CN103488796A - Inputting method based on context and mobile terminal - Google Patents
Inputting method based on context and mobile terminal Download PDFInfo
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- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
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- G06F16/24575—Query processing with adaptation to user needs using context
Abstract
The invention discloses an inputting method based on the context and a mobile terminal. The method comprises the steps of obtaining conversation information of a preset conversation type; analyzing the conversation information of the preset conversation type in order to obtain the vocabulary contained in the conversation information of the preset conversation type; counting the vocabulary contained in the conversation information and ordering the vocabulary contained in the conversation information ahead to obtained the ordered vocabulary; storing the preset conversation type and the ordered vocabulary to the local after the preset conversation type and the ordered vocabulary are associated. By means of the scheme, the vocabulary and the preset conversation type can be associated, so that when a user uses different conversation types, the vocabulary of each conversation type can be respectively used and bound, the relevance between a displayed candidate word and a keyword is improved when the keyword is input, and therefore the input efficiency of the user is improved.
Description
Technical field
The application relates to communication technical field, particularly relates to a kind of based on context method and the mobile terminal of input.
Background technology
Variation along with the smart mobile phone function, and 3G network is universal, people use mobile terminal to carry out interactive scene and also get more and more, as QQ, micro-letter, note, MSN etc., in these application, all use more or less input method, therefore, the user more and more pays close attention to the input efficiency of input method, and the vocabulary in input method directly affects input efficiency as the important component part of input method.Prior art is by the online upgrading dictionary, manually add the method such as vocabulary to enrich dictionary, thereby provides more vocabulary to select for users to the user, to improve input efficiency.Input method vocabulary is abundanter, can list the vocabulary of selecting for the user during input just more, still, dictionary is larger, make the vocabulary that meets the current input of user more and more, the user needs the increasing time to select wanted vocabulary in lexicon, has affected user's input efficiency.For example, when user entered keyword symbol " sx ", input method is at once by candidate's vocabulary: " at first ", " realization ", " shooting ", " going to school " etc. are recommended the user and are selected, but, the user is actual, and what think input is place " Shanxi ", the vocabulary of listing due to input method is a lot, and " Shanxi " this vocabulary will just can find in back very.
In traditional input method, under the same input mode, to all application scenarioss (for example, input Apply Names, newly-built or replied mail etc. in navigator in Input Address, phone directory in inputting contact information, software market) all adopt identical input processing mode, by all vocabulary that will meet active user's input, enumerate to the user, cause the user no matter at which kind of to input under application scenarios, all need to be searched to find needed vocabulary the vocabulary from many, affected user's input efficiency.
Summary of the invention
The technical matters that the application mainly solves is to provide a kind of based on context method and the mobile terminal of input, dictionary and current sessions type association can be got up, thereby make the user when using different conversation type, use respectively the dictionary of this conversation type of binding, improve candidate's vocabulary shown while inputting key character and the degree of correlation of key character, thereby improve user's input efficiency.
For solving the problems of the technologies described above, the technical scheme that the present invention adopts is: a kind of based on context method of input is provided, described method comprises the steps: to obtain the session information of current sessions type, wherein, described conversation type comprises application message and the user profile under described application message of session; Resolve the session information of current sessions type with included vocabulary in the session information that obtains the current sessions type; Add up vocabulary included in described session information, and vocabulary included in described session information is sorted front, to obtain the dictionary after sorting; Dictionary association after described current sessions type and sequence is kept to this locality, when for the user, reusing the session of described current sessions type and inputting key character, sequence in dictionary according to candidate's vocabulary after the sequence with described current sessions type association, preferentially input demonstration to the candidate's vocabulary the preceding that sorts.
Wherein, the session information of parsing current sessions type comprises with the step of vocabulary included in the session information that obtains the current sessions type: obtain the text message in described session information; Resolve sentence by sentence sequentially every text message, to obtain vocabulary included in described text message; The described vocabulary that record obtains after resolving.
Wherein, add up the frequency of occurrences of described vocabulary, and comprise according to the step that the frequency of occurrences of described vocabulary is sorted to obtain the dictionary after sequence: the frequency of occurrences of the described vocabulary after statistics is resolved; According to the frequency of occurrences of described vocabulary, sorted from high to low; Described vocabulary is stored in dictionary by the sequence that frequency occurs, to obtain the dictionary after sorting.
Wherein, also comprise before obtaining the step of session information of current sessions type: determine whether to use for the first time the session of current sessions type; If so, call the acquiescence dictionary and preferentially the candidate's vocabulary the preceding that sorts is inputted to demonstration in the acquiescence dictionary; If not, call the dictionary after sequence and preferentially the candidate's vocabulary the preceding that sorts in the dictionary after sequence inputted to demonstration.
