CN111103986A - User word stock management method and device and input method and device - Google Patents
User word stock management method and device and input method and device Download PDFInfo
- Publication number
- CN111103986A CN111103986A CN201811256879.0A CN201811256879A CN111103986A CN 111103986 A CN111103986 A CN 111103986A CN 201811256879 A CN201811256879 A CN 201811256879A CN 111103986 A CN111103986 A CN 111103986A
- Authority
- CN
- China
- Prior art keywords
- user
- environment
- word
- information
- user 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
- 238000000034 method Methods 0.000 title claims abstract description 82
- 238000007726 management method Methods 0.000 title claims abstract description 29
- 238000012163 sequencing technique Methods 0.000 claims abstract description 8
- 230000007613 environmental effect Effects 0.000 claims description 6
- 238000012423 maintenance Methods 0.000 claims description 5
- 238000004891 communication Methods 0.000 description 12
- 238000012545 processing Methods 0.000 description 12
- 238000010586 diagram Methods 0.000 description 9
- 230000008859 change Effects 0.000 description 6
- 238000005516 engineering process Methods 0.000 description 5
- 230000006870 function Effects 0.000 description 5
- 230000003287 optical effect Effects 0.000 description 4
- 230000005236 sound signal Effects 0.000 description 4
- 230000003993 interaction Effects 0.000 description 3
- 230000008569 process Effects 0.000 description 3
- 230000001133 acceleration Effects 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 241000282414 Homo sapiens Species 0.000 description 1
- 230000009471 action Effects 0.000 description 1
- 230000006978 adaptation Effects 0.000 description 1
- 230000003044 adaptive effect Effects 0.000 description 1
- 238000003491 array Methods 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 238000012937 correction Methods 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 238000003384 imaging method Methods 0.000 description 1
- 230000010365 information processing Effects 0.000 description 1
- 239000004973 liquid crystal related substance Substances 0.000 description 1
- 238000013507 mapping Methods 0.000 description 1
- 230000005055 memory storage Effects 0.000 description 1
- 230000002093 peripheral effect Effects 0.000 description 1
- 230000002085 persistent effect Effects 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 230000001052 transient effect Effects 0.000 description 1
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
- G06F3/0237—Character input methods using prediction or retrieval techniques
Abstract
The invention discloses a user word stock management method and device and also discloses an input method and device. The input method comprises the following steps: acquiring candidate words matched with input information of a user; determining whether the candidate word is a user word in a user word bank; the user lexicon comprises: user words, attribute information thereof and environment types; if yes, acquiring the environment category of the user word; if the environment type of the user word is a common environment, adjusting the sequencing weight of the user word according to the attribute information of the user word; if the environment category of the user word is a specific environment, determining the current environment category of the candidate word; and if the current environment type is the same as the environment type of the user word, adjusting the sequencing weight of the user word according to the attribute information of the user word. By using the method and the device, the intelligence of the input method can be improved, the output candidate words are more accurate, and the input experience of a user is improved.
Description
Technical Field
The invention relates to the field of information processing, in particular to a user word stock management method and device and an input method and device.
Background
The input method is a coding method for inputting various symbols into a computer or other equipment, and is an indispensable tool for interaction between human beings and the computer. For an input method system, a general word stock and a user word stock are usually set. The user word bank is a user personalized word bank generated according to historical input data of a user, and is mainly used for recording words on a screen of the user and preferentially displaying words in the user word bank when the input method displays candidate words.
The word bank of the user brings convenience to the input of the user, but can interfere the input of the user in some cases, for example, some words are used frequently by the user recently, and according to the existing word frequency determining mode of sorting, the words are always arranged at the front position when the user inputs the words, but in some input scenes, if other words which the user wants to input are exactly the same as the codes (such as pinyin, five strokes and the like) of the words, the words are arranged at the front position, interference is brought to the input of the user, the user can find out the candidate items which the user wants to input by the user only by performing operations such as page turning and the like, the input cost is high, and the user experience is influenced.
Disclosure of Invention
The embodiment of the invention provides a user word stock management method and device on the one hand, so that information in a user word stock can be better adapted to different input environments.
The embodiment of the invention also provides an input method and device, so that the intelligence of the input method is improved, the output candidate words are more accurate, and the input experience of a user is improved.
Therefore, the invention provides the following technical scheme:
a method of user thesaurus management, the method comprising:
acquiring user words and attribute information thereof according to historical input information of the user;
determining an environment category for the user word, the environment category comprising: specific environment, general environment;
and adding the user words, the attribute information thereof and the environment types into a user word bank.
Optionally, the historical input information includes: word frequency information, time information and environment information of the user words; the environment information includes: a language environment, and/or an application environment;
the determining the environmental category of the user word comprises:
and counting or clustering the historical input information of the user to obtain the environment category of the user word.
Optionally, the specific environment includes any one or more of: the fixed upper environment and the fixed application environment;
the method further comprises determining a particular context of the user word as follows:
counting the use frequency of the user word and the binary co-occurrence frequency N of the user word and a specific text, and if the ratio of the co-occurrence frequency N to the use frequency of the user word is greater than a set value, determining that the environment type of the user word is a fixed context environment;
counting the use frequency of the user word and the co-occurrence frequency M of the user word in a specific application environment, and if the ratio of the co-occurrence frequency M to the use frequency of the user word is greater than a set value, determining that the environment type of the user word is a fixed application environment.
Optionally, the attribute information includes: word frequency information and time information.
A method of inputting, the method comprising:
acquiring candidate words matched with input information of a user;
determining whether the candidate word is a user word in a user word bank; the user lexicon comprises: the user words, attribute information of the user words and environment categories, wherein the environment categories comprise: specific environment, general environment;
if yes, acquiring the environment category of the user word;
if the environment type of the user word is a common environment, adjusting the sequencing weight of the user word according to the attribute information of the user word;
if the environment category of the user word is a specific environment and the environment category of the candidate word is the same as the environment category of the user word, adjusting the ranking weight of the user word according to the attribute information of the user word.
