CN108536684A - Automatically generate the method and device of English multiple-choice question answer choice - Google Patents
Automatically generate the method and device of English multiple-choice question answer choice Download PDFInfo
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Classifications
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/20—Natural language analysis
- G06F40/205—Parsing
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- G—PHYSICS
- G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
- G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
- G09B7/00—Electrically-operated teaching apparatus or devices working with questions and answers
- G09B7/02—Electrically-operated teaching apparatus or devices working with questions and answers of the type wherein the student is expected to construct an answer to the question which is presented or wherein the machine gives an answer to the question presented by a student
Abstract
The disclosure is directed to a kind of method, apparatus automatically generating English multiple-choice question answer choice, electronic equipment and storage mediums.Wherein, this method includes:Establish English feature-based data model, the data model includes multiple feature groups, obtain the investigation word in English multiple-choice question stem and the English multiple-choice question stem, it extracts the English multiple-choice question stem feature and investigates word feature, it is matched in the data model according to the investigation word feature, determine the specific characteristic group where the investigation word feature, the noise word of preset quantity is chosen from the specific characteristic group and/or other feature groups as interference option, using the preset investigation word as the correct option, described the correct option and the interference option combination are generated into English multiple-choice question answer choice.The disclosure can automatically generate English multiple-choice question answer choice by English multiple-choice question and wherein investigating the analysis of the feature of word.
Description
Technical field
This disclosure relates to which field of computer technology, English multiple-choice question answer choice is automatically generated in particular to one kind
Method, apparatus, electronic equipment and computer readable storage medium.
Background technology
Currently, deepening continuously with educational mode, various tests, examination ratio are consequently increased, to avoid testting, examine
Examination question mesh repeats, and needs the exam pool there are one topic substantial amounts.Particularly, it on the setting a question of English multiple-choice question, even more needs
Focus on quantity while ensure Item Quality, such as each examination question wrong option setting be bonded as far as possible user's fallibility point,
Or examination question option can deepen understanding of the student to different knowledge points.
However, the speed that professional sets a question is limited, to meet the topic of above-mentioned exam pool quantity, when needing to expend a large amount of
Between and energy, meanwhile, manually set a question and rely on experience that examination question option is set more, can not establish that effective, can grow up study
Model, the fallibility point of intelligent analytic induction user, knowledge weak spot.
In the prior art, there is no automatic answer choice or the existing skills of correlation of generation English multiple-choice question answer choice
Art.
Accordingly, it is desirable to provide one or more technical solutions that can at least solve the above problems.
It should be noted that information is only used for reinforcing the reason to the background of the disclosure disclosed in above-mentioned background technology part
Solution, therefore may include the information not constituted to the prior art known to persons of ordinary skill in the art.
Invention content
The disclosure be designed to provide a kind of method, apparatus automatically generating English multiple-choice question answer choice, electronics is set
Standby and computer readable storage medium, and then overcome at least to a certain extent due to the limitation and defect of the relevant technologies and lead
One or more problem caused.
According to one aspect of the disclosure, a kind of method automatically generating English multiple-choice question answer choice is provided, including:
Model foundation step, establishes English feature-based data model, and the data model includes multiple feature groups;
Stem obtaining step obtains the investigation word in English multiple-choice question stem and the English multiple-choice question stem;
Characteristic extraction step extracts the English multiple-choice question stem feature and investigates word feature, according to the investigation word
Feature is matched in the data model, determines the specific characteristic group where the investigation word feature;
Option selecting step, the noise word that preset quantity is chosen from the specific characteristic group and/or other feature groups are made
To interfere option;
Option generation step, using the preset investigation word as the correct option, by described the correct option and the interference
Option combination generates English multiple-choice question answer choice.
In a kind of exemplary embodiment of the disclosure, the stem feature includes temporal feature, logical implication, the choosing
Selecting step includes:
According to the characteristic attribute for investigating word described in the English multiple-choice question stem signature analysis, when the characteristic attribute includes
State attribute, logical attribute;
Identical with the investigation characteristic attribute of word Feature Words are screened in each feature group, by with the investigation word
The identical Feature Words of characteristic attribute are as interference option.
In a kind of exemplary embodiment of the disclosure, the option generation step includes:
Judge to whether there is recurrence option in English multiple-choice question answer choice;
If in the presence of the recurrence option of preset quantity is deleted, and choose in other described feature groups and selected with the repetition deleted
The identical Feature Words of item quantity are as interference option.
In a kind of exemplary embodiment of the disclosure, the model foundation step includes:
The degree of disturbance of each Feature Words is calculated according to the characteristic attribute for investigating word in each feature group;
Descending sort is carried out to the Feature Words in each feature group according to the degree of disturbance.
