NONSTANDARD LOCALITY-BASED TEXT ENTRY

1 - 20 . (canceled)

21 . A device comprising:

at least one processor; and

at least one module operable by the at least one processor to:

receive a plurality of user input inputs, wherein each respective user input from the plurality of user inputs corresponds to a respective location of a keyboard;

disambiguate the plurality of user inputs to determine at least one word;

output the at least one word for display;

determine a context comprising the at least one word

determine, based at least in part on the context and co-concurrence data, a particular co-current term from a plurality of co-concurrence terms, wherein the co-concurrence data indicates a probability of the particular co-concurrent term based on the context; and

responsive to determining the co-current term, output, based at least in part on the probability of the co-concurrent term, for display, the co-current term as a candidate term in a plurality of candidate terms.

22 . The device of claim 21 , wherein the at least one module is operable by the at least one processor to:

receive a dictionary from a remote computing device, wherein the dictionary includes the co-concurrence data that indicates the probability of the particular co-concurrent term based on the context.

23 . The device of claim 22 , wherein the dictionary comprises the plurality of co-concurrence terms, and wherein the dictionary comprises at least one weighting for at least one co-concurrence event between the co-current term and at least one other term in the plurality of co-concurrence terms.

24 . The device of claim 21 , wherein the co-concurrence data is based at least in part on usage of the device by a user.

25 . The device of claim 21 , wherein the co-concurrence data is indicative of information having an expected usage in combination with one or more matches of a set of possible matches, wherein the at least one module is operable by the at least one processor to:

provide an indication of a probable match from the set of possible matches and the co-concurrence data, wherein the probable match is the co-current term.

26 . The device of claim 25 , wherein the probable match is selected automatically by the device when a score of the probable match exceeds a score of a second-best possible match by a predetermined level.

27 . The device of claim 25 , wherein the at least one module is operable by the at least one processor to:

responsive to obtaining the probable match, increase an occurrence level for the probable match.

28 . A method comprising:

receiving, by a computing device, a plurality of user input inputs, wherein each respective user input from the plurality of user inputs corresponds to a respective location of a keyboard;

disambiguating the plurality of user inputs to determine at least one word;

outputting the at least one word for display;

determining a context comprising the at least one word;

determining, based at least in part on the context and co-concurrence data, a particular co-current term from a plurality of co-concurrence terms, wherein the co-concurrence data indicates a probability of the particular co-concurrent term based on the context; and

responsive to determining the co-current term, outputting, based at least in part on the probability of the co-concurrent term, for display, the co-current term as a candidate term in a plurality of candidate terms.

29 . The method of claim 28 , further comprising:

receiving a dictionary from a remote computing device, wherein the dictionary includes the co-concurrence data that indicates the probability of the particular co-concurrent term based on the context.

30 . The method of claim 29 , wherein the dictionary comprises the plurality of co-concurrence terms, and wherein the dictionary comprises at least one weighting for at least one co-concurrence event between the co-current term and at least one other term in the plurality of co-concurrence terms.

31 . The method of claim 28 , wherein the co-concurrence data is based at least in part on usage of the device by a user.

32 . The method of claim 28 , wherein the co-concurrence data is indicative of information having an expected usage in combination with one or more matches of a set of possible matches, the method further comprising:

providing an indication of a probable match from the set of possible matches and the co-concurrence data, wherein the probable match is the co-current term.

33 . The method of claim 32 , wherein the probable match is selected automatically by the computing device when a score of the probable match exceeds a score of a second-best possible match by a predetermined level.

34 . The method of claim 32 , further comprising:

responsive to obtaining the probable match, increasing an occurrence level for the probable match.

35 . A non-transitory, machine-readable medium encoded with instructions that, when executed, cause at least one processor of a computing device to:

receive a plurality of user input inputs, wherein each respective user input from the plurality of user inputs corresponds to a respective location of a keyboard;

disambiguate the plurality of user inputs to determine at least one word;

output the at least one word for display;

determine a context comprising the at least one word;

determine, based at least in part on the context and co-concurrence data, a particular co-current term from a plurality of co-concurrence terms, wherein the co-concurrence data indicates a probability of the particular co-concurrent term based on the context; and

responsive to determining the co-current term, output, based at least in part on the probability of the co-concurrent term, for display, the co-current term as a candidate term in a plurality of candidate terms.

36 . The non-transitory, machine-readable medium of claim 35 , further encoded with instructions that, when executed, cause the at least one processor of the computing device to:

receive a dictionary from a remote computing device, wherein the dictionary includes the co-concurrence data that indicates the probability of the particular co-concurrent term based on the context.

37 . The non-transitory, machine-readable medium of claim 36 , wherein the dictionary comprises the plurality of co-concurrence terms, and wherein the dictionary comprises at least one weighting for at least one co-concurrence event between the co-current term and at least one other term in the plurality of co-concurrence terms.

38 . The non-transitory, machine-readable medium of claim 35 , wherein the co-concurrence data is based at least in part on usage of the device by a user.

39 . The non-transitory, machine-readable medium of claim 35 , wherein the co-concurrence data is indicative of information having an expected usage in combination with one or more matches of a set of possible matches, and wherein the non-transitory machine-readable medium is further encoded with instructions that, when executed, cause the at least one processor of the computing device to:

provide an indication of a probable match from the set of possible matches and the co-concurrence data, wherein the probable match is the co-current term.

40 . The non-transitory, machine-readable medium of claim 39 , wherein the probable match is selected automatically by the computing device when a score of the probable match exceeds a score of a second-best possible match by a predetermined level.

41 . The non-transitory, machine-readable medium of claim 39 , further encoded with instructions that, when executed, cause the at least one processor of the computing device to:

responsive to obtaining the probable match, increase an occurrence level for the probable match.