Optionally, the method further comprises:
establishing the user word bank according to the historical input information of the user, wherein the historical input information comprises: word frequency information, time information and environment information of the user words; the environment information includes: a language environment, and/or an application environment.
Optionally, the specific environment includes any one or more of: the fixed upper environment and the fixed application environment;
the method further comprises determining a particular context of the user word as follows:
counting the use frequency of the user word and the binary co-occurrence frequency N of the user word and a specific text, and if the ratio of the co-occurrence frequency N to the use frequency of the user word is greater than a set value, determining that the environment type of the user word is a fixed context environment;
counting the use frequency of the user word and the co-occurrence frequency M of the user word in a specific application environment, and if the ratio of the co-occurrence frequency M to the use frequency of the user word is greater than a set value, determining that the environment type of the user word is a fixed application environment.
Optionally, the method further comprises:
sequencing the candidate words according to the sequencing weight of the user words and the general word frequency information thereof, wherein the general word frequency information of the user words refers to the word frequency information of the user words in a general word bank;
and outputting the candidate words according to the sorting result.
Optionally, the method further comprises:
if the candidate word is a user word and the environment category of the user word is a specific environment, generating an association candidate word conforming to the specific environment;
and outputting the associated candidate words.
A user lexicon management apparatus, the apparatus comprising:
the recording module is used for recording historical input information of a user;
the user word acquisition module is used for acquiring user words and attribute information thereof according to the historical user input information;
an environment category determination module configured to determine an environment category of the user word, the environment category including: specific environment, general environment;
and the word bank maintenance module is used for adding the user words, the attribute information of the user words and the environment types into the user word bank.
Optionally, the historical input information includes: word frequency information, time information and environment information of the user words; the environment information includes: a language environment, and/or an application environment;
the environment category determining module is specifically configured to count or cluster the user history input information to obtain an environment category of the user word.
Optionally, the specific environment includes any one or more of: the fixed upper environment and the fixed application environment;
the environment category determination module determines a particular environment of the user word as follows:
counting the use frequency of the user word and the binary co-occurrence frequency N of the user word and a specific text, and if the ratio of the co-occurrence frequency N to the use frequency of the user word is greater than a set value, determining that the environment type of the user word is a fixed context environment;
counting the use frequency of the user word and the co-occurrence frequency M of the user word in a specific application environment, and if the ratio of the co-occurrence frequency M to the use frequency of the user word is greater than a set value, determining that the environment type of the user word is a fixed application environment.
Optionally, the attribute information includes: word frequency information and time information.
Optionally, the word stock maintenance module is further configured to update the user word stock in real time or at certain time intervals.
An input device, the device comprising: the system comprises a candidate word acquisition module, a first judgment module, an environment information acquisition module, a weight adjustment module, an environment determination module and a second judgment module;
the candidate word acquisition module is used for acquiring candidate words matched with the input information of the user;
the first judging module is used for determining whether the candidate word is a user word in a user word bank; the user lexicon comprises: the user words, attribute information of the user words and environment categories, wherein the environment categories comprise: specific environment, general environment;
the environment information acquisition module is used for acquiring the environment type of the user word;
the weight adjusting module is used for adjusting the sequencing weight of the user words according to the attribute information of the user words when the environment type of the user words is a common environment;
the environment determining module is used for determining the environment category of the candidate word when the environment category of the user word is a specific environment;
the second judging module is configured to determine whether the environment type of the candidate word is the same as the environment type of the user word, and trigger the weight adjusting module to adjust the ranking weight of the user word according to the attribute information of the user word when the environment type of the candidate word is the same as the environment type of the user word.
Optionally, the apparatus further comprises:
the user word bank management module is used for establishing the user word bank according to the historical input information of the user, wherein the historical input information comprises: word frequency information, time information and environment information of the user words; the environment information includes: a language environment, and/or an application environment.
Optionally, the word stock management module is further configured to update the user word stock in real time or at certain time intervals.
Optionally, the specific environment includes any one or more of: the fixed upper environment and the fixed application environment;
the thesaurus management module determines the specific environment of the user word according to the following modes:
counting the use frequency of the user word and the binary co-occurrence frequency N of the user word and a specific text, and if the ratio of the co-occurrence frequency N to the use frequency of the user word is greater than a set value, determining that the environment type of the user word is a fixed context environment;
counting the use frequency of the user word and the co-occurrence frequency M of the user word in a specific application environment, and if the ratio of the co-occurrence frequency M to the use frequency of the user word is greater than a set value, determining that the environment type of the user word is a fixed application environment.
Optionally, the apparatus further comprises:
the sorting module is used for sorting the candidate words according to the sorting weight of the user words and the general word frequency information thereof, wherein the general word frequency information of the user words refers to the word frequency information of the user words in a general word bank;
and the output module is used for outputting the candidate words according to the sorting result.
Optionally, the apparatus further comprises:
the association candidate word generation module is used for generating an association candidate word which accords with a specific environment when the environment category of the user word acquired by the environment information acquisition module is the specific environment;
the output module is further used for outputting the association candidate words.
An electronic device, comprising: one or more processors, memory;
the memory is configured to store computer-executable instructions and the processor is configured to execute the computer-executable instructions to implement the method described above.
A readable storage medium having stored thereon instructions which are executed to implement the foregoing method.
According to the user word stock management method and device provided by the embodiment of the invention, the environment category information of the user words is added in the user word stock so as to distinguish the user words in different environment applications, so that the information in the user word stock can be better adapted to different input environments.
Further, based on the user lexicon, an embodiment of the present invention further provides an input method and apparatus, after a candidate word is obtained according to the user lexicon, the ranking weight of the candidate word is adjusted according to the current environment category of the candidate word and the environment category of the user word in the corresponding user lexicon, so that the ranking weight is adapted to the current input environment, the candidate word is ranked according to the ranking weight of the candidate word and the general word frequency information thereof, the candidate word is output according to the ranking result, the output candidate word is more accurate, and the intelligence of the input method is effectively improved.