In a kind of exemplary embodiment of the disclosure, the method further includes:
Grade of difficulty is arranged to the English multiple-choice question stem;
Generate the correspondence of grade of difficulty and English multiple-choice question answer choice degree of disturbance;
It is selected and the English multiple-choice question stem in each feature group for carrying out descending sort according to the correspondence
The Feature Words that grade of difficulty corresponds to degree of disturbance interfere option as the English multiple-choice question stem.
In a kind of exemplary embodiment of the disclosure, the method further includes:
The English multiple-choice question stem is carried out n times test with corresponding English multiple-choice question answer choice to be fitted;
The degree of disturbance of Feature Words in the data model and each feature group is updated according to test fitting result;
According to data model update interference option after update, new English multiple-choice question answer choice is generated.
In a kind of exemplary embodiment of the disclosure, the investigation word feature includes that alphabet size writes feature, plural number spy
At least one of in sign, temporal feature, fixed phrase feature, regular collocation feature, word complexity characteristics.
In a kind of exemplary embodiment of the disclosure, the method further includes:
The English multiple-choice question answer choice is randomly ordered.
In one aspect of the present disclosure, a kind of device automatically generating English multiple-choice question answer choice is provided, including:
Model building module, for establishing English feature-based data model, the data model includes multiple feature groups;
Stem acquisition module, for obtaining the investigation word in English multiple-choice question stem and the English multiple-choice question stem;
Characteristic extracting module is examined for extracting the English multiple-choice question stem feature and investigating word feature according to described
It examines word feature to be matched in the data model, determines the specific characteristic group where the investigation word feature;
Option chooses module, is used for choosing the interference of preset quantity from the specific characteristic group and/or other feature groups
Word is as interference option;
Option generation module, is used for using the preset investigation word as the correct option, by described the correct option with it is described
Option combination is interfered to generate English multiple-choice question answer choice.
In one aspect of the present disclosure, a kind of electronic equipment is provided, including:
Processor;And
Memory is stored with computer-readable instruction on the memory, and the computer-readable instruction is by the processing
The method according to above-mentioned any one is realized when device executes.
In one aspect of the present disclosure, a kind of computer readable storage medium is provided, computer program is stored thereon with, institute
State the method realized when computer program is executed by processor according to above-mentioned any one.
The method for automatically generating English multiple-choice question answer choice in the exemplary embodiment of the disclosure, establishes English feature
Data model, the data model include multiple feature groups, obtain English multiple-choice question stem and the English multiple-choice question stem
In investigation word, extract the English multiple-choice question stem feature and investigate word feature, according to the investigation word feature described
Matched in data model, determine it is described investigation word feature where specific characteristic group, from the specific characteristic group and/or its
The noise word that preset quantity is chosen in his feature group will using the preset investigation word as the correct option as interference option
Described the correct option generates English multiple-choice question answer choice with the interference option combination.On the one hand, due to automatically generating English
Multiple-choice question answer choice, saves personnel cost, can shorten the time of setting a question;On the other hand, it establishes stem feature and investigates word
Characteristic model, and by being analyzed again the statistics for testing fitting result, the wrong option of generation can be made more to be bonded the easy of user
It is wrong, improve teaching efficiency.
It should be understood that above general description and following detailed description is only exemplary and explanatory, not
The disclosure can be limited.
Description of the drawings
Its example embodiment is described in detail by referring to accompanying drawing, the above and other feature and advantage of the disclosure will become
It is more obvious.
Fig. 1 is shown according to the method for automatically generating English multiple-choice question answer choice of one exemplary embodiment of the disclosure
Flow chart;
Fig. 2 shows the topics according to the English multiple-choice question comprising answer choice to be generated of one exemplary embodiment of the disclosure
Multiple feature group schematic diagrames in the dry and described stem;
Fig. 3 is shown to be answered according to the method for automatically generating English multiple-choice question answer choice of one exemplary embodiment of the disclosure
With the schematic diagram of scene;
Fig. 4 is shown according to the device for automatically generating English multiple-choice question answer choice of one exemplary embodiment of the disclosure
Schematic block diagram;
Fig. 5 diagrammatically illustrates the block diagram of the electronic equipment according to one exemplary embodiment of the disclosure;And
Fig. 6 diagrammatically illustrates the schematic diagram of the computer readable storage medium according to one exemplary embodiment of the disclosure.
