CN103886043A - Method and device for showing candidate items - Google Patents
Method and device for showing candidate items Download PDFInfo
- Publication number
- CN103886043A CN103886043A CN201410088127.3A CN201410088127A CN103886043A CN 103886043 A CN103886043 A CN 103886043A CN 201410088127 A CN201410088127 A CN 201410088127A CN 103886043 A CN103886043 A CN 103886043A
- Authority
- CN
- China
- Prior art keywords
- cloud
- candidate
- local
- dictionary
- word
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
- G06F3/02—Input arrangements using manually operated switches, e.g. using keyboards or dials
- G06F3/023—Arrangements for converting discrete items of information into a coded form, e.g. arrangements for interpreting keyboard generated codes as alphanumeric codes, operand codes or instruction codes
- G06F3/0233—Character input methods
- G06F3/0236—Character input methods using selection techniques to select from displayed items
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/33—Querying
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- General Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Computational Linguistics (AREA)
- Data Mining & Analysis (AREA)
- Databases & Information Systems (AREA)
- Human Computer Interaction (AREA)
- Document Processing Apparatus (AREA)
- Machine Translation (AREA)
Abstract
The invention provides a method and device for showing candidate items. The method comprises the steps that an input string input by a user is analyzed, and a corresponding syllable sequence is obtained; according to the syllable sequence, checking is carried out in a local cloud word bank, a corresponding local cloud candidate is obtained; the local cloud word bank stores cloud results sent according to a cloud server for word learning, and entry information and corresponding syllable information are obtained; the local cloud candidate and a local common candidate are subjected to mixing sorting; and the mixing sorting results of the local cloud candidate and the local common candidate are shown. The input efficiency of a user can be greatly improved.
Description
Technical field
The application relates to input method technique field, particularly relates to a kind of method and device that represents candidate item.
Background technology
Tradition input method is limited to memory span and the CPU ability of local computer, the dictionary that use scale is less and language model, and input accuracy is limited.Cloud input method is the input method that relies on cloud computing technology, itself and traditional input method are the most significantly distinguished and are: do not need local input method file and completely by server support, it relies on powerful storage and the arithmetic capability of server cluster, have the incomparable advantage of traditional input method: larger, the dictionary that upgrades, more senior language model, these advantages make the accuracy rate of input have significant lifting.Be subject at present the restriction of Internet Transmission condition, the speed that local computer acquisition cloud input method returns results is always considerably slower than the speed of local conversion.In order to reduce cloud result lag behind the wait anxiety and the cognitive conflict that bring to user, input method is placed on two bit selectings by cloud result and puts mostly, but this way has been sacrificed the first-selected accuracy rate of cloud result undoubtedly.
In order to solve the hysteresis of cloud result and the contradictory problems of first-selected accuracy rate, existing a kind of disposal route is for opening up cloud buffer memory, cloud result medium cloud candidate is saved in this cloud buffer memory with corresponding input string, the entry in this cloud buffer memory can be placed directly in to first-selection under given conditions.
With reference to Fig. 1, show the method flow diagram that application cloud buffer memory carries out word input, specifically can comprise:
Conventionally, the condition of request cloud is that local dictionary hits unsuccessfully.
But, shown in Fig. 1 in technical scheme, input string need to meet the effect of specified conditions competence exertion cloud buffer memory: first, should meet the condition of request cloud, this just requires local dictionary there is no the candidate item that input string is corresponding, secondly, and when the input string that input string must be crossed Cloud Server with once-requested mates completely, could in cloud buffer memory, successfully inquire about the entry that this input string is corresponding, this scene that causes cloud buffer memory to play a role is very limited.
Suppose that input string is for " yihulvc ", if all entry corresponding to this input string not of local dictionary and cloud buffer memory, can be to cloud result corresponding to this input string of Cloud Server request, suppose that Cloud Server has returned to cloud candidate " a kettle green tea ", the corresponding relation of " yihulvc " and " a kettle green tea " can be saved in this cloud buffer memory; Suppose now to continue input, make this input string become " yihulvch ", local dictionary and cloud buffer memory still do not have the entry that current input string is corresponding, therefore can again ask Cloud Server; Continue afterwards input, make input string become " yihulvcha ", in like manner, also can again ask again Cloud Server.Above-mentioned character input process can bring bad experience: when input string is " yihulvc ", user just can put " a kettle green tea " of seeing that Cloud Server returns in two bit selectings, when input string is " yihulvch " and " yihulvcha ", candidate item " a kettle green tea " remains unchanged, and the position in the second candidate is refreshed again and again, and before shielding on completing, cloud candidate " a kettle green tea " preferred location of having no chance all the time to appear at that Cloud Server returns; In a word, for user, both spent the time of waiting for Cloud Server response, and cannot see the entry of wanting in preferred location again, this has had a strong impact on input efficiency.
Summary of the invention
Technical problems to be solved in this application are to provide a kind of method and device that represents candidate item, can greatly promote user's input efficiency.