Drawings
In order to more clearly illustrate the embodiments of the present application or technical solutions in the prior art, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments described in the present invention, and other drawings can be obtained by those skilled in the art according to the drawings.
FIG. 1 is a flow chart of a method for managing a dictionary in accordance with an embodiment of the present invention;
FIG. 2 is a schematic structural diagram of a word bank management method according to an embodiment of the present invention;
FIG. 3 is a flow chart of an input method according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of an input device according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of another exemplary input device;
FIG. 6 is a block diagram illustrating an apparatus for an input method in accordance with an exemplary embodiment;
fig. 7 is a schematic structural diagram of a server in an embodiment of the present invention.
Detailed Description
In order to make the technical field of the invention better understand the scheme of the embodiment of the invention, the embodiment of the invention is further described in detail with reference to the drawings and the implementation mode.
Aiming at the problems that the information in the user word bank of the existing input method cannot well meet the ordering requirement of candidate words under different input environments and influence the user experience, the embodiment of the invention provides a user word bank management method and a user word bank management device. Further, based on the user lexicon, an embodiment of the present invention further provides an input method and system, after a candidate word is obtained according to the user lexicon, the ranking weight of the candidate word is adjusted according to the current environment category of the candidate word and the environment category of the user word in the corresponding user lexicon, and then the candidate word is ranked according to the ranking weight of the candidate word and the general word frequency information thereof, so that the ranking result is more adaptive to the current input environment, and the candidate word is output according to the ranking result, so that the output candidate word is more accurate, and the intelligence of the input method is effectively improved.
As shown in fig. 1, it is a flowchart of a word stock management method according to an embodiment of the present invention, and the method includes the following steps:
In the field of input methods, for characters such as Chinese, Japanese, Korean and the like, input codes of users are converted into characters of corresponding languages to obtain corresponding candidate words, and then the users select output contents, namely on-screen contents. The order of the candidate words is usually determined according to information such as word frequency.
In order to improve the input efficiency of the user, the historical input information of the user is usually recorded, and the historical input information mainly includes: the existing words and corresponding attribute information input by the user can also comprise self-made words and corresponding attribute information input by the user; the attribute information may include, for example: word frequency information, time information, etc. of the user words. The word frequency refers to the frequency of use of a word or a single word, and specifically may be an absolute word frequency, or a relative word frequency, or another numerical value capable of indirectly indicating the frequency of use of the word or the single word.
And according to the historical input information, learning or updating the on-screen content into the user word stock. Correspondingly, when the user inputs the subsequent input, the input method application program firstly searches the entry matched with the input code character string, namely the user word from the user word bank, and orders the hit user word according to the attribute information such as the word frequency, the time and the like.
In this embodiment of the present invention, the attribute information of the user word may include: some conventional information such as word frequency information, time information, etc. of the user word may also include some other attribute information according to the actual application needs, and the present invention is not limited to this.
Unlike the conventional prior art, in the embodiment of the present invention, the history input information to be recorded includes not only: conventional information in the prior art, such as word frequency information and time information of a user word, also needs to record environmental information of the user word; the environment information includes: a language environment, and/or an application environment. The language environment mainly refers to grammatical features of the user words, such as parts of speech, categories and the like of the user words; the application environment mainly refers to a specific application category in which the user input is located.
In the embodiment of the present invention, the environment categories may be divided into two major categories, that is: the method comprises the following steps of (1) taking other environments except a specific environment as common environments; the specific environment may be divided from different angles, and may include one or more of, for example, a fixed context, a fixed application environment, and the like. The fixed context refers to a word of the user whose upper part is fixed, rather than an arbitrary word, such as: the front of the building is matched with a number word; the fixed application environment refers to that the current application is a specific application, such as search software, text processing software, chat software, communication software and other applications.
For each specific application, the relevant information can be obtained through a corresponding system function, an interface of the current application program and the like, the type of the current application is obtained according to the relevant information, and whether the environment of the user word is a fixed application environment can be further obtained.
For example, in a Windows operating system, a system function GetModuleFilename can be called to obtain a path name of an application program, so as to obtain a file name of a current input, for example, the file name is "winword.
For another example, a COM object of a web browser may be obtained by using an interface of a current application program, so as to obtain information such as a URL (Uniform Resource Location) or text content of a current page, and according to the information, it may be known that the current application is web page search.
In practical application, the environment category of the user word can be obtained by counting or clustering the historical input information of the user.
For example, the scenes used by the user words are divided into two types: the method comprises the following steps of fixing the above environment and the application environment, and counting the use environment information of the user words within a period of time (such as 1 day) by using a statistical mode:
for a fixed-context environment, counting the use frequency of a certain user word and the binary co-occurrence frequency N of the user word and a specific context, and if the ratio of the use frequency of the user word to the N is greater than a set value (for example, 80%), determining that the context type of the user word is the fixed-context environment;
for a fixed application environment, counting the use frequency of a certain user word and the co-occurrence frequency of the user word in a certain specific application environment, and if the ratio of the co-occurrence frequency to the use frequency of the user word is greater than a set value, determining that the environment category of the user word is the fixed application environment.
It should be noted that there may be one or more environment types corresponding to each user word, for example, if the user frequently mentions take-away in a chat, the user word "take-away" may be obtained according to the user history input information, and the corresponding environment types are "fixed context" and "fixed application environment".
And 103, adding the user words, the attribute information of the user words and the environment types into a user word bank.
It should be noted that, in the user input process, the user lexicon may be updated continuously according to the content of the screen, specifically, the user lexicon may be updated in real time, or may be updated at certain time intervals. In addition, according to the user lexicon obtained by the embodiment of the invention, the environment classification in the user lexicon can change along with the increase of data or the change of practical application.
According to the user word stock management method provided by the embodiment of the invention, the environment category information of the user words is added in the user word stock to distinguish the user words in different environment applications, so that the information in the user word stock can be better adapted to different input environments, further, in the user input process, the ordering of the output candidate words can be better matched with the current input environment, and the user can conveniently obtain the object required by input.