Specific implementation mode
Example embodiment is described more fully with reference to the drawings.However, example embodiment can be real in a variety of forms
It applies, and is not understood as limited to embodiment set forth herein;On the contrary, thesing embodiments are provided so that the disclosure will be comprehensively and complete
It is whole, and the design of example embodiment is comprehensively communicated to those skilled in the art.Identical reference numeral indicates in figure
Same or similar part, thus repetition thereof will be omitted.
In addition, described feature, structure or characteristic can be incorporated in one or more implementations in any suitable manner
In example.In the following description, many details are provided to fully understand embodiment of the disclosure to provide.However,
It will be appreciated by persons skilled in the art that can be with technical solution of the disclosure without one in the specific detail or more
It is more, or other methods, constituent element, material, device, step may be used etc..In other cases, it is not shown in detail or describes
Known features, method, apparatus, realization, material or operation are to avoid fuzzy all aspects of this disclosure.
Block diagram shown in attached drawing is only functional entity, not necessarily must be corresponding with physically separate entity.
I.e., it is possible to realize these functional entitys using software form, or these are realized in the module of one or more softwares hardening
A part for functional entity or functional entity, or realized in heterogeneous networks and/or processor device and/or microcontroller device
These functional entitys.
In this exemplary embodiment, a kind of method automatically generating English multiple-choice question answer choice is provided firstly, it can be with
Applied to electronic equipments such as computers;With reference to shown in figure 1, which can wrap
Include following steps:
Model foundation step S110. establishes English feature-based data model, and the data model includes multiple feature groups;
Stem obtaining step S120. obtains the investigation word in English multiple-choice question stem and the English multiple-choice question stem;
Characteristic extraction step S130. extracts the English multiple-choice question stem feature and investigates word feature, is examined according to described
It examines word feature to be matched in the data model, determines the specific characteristic group where the investigation word feature;
Option selecting step S140. chooses the interference of preset quantity from the specific characteristic group and/or other feature groups
Word is as interference option;
Option generation step S150. using the preset investigation word as the correct option, by described the correct option with it is described
Option combination is interfered to generate English multiple-choice question answer choice.
According to the method for automatically generating English multiple-choice question answer choice in this example embodiment, on the one hand, due to automatic
English multiple-choice question answer choice is generated, personnel cost is saved, the time of setting a question can be shortened;On the other hand, stem feature is established
And word characteristic model is investigated, and by being analyzed again the statistics for testing fitting result, the wrong option of generation can be made more to be bonded
The fallibility point of user, improves teaching efficiency.
In the following, will be carried out to the method for automatically generating English multiple-choice question answer choice in this example embodiment further
Explanation.
In model foundation step S110, English feature-based data model can be established, the data model includes multiple spies
Sign group.
In this example embodiment, the purpose for establishing data model is to be chosen in the model and investigate word feature
Consistent noise word forms the answer choice of English multiple-choice question as interference option together with investigation word, and the feature group includes
But it is not limited to alphabet size and writes feature, Complex eigenvalues, temporal feature, fixed phrase feature, regular collocation feature, word complexity
Feature, temporal feature, logical implication etc..
In stem obtaining step S120, it can obtain in English multiple-choice question stem and the English multiple-choice question stem
Investigate word.
In this example embodiment, after establishing the namely specific multiple feature groups of English feature-based data model, obtain
The stem of the English multiple-choice question, and the investigation word included in the English multiple-choice question stem, while obtaining investigation word and existing
Position in English multiple-choice question stem.Further, the acquisition English multiple-choice question stem and English selection are being obtained
After inscribing the investigation word in stem, the investigation word can be replaced in the English multiple-choice question stem with special symbol, it is described
Comprising multiple investigation words in English multiple-choice question stem, word order label conduct can also be investigated to increasing in the special symbol
The serial number of English multiple-choice question, it is convenient to be examined with multiple in the English multiple-choice question stem after generating English multiple-choice question answer choice
Examine word one-to-one correspondence.
In characteristic extraction step S130, the English multiple-choice question stem feature can be extracted and investigate word feature, root
It is matched in the data model according to the investigation word feature, determines the specific characteristic group where the investigation word feature.
In this example embodiment, the investigation word in obtaining English multiple-choice question stem and the English multiple-choice question stem
Afterwards, the English multiple-choice question stem feature is obtained in the English multiple-choice question stem and investigation word and investigate word spy respectively
Sign, the English multiple-choice question stem feature and investigation word feature are consistent with the default feature group established, by the consistent institute of feature
It states English multiple-choice question stem feature and investigates word feature and matched with feature group, determine the specified spy where the investigation word feature
Sign group.