Wherein, in the step of statistics included vocabulary in described session information, specifically comprise: included vocabulary in adding up described session information, and by vocabulary sequence included in described session information front; Add up the frequency of occurrences of vocabulary included in described session information, and, by sequence included in described session information vocabulary the preceding, sorted according to the frequency of occurrences of vocabulary included in described session information, to obtain the dictionary after sequence.
For solving the problems of the technologies described above, another technical solution used in the present invention is: a kind of mobile terminal is provided, and described device comprises: acquisition module, vocabulary parsing module, dictionary administration module, input method module; Described acquisition module is for obtaining the session information of current sessions type, wherein, described conversation type comprises application message and the user profile under described application message of session, and described acquisition module sends the session information of described current sessions type and conversation type to described vocabulary parsing module; Described vocabulary parsing module is for receiving the session information of described current sessions type and conversation type, session information according to described current sessions type and current sessions type, resolve the session information of current sessions type with included vocabulary in the session information that obtains the current sessions type, described vocabulary parsing module sends the vocabulary after described current sessions type and parsing to described dictionary administration module; Described dictionary administration module is for the vocabulary after receiving described current sessions type and resolving, according to included vocabulary in the described session information of the glossary statistic after described parsing, and vocabulary included in described session information is sorted front, to obtain the dictionary after sorting, described dictionary administration module sends the dictionary after described current sessions type and sequence to described input method module; Described input method module is for the dictionary after receiving described current sessions type and sorting, according to described current sessions type with the sequence after dictionary by described current sessions type and the sequence after the associated this locality that is kept at of dictionary, when for the user, reusing the session of described current sessions type and inputting key character, sequence in dictionary according to candidate's vocabulary after the sequence with described current sessions type association, preferentially input demonstration to the candidate's vocabulary the preceding that sorts.
Wherein, described vocabulary parsing module is for obtaining the text message of described session information, resolve sentence by sentence sequentially every text message according to described text message, to obtain vocabulary included in described text message, and the described vocabulary obtained after the record parsing.
Wherein, described glossary statistic module, for adding up the frequency of occurrences of the described vocabulary after parsing, is sorted from high to low according to the frequency of occurrences of described vocabulary, and the described vocabulary after sequence is preferentially come in dictionary, to obtain the dictionary after sequence.
Wherein, described mobile terminal also comprises judge module, and described judge module is for determining whether to use for the first time the session of current sessions type; When described judge module judgment result is that while being, described input method module is also for calling the acquiescence dictionary and preferentially the candidate's vocabulary the preceding that sorts at the acquiescence dictionary being inputted to demonstration; When described judge module when the determination result is NO, described input method module is also for calling dictionary after sequence and preferentially the candidate's vocabulary the preceding that sorts of the dictionary after sequence being inputted to demonstration; Described judge module sends judged result to described input method module.
Wherein, described vocabulary analytical method module is used for adding up the included vocabulary of described session information, and vocabulary included in described session information is sorted front; Described vocabulary analytical method module is also for adding up the frequency of occurrences of the included vocabulary of described session information, and by sequence included in described session information vocabulary the preceding, according to the frequency of occurrences of vocabulary included in described session information, sorted, to obtain the dictionary after sorting.
The invention has the beneficial effects as follows: the situation that is different from prior art, the present invention is by obtaining and resolve the session information of current sessions type and current sessions type, wherein, conversation type comprises application message and the user profile under described application message of session, thereby included vocabulary in the session information of acquisition current sessions type, sequence by vocabulary included in the described session information after resolving is front, and sorted according to the frequency of occurrences of described vocabulary, obtain the dictionary after sorting, be kept at this locality by the dictionary association by after current sessions type and sequence, dictionary and current sessions type association can be got up, thereby make the user when using different conversation type, use respectively the dictionary of this conversation type of binding, improve candidate's vocabulary shown while inputting key character and the degree of correlation of key character, thereby improve user's input efficiency.
The accompanying drawing explanation
Fig. 1 is the method one embodiment process flow diagram that based on context the application inputs;
Fig. 2 is another embodiment process flow diagram of method that based on context the application inputs;
Fig. 3 is the application's mobile terminal one embodiment structural representation;
Fig. 4 is another embodiment structural representation of the application's mobile terminal.
Embodiment
Below in conjunction with accompanying drawing and concrete embodiment, be described.
Consult Fig. 1, Fig. 1 is based on context input method one embodiment process flow diagram of the application.In present embodiment, based on context input method comprises the following steps:
Step S101: the session information that obtains the current sessions type.Wherein, conversation type comprises application message and the user profile under application message of session.
