Adaptive input interface
First Claim
1. A system for predicting user text input in an electronic environment, comprising:
- one or more device processors; and
a memory device including instructions that, when executed by the one or more device processors, cause the system to;
receive, over a communications network, the user text input;
access a text repository storing a plurality of text items classified according to a Bayesian network;
infer one or more input predictions through, at least in part, locating the user text input in the Bayesian network;
transmit data, over the communications network, including a suggested text based at least in part on the user text input and the inferred one or more input predictions;
receive, over the communications network, an indication of a user override of the suggested text, the user override including one or more entries of a backspace key and replacement user text input; and
update a probability of at least one node of the Bayesian network corresponding to the user override,wherein the probability of the at least one node is based at least in part upon an average probability of one or more other nodes of the Bayesian network when the at least one node is a new node of the Bayesian network, the one or more other nodes corresponding to a same intermediary node of the Bayesian network as the at least one node.
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Abstract
User input on a computing device can be intelligently predicted using one or more learning algorithms. When user text input is received, an input repository comprising a plurality of text items is accessed. The plurality of text items includes a plurality of user-specific text items, which are classified according to a probabilistic model. One or more input predictions are inferred by applying the probabilistic model to the user text input. A suggested text input is presented using an output element of the computing device. The suggested text input is based on the user text input and one or more text items from the input repository. Additional input is received which overrides the suggested text. Any text associated with the user override is then classified within the probabilistic model, thereby updating the input repository based on the user override.
64 Citations
25 Claims
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1. A system for predicting user text input in an electronic environment, comprising:
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one or more device processors; and a memory device including instructions that, when executed by the one or more device processors, cause the system to; receive, over a communications network, the user text input; access a text repository storing a plurality of text items classified according to a Bayesian network; infer one or more input predictions through, at least in part, locating the user text input in the Bayesian network; transmit data, over the communications network, including a suggested text based at least in part on the user text input and the inferred one or more input predictions; receive, over the communications network, an indication of a user override of the suggested text, the user override including one or more entries of a backspace key and replacement user text input; and update a probability of at least one node of the Bayesian network corresponding to the user override, wherein the probability of the at least one node is based at least in part upon an average probability of one or more other nodes of the Bayesian network when the at least one node is a new node of the Bayesian network, the one or more other nodes corresponding to a same intermediary node of the Bayesian network as the at least one node. - View Dependent Claims (2, 3)
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4. A computer-implemented method for intelligently predicting user input entered on a computing device, comprising:
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receiving, on the computing device, user text input; accessing a text repository including a plurality of text items classified according to a probabilistic model; inferring, using a processor of the computing device, one or more input predictions by applying the probabilistic model to the user text input; presenting, using a visual output element of the computing device, a suggested text based on the one or more input predictions; receiving, on the computing device, an indication of a user override of the suggested text; and updating at least one probability of the probabilistic model, the at least one probability corresponding to the user override, wherein the at least one probability is based at least in part upon an average probability of one or more other probabilities of the probabilistic model when the user override is a new probability of the probabilistic model, the one or more other probabilities corresponding to the text items that have at least some same text as the user override. - View Dependent Claims (5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16)
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17. A computing device, comprising:
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a processor; at least one input detection element; at least one display element; and a memory device including instructions operable to be executed by the processor to perform a set of actions, enabling the computing device to; receive user text input via the at least one input detection element; compare the user text input against a text repository including a plurality of text items classified according to a probabilistic model to determine at least one predicted input string; provide the at east one predicted input string for display on the at least one display element; receive, via the at least one input detection element, an indication of a user override of the at least one predicted input string; and update at least one probability of the probabilistic model, the at least one probability corresponding to the user override, wherein the at least one probability is based at least in part upon an average probability of one or more other probabilities of the probabilistic model when the user override is a new probability of the probabilistic model, the one or more other probabilities corresponding to the text items that have at least some same text as the user override. - View Dependent Claims (18, 19, 20, 21)
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22. One or more non-transitory computer-readable storage media having collectively stored thereon instructions that, when executed by one or more processors of a network system, cause the network system to at least:
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obtain user text input entered by a user into an electronic device; determine at least one input prediction by applying a probabilistic model to the user text input and selecting one or more associated text items from a text repository classified according to the probabilistic model; transmit information including the at least one input suggestion for presentation to the user on the electronic device; receive an indication of a user override of the at least one input suggestion on the electronic device; and update at least one probability of the probabilistic model, the at least one probability corresponding to the user override, wherein the at least one probability is based at least in part upon an average probability of one or more other probabilities of the probabilistic model when the user override is a new probability of the probabilistic model, the one or more other probabilities corresponding to the one or more associated text items that have at least some same text as the user override. - View Dependent Claims (23, 24, 25)
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Specification