In order to address the above problem, the application discloses a kind of method that represents candidate item, comprising:
Input string to user's input is resolved, and obtains corresponding syllable sequence;
According to described syllable sequence, in local cloud dictionary, inquire about, obtain corresponding local cloud candidate; Wherein, described local cloud dictionary stores the cloud result word sending according to Cloud Server, the entry information obtaining and corresponding syllable information;
Described local cloud candidate and local common candidate are carried out to hybrid-sorting;
Represent described local cloud candidate and local common candidate's hybrid-sorting result.
Preferably, described local cloud dictionary also stores word frequency information corresponding to entry information obtaining according to cloud result word;
Described method also comprises: in the time inquiring more than one local cloud candidate corresponding to described syllable sequence, according to the highest one of word frequency in an above local cloud candidate described in word frequency Information Selection separately;
The described step that described local cloud candidate and local common candidate are carried out to hybrid-sorting is that a local cloud candidate and the local common candidate the highest to selected word frequency carry out hybrid-sorting;
The step that represents described local cloud candidate and local common candidate's hybrid-sorting result is, represents a local cloud candidate that selected word frequency is the highest and local common candidate's hybrid-sorting result.
Preferably, generate as follows described local cloud dictionary:
Syllable sequence and cloud candidate in the cloud result that Cloud Server returns are each time learned to word, and a newly-increased data recording is preserved and is learned syllable sequence that word obtains and the corresponding relation of entry in local cloud dictionary, and this corresponding relation is preserved, form local cloud dictionary.
Preferably, after local cloud candidate described in described hybrid-sorting result comes local dictionary candidate and before local group word candidate.
Preferably, described method also comprises:
When entry number in described local cloud dictionary reaches preset gate in limited time, abandon the entry that was not wherein queried and deposited at first.
Preferably, described method also comprises:
After the process of input method is closed, empty described local cloud dictionary.
Preferably, described method also comprises:
In the time not inquiring local cloud candidate corresponding to described syllable sequence, to cloud result corresponding to input string described in Cloud Server request.
Preferably, the common candidate in described this locality comprises: this locality group word candidate that the local dictionary candidate who obtains according to the common dictionary in this locality and/or intelligent word generate.
On the other hand, disclosed herein as well is a kind of device that represents candidate item, comprising:
Resolution unit, for the input string of user's input is resolved, obtains corresponding syllable sequence;
Query unit for according to described syllable sequence, is inquired about in local cloud dictionary, obtains corresponding local cloud candidate; Wherein, described local cloud dictionary stores the cloud result word sending according to Cloud Server, the entry information obtaining and corresponding syllable information;
Hybrid-sorting unit, for carrying out hybrid-sorting to described local cloud candidate and local common candidate; And
Represent unit, for representing described local cloud candidate and local common candidate's hybrid-sorting result.
Preferably, described local cloud dictionary also stores word frequency information corresponding to entry information obtaining according to cloud result word;
Described device also comprises: in the time inquiring more than one local cloud candidate corresponding to described syllable sequence, according to the highest selected cell of of word frequency in an above local cloud candidate described in word frequency Information Selection separately;
Described hybrid-sorting unit, specifically for carrying out hybrid-sorting to selected word frequency the highest a local cloud candidate and local common candidate;
, represent unit, specifically for representing a local cloud candidate that selected word frequency is the highest and local common candidate's hybrid-sorting result.
Preferably, described device also comprises: for generating the generation unit of described local cloud dictionary;
Described generation unit comprises:
Learn lexon unit, for Cloud Server returns each time cloud result syllable sequence and cloud candidate are learned to word;
Preserve subelement, learn syllable sequence that word obtains and the corresponding relation of entry for preserving in the newly-increased data recording of local cloud dictionary, and this corresponding relation is preserved, form local cloud dictionary.
Compared with prior art, the application has the following advantages:
The cloud result word that the application returns Cloud Server, and the entry information that study is obtained and syllable information are saved in local cloud dictionary; And the inquiry of described local cloud dictionary can be carried out with the inquiry of the common dictionary in this locality and local intelligent group word simultaneously, and can participate in hybrid-sorting together with the common candidate in this locality according to the local cloud candidate that described local cloud thesaurus-lookups obtains;
The first, with respect to needing to meet the inquiry of asking the condition of cloud could trigger local cloud buffer memory in prior art, in the application, the inquiry of local cloud dictionary, without any condition restriction, can be carried out with the inquiry of the common dictionary in this locality and local intelligent group word simultaneously; Therefore can greatly promote inquiry probability and the utilization factor of local cloud candidate in local cloud dictionary;
Second, in prior art, cloud buffer memory be the input string of once-requested Cloud Server and the cloud candidate's that Cloud Server returns corresponding relation, therefore want successfully to inquire about the entry that this input string is corresponding in cloud buffer memory, require this input string must be in full accord with the input string of once-requested Cloud Server, this scene that causes cloud buffer memory to play a role be very limited; And in the application, the storage of described local cloud dictionary be entry information and the syllable information obtaining according to cloud result word, without the input string successful inquiring that gets final product in full accord of this input string and once-requested Cloud Server, therefore, can greatly promote the query success rate of the corresponding entry of input string;
The 3rd, the local cloud candidate who obtains according to described local cloud thesaurus-lookups can participate in hybrid-sorting together with the common candidate in this locality, greatly promotes local cloud candidate item and appears at probability first-selected in each candidate item therefore can increase;
To sum up, the application can either save the time of waiting for Cloud Server response, can greatly promote again the utilization factor of local cloud candidate item and appear at first-selected probability, therefore can promote to greatest extent user's input efficiency.