The thesaurus management methods of the present invention may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The inventive methods may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
Correspondingly, an embodiment of the present invention further provides a user lexicon management device, which is a schematic structural diagram of the device, as shown in fig. 2.
In this embodiment, the apparatus includes the following modules:
a recording module 201, configured to record user history input information;
a user word obtaining module 202, configured to obtain a user word and attribute information thereof according to the historical user input information;
an environment category determination module 203, configured to determine an environment category of the user word, where the environment category includes: specific environment, general environment;
and the word bank maintenance module 204 is configured to add the user word, the attribute information thereof, and the environment category to the user word bank.
In the embodiment of the present invention, the user history input information recorded by the recording module 201 not only includes user words and their attribute information, such as word frequency information, time information and other conventional information in the prior art, but also needs to record the environment information of the user words; the environment information includes: a language environment, and/or an application environment. The language environment mainly refers to grammatical features of the user words, such as parts of speech, categories and the like of the user words; the application environment mainly refers to a specific application category in which the user input is located. The determination of the application environment may be determined by acquiring relevant information through a corresponding system function, an interface of the current application program, and the like, and determining based on the information.
Correspondingly, when determining the environment category of the user word, the environment category determining module 203 may obtain the environment information of each user word according to the historical input information of the user, and then perform statistics or clustering on each record to obtain the environment category of the user word.
In the embodiment of the present invention, the environment categories may be divided into two major categories, that is: the method comprises the following steps of (1) taking other environments except a specific environment as common environments; the specific environment may be divided from different angles, and may include one or more of, for example, a fixed context, a fixed application environment, and the like. The fixed-above environment refers to that the above of the user words is a fixed word of a certain type, but not an arbitrary word; the fixed application environment refers to that the current application is a specific application, such as search software, text processing software, chat software, communication software and other applications.
Accordingly, the environment category determination module 203 may determine the particular environment of the user word as follows:
counting the use frequency of the user word and the binary co-occurrence frequency N of the user word and a specific text, and if the ratio of the co-occurrence frequency N to the use frequency of the user word is greater than a set value, determining that the environment type of the user word is a fixed context environment;
counting the use frequency of the user word and the co-occurrence frequency M of the user word in a specific application environment, and if the ratio of the co-occurrence frequency M to the use frequency of the user word is greater than a set value, determining that the environment type of the user word is a fixed application environment.
It should be noted that, in the user input process, the word stock maintenance module 204 may also update the user word stock in real time or at certain time intervals or after certain conditions are met. In addition, according to the user lexicon obtained by the embodiment of the invention, the environment classification in the user lexicon can change along with the increase of data or the change of practical application.
It should be noted that the method and apparatus for word stock management provided in the embodiments of the present invention may be applied to input method platforms of various input methods, including keyboard input, handwriting input, voice input, and the like, that is, the input information may include encoded character strings, handwriting input information, and voice input information. No matter which input method platform is used, the word stock is needed to sort the candidate items. Since the information conversion in these input modes is well known in the art, it will not be described in detail here.
In addition, since the input method platform can be operated on various computing devices in the prior art, such as a personal computer, a personal digital assistant, a mobile terminal device, and the like, the present invention can also be applied to the various computing devices.
The word stock management method and device provided by the embodiment of the invention can be applied to not only a Chinese input method system, but also an input method system needing candidate word ordering, such as Japanese, Korean and the like, for example, for Japanese, when phrases are formed by hiragana and katakana in Japanese, the candidate word ordering needs to be carried out.
Further, based on the user lexicon, an embodiment of the present invention further provides an input method and system, after a candidate word is obtained according to the user lexicon, the ranking weight of the candidate word is adjusted according to the current environment category of the candidate word and the environment category of the user word in the corresponding user lexicon.
The input method provided by the embodiment of the invention can be applied to electronic equipment, and the electronic equipment can include but is not limited to a smart phone, a tablet computer, a portable computer, a desktop computer and the like. The electronic equipment receives input information of a user, inquires candidate words matched with the input information in a pre-established user word bank, calculates the ranking weight of the candidate words according to the attribute information of the user words, and ranks and outputs the candidate words.
As shown in fig. 3, it is a flowchart of an input method according to an embodiment of the present invention, and includes the following steps:
The input information of the user may be a code string input by the user.
The candidate words can be obtained by searching the user word stock and the general word stock. Of course, in practical application, other word libraries may be set according to application requirements, and the embodiment of the present invention is not limited thereto.
In the embodiment of the present invention, the user lexicon includes: the user words, attribute information of the user words and environment categories, wherein the environment categories comprise: specific environment, general environment. The specific environment can be subdivided into: fixed above environment, fixed application environment, etc. The meaning of various information of the user lexicon and how to obtain the information have been described in detail above, and are not described herein again.
Wherein the specific environmental category for the user word may be determined as follows:
counting the use frequency of the user word and the binary co-occurrence frequency N of the user word and a specific text, and if the ratio of the co-occurrence frequency N to the use frequency of the user word is greater than a set value, determining that the environment type of the user word is a fixed context environment;
counting the use frequency of the user word and the co-occurrence frequency M of the user word in a specific application environment, and if the ratio of the co-occurrence frequency M to the use frequency of the user word is greater than a set value, determining that the environment type of the user word is a fixed application environment.
The environment category of the user word refers to the environment category to which the user word belongs in the user word library, and one or more environment categories to which the user word belongs may be provided.
The environment type of the candidate word refers to a currently input environment type, for example, whether the current environment type is a fixed-context environment may be determined according to the currently input context, and then, for example, related information may be obtained through a corresponding system function, an interface of a current application program, and the like, and a type of a current application may be obtained according to the related information, so that whether the environment of the user word is a fixed-context environment may be obtained.