In this example embodiment, the investigation word feature include alphabet size write feature, Complex eigenvalues, temporal feature,
At least one of in fixed phrase feature, regular collocation feature, word complexity characteristics.
In this example embodiment, the stem feature includes at least one in temporal feature, logical implication.
In this example embodiment, the option selecting step includes:According to the English multiple-choice question stem signature analysis
The characteristic attribute for investigating word, the characteristic attribute includes tense attribute, logical attribute;Screening and institute in each feature group
The identical Feature Words of characteristic attribute for investigating word are stated, are selected Feature Words identical with the investigation characteristic attribute of word as interference
.For the English short essay in Fig. 2, wherein " She (loved) him very much and as he was not a
(strong) in child " one, " She () him very much and as he was not a () child " is stem portion
Point because there is keyword " was ", the tense attribute of stem feature is " past tense " because have keyword " as " and
" not ", so the logical attribute " turnover " of stem feature;" loved " " strong " is two investigation words, is belonging respectively to " dynamic
Multiple investigation word feature groups such as word " " temporal feature " " word complexity characteristics ";The feature group is matched with default feature group,
And Feature Words identical with the investigation characteristic attribute of word are screened in each feature group, by the feature category with the investigation word
Property identical Feature Words as interference option;It is " loved " that first, which is investigated word, and word feature and stem feature are investigated according to it
Tense attribute determines that an interference option is:" love " investigates the tense attribute and logic of word feature, stem feature according to it
Attribute determines that another two interference option is:“hate”“hated”.
In this example embodiment, the option generation step includes:Judge whether deposited in English multiple-choice question answer choice
In recurrence option;If in the presence of the recurrence option of preset quantity is deleted, and choose the repetition with deletion in other described feature groups
The identical Feature Words of number of options are as interference option.Such as wherein " She (loved) the him very much of above-mentioned English short essay
For and as he was not a (strong) child " one, in the investigation word feature and logic of Feature Words " strong "
It in the stem feature of attribute, is likely to select noise word " happy ", at this time, it is necessary to it is identical dry to delete one of them
Word is disturbed, and chooses another noise word in other described feature groups and generates interference option.
In this example embodiment, the model foundation step includes:According to the investigation word in each feature group
Characteristic attribute calculates the degree of disturbance of each Feature Words, and the foundation of degree of disturbance can be determined according to user preset disturbance level
, it can also be repeatedly to be fitted in test process by examination question tester after generating examination question, data acquisition point chosen to test
The degree of disturbance obtained is analysed, after establishing degree of disturbance, descending row is carried out to the Feature Words in each feature group according to the degree of disturbance
Sequence.
In this example embodiment, when if there is investigating word feature and stem characteristic less than preset options number, just
It needs to choose multiple noise words in same feature race, and when the interference option chosen is multiple noise words in same feature group
When, then it sorts and chooses according to the degree of disturbance of noise word in each feature group.
In option selecting step S140, present count can be chosen from the specific characteristic group and/or other feature groups
The noise word of amount is as interference option.
In this example embodiment, after determining the noise word by degree of disturbance, using the noise word as interference option,
Quantity is the difference of default English multiple-choice question answer choice number and investigation word quantity.It is illustrated in figure 3 the generation of certain English multiple-choice question
A cloze test examination question, it is 4 often to inscribe and preset English multiple-choice question answer choice number, and it is 1 to investigate word quantity, so often
A investigation word needs corresponding 3 noise words of selection as interference option.
In this example embodiment, the method further includes:Grade of difficulty is arranged to the English multiple-choice question stem;It generates
The correspondence of grade of difficulty and English multiple-choice question answer choice degree of disturbance;Descending sort is being carried out according to the correspondence
The Feature Words of degree of disturbance corresponding with the English multiple-choice question stem grade of difficulty are selected to be selected as the English in each feature group
Select topic stem interference option.By the above method, it can select different difficulty when generating English multiple-choice question answer choice and generate
The answer choice of corresponding difficulty can thus use same English multiple-choice question, for different users, automated intelligent generate with
The user corresponds to the English multiple-choice question of difficulty.
In this example embodiment, the method further includes:The English multiple-choice question stem is selected with corresponding English
It inscribes answer choice and carries out n times test fitting;It is updated according to test fitting result special in the data model and each feature group
Levy the degree of disturbance of word;According to data model update interference option after update, new English multiple-choice question answer choice is generated.In reality
When the establishment of English multiple-choice question answer choice, especially in some more important examination test occasions, a certain number of surveys are organized
Examination person carries out n times test fitting training to the English multiple-choice question answer choice, on the one hand can gather special in each feature group
The confidence interval for levying the degree of disturbance of word, excludes low options, makes English multiple-choice question answer choice more added with the property investigated;Another party
Face selects different testers to carry out n times test fitting training to the English multiple-choice question answer choice according to different users,
English multiple-choice question answer choice can be made more targeted, can more reach investigation and promote the destination of study.
