Personalizing user interfaces across operating systems

• US 7,089,499 B2
• Filed: 02/28/2001
• Issued: 08/08/2006
• Est. Priority Date: 02/28/2001
• Status: Expired due to Fees

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Trewin, Sharon M., Steichen, Jennifer L., Kim, Myung W.
• Primary Examiner(s): Kincaid, Kristine
• Assistant Examiner(s): Zhou, Ting
• Application Number:
  US09/794,338
• Publication Number:
  US 20020118223A1
• Time in Patent Office: 1,987 Days
• Field of Search: 345/707, 345/744, 345/745, 345/746, 345/747, 715/744, 715/745, 715/746, 715/747, 715/748, 715/707, 706/11, 706/15, 706/46
• US Class Current: 715/744
• CPC Class Codes: G06F 3/033 Pointing devices displaced or positioned by the user , e.g. mice, trackballs, pens or joysticks; Accessories therefor digitisers characterised by the transducing means G06F3/041
• CPC Class Codes: G06F 3/0489 using dedicated keyboard keys or combinations thereof
• CPC Class Codes: G09B 5/00 Electrically-operated educational appliances working with questions and answers G09B7/00; simulators G09B9/00; advertising or displaying in general G09F

Abstract

A user-centered interface agent learns user preferences and typical behaviors and, based on what is learned, predicts the user'"'"'s preferred user interface for different types of host computers. The interface agent consists of a learning program which operates on the user'"'"'s primary computer, a shadow program which is installed on a Personal Digital Assistant (PDA), and a remote program which operates on host computers. The PDA transfers data between the primary and remote machines, and can also be used as the user'"'"'s primary computer. On the primary computer, the agent learns a user'"'"'s preferences automatically by observing the user'"'"'s actions, requiring minimal initialization by the user. The learning algorithm may be statistical, rule-based, case-based, neural network, or employ any other technique for reasoning under uncertainty. The automated personalizing of a user interface configuration has a particular advantage for individuals with disabilities who require configuration before they can use a new computer system.

Claims

1. A computer User Interface Agent comprising:

computer implemented means for learning computer user preferences and behaviors on a primary computer based upon automated observation of said user'"'"'s use of a user interface on said primary computer without forcing the user to explicitly teach the Agent; and

computer implemented means for reasoning from a) the learned preferences and behaviors and b) a host computer'"'"'s user interface capabilities in order to predict a preferred interface of said user on the host computer, said learned preferences on the primary computer being preferences for selected values of user interface settings on the primary computer and said predicted preferences on the host computer being preferences for selected values of user interface settings on the host computer, said primary computer settings and selected values being different from said host computer settings and selected values, said reasoning means being able to translate from said primary computer settings and selected values to a closest available set of said host computer settings and selected values where ideal primary computer settings are not available because of said differences,

wherein said translation by said reasoning means employs a technique for reasoning under uncertainty to obtain said closest available set of host computer settings.

2. The computer User Interface Agent according to claim 1, wherein said means for learning comprises a software module which downloads user preferences existing on the primary computer and observes user behavior in using the primary computer, the means for learning including storing means for storing data on preferences and behavior.

3. The computer User Interface Agent according to claim 2, wherein said storing means stores data in operating system independent format.

4. The computer User Interface Agent according to claim 3, wherein said means for reasoning comprises a software module which accesses data stored by said storing means and accesses information of the host computer'"'"'s hardware and software capabilities and generates a user interface on the host computer which most closely approximates the user interface on the primary computer, and wherein said technique for reasoning under uncertainty is a neural network.

5. The computer User Interface Agent according to claim 4, further comprising a utility program running on the host computer providing information on the host computer'"'"'s hardware and software capabilities and responding to the means for reasoning to generate the user interface on the host computer.

6. The computer User Interface Agent according to claim 5, wherein the User Interface Agent runs on a personal digital assistant (PDA) which is first connected to the primary computer to learn user preferences and behaviors and then connected to the host computer to predict the user'"'"'s preferred interface.

7. The computer User Interface Agent according to claim 5, wherein the User Interface Agent runs on the primary computer to first learn user preferences and behaviors and subsequently, through a remote connection to the host computer, to predict the user'"'"'s preferred interface on the host computer.