In the embodiment of the present invention, the determining of the ranking weight of the user word may adopt some existing algorithms and manners, for example, the ranking weight of the user word is determined by comprehensively considering word frequency and time information, and the closer the usage time is to the current time, the more the usage frequency is, i.e., the higher the word frequency is, the higher the usage frequency is. Of course, in practical applications, other parameters may also be considered comprehensively for the calculation of the ranking weight, and the embodiment of the present invention is not limited thereto.
And step 307, ending.
It can be seen that, in the input method provided in the embodiment of the present invention, after candidate words are obtained according to the user word library, the ranking weights of all user words are not adjusted in the same manner in the prior art, but the ranking weights of user words in a common environment category and a specific environment category are adjusted in different manners based on the environment category of the user word, instead of adjusting the ranking weights in the same manner for all user words in the prior art. Specifically, the user words of the common environment category are adjusted each time; for a user word of a specific environment category, adjusting only in the case of the specific environment, for example, if the user word belongs to a fixed above environment category, then recalculating the ranking weight only in the case of the specific above; if the user word belongs to a fixed application context category, its ranking weight is only recalculated in case of a specific application context. Through the processing, the sorting weight of the candidate words can be matched with the current input environment, the candidate words are sorted according to the sorting weight of the candidate words, the candidate words are output according to the sorting result, the output candidate words are more accurate, and the intelligence of the input method is effectively improved.
For example, the user inputs "xtq" in a simplified spelling in the context of a mapping application, resulting in the user word "Xuan Tech". In the prior art, as long as the user inputs "xtq", the candidate word "special dazzling area" is arranged at a more front position under any environment; by using the scheme of the invention, the candidate word can be adjusted to a position closer to the front only in the map environment according to the environment type of the user word 'dazzling area'.
It should be noted that, in practical applications, when the candidate words are ranked and output according to a ranking result, if the candidate words are user words, only the ranking weight of the user words may be considered, or the ranking weight of the user words and the general word frequency information thereof may be considered comprehensively to rank the candidate words, where the general word frequency information of the user words refers to the word frequency information of the user words in a general word bank, which is not limited in this embodiment of the present invention. In addition, the candidate words are output according to the sorting result.
Further, in practical applications, if the candidate word is a user word and the environment category of the user word is a specific environment, an association candidate word meeting the specific environment may be further generated and output.
Correspondingly, an input device is further provided in an embodiment of the present invention, as shown in fig. 4, which is a schematic structural diagram of the input device in the embodiment of the present invention.
In this embodiment, the input device includes: the system comprises a candidate word acquisition module 401, a first judgment module 402, an environment information acquisition module 403, a weight adjustment module 404, an environment determination module 405 and a second judgment module 406. Wherein:
the candidate word acquiring module 401 is configured to acquire a candidate word matched with input information of a user;
the first determining module 402 is configured to determine whether the candidate word is a user word in a user word bank;
the environment information obtaining module 403 is configured to obtain an environment category of the user word, that is, an environment category to which the user word recorded in the user word library belongs;
the weight adjusting module 404 is configured to adjust the sorting weight of the user word according to the attribute information of the user word when the environment category of the user word is a common environment;
the environment determining module 405 is configured to determine an environment category of the candidate word when the environment category of the user word is a specific environment;
the second determining module 406 is configured to determine whether the environment category of the candidate word is the same as the environment category of the user word, and trigger the weight adjusting module 404 to adjust the ranking weight of the user word according to the attribute information of the user word when the environment category of the candidate word is the same as the environment category of the user word.
The candidate word obtaining module 401 is configured to obtain a candidate word matched with the input information of the user by specifically searching the user word bank and the general word bank. Of course, in practical application, other word libraries may be set according to application requirements, and the embodiment of the present invention is not limited thereto.
In the embodiment of the present invention, the user lexicon is different from a conventional user lexicon in the prior art, and is mainly embodied in the user lexicon of the embodiment of the present invention, and includes not only user words and their conventional attribute information, such as word frequency information, time information, etc., of the user words, but also includes environment category information of the user words, where the environment category includes: specific environment, general environment; the specific environment can be subdivided into: fixed above environment, fixed application environment, etc. The meaning of various information of the user lexicon and how to obtain the information have been described in detail above, and are not described herein again.
It should be noted that, in the user word library, there may be one or more environmental categories to which each user word belongs.
The user thesaurus may be established and updated by a user thesaurus management module (not shown), specifically, the user thesaurus management module establishes the user thesaurus according to historical input information of the user, where the historical input information includes: word frequency information, time information and environment information of the user words; the environment information includes: a language environment, and/or an application environment.
For a particular environmental category of the user word, the thesaurus management module may determine as follows:
counting the use frequency of the user word and the binary co-occurrence frequency N of the user word and a specific text, and if the ratio of the co-occurrence frequency N to the use frequency of the user word is greater than a set value, determining that the environment type of the user word is a fixed context environment;
counting the use frequency of the user word and the co-occurrence frequency M of the user word in a specific application environment, and if the ratio of the co-occurrence frequency M to the use frequency of the user word is greater than a set value, determining that the environment type of the user word is a fixed application environment.
The word stock management module may update the user words in real time, or at certain time intervals, or when a set condition (for example, when a certain number of new history records are reached) is met.
The environment determining module 405 may specifically determine whether the current environment type is a fixed-context environment according to the currently input context, and for example, may obtain related information through a corresponding system function, an interface of the current application program, and the like, and obtain a type of the current application according to the related information, so as to obtain whether the environment of the user word is a fixed application environment.
The weight adjusting module 404 may use some existing algorithms and methods to calculate the ranking weight of the user word, for example, the ranking weight of the user word is determined by comprehensively considering word frequency and time information, and the closer the usage time is to the current time, the more the usage frequency is, i.e., the higher the word frequency is, the higher the usage frequency is. Of course, in practical applications, other parameters may also be considered comprehensively for the calculation of the ranking weight, and the embodiment of the present invention is not limited thereto.
Fig. 5 is a schematic view of another structure of an input device according to an embodiment of the present invention.
