MULTI-DIMENSIONAL INFORMATION ENTRY PREDICTION

• US 20140067731A1
• Filed: 09/06/2012
• Published: 03/06/2014
• Est. Priority Date: 09/06/2012
• Status: Abandoned Application

• Current Assignee: Scott Adams
• Original Assignee: Scott Adams
• Inventors: ADAMS, Scott
• Application Number:
  US13/605,314
• Publication Number:
  US 20140067731A1
• Time in Patent Office: Days
• US Class Current: 706/12
• CPC Class Codes: G06F 40/274 Converting codes to words; Guess-ahead of partial word inputs
• CPC Class Codes: G06N 20/00 Machine learning

Abstract

Intended meanings of user input character strings having multiple interpretations and having a single intended meaning are predicted in real time as they are entered by applying a profile thereto. The profile is generated by application of unsupervised and supervised learning techniques which identify predictive factors. Substantially simultaneously with application of the profile to the character strings, a plurality of remotely located profiles are accessed. The remotely located profiles are determined by application of supervised and unsupervised techniques to a plurality of third parties and are identified and ranked to determine those profiles that most nearly match one or more predictive factors in the user profile, where the predictive factors are weighted based on the ranking, the weighted predictive factors are combined with the user profile to determine the intended meaning of the character string from among the multiple interpretations, and the intended meaning is displayed to the user.

Claims

1. A computer implemented method for predicting intended meanings in real time from input character strings that have multiple interpretations, comprising:

providing a processor for receiving a plurality of user inputs from an input device, said user inputs comprising character strings that have multiple interpretations as entered and that have a single intended meaning;

said processor applying a profile to said character strings to predict said intended meaning thereof;

said processor generating said profile by application of an unsupervised learning technique in which user interaction and interaction context with said device are both observed and noted, and by application of a supervised learning technique comprising a processor implemented user survey, said processor executing said survey locally at said device to generate said user profile and to store said user profile at said device;

said unsupervised and supervised learning techniques identifying and applying at least two predictive factors; and

substantially simultaneously with application of said profile to said character strings, said processor accessing a plurality of remotely located profiles via a network, said remotely located profiles being determined by application of supervised and unsupervised techniques to a plurality of third parties; and

said processor identifying and ranking said remotely located profiles to determine those profiles that most nearly match one or more predictive factors in said user profile, weighting said predictive factors based on said ranking, combining said weighted predictive factors with said user profile to determine the intended meaning of said character string from among said multiple interpretations, and displaying said intended meaning to said user with those characters within said character string which have been determined by prediction highlighted.

2. The method of claim 1, said at least two predictive factors comprising any two or more of:

gender;

education level;

family and friends;

occupation/industry;

hobbies;

intended audience/recipient;

location;

style;

age;

intelligence;

favorite words often used;

most often mistyped keys; and

type and style of writing.

3. The method of claim 1, wherein said input device comprises any of a keyboard, touch or stylus text entry device, gesture responsive device, voice responsive device, or combination thereof.

4. The method of claim 1, said processor configured for user selection of a character string that contains highlighted characters and, in response to such selection, presenting said user with a ranked list of likely candidates from which said user can select the user'"'"'s intended meaning if a predicted interpretation initially presented to the user is not the user'"'"'s intended meaning.

5. The method of claim 4, said processor configured to capture said user selection and update said user'"'"'s profile.

6. The method of claim 4, said processor configured to provide said user selection information as a remote profile that is accessible by third parties.

7. An apparatus for predicting intended meanings in real time from input character strings that have multiple interpretations, comprising:

a processor configured for receiving a plurality of user inputs from an input device, said user inputs comprising character strings that have multiple interpretations as entered and that have a single intended meaning;

said processor configured for applying a profile to said character strings to predict said intended meaning thereof;

said processor configured for generating said profile by application of an unsupervised learning technique in which user interaction and interaction context with said device are both observed and noted, and by application of a supervised learning technique comprising a processor implemented user survey, said processor executing said survey locally at said device to generate said user profile and to store said user profile at said device;

said unsupervised and supervised learning techniques identifying and applying at least two predictive factors; and

said processor configured for, substantially simultaneously with application of said profile to said character strings, accessing a plurality of remotely located profiles via a network, said remotely located profiles being determined by application of supervised and unsupervised techniques to a plurality of third parties; and

said processor configured for identifying and ranking said remotely located profiles to determine those profiles that most nearly match one or more predictive factors in said user profile, weighting said predictive factors based on said ranking, combining said weighted predictive factors with said user profile to determine the intended meaning of said character string from among said multiple interpretations, and displaying said intended meaning to said user with those characters within said character string which have been determined by prediction highlighted.

8. The apparatus of claim 7, said at least two predictive factors comprising any two or more of:

gender;

education level;

family and friends;

occupation/industry;

hobbies;

intended audience/recipient;

location;

style;

age;

intelligence;

favorite words often used;

most often mistyped keys; and

type and style of writing.

9. The apparatus of claim 7, wherein said input device comprises any of a keyboard, touch or stylus text entry device, gesture responsive device, voice responsive device, or combination thereof.

10. The apparatus of claim 7, said processor configured for user selection of a character string that contains highlighted characters and, in response to such selection, presenting said user with a ranked list of likely candidates from which said user can select the user'"'"'s intended meaning if a predicted interpretation initially presented to the user is not the user'"'"'s intended meaning.

11. The apparatus of claim 10, said processor configured to capture said user selection and update said user'"'"'s profile.

12. The apparatus of claim 10, said processor configured to provide said user selection information as a remote profile that is accessible by third parties.