It, can be using the preset investigation word as the correct option, by the correct choosing in option generation step S150
Item generates English multiple-choice question answer choice with the interference option combination.
In this example embodiment, the method further includes:It, will be described after generating whole English multiple-choice question answer choices
English multiple-choice question answer choice is randomly ordered, and records the option for investigating word, conveniently gos over examination papers.
It should be noted that although describing each step of method in the disclosure with particular order in the accompanying drawings,
This, which does not require that or implies, to execute these steps according to the particular order, or has to carry out the step shown in whole
It could realize desired result.Additional or alternative, it is convenient to omit multiple steps are merged into a step and held by certain steps
Row, and/or a step is decomposed into execution of multiple steps etc..
In addition, in this exemplary embodiment, additionally providing a kind of device automatically generating English multiple-choice question answer choice.Ginseng
Shown in Fig. 4, which may include:Model building module 410, stem
Acquisition module 420, characteristic extracting module 430, option choose module 440 and option generation module 450.Wherein:
Model building module 410, for establishing English feature-based data model, the data model includes multiple feature groups;
Stem acquisition module 420, for obtaining the investigation in English multiple-choice question stem and the English multiple-choice question stem
Word;
Characteristic extracting module 430, for extracting the English multiple-choice question stem feature and investigating word feature, according to described
It investigates word feature to be matched in the data model, determines the specific characteristic group where the investigation word feature;
Option chooses module 440, is used for choosing the dry of preset quantity from the specific characteristic group and/or other feature groups
Word is disturbed as interference option;
Option generation module 450 is used for using the preset investigation word as the correct option, by described the correct option and institute
It states interference option combination and generates English multiple-choice question answer choice.
The detail of the apparatus module of English multiple-choice question answer choice is respectively automatically generated among the above in corresponding sound
Frequency range falls in recognition methods and is described in detail, therefore details are not described herein again.
It should be noted that although being referred to the device for automatically generating English multiple-choice question answer choice in above-detailed
400 several modules or unit, but this division is not enforceable.In fact, according to embodiment of the present disclosure, on
The feature and function of two or more modules either unit of text description can embody in a module or unit.Instead
It, the feature and function of an above-described module either unit can be further divided by multiple modules or unit Lai
It embodies.
In addition, in an exemplary embodiment of the disclosure, additionally providing a kind of electronic equipment that can realize the above method.
Person of ordinary skill in the field it is understood that various aspects of the invention can be implemented as system, method or
Program product.Therefore, various aspects of the invention can be embodied in the following forms, i.e.,:Complete hardware embodiment, completely
Software implementation (including firmware, microcode etc.) or hardware and software in terms of combine embodiment, may be collectively referred to as here
Circuit, " module " or " system ".
The electronic equipment 500 of this embodiment according to the present invention is described referring to Fig. 5.The electronics that Fig. 5 is shown is set
Standby 500 be only an example, should not bring any restrictions to the function and use scope of the embodiment of the present invention.
As shown in figure 5, electronic equipment 500 is showed in the form of universal computing device.The component of electronic equipment 500 can wrap
It includes but is not limited to:Above-mentioned at least one processing unit 510, above-mentioned at least one storage unit 520, connection different system component
The bus 530 of (including storage unit 520 and processing unit 510), display unit 540.
Wherein, the storage unit has program stored therein code, and said program code can be held by the processing unit 510
Row so that the processing unit 510 executes various according to the present invention described in above-mentioned " illustrative methods " part of this specification
The step of exemplary embodiment.For example, the processing unit 510 can execute step S110 as shown in fig. 1 to step
S150。
Storage unit 520 may include the readable medium of volatile memory cell form, such as Random Access Storage Unit
(RAM) 5201 and/or cache memory unit 5202, it can further include read-only memory unit (ROM) 5203.
Storage unit 520 can also include program/utility with one group of (at least one) program module 5205
5204, such program module 5205 includes but not limited to:Operating system, one or more application program, other program moulds
Block and program data may include the realization of network environment in each or certain combination in these examples.
Bus 530 can be to indicate one or more in a few class bus structures, including storage unit bus or storage
Cell controller, peripheral bus, graphics acceleration port, processing unit use the arbitrary bus structures in a variety of bus structures
Local bus.