Brief description of the drawings
Fig. 1 is a kind of method flow diagram of applying cloud buffer memory and carrying out word input of prior art;
Fig. 2 is the process flow diagram of a kind of embodiment of the method 1 that represents candidate item of the application;
Fig. 3 is the process flow diagram of a kind of embodiment of the method 2 that represents candidate item of the application;
Fig. 4 is the process flow diagram of a kind of embodiment of the method 3 that represents candidate item of the application;
Fig. 5 is the process flow diagram of a kind of embodiment of the method 4 that represents candidate item of the application;
Fig. 6 is the structural drawing of a kind of device embodiment that represents candidate item of the application.
Embodiment
For the above-mentioned purpose, the feature and advantage that make the application can become apparent more, below in conjunction with the drawings and specific embodiments, the application is described in further detail.
The cloud result word that the embodiment of the present application is returned Cloud Server, and the entry information that study is obtained and syllable information are saved in local cloud dictionary; And, in character input process, the inquiry of described local cloud dictionary can be carried out with the inquiry of the common dictionary in this locality and local intelligent group word simultaneously, and can participate in hybrid-sorting together with the common candidate in this locality according to the local cloud candidate that described local cloud thesaurus-lookups obtains; On the one hand, the inquiry of described local cloud dictionary is without any the restriction of condition, therefore can greatly promote inquiry probability and the utilization factor of local cloud candidate in local cloud dictionary, on the other hand, the storage of described local cloud dictionary be entry information and the syllable information obtaining according to cloud result word, without the input string successful inquiring that gets final product in full accord of this input string and once-requested Cloud Server, therefore, can greatly promote the query success rate of entry in local cloud dictionary; To sum up, the application can either save the time of waiting for Cloud Server response, can greatly promote again the utilization factor of local cloud candidate item and appear at first-selected probability, therefore can promote to greatest extent user's input efficiency.
With reference to Fig. 2, show the process flow diagram of a kind of embodiment of the method 1 that represents candidate item of the application, specifically can comprise:
The application can be applied to the input method system of the various input modes such as keyboard symbol, and user can carry out word input by coded string (being also the input string in this instructions).In input method field, no matter be the input method of Chinese, Japanese, Korean or other Languages, the coded string of user's input can be converted to the candidate item of corresponding language.Below mainly describe other Languages cross-reference as an example of Chinese example.
For example, user inputs " yihulvc " on the keyboard of pc client, can obtain input string " yihulvc "; And for example, user inputs " 94349265 " under the nine grids keyboard of cell-phone customer terminal, can obtain input string " 94349265 ".
Taking Chinese as example, in Chinese, there are about more than 400 syllables (not considering tone), in practice, can resolve described input string according to certain rule, obtain possible syllable sequence.
All input methods are supported spelling input: suppose that input string is for " fangan ", can be resolved is two different syllable sequence: [fan] [gan] and [fang] [an]; Suppose that input string is for " buguo ", can be resolved is a syllable sequence [bu] [guo].
Most of input methods are also supported simplicity input: suppose that input string, for " yihulvc ", can be resolved as multiple different syllable sequence: [yi] [hu] [lv] [cha], [yi] [hu] [lv] [chai], [yi] [hu] [lv] [chen] etc.; Suppose that input string, for " 94349265 ", can be resolved as multiple different syllable sequence: [xi] [di] [zan] [ji], [zi] [di] [wan] [ke], [yi] [di] [yan] [lei], [yi] [di] [yan] [le], [yi] [di] [yan] [li] etc.
Except spelling input, simplicity input, some input method can also be supported the input such as fuzzy phoneme, Two bors d's oeuveres, because Analytic principle is similar, therefore do not repeat them here.
In input method field, the process of cloud request generally includes: input method client sends cloud request for input string to Cloud Server, and for each input string, Cloud Server can return at least one cloud result corresponding to cloud request, and each cloud result wherein generally includes the information such as cloud candidate, word frequency that syllable sequence, Cloud Server are returned.In prior art, consistent with the corresponding relation of cloud request and cloud result, the cloud result that input method client can be returned from Cloud Server, pick out cloud candidate and be saved in this cloud buffer memory with corresponding input string.
