Human-to-mobile interfaces

• US 9,798,717 B2
• Filed: 03/23/2006
• Issued: 10/24/2017
• Est. Priority Date: 03/23/2005
• Status: Active Grant

• Current Assignee: Keypoint Technologies (Uk) Limited
• Original Assignee: Keypoint Technologies (Uk) Limited
• Inventors: Motaparti, Sunil, Patel, Sanjay
• Primary Examiner(s): Paula, Cesar
• Assistant Examiner(s): Faber, David
• Application Number:
  US11/887,019
• Publication Number:
  US 20090055732A1
• Time in Patent Office: 4,233 Days
• Field of Search: 715256, 715257, 715259-261, 715271
• CPC Class Codes: G06F 3/0237 using prediction or retrieval techniques
• CPC Class Codes: G06F 40/232 Orthographic correction, e.g. spell checking or vowelisation
• CPC Class Codes: G06F 40/242 Dictionaries
• CPC Class Codes: G06F 40/274 Converting codes to words; Guess-ahead of partial word inputs
• CPC Class Codes: G06F 40/279 Recognition of textual entities

Abstract

A method of character recognition for a mobile telephone having a plurality of data input keys. The method facilitates a reduction in the number of user interactions required to create a given data string to less than the number of characters within the data string. The method includes: storing a set of data strings each with a priority indicator; recognizing an event; looking up the most likely subsequent data string to follow the event from the set of data strings; and ordering the data strings for display based on the priority indicator of that data string. If included in the list, the required subsequent data string is selected. If not included in the list, an event is entered and the steps of recognizing the event, looking up and ordering data strings are repeated. The priority indicator of the selected data string and the set of data strings are updated.

Claims

1. A method of character recognition for a mobile telephone data input apparatus comprising a plurality of data input keys having multi-character indicia, said method adapted to facilitate a reduction in the number of user interactions required to create a given data string to less than the number of characters within said given data string, the method comprising the following steps:

step A comprising storing a set of a plurality of data strings each with a priority indicator associated therewith in a data dictionary, wherein each of the priority indicators is a measure of a plurality of derivatives associated with the data strings, wherein each derivative of the plurality of derivatives is a different one of a plurality of behavioral language properties that measures a different one of a plurality of characteristics of one or more patterns among the plurality of data strings, and wherein the plurality of derivatives are inter-related with each other such that a weight of one of the plurality of derivatives is influenced by a weight of another of the plurality of derivatives;

step B comprising recognizing an event;

step C comprising looking up a most likely subsequent data string to follow the event from the set of the plurality of data strings based on the plurality of derivatives;

step D comprising ordering the plurality of data strings for display based on the priority indicator of the most likely subsequent data string;

step E comprising if a required subsequent data string is included in a list, selecting the required subsequent data string;

step F comprising if the required subsequent data string is not included in the list entering an event and repeating steps B to E;

step G comprising updating the priority indicator of the selected required subsequent data string;

step H comprising updating the set of the plurality of data strings based on the updated priority indicator;

wherein associative maps are maintained between data strings within two or more data dictionaries, the maps being used to dynamically infer associations between data strings based on map statistics, probabilities and analytics; and

a lookup chain is maintained between data dictionaries such that dynamic mapping can be made from one dictionary to another.

2. The method of claim 1, further comprising providing the derivatives as a plurality of etymological derivatives.

3. The method of claim 1, further comprising providing the derivatives to include one or more of a timestamp, a cognitive coherence, a perceptual index, an associative index, a grammar orient, a correlative weight, an inference ratio and a pattern factorization.

4. The method of claim 1, further comprising determining the priority indicator from qualitative and quantitative data related to each data string in the set.

5. The method of claim 1, further comprising determining the priority indicator from one or more of the following:

statistical information;

probability information;

data string analysis information;

dictionary priority;

dictionary chains;

data string maps between other data strings; and

data string translations.

6. The method of claim 1, wherein the step of recognizing an event comprises recognizing one or more of a character, a graph, a multi-graph, a data string, a context, a symbol or any other user or machine generated input.

7. The method of claim 1, further comprising providing the set of the plurality of data strings as said dictionary including a plurality of words, phrases and any other data string which might be used in the communication of a message.

8. The method of claim 7, further comprising adding data strings to the dictionary as they are entered by a user.

9. The method of claim 1, further comprising updating all priority indicators dynamically in real-time.

10. The method of claim 1, further comprising ordering a data string in a first of said data dictionaries that is mapped to a plurality of data strings in one or more other data dictionaries based on the priority indicator to enable selection by a user.

11. The method of claim 1, further comprising displaying a list of the most likely subsequent data string in an order based on the priority indicator to enable the user to select the required subsequent data string.

12. The method of claim 1, further comprising providing the derivatives as a plurality of ontological derivatives.

13. A mobile phone including a character recognition apparatus, the mobile telephone comprising a plurality of data input keys having multi-character indicia, said apparatus adapted to facilitate a reduction in the number of user interactions required to create a given data string to less than the number of characters within said given data string, the apparatus comprising:

a memory, in which a set of a plurality of data strings can be stored, each with a priority indicator associated therewith in a data dictionary, wherein the indicator is a measure of a plurality of derivatives associated with the data strings, wherein each derivative of the plurality of derivatives is a different one of a plurality of behavioral language properties that measures a different one of a plurality of characteristics of one or more patterns among the plurality of data strings, and wherein the plurality of derivatives are inter-related with each other such that a weight of one of the plurality of derivatives is influenced by a weight of another of the plurality of derivatives;

an event recognition module; and

a processor, configured to;

look-up a most likely subsequent data string to follow an event recognized by the event recognition module from the set of the plurality of data strings based on the plurality of derivatives;

output for display a list of the most likely subsequent data string in an order based on the priority indicator of the most likely data string on a display;

select a required subsequent data string if it is included in the list;

receive data entry, wherein the data entered comprises an event;

update the priority indicator of any selected data string and the set of the plurality of data strings based on the updated priority indicator;

wherein associative maps are maintained between data strings within two or more data dictionaries, the maps being used to dynamically infer associations between data strings based on map statistics, probabilities and analytics; and

wherein a lookup chain is maintained between data dictionaries such that dynamic mapping can be made from one dictionary to another.

14. The mobile phone according to claim 13, wherein the plurality of derivatives comprise a plurality of etymological derivatives.

15. The mobile phone according to claim 13, wherein the derivatives include one or more of a timestamp, a cognitive coherence, a perceptual index, an associative index, a grammar orient, a correlative weight, an inference ratio and a pattern factorization.

16. The mobile phone according to claim 13, wherein the priority indicator is determined from qualitative and quantitative data related to each data string in the set.

17. The mobile phone according to claim 13, wherein the priority indicator includes one or more of the following:

statistical information;

probability information;

data string analysis information;

dictionary priority;

dictionary chains;

data string maps between other data strings; and

data string translations.

18. The mobile phone according to claim 13, wherein the event includes one or more of a character, a graph, a multi-graph, a data string, a context, a symbol or any other user or machine generated input.

19. The mobile phone according to claim 13, wherein the set of the plurality of data strings in said dictionary includes a plurality of words, phrases and any other data string which might be used in the communication of a message.

20. The mobile phone according to claim 19, wherein data strings are added to the dictionary as they are entered by a user.

21. The mobile phone according to claim 13, wherein the priority indicators are updated dynamically in real-time.

22. The mobile phone according to claim 13, further comprising a lookup map between two or more data dictionaries such that a given data string in a first of said data dictionaries is mapped to a data string or strings in one or more other data dictionaries for selection by a user.

23. The mobile phone according to claim 22, wherein the processor is further configured to order a data string in a first data dictionary that is mapped to a plurality of data strings in one or more other data dictionaries based on the priority indicator to enable selection by a user.

24. The mobile phone according to claim 13, wherein the most likely subsequent data string are ordered based on the priority indicator to enable the user to select the required subsequent data string.

25. The mobile phone according to claim 13, wherein the processor is further configured to allow a user to selectively enable or disable physical interactivity reduction characteristics of an interface system which facilitate a reduction in a number of key presses required to create a data string.

26. The mobile phone according to 25, wherein the physical interactivity reduction characteristics are selected from the group comprising but not limited to:

automatically entering a space after a selected data string;

limitation of displayed mnemonics to those having a total number of characters greater than the number of key presses required to display said mnemonic on the data display means;

automatically performing forward or backward translations between mnemonics or abbreviations or acronyms and their corresponding full data strings; and

prioritization of the data strings created by any given data input key having multi-character indicia, said prioritization being based on selected qualitative and/or quantitative information relating to an initial character, which matches any of the indicia on the data, input key.

27. The mobile phone according to claim 13, wherein the plurality of derivatives comprise a plurality of ontological derivatives.