Electronic equipment 500 can also be with one or more external equipments 570 (such as keyboard, sensing equipment, bluetooth equipment
Deng) communication, can also be enabled a user to one or more equipment interact with the electronic equipment 500 communicate, and/or with make
Any equipment that the electronic equipment 500 can be communicated with one or more of the other computing device (such as router, modulation /demodulation
Device etc.) communication.This communication can be carried out by input/output (I/O) interface 550.Also, electronic equipment 500 can be with
By network adapter 560 and one or more network (such as LAN (LAN), wide area network (WAN) and/or public network,
Such as internet) communication.As shown, network adapter 560 is communicated by bus 530 with other modules of electronic equipment 500.
It should be understood that although not shown in the drawings, other hardware and/or software module can not used in conjunction with electronic equipment 500, including but not
It is limited to:Microcode, device driver, redundant processing unit, external disk drive array, RAID system, tape drive and
Data backup storage system etc..
By the description of above embodiment, those skilled in the art is it can be readily appreciated that example embodiment described herein
It can also be realized in such a way that software is in conjunction with necessary hardware by software realization.Therefore, implemented according to the disclosure
The technical solution of example can be expressed in the form of software products, which can be stored in a non-volatile memories
In medium (can be CD-ROM, USB flash disk, mobile hard disk etc.) or on network, including some instructions are so that a computing device (can
To be personal computer, server, terminal installation or network equipment etc.) it executes according to the method for the embodiment of the present disclosure.
In an exemplary embodiment of the disclosure, a kind of computer readable storage medium is additionally provided, energy is stored thereon with
Enough realize the program product of this specification above method.In some possible embodiments, various aspects of the invention can be with
It is embodied as a kind of form of program product comprising program code, it is described when described program product is run on the terminal device
Program code be used for make the terminal device execute described in above-mentioned " illustrative methods " part of this specification according to the present invention
The step of various exemplary embodiments.
Refering to what is shown in Fig. 6, the program product 600 according to an embodiment of the invention for realizing the above method is described,
It may be used portable compact disc read only memory (CD-ROM) and includes program code, and can in terminal device, such as
It is run on PC.However, the program product of the present invention is without being limited thereto, in this document, readable storage medium storing program for executing can be appointed
What include or storage program tangible medium, the program can be commanded execution system, device either device use or and its
It is used in combination.
The arbitrary combination of one or more readable mediums may be used in described program product.Readable medium can be readable letter
Number medium or readable storage medium storing program for executing.Readable storage medium storing program for executing for example can be but be not limited to electricity, magnetic, optical, electromagnetic, infrared ray or
System, device or the device of semiconductor, or the arbitrary above combination.The more specific example of readable storage medium storing program for executing is (non exhaustive
List) include:It is electrical connection, portable disc, hard disk, random access memory (RAM) with one or more conducting wires, read-only
Memory (ROM), erasable programmable read only memory (EPROM or flash memory), optical fiber, portable compact disc read only memory
(CD-ROM), light storage device, magnetic memory device or above-mentioned any appropriate combination.
Computer-readable signal media may include in a base band or as the data-signal that a carrier wave part is propagated,
In carry readable program code.The data-signal of this propagation may be used diversified forms, including but not limited to electromagnetic signal,
Optical signal or above-mentioned any appropriate combination.Readable signal medium can also be any readable Jie other than readable storage medium storing program for executing
Matter, which can send, propagate either transmission for used by instruction execution system, device or device or and its
The program of combined use.
The program code for including on readable medium can transmit with any suitable medium, including but not limited to wirelessly, have
Line, optical cable, RF etc. or above-mentioned any appropriate combination.
It can be write with any combination of one or more programming languages for executing the program that operates of the present invention
Code, described program design language include object oriented program language-Java, C++ etc., further include conventional
Procedural programming language-such as " C " language or similar programming language.Program code can be fully in user
It executes on computing device, partly execute on a user device, being executed as an independent software package, partly in user's calculating
Upper side point is executed or is executed in remote computing device or server completely on a remote computing.It is being related to far
In the situation of journey computing device, remote computing device can pass through the network of any kind, including LAN (LAN) or wide area network
(WAN), it is connected to user calculating equipment, or, it may be connected to external computing device (such as utilize ISP
To be connected by internet).
In addition, above-mentioned attached drawing is only the schematic theory of the processing included by method according to an exemplary embodiment of the present invention
It is bright, rather than limit purpose.It can be readily appreciated that the time that above-mentioned processing shown in the drawings did not indicated or limited these processing is suitable
Sequence.In addition, being also easy to understand, these processing for example can be executed either synchronously or asynchronously in multiple modules.