The embodiment of the present application has broken through the restriction of the local cloud buffer memory medium cloud request of prior art and the corresponding relation of cloud result, the concept of local cloud dictionary is creatively proposed, the identical point of described local cloud dictionary and existing local cloud buffer memory is all can be for stored word bar information, and difference at least can comprise:
The first, with respect to needing to meet the inquiry of asking the condition of cloud could trigger local cloud buffer memory in prior art, in the application, the inquiry of local cloud dictionary, without any condition restriction, can be carried out with the inquiry of the common dictionary in this locality and local intelligent group word simultaneously; Therefore can greatly promote inquiry probability and the utilization factor of local cloud candidate in local cloud dictionary;
Second, in prior art, cloud buffer memory be the input string of once-requested Cloud Server and the cloud candidate's that Cloud Server returns corresponding relation, therefore want successfully to inquire about the entry that this input string is corresponding in cloud buffer memory, require this input string must be in full accord with the input string of once-requested Cloud Server, this scene that causes cloud buffer memory to play a role be very limited; And in the application, the storage of described local cloud dictionary be the entry information that obtains according to cloud result word and corresponding syllable information, without the input string successful inquiring that gets final product in full accord of this input string and once-requested Cloud Server, therefore, can greatly promote the query success rate of entry in local cloud dictionary;
The 3rd, the local cloud candidate who obtains according to described local cloud thesaurus-lookups can participate in hybrid-sorting together with the common candidate in this locality, greatly promotes local cloud candidate item and appears at first-selected probability therefore can increase.
In the embodiment of the present application, can generate as follows described local cloud dictionary: to the cloud result that Cloud Server returns each time, to wherein syllable sequence and cloud candidate learn word, and a newly-increased data recording is preserved and is learned syllable sequence that word obtains and the corresponding relation of entry in local cloud dictionary, and this corresponding relation is preserved, form local cloud dictionary; Include word frequency in cloud result time, also the corresponding relation of this syllable sequence, entry and word frequency can be saved to local cloud dictionary.
Wherein, learning word is existing technology in input method field, its objective is the information of safeguarding upper screen word by dictionary, Chinese character string safeguarded conventionally in existing dictionary, the information such as the word frequency of syllable string and Chinese character string, the word process of existing dictionary is generally, after in the each execution of user, screen operates, record the corresponding relation that screen on this operates corresponding Chinese character string and syllable string, and judge by searching dictionary a data recording that whether has the corresponding relation that comprises this Chinese character string and syllable string in dictionary, if exist, the word frequency of Chinese character string in this data recording is added to 1, if do not exist, newly-increased this Chinese character string in dictionary, the data recording that syllable string is corresponding associated with word frequency, wherein, the initial value of word frequency is 1.
The word of the embodiment of the present application and the principle of existing word are similar, are all to safeguard Word message by corresponding dictionary, and the information such as the word frequency of Chinese character string, syllable string and Chinese character string all can be safeguarded in corresponding dictionary;
The word of the embodiment of the present application specifically can comprise with respect to the difference of existing word:
Difference one, the embodiment of the present application are to safeguard by local cloud dictionary the cloud result that Cloud Server returns, this this locality cloud dictionary and local common dictionary are different dictionaries, and what local cloud dictionary was safeguarded is the information of cloud result, but not the information of the upper screen word of user;
Difference two, in the time that existence comprises a data recording of corresponding relation of this Chinese character string and syllable string, existing word only upgrades the word frequency in this data recording; And the application is to Cloud Server returns each time cloud result, no matter whether its medium cloud candidate overlaps with entry in local cloud dictionary, no matter whether its medium cloud candidate is demonstrated, word is learned to wherein syllable sequence and cloud candidate in capital, and a newly-increased data recording is preserved the corresponding relation of syllable sequence and entry;
Because the data of Cloud Server are continuous updatings, before and after upgrading, identical cloud request may obtain different cloud results, therefore this difference two can maximally utilise the existing cloud result of local cloud dictionary on the one hand, can not lose on the other hand the strong advantage of Cloud Server entry data promptness.
Provide below learn word application scenarios 1,
On pc client, user's input string is " yihulvc ", local preference is " medical care green tea ", but this first-selection " medical care green tea " is not the entry in local common dictionary, but this locality group word candidate that input method client generates by intelligent word, due to the restriction of client computing power and size of data, this candidate's " medical care green tea " quality is also bad; Therefore, input method client sends cloud request to Cloud Server, carries this input string " yihulvc " in this cloud request;
Suppose that Cloud Server has obtained and multiple cloud results of this character string and prefix matching thereof, wherein the first-selection of the plurality of cloud result is " a kettle green tea ", and syllable sequence is [yi] [hu] [lv] [cha]; Due to computing power and the data capacity client far away of Cloud Server, therefore the quality of this first-selection " a kettle green tea " is obviously better than the quality of " medical care green tea ";
Pc client can, according to syllable sequence [yi] [hu] [lv] [cha], be learned " a kettle green tea " into local cloud dictionary.