When receiving the session information of current sessions type, obtain the sign of current application message in system and the sign of user profile in system under current application information, determine the current sessions type, and obtain the session information of current sessions type according to the current sessions classification.For example, if the application message of current sessions is " MSN ", the user profile of current sessions under application message is " contact person Jack ", and the current sessions type is: in MSN with the session of contact person Jack; If the application message of current sessions is " QQ ", the user profile of current sessions under application message is " contact person Frank ", and the current sessions type is: in QQ with the session of contact person Frank.
Step S102: the session information of resolving the current sessions type.
Obtain the text message in the session information of current sessions type, and resolve sentence by sentence sequentially every text message, to obtain included vocabulary in text message, and record resolve after resulting vocabulary.
Particularly, first character since first text message, included character in first text message resolved in character one by one sequentially, by that analogy, until resolved included character in last text message in the session information of current sessions type.
First obtain first character and second character that joins successively and to arrange, by whether searching in the corresponding acquiescence dictionary of input method the vocabulary identical by the vocabulary formed with these two characters, take and judge whether these two characters are a vocabulary.
If find the vocabulary identical by the vocabulary formed with these two characters, judge that these two characters are a vocabulary, and this vocabulary is labeled as to the included vocabulary of session information of current sessions type.
If do not find the vocabulary identical by the vocabulary formed with these two characters, judge that these two characters are not a vocabulary.And then obtain again the 3rd character that joins and arrange with these two characters, and, by whether searching in the corresponding acquiescence dictionary of input method the vocabulary identical by the vocabulary formed with these three characters, take and judge whether these three characters are a vocabulary.
If find the vocabulary identical by the vocabulary formed with these three characters, judge that these three characters are a vocabulary, and this vocabulary is labeled as to the included vocabulary of session information of current sessions type.
If do not find the vocabulary identical by the vocabulary formed with these three characters, judge that these three characters are not a vocabulary.And then obtain again the 4th character that joins and arrange with these three characters, and, by whether searching in the corresponding acquiescence dictionary of input method the vocabulary identical by the vocabulary formed with these four characters, take and judge whether these four characters are a vocabulary.
If find the vocabulary identical by the vocabulary formed with these four characters, judge that these four characters are a vocabulary, and this vocabulary is labeled as to the included vocabulary of session information of current sessions type.
If do not find the vocabulary identical by the vocabulary formed with these four characters, judge that these four characters are not a vocabulary.
In view of the previous Chinese vocabulary of order at least comprises two characters, and comprise at the most 4 characters, so, in the present embodiment, if from first character, respectively with join successively rear three characters of arranging it fails to match respectively with first character after, judge that these four characters are not a vocabulary, and stop the terminology match with the first character, to join second character arranging as the first current character with the first character, repeat above-mentioned steps, until resolved last character in first text message.And the like, until resolved included character in last text message in the session information of current sessions type.
If from first character, respectively with join successively latter two character of arranging it fails to match respectively with first character after, but with it, join successively while arranging the 4th character match success, judge that these four characters are a vocabulary, and stop the terminology match with the first character.To join successively second character arranging as the first current character with the first character, repeat above-mentioned steps, until resolved last character in first text message.And the like, until resolved included character in last text message in the session information of current sessions type.
Preferably, if from first character, respectively with join successively latter two character of arranging it fails to match respectively with first character after, but with the 4th the character match success of joining successively and arranging, judge that these four characters are a vocabulary, and after stopping the terminology match with the first character, to join the 5th character arranging as the first current character with the 4th character, repeat above-mentioned steps, until resolved in the session information of current sessions type last character in first text message.After having resolved in the session information of current sessions type first text message, resolve and first second text message that text message is arranged in turn, and the like, until resolved included character in last text message in the session information of current sessions type.
Optionally, at the session information that vocabulary is labeled as to the current sessions type, during included vocabulary, the frequency of occurrences of this vocabulary is added to one, and record resolve after resulting vocabulary.
In other embodiments, a vocabulary also can comprise that 4 more than character, and to form common saying or two-part allegorical saying etc., its specific implementation process and above-mentioned embodiment are similar, do not repeat herein.
Step S103: add up vocabulary included in described session information, and vocabulary included in described session information is sorted front.
Because the probability of the vocabulary occurred in current sessions in follow-up appearance can improve greatly, so according to resulting vocabulary after resolving, included vocabulary in the session information of statistics current sessions type, and vocabulary included in the session information of current sessions type is done to the as a whole foremost that comes the corresponding acquiescence dictionary of current input method, thereby obtain the dictionary after sequence.