Those skilled in the art after considering the specification and implementing the invention disclosed here, will readily occur to its of the disclosure
His embodiment.This application is intended to cover any variations, uses, or adaptations of the disclosure, these modifications, purposes or
Adaptive change follow the general principles of this disclosure and include the undocumented common knowledge in the art of the disclosure or
Conventional techniques.The description and examples are only to be considered as illustrative, and the true scope and spirit of the disclosure are by claim
It points out.
It should be understood that the present disclosure is not limited to the precise structures that have been described above and shown in the drawings, and
And various modifications and changes may be made without departing from the scope thereof.The scope of the present disclosure is only limited by the attached claims.
Claims (11)
1. a kind of method automatically generating English multiple-choice question answer choice, which is characterized in that including:
Model foundation step, establishes English feature-based data model, and the data model includes multiple feature groups;
Stem obtaining step obtains the investigation word in English multiple-choice question stem and the English multiple-choice question stem;
Characteristic extraction step extracts the English multiple-choice question stem feature and investigates word feature, according to the investigation word feature
It is matched in the data model, determines the specific characteristic group where the investigation word feature;
Option selecting step chooses the noise word of preset quantity as dry from the specific characteristic group and/or other feature groups
Disturb option;
Option generation step, using the preset investigation word as the correct option, by described the correct option and the interference option
Combination producing English multiple-choice question answer choice.
2. the method as described in claim 1, which is characterized in that the stem feature includes temporal feature, logical implication, described
Option selecting step includes:
According to the characteristic attribute for investigating word described in the English multiple-choice question stem signature analysis, the characteristic attribute includes tense category
Property, logical attribute;
Feature Words identical with the investigation characteristic attribute of word are screened in each feature group, by the feature with the investigation word
The identical Feature Words of attribute are as interference option.
3. method as claimed in claim 1 or 2, which is characterized in that the option generation step includes:
Judge to whether there is recurrence option in English multiple-choice question answer choice;
If in the presence of the recurrence option of preset quantity is deleted, and choose the recurrence option number with deletion in other described feature groups
Identical Feature Words are measured as interference option.
4. method as claimed in claim 2, which is characterized in that the model foundation step includes:
The degree of disturbance of each Feature Words is calculated according to the characteristic attribute for investigating word in each feature group;
Descending sort is carried out to the Feature Words in each feature group according to the degree of disturbance.
5. method as claimed in claim 4, which is characterized in that the method further includes:
Grade of difficulty is arranged to the English multiple-choice question stem;
Generate the correspondence of grade of difficulty and English multiple-choice question answer choice degree of disturbance;
It is selected and the English multiple-choice question stem difficulty in each feature group for carrying out descending sort according to the correspondence
The Feature Words that grade corresponds to degree of disturbance interfere option as the English multiple-choice question stem.
6. method as described in claim 1 or 4, which is characterized in that the method further includes:
The English multiple-choice question stem is carried out n times test with corresponding English multiple-choice question answer choice to be fitted;
The degree of disturbance of Feature Words in the data model and each feature group is updated according to test fitting result;
According to data model update interference option after update, new English multiple-choice question answer choice is generated.
7. the method as described in claim 1, which is characterized in that the investigation word feature includes that alphabet size writes feature, plural number
At least one of in feature, temporal feature, fixed phrase feature, regular collocation feature, word complexity characteristics.
8. the method as described in claim 1, which is characterized in that the method further includes:
The English multiple-choice question answer choice is randomly ordered.
9. a kind of device automatically generating English multiple-choice question answer choice, which is characterized in that described device includes:
Model building module, for establishing English feature-based data model, the data model includes multiple feature groups;
Stem acquisition module, for obtaining the investigation word in English multiple-choice question stem and the English multiple-choice question stem;
Characteristic extracting module, for extracting the English multiple-choice question stem feature and investigating word feature, according to the investigation word
Feature is matched in the data model, determines the specific characteristic group where the investigation word feature;
Option chooses module, and the noise word for being used for choosing preset quantity from the specific characteristic group and/or other feature groups is made
To interfere option;
Option generation module is used for using the preset investigation word as the correct option, by described the correct option and the interference
Option combination generates English multiple-choice question answer choice.
10. a kind of electronic equipment, which is characterized in that including:
Processor;And
Memory is stored with computer-readable instruction on the memory, and the computer-readable instruction is held by the processor
Method according to any one of claim 1 to 8 is realized when row.
11. a kind of computer readable storage medium, is stored thereon with computer program, the computer program is executed by processor
Shi Shixian is according to any one of claim 1 to 8 the method.