It should be noted that, described this locality common candidate specifically can comprise: this locality group word candidate that the local dictionary candidate who obtains according to the common dictionary in this locality and/or intelligent word generate; Local common dictionary specifically can comprise: local system dictionary, local user vocabulary etc., and in the time that user inputs long sentence or uncommon word first, probably not this long sentence or uncommon word in local common dictionary, local dictionary candidate be sky in such cases.
Be appreciated that those skilled in the art can adopt various hybrid-sorting strategies according to actual demand.
In a kind of application example of the application, for bringing into play to greatest extent the advantage that Cloud Server computing power and data scale are large, first local cloud candidate can be forced to come first-selection.
In a preferred embodiment of the present application, consider the high-quality entry that stores systematic collection in local system dictionary, and in local user vocabulary, store the entry of the upper screen of user, therefore can think that local common candidate's quality is better than local cloud candidate; Simultaneously compare input method client and there are stronger computing power and more massive data due to Cloud Server, be obviously better than therefore Cloud Server obtains cloud candidate's quality this locality group word candidate that input method client group word generates; Therefore, in this preferred embodiment, after described local cloud candidate can being come to local dictionary candidate and before local group word candidate.
Corresponding to above-mentioned application scenarios 1, suppose that user continues input " h ", be that current input string is " yihulvch ", local common dictionary does not inquire corresponding entry yet, the candidate that input method client generates by intelligent word is still " medical care green tea ", but owing to now having had entry " a kettle green tea " corresponding to syllable sequence [yi] [hu] [lv] [cha] in local cloud dictionary, and should " a kettle green tea " be the first-selection that Cloud Server obtains, Cloud Server is compared input method client and is had stronger computing power and more massive data, therefore the quality that obtains cloud candidate according to Cloud Server is obviously better than this locality group word candidate's that input method client group word generates, therefore, can come local group word candidate " medical care green tea " before with the local cloud candidate " a kettle green tea " that the local cloud thesaurus-lookups of foundation is obtained, and because local dictionary candidate is empty, therefore local cloud candidate " a kettle green tea " is final first-selection.
In application scenarios 1, can either save the time of waiting for Cloud Server response, local cloud candidate can be presented in to first-selection again, because local cloud candidate's quality is obviously better than this locality group word candidate that input method client group word generates, therefore can provide better first-selected result for user.
With reference to Fig. 3, show the process flow diagram of a kind of embodiment of the method 2 that represents candidate item of the application, specifically can comprise:
The local cloud dictionary of the present embodiment, on above-mentioned basis embodiment illustrated in fig. 2, further can also be stored word frequency information corresponding to entry information obtaining according to cloud result word; This word frequency information is for representing user's frequency of utilization of corresponding entry information, be generally the number of times that the corresponding entry information of Cloud Server statistics is used or is transfused to, this word frequency information is carried in cloud result and returns to input method client, by input method client word in corresponding local cloud dictionary.
The method that represents candidate item of the present embodiment is on above-mentioned basis embodiment illustrated in fig. 2, further can also comprise: in the time inquiring more than one local cloud candidate corresponding to described syllable sequence, according to the highest one of the word frequency in an above local cloud candidate described in word frequency Information Selection separately; A highest selected word frequency local cloud candidate is participated in to hybrid-sorting and mixing represents.
In a word, the present embodiment is in the time inquiring more than one local cloud candidate corresponding to described syllable sequence, select the highest one of word frequency wherein to participate in hybrid-sorting and mixing represents, the highest entry of user's frequency of utilization that Cloud Server can be returned offers user, therefore can improve user's input efficiency.
With reference to Fig. 4, show the process flow diagram of a kind of embodiment of the method 3 that represents candidate item of the application, specifically can comprise:
In the method that represents candidate item of the present embodiment, step 403-step 404 is the treatment scheme of middle correspondence embodiment illustrated in fig. 2 in the time inquiring local cloud candidate corresponding to described syllable sequence, the treatment scheme of step 405-step 406 correspondence in the time not inquiring local cloud candidate corresponding to described syllable sequence, its routinely cloud position candidate represent at random described cloud result.Suppose to include in described cloud result several clouds candidate, if have the cloud candidate different from local candidate in cloud result, can select first cloud candidate different from local candidate of position display local two so, if there is not the cloud candidate different from local candidate in described cloud result, also be, if each cloud candidate has a local candidate identical with it, local two bit selectings are put and are left a blank.
Be appreciated that for the cloud result in step 405, can also, to wherein syllable sequence, cloud candidate and word frequency word, obtain the corresponding relation of syllable sequence, entry and word frequency, and this corresponding relation is saved to local cloud dictionary; Wherein the effect of syllable sequence, entry and word frequency is respectively: search index, Query Result and selection foundation.
With reference to Fig. 5, show the process flow diagram of a kind of embodiment of the method 4 that represents candidate item of the application, specifically can comprise:
The method that represents candidate item of the present embodiment, on above-mentioned basis embodiment illustrated in fig. 2, further can also comprise the step 505 for safeguarding local cloud dictionary.
