specific actions and a plurality of specific times, said information defining a likelihood that one of said actions will be carried out at one of said times;

using the computer based device for comparing a current time to said times in said data structure;

determining an action which is probabilistically likely to happen in the computer based device at an operation time, where said operation time includes at least one of a current time and times subsequent to said current time; and

taking an action on the computer based device, based on what is most likely to happen at said operation time, prior to said action actually happening, wherein said action comprises determining that a program is likely to be started, and responsive to determining that the program is likely to be started, loading at least some part of said program into a memory prior to the program being actually started.

10. A method as in claim 9, wherein said data structure includes information about specific actions requested by a user to be taken, and wherein said action comprises loading said part of said program into said memory without said user requesting the program be loaded into memory.

11. A method comprising:

in a computer-based device, storing a data structure which includes information about a plurality of specific actions and a plurality of specific times, said information defining a likelihood that one of said actions will be carried out at one of said times;

using the computer based device for comparing a current time to said times in said data structure;

determining an action which is probabilistically likely to happen in the computer based device at an operation time, where said operation time includes at least one of a current time and times subsequent to said current time; and

taking an action on the computer based device, based on what is most likely to happen at said operation time, prior to said action actually happening, wherein said action comprises determining a likelihood of how likely it is that the computer will be used at said operation time, automatically selecting an aggressive sleep state for a first likelihood that the computer will be used and automatically selecting a less aggressive sleep state for a second likelihood that the computer will be used.

12. A method as in claim 11, wherein said data structure includes information about specific actions requested by a user to be taken, and wherein said action comprises using a different aggressiveness of sleep state depending on what the user is likely to do.