In this embodiment, the input device includes not only the candidate word obtaining module 401, the first determining module 402, the environment information obtaining module 403, the weight adjusting module 404, the environment determining module 405, and the second determining module 406, but also the sorting module 407 and the output module 408. Wherein:
the sorting module 407 is configured to sort the candidate words according to the sorting weight of the user word and the general word frequency information thereof, where the general word frequency information of the user word refers to the word frequency information of the user word in a general word bank;
the output module 408 is configured to output the candidate word according to the sorting result.
In another embodiment of the input device of the present invention, the input device may further include an association candidate generating module (not shown) configured to generate an association candidate word conforming to a specific environment when the environment category of the user word acquired by the environment information acquiring module 403 is the specific environment. Correspondingly, the output module 408 is further configured to output the associated candidate word.
According to the input device provided by the embodiment of the invention, after the candidate word is obtained according to the user word bank, the sorting weight of the candidate word is adjusted according to the current environment type of the candidate word and the environment type of the user word in the corresponding user word bank, so that the sorting weight of the candidate word is matched with the current input environment, the candidate word is further sorted according to the sorting weight of the candidate word and the general word frequency information thereof, the candidate word is output according to the sorting result, the output candidate word is more accurate, and the intelligence of the input method is effectively improved.
It should be noted that the input method and apparatus provided in the embodiments of the present invention may be applied to input method platforms of various input methods, including keyboard input, handwriting input, voice input, and the like, that is, the input information may include encoded character strings, handwriting input information, and voice input information. No matter which input method platform is used, the word stock is needed to sort the candidate items.
In addition, since the input method platform in the prior art can be run on various computing devices, such as a personal computer, a personal digital assistant, a mobile terminal device, and the like, the input method and apparatus provided by the embodiments of the present invention can also be applied to the various computing devices.
The word stock management method and device provided by the embodiment of the invention can be applied to not only a Chinese input method system, but also an input method system needing candidate word ordering, such as Japanese, Korean and the like, for example, for Japanese, when phrases are formed by hiragana and katakana in Japanese, the candidate word ordering needs to be carried out.
FIG. 6 is a block diagram illustrating an apparatus 800 of an input method according to an example embodiment. For example, the apparatus 800 may be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, an exercise device, a personal digital assistant, and the like.
Referring to fig. 6, the apparatus 800 may include one or more of the following components: processing component 802, memory 804, power component 806, multimedia component 808, audio component 810, input/output (I/O) interface 812, sensor component 814, and communication component 816.
The processing component 802 generally controls overall operation of the device 800, such as operations associated with display, telephone calls, data communications, camera operations, and recording operations. The processing elements 802 may include one or more processors 820 to execute instructions to perform all or a portion of the steps of the methods described above. Further, the processing component 802 can include one or more modules that facilitate interaction between the processing component 802 and other components. For example, the processing component 802 can include a multimedia module to facilitate interaction between the multimedia component 808 and the processing component 802.
The memory 804 is configured to store various classes of data to support operations at the device 800. Examples of such data include instructions for any application or method operating on device 800, contact data, phonebook data, messages, pictures, videos, and so forth. The memory 804 may be implemented by any type or combination of volatile or non-volatile memory devices, such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disks.
The multimedia component 808 includes a screen that provides an output interface between the device 800 and a user. In some embodiments, the screen may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive an input signal from a user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundary of a touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 808 includes a front facing camera and/or a rear facing camera. The front-facing camera and/or the rear-facing camera may receive external multimedia data when the device 800 is in an operating mode, such as a shooting mode or a video mode. Each front camera and rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.
The audio component 810 is configured to output and/or input audio signals. For example, the audio component 810 includes a Microphone (MIC) configured to receive external audio signals when the apparatus 800 is in an operational mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signals may further be stored in the memory 804 or transmitted via the communication component 816. In some embodiments, audio component 810 also includes a speaker for outputting audio signals.
The I/O interface 812 provides an interface between the processing component 802 and peripheral interface modules, which may be keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to: a home button, a volume button, a start button, and a lock button.
The sensor assembly 814 includes one or more sensors for providing various aspects of state assessment for the device 800. For example, the sensor assembly 814 may detect the open/closed state of the device 800, the relative positioning of the components, such as a display and keypad of the apparatus 800, the sensor assembly 814 may also detect a change in position of the apparatus 800 or a component of the apparatus 800, the presence or absence of user contact with the apparatus 800, orientation or acceleration/deceleration of the apparatus 800, and a change in temperature of the apparatus 800. Sensor assembly 814 may include a proximity sensor configured to detect the presence of a nearby object without any physical contact. The sensor assembly 814 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 814 may also include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.
The communication component 816 is configured to facilitate communications between the apparatus 800 and other devices in a wired or wireless manner. The device 800 may access a wireless network based on a communication standard, such as WiFi, 2G or 3G, or a combination thereof. In an exemplary embodiment, the communication component 816 receives a broadcast signal or broadcast associated information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communications component 816 further includes a Near Field Communication (NFC) module to facilitate short-range communications. For example, the NFC module may be implemented based on Radio Frequency Identification (RFID) technology, infrared data association (IrDA) technology, Ultra Wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.
In an exemplary embodiment, the apparatus 800 may be implemented by one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), controllers, micro-controllers, microprocessors or other electronic components for performing the above-described methods.
In an exemplary embodiment, a non-transitory computer-readable storage medium comprising instructions, such as the memory 804 comprising instructions, executable by the processor 820 of the device 800 to perform the key press false touch correction method described above is also provided. For example, the non-transitory computer readable storage medium may be a ROM, a Random Access Memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.
The present invention also provides a non-transitory computer readable storage medium having instructions which, when executed by a processor of a mobile terminal, enable the mobile terminal to perform all or part of the steps of the above-described method embodiments of the present invention.
