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At block 230, the processor assigns scores (e.g., values) for the predicted strings generated at block 220. A rating assigned to a predicted string displays, for instance, a chance that the user intends to find more input that predicted string, that is, the chance that the anticipated string is the supposed enter, given the already inputted input string. A excessive rating can indicate excessive likelihood, and vice versa, a low rating can point out decrease probability. In those embodiments, a decrease rank value can point out a better rank, that is, a better chance that the predicted string is the input supposed by the person. In some embodiments, the score also is determined by a predetermined pace threshold.

For example, if the string "the" has already been inputted into display, the processor can use the contextual data to find out that a noun or an adjective - as an alternative of a verb - would be the next string after "the". Likewise, if the string "Guy Lafleur performed in the National Hockey" was inputted, based on the context, the processor can decide the following string is more doubtless to be "League". Using the contextual information, the processor can even decide whether or not one or more characters in the enter string are incorrect. For instance, the processor can decide that the inputted character was supposed to be a "w" as a substitute of an "a", given the proximity of these characters on a QWERTY virtual keyboard.

The response time interval is, for example, the time interval that may take a mean consumer to notice the displayed predicted string, learn it, determine whether or not it's the meant string, and select it if it is. In some embodiments, the response time period is a predetermined time interval, corresponding to zero.3 seconds, 0.5 seconds, 1 second, and so forth. In other embodiments, the response time interval may be decided dynamically, for example, by checking how lengthy it took the consumer to react to a quantity of beforehand displayed predicted strings.

The processes and logic flows may also be performed by, and apparatus can also be applied as, particular function logic circuitry, e.g., an FPGA or an ASIC . 1 is an example block diagram of an digital gadget, according to embodiments disclosed herein. Certain options which, for readability, are described in this specification in the context of separate embodiments, may also be provided in combination in a single embodiment. Conversely, numerous options which, for brevity, are described within the context of a single embodiment, can also be provided in a quantity of embodiments separately or in any suitable subcombination.

In some embodiments, the processor uses contextual knowledge for generating a predicted string. Contextual information considers the context during which the enter string is entered. Contextual data can include, for example, information great site about strings previously inputted by the person, grammatical attributes of the enter string , or any combination thereof.

Any known predictive approach or software can be utilized to process the input string and the contextual data in generating the anticipated strings at block 220. In an instance embodiment, the predictor is one of the applications 148 residing in memory 110 of electronic device 100. Accordingly, methodology 200 features a predictor for generating predicted strings comparable to the enter string of characters. It can be appreciated that while the instance embodiments described herein are directed to a predictor program executed by a processor, the predictor can be executed, for example, by a virtual keyboard controller. The processor shows one or more predicted strings on touchscreen 118.