Patent application number | Description | Published |
20090094263 | ENHANCED UTILIZATION OF NETWORK BANDWIDTH FOR TRANSMISSION OF STRUCTURED DATA - Systems and methods are described that improve the efficiency of byte caching mechanisms when transmitting or receiving structured data. Some of these techniques may normalize the structured data before transmission over the network. Other techniques may use templates or semantic differences. | 04-09-2009 |
20110201387 | REAL-TIME TYPING ASSISTANCE - An apparatus and method are disclosed for providing feedback and guidance to touch screen device users to improve the text entry user experience and performance through the use of indicators such as feedback semaphores. Also disclosed are suggestion candidates, which allow a user to quickly select next words to add to text input data, or replacement words for words that have been designated as incorrect. According to one embodiment, a method comprises receiving text input data, providing an indicator for possible correction of the text input data, displaying suggestion candidates associated with alternative words for the data, receiving a single touch screen input selecting one of the suggestion candidates, and modifying the input data using the word associated with the selected suggestion candidate. | 08-18-2011 |
20110202836 | TYPING ASSISTANCE FOR EDITING - Apparatus and methods are disclosed for providing feedback and guidance to touch screen device users to improve the text entry user experience and performance. According to one embodiment, a method comprises receiving a text entry, receiving input on a touch screen in the form of a first single touch input located over a word of previously entered text, and presenting the user with one or more suggestion candidates indicated possible replacement words related to the selected word. The user can then select one of the suggestion candidates using a second single touch input to replace the selected word with a word associated with the selected suggestion candidate. | 08-18-2011 |
20110202876 | USER-CENTRIC SOFT KEYBOARD PREDICTIVE TECHNOLOGIES - An apparatus and method are disclosed for providing feedback and guidance to touch screen device users to improve text entry user experience and performance by generating input history data including character probabilities, word probabilities, and touch models. According to one embodiment, a method comprises receiving first input data, automatically learning user tendencies based on the first input data to generate input history data, receiving second input data, and generating auto-corrections or suggestion candidates for one or more words of the second input data based on the input history data. The user can then select one of the suggestion candidates to replace a selected word with the selected suggestion candidate. | 08-18-2011 |
20120304124 | CONTEXT AWARE INPUT ENGINE - Context aware input engines are provided. Through the use of such engines, various input elements may be determined based on analyzing context. A variety of contexts may be analyzed in determining input elements. Contexts may include, for example, a communication recipient, a location, a previous user interaction, a computing device being utilized, or any combination thereof. Such contexts may be analyzed to advantageously provide an input element to a user. Input elements may include, for example, an onscreen keyboard of a certain layout, an onscreen keyboard of a certain language, a certain button, a voice recognition module, or text-selection options. One or more such input elements may be provided to the user based on analyzed context. | 11-29-2012 |
20130198115 | CLUSTERING CROWDSOURCED DATA TO CREATE AND APPLY DATA INPUT MODELS - The collection and clustering of data input characteristics from a plurality of computing devices is provided. The clustered data input characteristics define user groups to which users are assigned. Input models such as language models and touch models are created for, and distributed to, each of the user groups based on the data input characteristics of the users assigned thereto. For example, an input model may be selected for a computing device based on a current context of the computing device. The selected input model is applied to the computing device during the current context to alter the interpretation of input received from the user via the computing device. | 08-01-2013 |
20130339283 | STRING PREDICTION - In a mobile device, the text entered by users is analyzed to determine a set of responses commonly entered by users into text applications such as SMS applications in response to received messages. This set of responses is used to provide suggested responses to a user for a currently received message in a soft input panel based on the text of the currently received message. The suggested responses are provided before any characters are provided by the user. After the user provides one or more characters, the suggested responses in the soft input panel are updated. The number of suggested responses displayed to the user in the soft input panel is limited to a total confidence value to reduce user distraction and to allow for easier selection. An undo feature for inadvertent selections of suggested responses is also provided. | 12-19-2013 |
20130339983 | CREATION AND CONTEXT-AWARE PRESENTATION OF CUSTOMIZED EMOTICON ITEM SETS - Embodiments provide context-aware inclusion of emoticon item sets in applications and/or services. The emoticon item sets include a plurality of emoticon images or other emoticons. A computing device creates custom emoticon item sets for each of the applications. Based on a determined execution context, the computing device selects the emoticon item set and presents the selected emoticon item set for use within the execution context by a user of the computing device. | 12-19-2013 |
20140032206 | GENERATING STRING PREDICTIONS USING CONTEXTS - In a mobile device, a context is determined for the mobile device. The context is determined based on a variety of characteristics of the mobile device environment including, for example, the current application being used, any contacts that a user of the mobile device is interacting with or having a conversation with, the current date and/or time, a current topic of the conversation, a current style of the conversation, etc. Based on a set of strings associated with the determined context and user generated text, one or more string predictions are generated for the user generated text. The string predictions may be presented to the user as suggested completions of the user generated text. | 01-30-2014 |
20140267045 | Adaptive Language Models for Text Predictions - Adaptive language models for text predictions are described herein. In one or more implementations, text prediction candidates corresponding to detected text characters are generated according to an adaptive language model. The adaptive language model may be configured to include multiple individual language model dictionaries having respective scoring data that is combined together to rank and select prediction candidates for different interaction scenarios. In addition to a pre-defined general population dictionary, the dictionaries may include a personalized dictionary and/or interaction-specific dictionaries that are learned by monitoring a user's typing activity to adapt predictions to the user's style. Combined probabilities for predictions are then computed as a weighted combination of individual probabilities from multiple dictionaries of the adaptive language model. In an implementation, dictionaries corresponding to multiple different languages may be combined to produce multi-lingual predictions. | 09-18-2014 |
20140278349 | Language Model Dictionaries for Text Predictions - Techniques are described to generate text prediction candidates corresponding to detected text characters according to an adaptive language model that includes multiple individual language model dictionaries. Respective scoring data from the dictionaries is combined to select prediction candidates in different interaction scenarios. In an implementation, dictionaries corresponding to multiple different languages are combined to produce multi-lingual predictions. Predictions for different languages may be weighted proportionally according to relative usage by a user. Weights used to combine contributions from multiple dictionaries may also depend upon factors such as how recently a word is used, number of times used, and so forth. Further, the dictionaries may include interaction-specific dictionaries that are learned by monitoring a user's typing activity to adapt predictions to corresponding usage scenarios. Interaction-specific dictionaries may be applied selectively for predictions in respective usage scenarios, including interaction with a particular application, application type, person, contact group, or location. | 09-18-2014 |
20140310213 | USER-CENTRIC SOFT KEYBOARD PREDICTIVE TECHNOLOGIES - An apparatus and method are disclosed for providing feedback and guidance to touch screen device users to improve text entry user experience and performance by generating input history data including character probabilities, word probabilities, and touch models. According to one embodiment, a method comprises receiving first input data, automatically learning user tendencies based on the first input data to generate input history data, receiving second input data, and generating auto-corrections or suggestion candidates for one or more words of the second input data based on the input history data. The user can then select one of the suggestion candidates to replace a selected word with the selected suggestion candidate. | 10-16-2014 |