Statistical models and methods to support the personalization of applications and services via consideration of preference encodings of a community of users

• US 7,774,349 B2
• Filed: 06/30/2004
• Issued: 08/10/2010
• Est. Priority Date: 12/11/2003
• Status: Expired due to Fees

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Subramani, Murugesan S., Horvitz, Eric J., Apacible, Johnson T.
• Primary Examiner(s): Vo; Tim T.
• Assistant Examiner(s): Ahn; Sangwoo
• Application Number:
  US10/882,867
• Publication Number:
  US 20050132014A1
• Time in Patent Office: 2,232 Days
• Field of Search: 707 1- 10
• US Class Current: 707/749
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising

Abstract

A statistical methodology is employed for assisting people with the setting of parameters of software applications or services. With the method, information about demographics and/or about the complete or partial preferences of other people, are analyzed to infer recommendations for settings and functionality of a computer application or service. A system is reviewed with the ability to receive data regarding a plurality of users, and stores respective profiles for these users in a community store. The system can leverage off of these completed and/or partially completed profiles of parameters representing preferences about software operation in connection with building new profiles for users (new and/or existing). Data regarding a user that desires to build a new profile is employed in connection with the community profiles to facilitate the user building a personalized profile. Various statistical and/probabilistic schemes can be employed, for example, collaborative filtering techniques to identify to the user the top n settings by particular parameter(s), top m settings by popularity, top x most similar profiles to facilitate the user selecting most appropriate sub-profiles as part of a personalized profile building and selection effort.

Claims

1. A system that facilitates generation of a system profile, comprising:

a storage component that receives data relating to respective existing profiles of a community of disparate users, the existing profiles are generated by a plurality of client computers and represent application configuration settings used by the respective users of the client computers;

an analyzer that processes the existing profile data for the community of users in view of demographic data of a first user and selects a subset of the existing profiles to present to the first user based on similarities between the first user and the respective users in the community;

a filter component that applies collaborative filtering in accordance with the analyzer to process previous system settings preferences of existing users in the community to predict likely or possible settings or profiles for new users of a system, the filter component identifies software settings or preferences about context-sensitive computing that are applicable to an application employed by the first user; and

a user interface that displays the subset of existing profiles selected by the analyzer, the user interface having at least one input to select from the displayed subset of profiles, the selected profile is used to configure the application settings for the first user;

wherein

the profiles include user definitions of a cost of interruption associated with each of a set of activities defined in a communications application, and the filter component selects at least one of the profiles for presentation to the first user based on a calculated similarity between the cost of interruption definitions in the existing profiles and the first user'"'"'s cost of interruption definitions, wherein selection of the at least one profile by the first user applies the configuration settings defined in the selected profile to the communications application employed by the first user.

2. The system of claim 1, the analyzer employs collaborative filtering to select the subset of existing profiles to present to the first user.

3. The system of claim 1, the existing profiles are generated from a plurality of client computers belonging to the users in the community that generate profile settings in accordance with various applications.

4. The system of claim 3, the applications include communications systems, general computing system, operating system settings, development system applications, and applications employing configuration or operation settings that are applied to customize the applications according to users preferences.

5. The system of claim 1, the analyzer applies statistical processes, mathematical processes, or models to the storage component to determine one or more existing profiles to be displayed for selection at the user interface.

6. The system of claim 1, the filter component includes one or more algorithms including memory based methods, model-based methods, and hybrid methods employing portions of the memory and model based methods.

7. The system of claim 1, the filter component employs explicit or implicit voting to determine the system settings preferences of disparate users in the community in order to predict the likely or possible settings or profiles for new users of the system.

8. The system of claim 7, the filtering component determines votes of an active user in the community of users based on partial information regarding the active user and a set of weights calculated from a user database.

9. The system of claim 1, the filter component employs at least one of a Bayesian classifier or a Bayesian network to determine a potential profile.

10. The system of claim 1, the filter component employs inference techniques or statistical clustering methods to reason about a likelihood that a user with some preferences or demographic information would agree with other previously unspecified settings or preferences.

11. The system of claim 1, the application processes context, including time of day, day of week, a call priority of individuals, and groups of people.

12. The system of claim 1, the application employs cost-benefit rules for routing messages between parties.

13. The system of claim 1, the analyzer determines a recommended profile for the first user based on demographic information of the first user, according to a popularity of the existing profiles, according to similarity between the existing profiles and the first user'"'"'s demographic information, and according to settings associated with a parameter.

14. The system of claim 1, further comprising a profile assistant interface that provides recommended profile settings to the first user.

15. The system of claim 14, the profile assistant is a web-based application.

16. A computer readable medium having computer readable instructions stored thereon for implementing the components of claim 1.

17. A method for automatically generating a preference profile, comprising:

employing a processor executing computer-executable instructions stored on a computer-readable storage medium to implement the following acts;

storing a plurality of preference settings for a communications application in a database, the plurality of preference settings are those used by a corresponding plurality of users of the communications application and are employed to configure the communications application, the preference settings including user definitions of a cost of interruption associated with each of a set of activities defined in a communications application;

automatically applying collaborative filtering to the database to process previous system settings preferences of the plurality of users to predict likely or possible settings or profiles for new users to determine a subset of the plurality of preference settings for presentation to a new user of the communications application;

identifying software settings or preferences about context-sensitive computing that are applicable to an application employed by the new user;

selecting one of the subset of preference settings for presentation to the new user based at least in part on similarities between cost of interruption definitions indicated by the new user and the cost of interruption definitions employed by the plurality of users for the communications application;

configuring the communications application for the new user using the selected preference setting.

18. A system embodied on a computer-readable storage medium for automatically generating a preference profile, comprising:

means for aggregating existing configurations employed by a community of disparate users for a computer or a computer application, each existing configuration corresponding to a disparate user in the community and including a user definition of a cost of interruption associated with each of a set of activities defined in a communications application;

means for filtering the existing configurations to process previous system settings preferences of the community of disparate users to predict likely or possible settings or profiles for new users, the means for filtering identifies software settings or preferences about context-sensitive computing that are applicable to an application employed by a new user;

means for selecting one of the potential subset of configuration settings based on calculated similarities between the cost of interruption definitions in the existing configurations and a new user'"'"'s cost of interruption definitions to determine a potential subset of configuration settings for use by the new user;

means for configuring the new user'"'"'s computer or computer application using the selected configuration setting;

means for updating the new user'"'"'s configuration with the selected configuration setting; and

means for refiltering the existing configurations based on the updated configuration.