Fig. 7 is a schematic structural diagram of a server in an embodiment of the present invention. The server 1900, which may vary widely in configuration or performance, may include one or more Central Processing Units (CPUs) 1922 (e.g., one or more processors) and memory 1932, one or more storage media 1930 (e.g., one or more mass storage devices) that store applications 1942 or data 1944. Memory 1932 and storage medium 1930 can be, among other things, transient or persistent storage. The program stored in the storage medium 1930 may include one or more modules (not shown), each of which may include a series of instructions operating on a server. Still further, a central processor 1922 may be provided in communication with the storage medium 1930 to execute a series of instruction operations in the storage medium 1930 on the server 1900.
The server 1900 may also include one or more power supplies 1926, one or more wired or wireless network interfaces 1950, one or more input-output interfaces 1958, one or more keyboards 1956, and/or one or more operating systems 1941, such as Windows Server, Mac OS XTM, UnixTM, LinuxTM, FreeBSDTM, etc.
Other embodiments of the invention will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the invention and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the invention being indicated by the following claims.
It will be understood that the invention is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the invention is limited only by the appended claims.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (10)
1. A user lexicon management method, characterized in that the method comprises:
acquiring user words and attribute information thereof according to historical input information of the user;
determining an environment category for the user word, the environment category comprising: specific environment, general environment;
and adding the user words, the attribute information thereof and the environment types into a user word bank.
2. The method of claim 1, wherein the historical input information comprises: word frequency information, time information and environment information of the user words; the environment information includes: a language environment, and/or an application environment;
the determining the environmental category of the user word comprises:
and counting or clustering the historical input information of the user to obtain the environment category of the user word.
3. The method of claim 2, wherein the particular environment comprises any one or more of: the fixed upper environment and the fixed application environment;
the method further comprises determining a particular context of the user word as follows:
counting the use frequency of the user word and the binary co-occurrence frequency N of the user word and a specific text, and if the ratio of the co-occurrence frequency N to the use frequency of the user word is greater than a set value, determining that the environment type of the user word is a fixed context environment;
counting the use frequency of the user word and the co-occurrence frequency M of the user word in a specific application environment, and if the ratio of the co-occurrence frequency M to the use frequency of the user word is greater than a set value, determining that the environment type of the user word is a fixed application environment.
4. An input method, characterized in that the method comprises:
acquiring candidate words matched with input information of a user;
determining whether the candidate word is a user word in a user word bank; the user lexicon comprises: the user words, attribute information of the user words and environment categories, wherein the environment categories comprise: specific environment, general environment;
if yes, acquiring the environment category of the user word;
if the environment type of the user word is a common environment, adjusting the sequencing weight of the user word according to the attribute information of the user word;
if the environment category of the user word is a specific environment and the environment category of the candidate word is the same as the environment category of the user word, adjusting the ranking weight of the user word according to the attribute information of the user word.
5. The input method according to claim 4, characterized in that the method further comprises:
establishing the user word bank according to the historical input information of the user, wherein the historical input information comprises: word frequency information, time information and environment information of the user words; the environment information includes: a language environment, and/or an application environment.
6. The input method of claim 4, wherein the specific environment comprises any one or more of: the fixed upper environment and the fixed application environment;
the method further comprises determining a particular context of the user word as follows:
counting the use frequency of the user word and the binary co-occurrence frequency N of the user word and a specific text, and if the ratio of the co-occurrence frequency N to the use frequency of the user word is greater than a set value, determining that the environment type of the user word is a fixed context environment;
counting the use frequency of the user word and the co-occurrence frequency M of the user word in a specific application environment, and if the ratio of the co-occurrence frequency M to the use frequency of the user word is greater than a set value, determining that the environment type of the user word is a fixed application environment.
7. A user lexicon management apparatus, characterized in that the apparatus comprises:
the recording module is used for recording historical input information of a user;
the user word acquisition module is used for acquiring user words and attribute information thereof according to the historical user input information;
an environment category determination module configured to determine an environment category of the user word, the environment category including: specific environment, general environment;
and the word bank maintenance module is used for adding the user words, the attribute information of the user words and the environment types into the user word bank.
8. An input device, the device comprising: the system comprises a candidate word acquisition module, a first judgment module, an environment information acquisition module, a weight adjustment module, an environment determination module and a second judgment module;
the candidate word acquisition module is used for acquiring candidate words matched with the input information of the user;
the first judging module is used for determining whether the candidate word is a user word in a user word bank; the user lexicon comprises: the user words, attribute information of the user words and environment categories, wherein the environment categories comprise: specific environment, general environment;
the environment information acquisition module is used for acquiring the environment type of the user word;
the weight adjusting module is used for adjusting the sequencing weight of the user words according to the attribute information of the user words when the environment type of the user words is a common environment;
the environment determining module is used for determining the environment category of the candidate word when the environment category of the user word is a specific environment;
the second judging module is configured to determine whether the environment type of the candidate word is the same as the environment type of the user word, and trigger the weight adjusting module to adjust the ranking weight of the user word according to the attribute information of the user word when the environment type of the candidate word is the same as the environment type of the user word.
9. An electronic device, comprising: one or more processors, memory;
the memory is for storing computer-executable instructions, and the processor is for executing the computer-executable instructions to implement the method of any one of claims 4 to 6.