Because the data of Cloud Server are continuous updatings, before and after upgrading, identical cloud request may obtain different cloud results, therefore, the present embodiment can be based on the recent minimum use algorithm of LRU(, Least Recently Used) principle safeguards local cloud dictionary, be the interim dictionary of fixed size, reach preset gate in limited time when preserving entry number, will abandon the entry that was not wherein queried and deposited at first.
In a preferred embodiment of the present application, described method can also comprise: after the process of input method (shut down, restart as input method place pc client etc.) is closed, empty described local cloud dictionary.
The design of local cloud dictionary, make input method client in most of the cases still retain the ability of request Cloud Server, can obtain in real time the up-to-date cloud result of Cloud Server, can maximally utilise the existing cloud result of local cloud dictionary on the one hand, can not lose on the other hand the strong advantage of Cloud Server entry data promptness.
Fig. 2-embodiment illustrated in fig. 5 is illustrated the method that represents candidate item respectively, be appreciated that, those skilled in the art can use one or more in described embodiment according to the actual requirements, and also, Fig. 2-embodiment illustrated in fig. 5 mutually combining is also feasible.
Embodiment is corresponding with preceding method, and the application also provides a kind of device that represents candidate item, with reference to the structural drawing shown in Fig. 6, specifically can comprise:
Resolution unit 601, for the input string of user's input is resolved, obtains corresponding syllable sequence;
Query unit 602 for according to described syllable sequence, is inquired about in local cloud dictionary, obtains corresponding local cloud candidate; Wherein, described local cloud dictionary stores the entry information and the corresponding syllable information that obtain according to the cloud result word of Cloud Server transmission;
Hybrid-sorting unit 603, for carrying out hybrid-sorting to described local cloud candidate and local common candidate; And
Represent unit 604, for representing described local cloud candidate and local common candidate's hybrid-sorting result.
In a kind of application example of the application, described this locality common candidate specifically can comprise: this locality group word candidate that the local dictionary candidate who obtains according to the common dictionary in this locality and/or intelligent word generate;
In a preferred embodiment of the present application, described local cloud dictionary can also store word frequency information corresponding to entry information obtaining according to cloud result word;
Described device can also comprise: in the time inquiring more than one local cloud candidate corresponding to described syllable sequence, according to the highest selected cell of of word frequency in an above local cloud candidate described in word frequency Information Selection separately;
Described hybrid-sorting unit 603, can be specifically for carrying out hybrid-sorting to selected word frequency the highest a local cloud candidate and local common candidate;
, represent unit 604, can be specifically for representing a local cloud candidate that selected word frequency is the highest and local common candidate's hybrid-sorting result.
In another preferred embodiment of the application, described device can also comprise: for generating the generation unit of described local cloud dictionary;
Described generation unit specifically can comprise:
Learn lexon unit, for Cloud Server returns each time cloud result syllable sequence and cloud candidate are learned to word;
Preserve subelement, learn syllable sequence that word obtains and the corresponding relation of entry for preserving in the newly-increased data recording of local cloud dictionary, and this corresponding relation is preserved, form local cloud dictionary.
In the embodiment of the present application, preferably, after local cloud candidate described in described hybrid-sorting result comes local dictionary candidate and before local group word candidate.
In the embodiment of the present application, preferably, described device can also comprise: discarding unit, for reaching preset gate when described local cloud dictionary entry number in limited time, abandons the entry that was not wherein queried and deposited at first.
In the embodiment of the present application, preferably, described device can also comprise: empty unit, after closing when the process of input method, empty described local cloud dictionary.
Each embodiment in this instructions all adopts the mode of going forward one by one to describe, and what each embodiment stressed is and the difference of other embodiment, between each embodiment identical similar part mutually referring to.For system embodiment, because it is substantially similar to embodiment of the method, so description is fairly simple, relevant part is referring to the part explanation of embodiment of the method.
A kind of method and the device that represents candidate item above the application being provided, be described in detail, applied principle and the embodiment of specific case to the application herein and set forth, the explanation of above embodiment is just for helping to understand the application's method and core concept thereof; , for one of ordinary skill in the art, according to the application's thought, all will change in specific embodiments and applications, in sum, this description should not be construed as the restriction to the application meanwhile.
Claims (11)
1. a method that represents candidate item, is characterized in that, comprising:
Input string to user's input is resolved, and obtains corresponding syllable sequence;
According to described syllable sequence, in local cloud dictionary, inquire about, obtain corresponding local cloud candidate; Wherein, described local cloud dictionary stores the cloud result word sending according to Cloud Server, the entry information obtaining and corresponding syllable information;
Described local cloud candidate and local common candidate are carried out to hybrid-sorting;
Represent described local cloud candidate and local common candidate's hybrid-sorting result.
2. the method for claim 1, is characterized in that, described local cloud dictionary also stores word frequency information corresponding to entry information obtaining according to cloud result word;
Described method also comprises: in the time inquiring more than one local cloud candidate corresponding to described syllable sequence, according to the highest one of word frequency in an above local cloud candidate described in word frequency Information Selection separately;
The described step that described local cloud candidate and local common candidate are carried out to hybrid-sorting is that a local cloud candidate and the local common candidate the highest to selected word frequency carry out hybrid-sorting;
The step that represents described local cloud candidate and local common candidate's hybrid-sorting result is, represents a local cloud candidate that selected word frequency is the highest and local common candidate's hybrid-sorting result.