Optionally, according to resulting vocabulary after resolving, in the session information of statistics current sessions type, during included vocabulary, can also count the frequency of occurrences of resulting each vocabulary after resolving simultaneously.Correspondingly, after in the session information by the current sessions type, the as a whole foremost that comes the corresponding acquiescence dictionary of current input method done in included vocabulary, can also again be sorted from high to low according to the frequency of occurrences of resulting each vocabulary after resolving, and these vocabulary are stored in dictionary by the sequence that frequency occurs, thereby obtain the dictionary after sequence.
Step S104: the dictionary association after described current sessions type and sequence is kept to this locality.
Dictionary association after current sessions type and sequence is kept to this locality, when for the user, reusing the session of this conversation type and inputting key character, in dictionary according to key character after sequence, search and the corresponding candidate's vocabulary of key character, and the sequence in the dictionary after the sequence associated with this current conversation type according to candidate's vocabulary, preferentially the candidate's vocabulary the preceding that sorts is inputted to demonstration, so that the user therefrom selects the vocabulary of required input.
Consult Fig. 2, Fig. 2 is based on context another embodiment process flow diagram of input method of the application.In the present embodiment, based on context input method comprises the steps:
Step S201: use input method to be inputted key character.
Use current input method to input key character in the session of current sessions type.
Step S202: determine whether to use for the first time the session of current sessions type.
The sign of user profile in system under sign according to current application message in system and current application information, determine the current sessions type.For example, if the application message of current sessions is " MSN ", the user profile of current sessions under application message is " contact person Jack ", and the current sessions type is: in MSN with the session of contact person Jack; If the application message of current sessions is " QQ ", the user profile of current sessions under application message is " contact person Frank ", and the current sessions type is: in QQ with the session of contact person Frank.Because used conversation type can be recorded in this locality, thus can whether be recorded according to the current sessions type, thus determine whether to use for the first time the session of current sessions type.
If not the session of using for the first time the current sessions type, perform step S203.
If use for the first time the session of current sessions type, perform step S208.
Step S203: call the dictionary after sequence.
When judgment result is that of execution of step S202 is not to use for the first time the session of current sessions type, call the dictionary after sequence.
Step S204: the key character that receives user's input.
Receive the key character of user's input.
Step S205: judge whether to find the candidate vocabulary corresponding with key character.
After receiving the key character of user's input, search the candidate vocabulary corresponding with key character in the dictionary of the key character of inputting according to the user after sequence, and judge whether to find the candidate vocabulary corresponding with key character.
If find the candidate vocabulary corresponding with key character, perform step S206.
If do not find the candidate vocabulary corresponding with key character, perform step S208.
Step S206: judge whether the user inputs the candidate vocabulary corresponding with key character found.
When finding the candidate vocabulary corresponding with key character, judge whether the user inputs the candidate dictionary corresponding with key character found.
If the candidate dictionary corresponding with key character that input has found, perform step S207.
If do not input the candidate dictionary corresponding with key character found, perform step S209.
Step S207: preferentially the candidate's vocabulary the preceding that sorts in the dictionary after sequence is inputted to demonstration.
When the user judges the candidate dictionary corresponding with key character that needs input to find, sequence in dictionary according to candidate's vocabulary after the sequence with the current sessions type association, preferentially the candidate's vocabulary the preceding that sorts is inputted to demonstration, so that the user therefrom selects the vocabulary of required input.
Step S208: call the acquiescence dictionary.
When execution of step S202 judgment result is that the session of using for the first time the current sessions type time, call the dictionary after sequence.
When judgment result is that in the dictionary of key character after sequence according to user's input of execution of step S205 can not be found the candidate dictionary corresponding with key character, call the acquiescence dictionary.
Step S209: preferentially the candidate's dictionary the preceding that sorts is inputted to demonstration in the acquiescence dictionary.
Search the candidate vocabulary corresponding with key character according to the key character of user's input in the acquiescence dictionary, and the sequence in the acquiescence dictionary according to candidate's vocabulary, preferentially the candidate's vocabulary the preceding that sorts is inputted to demonstration.
Consult Fig. 3, Fig. 3 is the application's mobile terminal one embodiment structural representation.In the present embodiment, mobile terminal comprises: acquisition module 310, vocabulary parsing module 320, dictionary administration module 330, input method module 340.
Such as, when mobile terminal receives the session information of current sessions type, acquisition module 310 obtains the sign of current application message in system and the sign of user profile in system under current application information, determine the current sessions type, and obtain the session information of current sessions type according to the current sessions classification.For example, if the application message of current sessions is " MSN ", the user profile of current sessions under application message is " contact person Jack ", and the current sessions type is: in MSN with the session of contact person Jack; If the application message of current sessions is " QQ ", the user profile of current sessions under application message is " contact person Frank ", and the current sessions type is: in QQ with the session of contact person Frank.Acquisition module 310 according in MSN with the session of contact person Jack, obtain in MSN the session information with contact person Jack; According in QQ with the session of contact person Frank, obtain in QQ the session information with contact person Frank.
Such as, vocabulary parsing module 320 obtains the text message in the session information of current sessions type, and resolve sentence by sentence sequentially every text message, thereby obtain included vocabulary in text message, and record resolve after resulting vocabulary.
Particularly, vocabulary parsing module 320 is since the first character of first text message, included character in first text message resolved in character one by one sequentially, by that analogy, until resolved included character in last text message in the session information of current sessions type.
If vocabulary parsing module 320 finds the vocabulary identical by the vocabulary formed with these two characters, judge that these two characters are a vocabulary, and this vocabulary is labeled as to the included vocabulary of session information of current sessions type.
If vocabulary parsing module 320 does not find the vocabulary identical by the vocabulary formed with these two characters, judge that these two characters are not a vocabulary.And then obtain again the 3rd character that joins and arrange with these two characters, and, by whether searching in the corresponding acquiescence dictionary of input method the vocabulary identical by the vocabulary formed with these three characters, take and judge whether these three characters are a vocabulary.
If vocabulary parsing module 320 finds the vocabulary identical by the vocabulary formed with these three characters, judge that these three characters are a vocabulary, and this vocabulary is labeled as to the included vocabulary of session information of current sessions type.
If vocabulary parsing module 320 does not find the vocabulary identical by the vocabulary formed with these three characters, judge that these three characters are not a vocabulary.And then obtain again the 4th character that joins and arrange with these three characters, and, by whether searching in the corresponding acquiescence dictionary of input method the vocabulary identical by the vocabulary formed with these four characters, take and judge whether these four characters are a vocabulary.
If vocabulary parsing module 320 finds the vocabulary identical by the vocabulary formed with these four characters, judge that these four characters are a vocabulary, and this vocabulary is labeled as to the included vocabulary of session information of current sessions type.
If vocabulary parsing module 320 does not find the vocabulary identical by the vocabulary formed with these four characters, judge that these four characters are not a vocabulary.
In view of a Chinese vocabulary generally at least comprises two characters, and comprise at the most 4 characters, so, in the present embodiment, if vocabulary parsing module 320 is from first character, respectively with join successively rear three characters of arranging it fails to match respectively with first character after, judge that these four characters are not a vocabulary, and stop the terminology match with the first character, to join second character arranging as the first current character with the first character, repeat above-mentioned steps, until resolved last character in first text message.And the like, until resolved included character in last text message in the session information of current sessions type.
If vocabulary parsing module 320 is from first character, respectively with join successively latter two character of arranging it fails to match respectively with first character after, but and join successively while arranging the 4th character match success with it, judge that these four characters are a vocabulary, and stop the terminology match with the first character.To join successively second character arranging as the first current character with the first character, repeat above-mentioned steps, until resolved last character in first text message.And the like, until resolved included character in last text message in the session information of current sessions type.
Preferably, if vocabulary parsing module 320 is from first character, respectively with join successively latter two character of arranging it fails to match respectively with first character after, but with the 4th the character match success of joining successively and arranging, judge that these four characters are a vocabulary, and after stopping the terminology match with the first character, to join the 5th character arranging as the first current character with the 4th character, repeat above-mentioned steps, until resolved in the session information of current sessions type last character in first text message.After vocabulary parsing module 320 has been resolved in the session information of current sessions type first text message, resolve and first second text message that text message is arranged in turn, and the like, until resolved included character in last text message in the session information of current sessions type.
Optionally, vocabulary parsing module 320 also during included vocabulary, adds one by the frequency of occurrences of this vocabulary for the session information vocabulary being labeled as to the current sessions type, and record resolve after resulting vocabulary.
In other embodiments, a vocabulary can be also to comprise that 4 more than character, and to form common saying or two-part allegorical saying etc., its specific implementation process and above-mentioned embodiment are similar, do not repeat herein.
Such as, because the probability of the vocabulary occurred in current sessions in follow-up appearance can improve greatly, so dictionary administration module 330 is according to resulting vocabulary after resolving, included vocabulary in the session information of statistics current sessions type, and vocabulary included in the session information of current sessions type is done to the as a whole foremost that comes the corresponding acquiescence dictionary of current input method, thereby obtain the dictionary after sequence.
Optionally, vocabulary parsing module 320 is also for according to resulting vocabulary after resolving, and in the session information of statistics current sessions type, during included vocabulary, counts the frequency of occurrences of resulting each vocabulary after resolving simultaneously.Correspondingly, dictionary administration module 330 is also for after at vocabulary parsing module 320, by the session information of current sessions type, the as a whole foremost that comes the corresponding acquiescence dictionary of current input method done in included vocabulary, according to the frequency of occurrences of resulting each vocabulary after resolving, again sorted from high to low, and these vocabulary are stored in dictionary by the sequence that frequency occurs, thereby obtain the dictionary after sequence.For example, if the application message of current sessions is " MSN ", the user profile of current sessions under application message is " contact person Jack ", the current sessions type is: in MSN with the session of contact person Jack, the session information that contact person Jack sends is: yesterday, we went to Sha County to travel, and had removed to eat snack there; The vocabulary occurred in current sessions " Sha County ", " snack " can improve greatly at the probability of follow-up appearance, dictionary administration module 330 makes by vocabulary " Sha County ", " snack " foremost that an integral body comes the corresponding acquiescence dictionary of current input method, thereby obtains the dictionary after sequence.
Such as, input method module 340 is kept at this locality by the dictionary association after current sessions type and sequence, when the user reuses current input method when the current sessions type is carried out session, the key character that input method module 340 is inputted according to the user, search the candidate vocabulary corresponding with key character in dictionary by dictionary administration module 330 after sequence, and the sequence in the dictionary after the sequence associated with this current conversation type according to candidate's vocabulary, preferentially the candidate's vocabulary the preceding that sorts is inputted to demonstration, so that the user therefrom selects the vocabulary of required input.For example, current conversation type is: in MSN, with the session of contact person Jack, the dictionary after sequence is: vocabulary " Sha County ", " snack " are preferentially arranged dictionary the preceding.Input method module 340 by used MSN with associated this locality that remains on of dictionary after the session of contact person Jack and sequence.When the user reuses current input method carry out session with contact person Jack in MSN, input key character " sx " in dialog box, during with input vocabulary " Sha County ", the key character that input method module 340 is inputted according to the user " sx ", search the candidate vocabulary corresponding with key character " sx " in dictionary by dictionary administration module 330 after sequence corresponding to current input method, sequence in dictionary according to candidate's vocabulary after sequence, the preferential candidate's vocabulary the preceding that sorts that shows: " Sha County ", " realization ", " at first ", " be familiar with ", " shooting ", " go to school " etc., therefrom select to need the vocabulary " Sha County " of input for the user.
Consult Fig. 4, Fig. 4 is another embodiment structural representation of the application's mobile terminal.Be different from above-mentioned embodiment, in the present embodiment, mobile terminal comprises: acquisition module 410, vocabulary parsing module 420, dictionary administration module 430, input method module 440, judge module 450.
With the difference of above-described embodiment, be:
Such as, when the user uses when load module 440 provides user interface for the user, acquisition module 410 obtains the sign of current application message in system and the sign of user profile in system under current application information, determine the current sessions type, and obtain the session information of current sessions type according to the current sessions classification.For example, if the application message of current sessions is " MSN ", the user profile of current sessions under application message is " contact person Jack ", and the current sessions type is: in MSN with the session of contact person Jack.When input method module 440 provides the dialog box with the session of contact person Jack for the user.Acquisition module 410 obtains sign and the contact person Jack sign in system of MSN in system, determines the current sessions type, and according in MSN with the session information of the session of the acquisition conversation of contact person Jack and contact person Jack.
If the result of judge module 450 judgements is to be while using for the first time the session of current sessions type, input method module 440 is also for calling the acquiescence dictionary by dictionary administration module 430.
If the result of judge module 450 judgement is for being not while using for the first time the session of current sessions type, input method module 440 is also for calling the dictionary after sequence by dictionary administration module 430.
The judged result that input method module 440 also sends for receiving judge module 450, when for the user, providing user interface, call alternative dictionary according to judged result by dictionary administration module 430.Wherein, alternative dictionary comprises the corresponding acquiescence dictionary of input method, and the dictionary after sequence.
Such as, in input method module 440, for the user provides user interface, the result of the judgement of judge module 450 is to be that while using for the first time the session of current sessions type, input method module 440 is called the acquiescence dictionary by dictionary administration module 430.
When the result of the judgement of judge module 450, for being not while using for the first time the session of current sessions type, input method module 440 is called the dictionary after sequence by dictionary administration module 430.
The key character that input method module 440 is also inputted at user interface for receiving the user, and search the candidate vocabulary corresponding with key character in dictionary according to the key character of user's input after sequence.Such as, when the user reuse current input method in MSN with the dialog box of the session of contact person Jack in while inputting key character " sx ", during with input " Sha County " this vocabulary, input method module 440 receives the key character " sx " that the user inputs, and call the dictionary after sequence by dictionary administration module 430, search the candidate vocabulary corresponding with key character " sx " in the dictionary of key character " sx " after sequence according to user's input.