8. A method for personalizing user interfaces across operating systems comprising the steps of:

learning by a computer a user'"'"'s preferences and behavior on a primary computer based upon automated observation of said user'"'"'s use of a user interface on said primary computer without forcing the user to explicitly teach the computer;

storing data defining the learned preferences and behavior; and

reasoning by a computer from a) the stored learned preferences and behavior and b) knowledge of a host computer'"'"'s user interface capabilities to predict a user'"'"'s preferred interface on the host computer, said learned preferences on the primary computer being preferences for selected values of user interface settings on the primary computer and said predicted preferences on the host computer being preferences for selected values of user interface settings on the host computer, said primary computer settings and selected values being different from said host computer settings and selected values, said reasoning means being able to translate from said primary computer settings and selected values to a closest available set of said host computer settings and selected values where ideal primary computer settings are not available because of said differences,

wherein said translation by said reasoning means employs a technique for reasoning under uncertainty to obtain said closest available set of host computer settings.

9. The method for personalizing user interfaces across operating systems according to claim 8, wherein the stored data is in a format independent of operating systems.

10. The method for personalizing user interfaces across operating systems according to claim 9, wherein the step of learning is performed by a software learning module running on a personal digital assistant (PDA), the software learning module operating to download user preferences existing on the primary computer and to observe user behavior in using the primary computer.

11. The method for personalizing user interfaces across operating systems according to claim 10, wherein the step of reasoning is performed by a software reasoning module running on the PDA which accesses stored data and accesses information of the host computer'"'"'s hardware and software capabilities and generates a user interface on the host computer that most closely approximates the user interface on the primary computer, and wherein said technique for reasoning under uncertainty is a neural network.

12. The method for personalizing user interfaces across operating systems according to claim 11, further comprising the step of running a utility program running on the host computer to provide information on the host computer'"'"'s hardware and software capabilities that is accessed by the reasoning software module to generate the user interface on the host computer.

13. The method for personalizing user interfaces across operating systems according to claim 9, wherein the step of learning is performed by a software learning module running on the primary computer, the software learning module operating to download user preferences existing on the primary computer and to observe user behavior in using the primary computer.

14. The method for personalizing user interfaces across operating systems according to claim 13, wherein the step of reasoning is performed by a software reasoning module running on the primary computer which accesses stored data and accesses information of the host computer'"'"'s hardware and software capabilities and generates a user interface on the host computer that most closely approximates the user interface on the primary computer.

15. The method for personalizing user interfaces across operating systems according to claim 14, further comprising the step of running a utility program running on the host computer to provide information on the host computer'"'"'s hardware and software capabilities that is accessed by the reasoning software module to generate the user interface on the host computer.

16. An interface agent that improves accessibility of computers running different operating systems for users with disabilities comprising:

computer implemented means for automatic learning of computer user preferences and behaviors on a primary computer, said means for learning further comprising means for observing a user'"'"'s actions without forcing the user to explicitly teach the interface agent, said actions including at least keystrokes and error correction behavior; and

computer implemented means for reasoning from a) the learned preferences and behaviors and b) a host computer'"'"'s capabilities in order to predict and automatically implement said user'"'"'s preferred interface on the host computer, said learned preferences on the primary computer being preferences for selected values of settings on the primary computer and said predicted preferences on the host computer being preferences for selected values of settings on the host computer, said primary computer settings and selected values being different from said host computer settings and selected values, said reasoning means being able to translate from said primary computer settings and selected values to a closest available set of said host computer settings and selected values where ideal primary computer settings are not available because of said differences,

wherein said translation by said reasoning means employs a technique for reasoning under uncertainty to obtain said closest available set of host computer settings.

17. The interface agent according to claim 16, wherein said means for learning comprises a software module which downloads user preferences from the primary computer and observes user behavior in using the primary computer, the means for learning including storing means for storing data in operating system independent format on preferences and behavior.

18. The interface according to claim 17, wherein said means for reasoning comprises a software module which accesses data stored by said storing means and accesses information of the host computer'"'"'s hardware and software capabilities and generates a user interface on the host computer which most closely approximates the user interface on the primary computer, and wherein said technique for reasoning under uncertainty is a neural network.

19. The interface according to claim 18, further comprising a utiity program running on the host computer providing information on the host computer'"'"'s hardware and software capabilities and responding to the means for reasoning to generate the user interface on the host computer, said reasoning software module further including a utility software module which may be installed on the host computer to implement essential preferences for the disabled user on the host computer where the operating system of the host computer does not support the essential preferences and the utility program running on the host computer translates the essential preferences into application program interface (API) functions calls on the host computer.

20. The interface according to claim 19, wherein the utility software module includes assistance to the disabled user for installing the utility software module.