3. the method for claim 1, is characterized in that, generates as follows described local cloud dictionary:
Syllable sequence and cloud candidate in the cloud result that Cloud Server returns are each time learned to word, and a newly-increased data recording is preserved and is learned syllable sequence that word obtains and the corresponding relation of entry in local cloud dictionary, and this corresponding relation is preserved, form local cloud dictionary.
4. method as claimed in claim 1 or 2, is characterized in that, after local cloud candidate described in described hybrid-sorting result comes local dictionary candidate and before local group word candidate.
5. method as claimed in claim 3, is characterized in that, also comprises:
When entry number in described local cloud dictionary reaches preset gate in limited time, abandon the entry that was not wherein queried and deposited at first.
6. method as claimed in claim 3, is characterized in that, also comprises:
After the process of input method is closed, empty described local cloud dictionary.
7. method as claimed in claim 1 or 2, is characterized in that, also comprises:
In the time not inquiring local cloud candidate corresponding to described syllable sequence, to cloud result corresponding to input string described in Cloud Server request.
8. method as claimed in claim 1 or 2, is characterized in that, described this locality common candidate comprise: this locality group word candidate that the local dictionary candidate who obtains according to the common dictionary in this locality and/or intelligent word generate.
9. a device that represents candidate item, is characterized in that, comprising:
Resolution unit, for the input string of user's input is resolved, obtains corresponding syllable sequence;
Query unit for according to described syllable sequence, is inquired about in local cloud dictionary, obtains corresponding local cloud candidate; Wherein, described local cloud dictionary stores the cloud result word sending according to Cloud Server, the entry information obtaining and corresponding syllable information;
Hybrid-sorting unit, for carrying out hybrid-sorting to described local cloud candidate and local common candidate; And
Represent unit, for representing described local cloud candidate and local common candidate's hybrid-sorting result.
10. device as claimed in claim 9, is characterized in that, described local cloud dictionary also stores word frequency information corresponding to entry information obtaining according to cloud result word;
Described device also comprises: in the time inquiring more than one local cloud candidate corresponding to described syllable sequence, according to the highest selected cell of of word frequency in an above local cloud candidate described in word frequency Information Selection separately;
Described hybrid-sorting unit, specifically for carrying out hybrid-sorting to selected word frequency the highest a local cloud candidate and local common candidate;
, represent unit, specifically for representing a local cloud candidate that selected word frequency is the highest and local common candidate's hybrid-sorting result.
11. devices as claimed in claim 9, is characterized in that, also comprise: for generating the generation unit of described local cloud dictionary;
Described generation unit comprises:
Learn lexon unit, for Cloud Server returns each time cloud result syllable sequence and cloud candidate are learned to word;
Preserve subelement, learn syllable sequence that word obtains and the corresponding relation of entry for preserving in the newly-increased data recording of local cloud dictionary, and this corresponding relation is preserved, form local cloud dictionary.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410088127.3A CN103886043B (en) | 2014-03-11 | 2014-03-11 | A kind of method and device for showing candidate item |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410088127.3A CN103886043B (en) | 2014-03-11 | 2014-03-11 | A kind of method and device for showing candidate item |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN103886043A true CN103886043A (en) | 2014-06-25 |
| CN103886043B CN103886043B (en) | 2017-10-20 |
Family
ID=50954935
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201410088127.3A Active CN103886043B (en) | 2014-03-11 | 2014-03-11 | A kind of method and device for showing candidate item |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN103886043B (en) |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106844651A (en) * | 2017-01-20 | 2017-06-13 | 上海傲硕信息科技有限公司 | Instruction results compare screening plant |
| CN106896975A (en) * | 2015-12-18 | 2017-06-27 | 北京搜狗科技发展有限公司 | A kind of input method and device, a kind of device for being input into |
| CN108304078A (en) * | 2017-01-11 | 2018-07-20 | 北京搜狗科技发展有限公司 | A kind of input method, device and electronic equipment |
| CN108549493A (en) * | 2018-04-04 | 2018-09-18 | 科大讯飞股份有限公司 | Candidate word screening technique and relevant device |
| CN108958503A (en) * | 2017-05-26 | 2018-12-07 | 北京搜狗科技发展有限公司 | input method and device |
| CN109712613A (en) * | 2018-12-27 | 2019-05-03 | 北京百佑科技有限公司 | Semantic analysis library update method, device and electronic equipment |