The result judged when judge module 450 is that while in the dictionary after sequence, having found the candidate vocabulary corresponding with key character, judge module 450 is also for judging whether the user inputs the candidate vocabulary corresponding with key character found.
When the candidate vocabulary corresponding with key character that judge module 450 judgement users input has found, input method module 440 is also for the sequence of the dictionary after sequence according to candidate's vocabulary, preferentially the candidate's vocabulary the preceding that sorts is inputted to demonstration, therefrom select the vocabulary of required input for the user.For example, current conversation type is: in MSN, with the session of contact person Jack, the dictionary after sequence is: vocabulary " Sha County ", " snack " are preferentially arranged dictionary the preceding.Input method module 340 by used MSN with associated this locality that remains on of dictionary after the session of contact person Jack and sequence.When reusing current input method, the user inputs key character " sx " in MSN with in the dialog box of the session of contact person Jack, with input vocabulary " Sha County ", input method module 440 is called the dictionary after sequence by dictionary administration module 430, and while according to the key character " sx " of user input, searching the vocabulary corresponding with key character " sx ", found the candidate vocabulary corresponding with key character in the dictionary of judge module 450 judgements after sequence, now, input method module 440 is according to the sequence with in the dictionary of the corresponding candidate's vocabulary of key character " sx " after sequence, the preferential candidate's vocabulary the preceding that sorts that shows: " Sha County ", " realization ", " at first ", " be familiar with ", " shooting ", " go to school " etc., therefrom select to need the vocabulary " Sha County " of input for the user.
When judge module 450 judgement users do not input the candidate vocabulary corresponding with key character found, input method module 440 is also called the acquiescence dictionary for manage 430 modules by dictionary, and the sequence in the acquiescence dictionary according to candidate's vocabulary, preferentially the candidate's vocabulary the preceding that sorts is inputted to demonstration, therefrom select the vocabulary of required input for the user.
The result judged when judge module 450 is while in the dictionary after sequence, not finding the candidate vocabulary corresponding with key character, input method module 440 is also called the acquiescence dictionary for manage 430 modules by dictionary, and the sequence in the acquiescence dictionary according to candidate's vocabulary, preferentially the candidate's vocabulary the preceding that sorts is inputted to demonstration, therefrom select the vocabulary of required input for the user.
For example, when reusing current input method, the user inputs key character " sx " in MSN with in the dialog box of contact person Jack, during with input " sequentially " this vocabulary, due to, do not comprise vocabulary " sequentially " in MSN with in the session information of the session of contact person Jack before, so, while in key character " sx " dictionary sequence after of input method module 404 according to user's input, searching the candidate vocabulary corresponding with key character " sx ", in the dictionary of judge module 450 judgements after sequence, do not find the candidate vocabulary corresponding with key character.Now, input method module 440 receives the key character " sx " of inputting according to the user, find the candidate vocabulary corresponding with key character " sx " in the acquiescence dictionary, sequence according to candidate's vocabulary in the acquiescence dictionary, the preferential candidate's vocabulary the preceding that sorts that shows: " realization ", " at first ", " being familiar with ", " shooting ", " going to school ", " sequentially " etc., therefrom select to need for the user vocabulary " sequentially " of inputting.
Such scheme, by obtaining and resolve the session information of current sessions type and current sessions type, wherein, conversation type comprises application message and the user profile under described application message of session, thereby included vocabulary in the session information of acquisition current sessions type, sequence by vocabulary included in the described session information after resolving is front, and sorted according to the frequency of occurrences of described vocabulary, obtain the dictionary after sorting, be kept at this locality by the dictionary association by after current sessions type and sequence, dictionary and current sessions type association can be got up, thereby make the user when using different conversation type, use respectively the dictionary of this conversation type of binding, improve candidate's vocabulary shown while inputting key character and the degree of correlation of key character, thereby improve user's input efficiency.
In above description, in order to illustrate rather than, in order limiting, to have proposed the detail such as particular system structure, interface, technology, in order to thoroughly understand the application.Yet, not it will be clear to one skilled in the art that in there is no other embodiment of these details and can realize the application yet.In other situation, omit the detailed description to well-known device, circuit and method, in order to avoid unnecessary details hinders the application's description.
Claims (10)
1. a method of based on context inputting, is characterized in that, described method comprises the steps:
Obtain the session information of current sessions type, wherein, described conversation type comprises application message and the user profile under described application message of session;
Resolve the session information of current sessions type with included vocabulary in the session information that obtains the current sessions type;
Add up vocabulary included in described session information, and vocabulary included in described session information is sorted front, to obtain the dictionary after sorting;
Dictionary association after described current sessions type and sequence is kept to this locality, when for the user, reusing the session of described current sessions type and inputting key character, sequence in dictionary according to candidate's vocabulary after the sequence with described current sessions type association, preferentially input demonstration to the candidate's vocabulary the preceding that sorts.
2. method according to claim 1, is characterized in that, the step of resolving vocabulary included in the session information of session information with acquisition current sessions type of current sessions type comprises:
Obtain the text message in described session information;
Resolve sentence by sentence sequentially every text message, to obtain vocabulary included in described text message;
The described vocabulary that record obtains after resolving.
3. method according to claim 1, is characterized in that, adds up the frequency of occurrences of described vocabulary, and comprise according to the step that the frequency of occurrences of described vocabulary is sorted to obtain the dictionary after sequence:
The frequency of occurrences of the described vocabulary after statistics is resolved;
According to the frequency of occurrences of described vocabulary, sorted from high to low;
Described vocabulary is stored in dictionary by the sequence that frequency occurs, to obtain the dictionary after sorting.
4. method according to claim 1, is characterized in that, the step of obtaining the session information of current sessions type also comprises before:
Determine whether to use for the first time the session of current sessions type;
If so, call the acquiescence dictionary and preferentially the candidate's vocabulary the preceding that sorts is inputted to demonstration in the acquiescence dictionary;
If not, call the dictionary after sequence and preferentially the candidate's vocabulary the preceding that sorts in the dictionary after sequence inputted to demonstration.
5. method according to claim 1, is characterized in that, in the described session information of statistics, the step of included vocabulary specifically comprises:
Add up vocabulary included in described session information, and vocabulary included in described session information is sorted front;
Add up the frequency of occurrences of vocabulary included in described session information, and, by sequence included in described session information vocabulary the preceding, sorted according to the frequency of occurrences of vocabulary included in described session information, to obtain the dictionary after sequence.
6. a mobile terminal, is characterized in that, described device comprises: acquisition module, vocabulary parsing module, dictionary administration module, input method module;
Described acquisition module is for obtaining the session information of current sessions type, wherein, described conversation type comprises application message and the user profile under described application message of session, and described acquisition module sends the session information of described current sessions type and conversation type to described vocabulary parsing module;
Described vocabulary parsing module is for receiving the session information of described current sessions type and conversation type, session information according to described current sessions type and current sessions type, resolve the session information of current sessions type with included vocabulary in the session information that obtains the current sessions type, described vocabulary parsing module sends the vocabulary after described current sessions type and parsing to described dictionary administration module;
Described dictionary administration module is for the vocabulary after receiving described current sessions type and resolving, according to included vocabulary in the described session information of the glossary statistic after described parsing, and vocabulary included in described session information is sorted front, to obtain the dictionary after sorting, described dictionary administration module sends the dictionary after described current sessions type and sequence to described input method module;
Described input method module is for the dictionary after receiving described current sessions type and sorting, according to described current sessions type with the sequence after dictionary by described current sessions type and the sequence after the associated this locality that is kept at of dictionary, when for the user, reusing the session of described current sessions type and inputting key character, sequence in dictionary according to candidate's vocabulary after the sequence with described current sessions type association, preferentially input demonstration to the candidate's vocabulary the preceding that sorts.
7. mobile terminal according to claim 6, it is characterized in that, described vocabulary parsing module is for obtaining the text message of described session information, resolve sentence by sentence sequentially every text message according to described text message, to obtain vocabulary included in described text message, and the described vocabulary obtained after the record parsing.
8. mobile terminal according to claim 6, it is characterized in that, described glossary statistic module is for adding up the frequency of occurrences of the described vocabulary after parsing, according to the frequency of occurrences of described vocabulary, sorted from high to low, and the described vocabulary after sequence is preferentially come in dictionary, to obtain the dictionary after sorting.
9. mobile terminal according to claim 6, is characterized in that, described mobile terminal also comprises judge module, and described judge module is for determining whether to use for the first time the session of current sessions type;
When described judge module judgment result is that while being, described input method module is also for calling the acquiescence dictionary and preferentially the candidate's vocabulary the preceding that sorts at the acquiescence dictionary being inputted to demonstration;
When described judge module when the determination result is NO, described input method module is also for calling dictionary after sequence and preferentially the candidate's vocabulary the preceding that sorts of the dictionary after sequence being inputted to demonstration;
Described judge module sends judged result to described input method module.
10. mobile terminal according to claim 9, is characterized in that,
Described vocabulary analytical method module is used for adding up the included vocabulary of described session information, and vocabulary included in described session information is sorted front;
Described vocabulary analytical method module is also for adding up the frequency of occurrences of the included vocabulary of described session information, and by sequence included in described session information vocabulary the preceding, according to the frequency of occurrences of vocabulary included in described session information, sorted, to obtain the dictionary after sorting.
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