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PCT/CN2018/092779 WO2019200706A1 (en) | 2018-04-18 | 2018-06-26 | Method and device for automatically generating answer options to english multiple-choice question |
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Cited By (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN109615947A (en) * | 2018-12-07 | 2019-04-12 | 深圳市柯达科电子科技有限公司 | A kind of method and readable storage medium storing program for executing assisting foreign language learning |
CN109859554A (en) * | 2019-03-29 | 2019-06-07 | 上海乂学教育科技有限公司 | Adaptive english vocabulary learning classification pushes away topic device and computer learning system |
CN109949637A (en) * | 2019-03-13 | 2019-06-28 | 广东小天才科技有限公司 | A kind of objective item purpose answers method and apparatus automatically |
CN110516232A (en) * | 2019-07-22 | 2019-11-29 | 北京师范大学 | A kind of automatic proposition method and system for Chinese evaluation and test |
CN113239689A (en) * | 2021-07-07 | 2021-08-10 | 北京语言大学 | Selection question interference item automatic generation method and device for confusing word investigation |
CN113706951A (en) * | 2021-08-26 | 2021-11-26 | 陕西万唯教育传媒有限公司 | On-line education method, system and computer storage medium |
Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20040253569A1 (en) * | 2003-04-10 | 2004-12-16 | Paul Deane | Automated test item generation system and method |
CN101308486A (en) * | 2008-03-21 | 2008-11-19 | 北京印刷学院 | Test question automatic generation system and method |
CN103136453A (en) * | 2013-03-25 | 2013-06-05 | 华北电力大学(保定) | Automatic test paper formation method and automatic scoring method of document manipulation subjects |
Family Cites Families (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5565316A (en) * | 1992-10-09 | 1996-10-15 | Educational Testing Service | System and method for computer based testing |
CN101470695A (en) * | 2007-12-28 | 2009-07-01 | 英业达股份有限公司 | System and method for dynamically generating examination questions |
CN101261617A (en) * | 2008-04-08 | 2008-09-10 | 黎章 | Machine proposition method and system |
US20100273138A1 (en) * | 2009-04-28 | 2010-10-28 | Philip Glenny Edmonds | Apparatus and method for automatic generation of personalized learning and diagnostic exercises |
CN107463537A (en) * | 2016-06-03 | 2017-12-12 | 北京新唐思创教育科技有限公司 | A kind of method that structuring processing is carried out to text message |
-
2018
- 2018-04-18 CN CN201810349667.0A patent/CN108536684A/en active Pending
- 2018-06-26 WO PCT/CN2018/092779 patent/WO2019200706A1/en active Application Filing
Patent Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20040253569A1 (en) * | 2003-04-10 | 2004-12-16 | Paul Deane | Automated test item generation system and method |
CN101308486A (en) * | 2008-03-21 | 2008-11-19 | 北京印刷学院 | Test question automatic generation system and method |
CN103136453A (en) * | 2013-03-25 | 2013-06-05 | 华北电力大学(保定) | Automatic test paper formation method and automatic scoring method of document manipulation subjects |
Non-Patent Citations (1)
Title |
---|
丁向民 等: "多项选择题自动生成技术综述", 《现代计算机》 * |
Cited By (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN109615947A (en) * | 2018-12-07 | 2019-04-12 | 深圳市柯达科电子科技有限公司 | A kind of method and readable storage medium storing program for executing assisting foreign language learning |
CN109949637A (en) * | 2019-03-13 | 2019-06-28 | 广东小天才科技有限公司 | A kind of objective item purpose answers method and apparatus automatically |
CN109949637B (en) * | 2019-03-13 | 2021-07-16 | 广东小天才科技有限公司 | Automatic answering method and device for objective questions |
CN109859554A (en) * | 2019-03-29 | 2019-06-07 | 上海乂学教育科技有限公司 | Adaptive english vocabulary learning classification pushes away topic device and computer learning system |
CN110516232A (en) * | 2019-07-22 | 2019-11-29 | 北京师范大学 | A kind of automatic proposition method and system for Chinese evaluation and test |
CN110516232B (en) * | 2019-07-22 | 2021-06-22 | 北京师范大学 | Automatic proposition method and system for Chinese evaluation |
CN113239689A (en) * | 2021-07-07 | 2021-08-10 | 北京语言大学 | Selection question interference item automatic generation method and device for confusing word investigation |
CN113706951A (en) * | 2021-08-26 | 2021-11-26 | 陕西万唯教育传媒有限公司 | On-line education method, system and computer storage medium |
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