10. A readable storage medium having stored thereon instructions that are executed to implement the method of any of claims 4 to 6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811256879.0A CN111103986B (en) | 2018-10-26 | 2018-10-26 | User word stock management method and device, and user word stock input method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811256879.0A CN111103986B (en) | 2018-10-26 | 2018-10-26 | User word stock management method and device, and user word stock input method and device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111103986A true CN111103986A (en) | 2020-05-05 |
| CN111103986B CN111103986B (en) | 2023-11-14 |
Family
ID=70418466
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811256879.0A Active CN111103986B (en) | 2018-10-26 | 2018-10-26 | User word stock management method and device, and user word stock input method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111103986B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112395044A (en) * | 2020-11-10 | 2021-02-23 | 新华三技术有限公司合肥分公司 | Command line keyword filling method and device and network equipment |
Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101271459A (en) * | 2007-03-22 | 2008-09-24 | 北京搜狗科技发展有限公司 | Word library generation method, input method and input method system |
| CN101388011A (en) * | 2007-09-13 | 2009-03-18 | 北京搜狗科技发展有限公司 | Method and apparatus for recording information into user thesaurus |
| CN101398834A (en) * | 2007-09-29 | 2009-04-01 | 北京搜狗科技发展有限公司 | Processing method and device for input information and input method system |
| JP2010257392A (en) * | 2009-04-28 | 2010-11-11 | Sharp Corp | Device and method for inputting character, computer readable program, and recording medium |
| US20110173172A1 (en) * | 2007-04-11 | 2011-07-14 | Google Inc. | Input method editor integration |
| CN102207816A (en) * | 2010-07-16 | 2011-10-05 | 北京搜狗科技发展有限公司 | Method for performing adaptive input based on input environment, and input method system |
| CN102646022A (en) * | 2012-04-10 | 2012-08-22 | 北京搜狗科技发展有限公司 | Method and device for obtaining candidate |
| CN103376909A (en) * | 2012-04-19 | 2013-10-30 | 腾讯科技（深圳）有限公司 | Method and system of adjusting sequence of candidate characters in use of input methods |
| CN103956169A (en) * | 2014-04-17 | 2014-07-30 | 北京搜狗科技发展有限公司 | Speech input method, device and system |
| CN104317851A (en) * | 2014-10-14 | 2015-01-28 | 小米科技有限责任公司 | Word prompt method and device |
| CN106708282A (en) * | 2015-12-02 | 2017-05-24 | 北京搜狗科技发展有限公司 | Recommending method and device and device for recommending |
| CN107102746A (en) * | 2016-02-19 | 2017-08-29 | 北京搜狗科技发展有限公司 | Candidate word generation method, device and the device generated for candidate word |
| CN108427508A (en) * | 2017-02-15 | 2018-08-21 | 北京搜狗科技发展有限公司 | Input method and device, the method and apparatus for establishing LAN dictionary |
-
2018
- 2018-10-26 CN CN201811256879.0A patent/CN111103986B/en active Active
Patent Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101271459A (en) * | 2007-03-22 | 2008-09-24 | 北京搜狗科技发展有限公司 | Word library generation method, input method and input method system |
| US20110173172A1 (en) * | 2007-04-11 | 2011-07-14 | Google Inc. | Input method editor integration |
| CN101388011A (en) * | 2007-09-13 | 2009-03-18 | 北京搜狗科技发展有限公司 | Method and apparatus for recording information into user thesaurus |
| CN101398834A (en) * | 2007-09-29 | 2009-04-01 | 北京搜狗科技发展有限公司 | Processing method and device for input information and input method system |
| JP2010257392A (en) * | 2009-04-28 | 2010-11-11 | Sharp Corp | Device and method for inputting character, computer readable program, and recording medium |
| CN102207816A (en) * | 2010-07-16 | 2011-10-05 | 北京搜狗科技发展有限公司 | Method for performing adaptive input based on input environment, and input method system |
| CN102646022A (en) * | 2012-04-10 | 2012-08-22 | 北京搜狗科技发展有限公司 | Method and device for obtaining candidate |
| CN103376909A (en) * | 2012-04-19 | 2013-10-30 | 腾讯科技（深圳）有限公司 | Method and system of adjusting sequence of candidate characters in use of input methods |
| CN103956169A (en) * | 2014-04-17 | 2014-07-30 | 北京搜狗科技发展有限公司 | Speech input method, device and system |
| CN104317851A (en) * | 2014-10-14 | 2015-01-28 | 小米科技有限责任公司 | Word prompt method and device |
| CN106708282A (en) * | 2015-12-02 | 2017-05-24 | 北京搜狗科技发展有限公司 | Recommending method and device and device for recommending |
| CN107102746A (en) * | 2016-02-19 | 2017-08-29 | 北京搜狗科技发展有限公司 | Candidate word generation method, device and the device generated for candidate word |
| CN108427508A (en) * | 2017-02-15 | 2018-08-21 | 北京搜狗科技发展有限公司 | Input method and device, the method and apparatus for establishing LAN dictionary |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112395044A (en) * | 2020-11-10 | 2021-02-23 | 新华三技术有限公司合肥分公司 | Command line keyword filling method and device and network equipment |
| CN112395044B (en) * | 2020-11-10 | 2023-04-28 | 新华三技术有限公司合肥分公司 | Command line keyword filling method and device and network equipment |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111103986B (en) | 2023-11-14 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107608532B (en) | Association input method and device and electronic equipment | |
| CN107247519B (en) | Input method and device | |
| CN107544684B (en) | Candidate word display method and device | |
| CN107621886B (en) | Input recommendation method and device and electronic equipment | |
| CN107918496B (en) | Input error correction method and device for input error correction | |
| CN108073303B (en) | Input method and device and electronic equipment | |
| CN107564526B (en) | Processing method, apparatus and machine-readable medium | |
| CN107424612B (en) | Processing method, apparatus and machine-readable medium | |
| CN107291260B (en) | Information input method and device for inputting information | |
| CN109521888B (en) | Input method, device and medium | |
| CN111103986B (en) | User word stock management method and device, and user word stock input method and device | |
| CN108073294B (en) | Intelligent word forming method and device for intelligent word forming | |
| CN108073293B (en) | Method and device for determining target phrase | |
| CN109388252B (en) | Input method and device | |
| CN112181163A (en) | Input method, input device and input device | |
| CN109426359B (en) | Input method, device and machine readable medium | |
| CN114610163A (en) | Recommendation method, apparatus and medium | |
| CN108227952B (en) | Method and system for generating custom word and device for generating custom word | |
| CN113407099A (en) | Input method, device and machine readable medium | |
| CN110633017A (en) | Input method, input device and input device | |
| CN112083811B (en) | Candidate item display method and device | |
| CN112987941B (en) | Method and device for generating candidate words | |
| CN110858100B (en) | Method and device for generating association candidate words | |
| CN113703588A (en) | Input method, input device and input device | |
| CN108874170B (en) | Input method and device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |