Human-to-mobile interfaces
First Claim
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.
1 Assignment
0 Petitions
Accused Products
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.
-
Citations
27 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. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
-
-
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. - View Dependent Claims (14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27)
-
Specification