| CN112748811A (en) * | 2021-01-21 | 2021-05-04 | 李博林 | English word input method and device |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20050146508A1 (en) * | 2004-01-06 | 2005-07-07 | International Business Machines Corporation | System and method for improved user input on personal computing devices |
| CN101334774A (en) * | 2007-06-29 | 2008-12-31 | 北京搜狗科技发展有限公司 | Character input method and input method system |
| CN101697109A (en) * | 2009-10-26 | 2010-04-21 | 北京搜狗科技发展有限公司 | Method and system for acquiring candidates of input method |
| CN102063452A (en) * | 2010-05-31 | 2011-05-18 | 百度在线网络技术（北京）有限公司 | Method, equipment, server and system for inputting characters by user |
| CN102722483A (en) * | 2011-03-29 | 2012-10-10 | 百度在线网络技术（北京）有限公司 | Method, apparatus and equipment for determining candidate-item sequence of input method |
-
2014
- 2014-03-11 CN CN201410088127.3A patent/CN103886043B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20050146508A1 (en) * | 2004-01-06 | 2005-07-07 | International Business Machines Corporation | System and method for improved user input on personal computing devices |
| CN101334774A (en) * | 2007-06-29 | 2008-12-31 | 北京搜狗科技发展有限公司 | Character input method and input method system |
| CN101697109A (en) * | 2009-10-26 | 2010-04-21 | 北京搜狗科技发展有限公司 | Method and system for acquiring candidates of input method |
| CN102063452A (en) * | 2010-05-31 | 2011-05-18 | 百度在线网络技术（北京）有限公司 | Method, equipment, server and system for inputting characters by user |
| CN102722483A (en) * | 2011-03-29 | 2012-10-10 | 百度在线网络技术（北京）有限公司 | Method, apparatus and equipment for determining candidate-item sequence of input method |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106896975A (en) * | 2015-12-18 | 2017-06-27 | 北京搜狗科技发展有限公司 | A kind of input method and device, a kind of device for being input into |
| CN108304078A (en) * | 2017-01-11 | 2018-07-20 | 北京搜狗科技发展有限公司 | A kind of input method, device and electronic equipment |
| CN108304078B (en) * | 2017-01-11 | 2024-01-30 | 北京搜狗科技发展有限公司 | Input method and device and electronic equipment |
| CN106844651A (en) * | 2017-01-20 | 2017-06-13 | 上海傲硕信息科技有限公司 | Instruction results compare screening plant |
| CN106844651B (en) * | 2017-01-20 | 2019-11-12 | 上海傲硕信息科技有限公司 | Instruction results compare screening plant |
| CN108958503A (en) * | 2017-05-26 | 2018-12-07 | 北京搜狗科技发展有限公司 | input method and device |
| CN108549493A (en) * | 2018-04-04 | 2018-09-18 | 科大讯飞股份有限公司 | Candidate word screening technique and relevant device |
| CN109712613A (en) * | 2018-12-27 | 2019-05-03 | 北京百佑科技有限公司 | Semantic analysis library update method, device and electronic equipment |
| CN112748811A (en) * | 2021-01-21 | 2021-05-04 | 李博林 | English word input method and device |
Also Published As
| Publication number | Publication date |
|---|---|
| CN103886043B (en) | 2017-10-20 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN103886043A (en) | Method and device for showing candidate items | |
| JP6634515B2 (en) | Question clustering processing method and apparatus in automatic question answering system | |
| CN105183720B (en) | Machine translation method and device based on RNN model | |
| CN110210029A (en) | Speech text error correction method, system, equipment and medium based on vertical field | |
| US11782998B2 (en) | Embedding based retrieval for image search | |
| EP2833271A1 (en) | Multimedia question and answer system and method | |
| US20140122407A1 (en) | Chatbot system and method having auto-select input message with quality response | |
| CN108875074A (en) | Based on answer selection method, device and the electronic equipment for intersecting attention neural network | |
| CN103714054B (en) | Interpretation method and translating equipment | |
| US20140201229A1 (en) | Providing display suggestions | |
| US20180173694A1 (en) | Methods and computer systems for named entity verification, named entity verification model training, and phrase expansion | |
| CN108628935A (en) | A kind of answering method based on end-to-end memory network | |
| US20220043985A1 (en) | Role labeling method, electronic device and storage medium | |
| CN109800303A (en) | A kind of document information extracting method, storage medium and terminal | |
| CN110737756B (en) | Method, apparatus, device and medium for determining answer to user input data | |
| US20230214689A1 (en) | Method and apparatus for processing dialogue, electronic device, and storage medium | |
| CN103577548B (en) | Method and device for matching characters with close pronunciation | |
| CN108763529A (en) | A kind of intelligent search method, device and computer readable storage medium | |
| CN116127020A (en) | Method for training generated large language model and searching method based on model | |
| US9906588B2 (en) | Server and method for extracting content for commodity | |
| EP4002156A1 (en) | System and method for product searching based on natural language processing | |
| CN109711708A (en) | Whole process engineering consulting method of servicing and system | |
| CN110502613A (en) | A kind of model training method, intelligent search method, device and storage medium | |
| CN112883719A (en) | Class word recognition method, model training method, device and system | |
| CN105740374B (en) | Three-dimensional platform data fuzzy query method based on distributed memory |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |