CN110473435A - A kind of the word assistant learning system and method for the quantification with learning cycle - Google Patents
A kind of the word assistant learning system and method for the quantification with learning cycle Download PDFInfo
- Publication number
- CN110473435A CN110473435A CN201910693170.5A CN201910693170A CN110473435A CN 110473435 A CN110473435 A CN 110473435A CN 201910693170 A CN201910693170 A CN 201910693170A CN 110473435 A CN110473435 A CN 110473435A
- Authority
- CN
- China
- Prior art keywords
- word
- study
- user
- module
- learning
- 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 30
- 238000011002 quantification Methods 0.000 title claims abstract description 14
- 238000012360 testing method Methods 0.000 claims abstract description 77
- 230000000694 effects Effects 0.000 claims abstract description 31
- 230000004044 response Effects 0.000 claims abstract description 14
- 239000011159 matrix material Substances 0.000 claims description 103
- 230000006870 function Effects 0.000 claims description 28
- 230000008569 process Effects 0.000 claims description 16
- 238000004422 calculation algorithm Methods 0.000 claims description 13
- 238000012797 qualification Methods 0.000 claims description 8
- 230000001186 cumulative effect Effects 0.000 claims description 4
- 238000009825 accumulation Methods 0.000 claims description 3
- 238000004458 analytical method Methods 0.000 claims description 3
- 235000013399 edible fruits Nutrition 0.000 claims description 3
- 238000007689 inspection Methods 0.000 claims description 3
- 238000005457 optimization Methods 0.000 claims description 2
- 235000010894 Artemisia argyi Nutrition 0.000 description 3
- 244000030166 artemisia Species 0.000 description 3
- 238000004364 calculation method Methods 0.000 description 3
- 230000008713 feedback mechanism Effects 0.000 description 3
- 230000006399 behavior Effects 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000007667 floating Methods 0.000 description 2
- 238000004445 quantitative analysis Methods 0.000 description 2
- 235000015170 shellfish Nutrition 0.000 description 2
- 238000007476 Maximum Likelihood Methods 0.000 description 1
- 230000003044 adaptive effect Effects 0.000 description 1
- 230000003542 behavioural effect Effects 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 210000004027 cell Anatomy 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 238000000151 deposition Methods 0.000 description 1
- 238000009795 derivation Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 230000002452 interceptive effect Effects 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 230000001343 mnemonic effect Effects 0.000 description 1
- 230000001737 promoting effect Effects 0.000 description 1
- 238000007493 shaping process Methods 0.000 description 1
- 210000000352 storage cell Anatomy 0.000 description 1
- 230000009897 systematic effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/20—Education
- G06Q50/205—Education administration or guidance
-
- 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
- G09B19/00—Teaching not covered by other main groups of this subclass
- G09B19/06—Foreign languages
-
- 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
- G09B5/00—Electrically-operated educational appliances
- G09B5/06—Electrically-operated educational appliances with both visual and audible presentation of the material to be studied
- G09B5/065—Combinations of audio and video presentations, e.g. videotapes, videodiscs, television systems
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Educational Administration (AREA)
- Educational Technology (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Tourism & Hospitality (AREA)
- Strategic Management (AREA)
- Multimedia (AREA)
- Entrepreneurship & Innovation (AREA)
- Health & Medical Sciences (AREA)
- Economics (AREA)
- General Health & Medical Sciences (AREA)
- Human Resources & Organizations (AREA)
- Marketing (AREA)
- Primary Health Care (AREA)
- General Business, Economics & Management (AREA)
- Electrically Operated Instructional Devices (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The present invention relates to a kind of word assistant learning system of quantification with learning cycle and methods, including client and server；The client includes: study request module, graphical study interface and learning effect feedback module；The server disposition has test module and study module before storage unit, intelligent decision unit,；Learn request to user to respond.The present invention is adaptively adjusted system response according to the difficulty difference of word and the learning ability difference of user, and auxiliary user carries out targeted, efficient word study.
Description
Technical field
The present invention relates to English study fields, are related to a kind of English assistant learning system, especially with learning cycle
The word assistant learning system and method for quantification.
Background technique
In English study, there are various electronic devices to learn for promoting the word of English learner in the prior art
Efficiency has in the beginning of this century and utilizes computer technology and Internet application assisted learning.Also have using mobile terminal using auxiliary
Help english vocabulary learning, however in the prior art, the interactive function of learning software is still extremely limited, and intelligence degree compared with
It is low.Therefore, this invention address that by ripe algorithm module and data scientific method, the degree of intelligence of learning system is improved.
Summary of the invention
Technology of the invention solves the problems, such as: overcome the deficiencies of the prior art and provide it is a kind of with learning cycle based on fixed
The English word learning system and method for quantitative analysis, improves the degree of intelligence of learning system.It is directed in each learning cycle
Property recommend word list, auxiliary user carries out efficient word study in each learning cycle.
Technical solution of the invention: the word assistant learning system of a quantification with learning cycle, study
Period refers to that user learns the behavior duration section an of word list；The selected learning cycle of this system is one day, also
I.e. daily 0 up to 24 times, the word list of system recommendation user study is fixed and invariable.System is according to the difficulty of word
Difference and the learning ability difference of user are adaptively adjusted system response, targetedly recommend word in each learning cycle
List, auxiliary user carry out efficient word study in each learning cycle.
Although the selected learning cycle of this system is one day, the similar solution for having the learning cycle as unit of day
Scheme can be converted into the solution that learning cycle is one day and being sub-divided into learning cycle daily, therefore similar
The solution of learning cycle as unit of day is also within the scope of the present invention.
Present system includes: client and server；
The client includes: study request module, graphical study interface and learning effect feedback module；Study request
Module is responsible for sending the study request of user to server, receives the operation result of study module in server；Graphical study
Interface passes through patterned study according to the operation result from intelligent decision module that study module in server is passed back
Interface, auxiliary user carry out word study；Learning effect feedback module connects together with graphical study interface in learning process
The response for receiving the study module in server, is collected simultaneously feedback information of the user about learning effect, the feedback information
Refer to the test result carried out after user learns each word the time it takes, and study to user's learning outcome；It will
The feedback information and corresponding user and word being collected into are bound into a data packet, feed back to the storage unit in server,
For updating storage User Information Database and word database in unit；
The server disposition has test module and study module before storage unit, intelligent decision unit,；Not to user
Request with the stage responds；
The storage unit, it is responsible to receive to learn by oneself the anti-of the learning effect feedback module in preceding test module and client
Feedforward information, User Information Database and word database inside updating unit；User Information Database is responsible for recording user's
Learn history, it is described study history, that is, user learned word, learn each word when the time it takes and user word test
In test result；Word database is responsible for recording the case where each word is learnt, and surveys including learning the ability of user of word
Test result, each user word in study consumed by the time summarize and to the inferred results of word difficulty；
The intelligent decision unit receives and carrys out the study comprising word list to be learned of self-learning module and request, from depositing
Storage unit obtains user's learning ability, word difficulty and the user's learning records that user reflects in learning process, and is based on
These data provide the word list of same day recommendation study for user；
Test module before utilizes the group of words in word database for testing user's learning ability of user
Volume, tests user's word learning ability, obtains test result；On the one hand test result is fed back into client and allows user
Know, test result is on the other hand passed to storage unit, for updating User Information Database and word database；
The study module is the module that server is used to communicate with client, it is not needed more in user information
Receive the study request from client when new, this request is then transmitted to intelligent decision module, to intelligent decision module
Solution finishes, and study module receives the word list for recommending study on the same day for solving and obtaining, by this word and corresponding use
Html language generation word learns the page, is back to the graphical study interface of client by http agreement, while by the same day
The word list of study is recommended to be transmitted to learning effect feedback module as learning records；The education resource include Chinese dispel misgivings and
The audio of word pronunciation.
The word assistant learning system of quantification with learning cycle, it is characterised in that: the intelligent decision unit packet
Include: cost matrix update module, Solving Assignment Problem module, one-zero programming solve module；The cost matrix update module is used for
The calculating of initial cost matrix, and cost matrix is modified during solving the daily word list for recommending study；
Solving Assignment Problem module run the Hungary Algorithm for solving assignment problem using cost matrix as input, calculating with
Family learns the inverse of requested word list, between day last, system daily requirement is recommended to learn to user for it
The word list of habit, and in inverseIt recommends study to the daily requirement provided between day last to user
Under word list, study number of days needed for each word, wherein W indicates that user learns the total words in request, and M indicates user
The daily word number learnt specified in study request；One-zero programming solves module and asks dedicated for solving one-zero programming
Topic, the study number of days needed for the word with maximum study number of days are greater than the word list that daily requirement recommends study to user
Corresponding total study number of days subtractsWhen, the daily requirement that Solving Assignment Problem module is obtained is recommended to user
Word list as input, one-zero programming problem solver module is called, to verify the word column that Solving Assignment Problem module obtains
The feasibility of table.
The word assisted learning method of quantification with learning cycle, it is characterised in that the following steps are included:
Step 1: user issues study request by client, and server receives this request, judges user information data
Whether user recent learning ability information is had in library；If user system for the first time log in or User Information Database in user
It is not updated within learning ability information one week or more, then calls test module before to test user's learning ability, go to
Step 2；If simultaneously non-first time logs in user, and user's learning ability information in user information database is updated in one day
It crosses, jumps directly to step 3；
Step 2: calling user's learning ability of test module test user before learning, utilize the group of words in word database
Volume, investigates user's word learning ability, obtains test result；Test volume is designed based on item response theory, using shellfish
This current learning ability of analysis method estimating subscriber's of leaf；After obtaining test result, test result is on the one hand fed back into client
It allows user to know, test result is on the other hand passed to storage unit, for updating User Information Database and word database；
Step 3: study module responds the study request of user, and user it is expected that the word list of study is sent as request
To intelligent decision unit；Intelligent decision unit responds this request, initializes, and reads user information from storage unit
And user it is expected the relevant information of the word in the word list of study, is used for intelligent decision；
Step 4: intelligent decision unit calls cost matrix update module, is assessed using forgetting curve and is pushed away on different opportunitys
Recommend different words to improve user's learning efficiency effect, then call Solving Assignment Problem module, using cost matrix as
Input, runs the Hungary Algorithm for solving assignment problem, calculates the inverse that user learns requested word list, between day last, system daily requirement recommends the word list of study to user for it.Later, intelligent decision list
Whether study number of days needed for word of the member first judgement with maximum study number of days is more than that daily requirement is recommended to learn to user
The corresponding total study number of days of word list subtractsIf it does, then by calculated word list and cost
Input matrix solves in module to one-zero programming, and the feasibility of module check solution, if solution is infeasible, intelligence are solved by one-zero programming
Energy decision package calls cost matrix update module, and updating in cost matrix has generation corresponding to the maximum word for learning number of days
Value, reruns Solving Assignment Problem module, and check again for solving result, repeatedly until the solution acquired is feasible.So
Afterwards, intelligent decision module provides word list of the system daily requirement to user's recommendation study, and the same day is needed to push away to user
The word list for recommending study is sent to study module.
Step 5: study module receives the word list for recommending study on the same day from intelligent decision module, uses html language
Speech generates the study page comprising word and education resource, and the graphical study interface of client is back to by http agreement,
The word list of study is recommended to be transmitted to learning effect feedback module as learning records the same day simultaneously, the education resource includes
The audio of Chinese paraphrase and word pronunciation；
Step 6: study is completed, and calls learning effect feedback module, collects feedback information of the user about learning effect, and
Use these information update User Information Databases and word database.
The cost matrix update module that is accomplished by of the cost matrix update module is responsible for calculating cost matrix.Cost
Matrix is indicated with letter C, is that a shape is, element is the matrix of positive integer.I-th in C matrix
The element representation of row jth column is cij, it indicates that the date by user's last time study word i is arranged in from entire learning process
Reciprocal the from finish timeIt when, user is in order to allow oneself to the qualification of word i in institute
There is word study to reach γ when finishingcOr more, learn the smallest cumulative learning number of days, also known as cost required for word i,
In the narration of the element arranged above with respect to the i-th row jth in C matrix, i is taken all over 1 to all integers between W, including 1 and W, j take all over 1
It arrivesBetween all integers, including 1 HeThe qualification in forgetting curve theory by using
It is calculated in the function of fitting forgetting curve, forgetting curve function selects negative exponent function or models of negative index functions.In
Run cost matrix update module, cost matrix update module will be used according in theory completely for the first time after user's study request arrives
Cost matrix is calculated in the function of fitting forgetting curve, and calculated cost matrix is separately standby as initial cost matrix
Part.If solution is sent to one-zero programming due to can not judge whether solution is feasible and solves module, and 0-1 by Solving Assignment Problem module
Programming evaluation module discovery solution is infeasible, and cost matrix update module is responsible for updating cost matrix at this time: if total acquired
Study number of days needed for number of days is less than the word with maximum study number of days is practised, then cost matrix update module increases cost matrix
In there is study number of the word of maximum study number of days under the currently assigned scheme corresponding date, every time plus 1, until total learn
Practising number of days can be not less than maximum study number of days；If the total study number of days acquired is not less than the word institute with maximum study number of days
The study number of days needed, but solution is still infeasible, then and then cost matrix update module increases in cost matrix with maximum cost matrix
Learn study number of the word under the currently assigned scheme corresponding date of number of days, every time plus 1, until total study number of days ratio is more
Total study number of days more 1 before new.
The Solving Assignment Problem module is accomplished by Solving Assignment Problem module reception cost matrix update module and provides
Cost matrix call Hungary Algorithm using cost matrix as input, obtain: one for indicating assignment schemeThe each element that each element of dimension takes the vector sol and W of nonnegative integral value to tie up takes the vector cnt of positive integer value.Institute
It states the positive integer value in vector sol not repeat mutually, the value sol of i-th of component of vector soliIt indicates: if soliIt is not 0, then
Reciprocal theIt include serial number sol in the word list of it recommended user's studyiWord；If
soliIt is 0, then without meaning.The vector cnt indicates the study number of days of each word accumulation, that is, i-th of component of vector cnt
Numerical value indicates that user learns the value for learning number of days that the word of the serial number i in request needs.Then, Solving Assignment Problem module
Whether study number of days needed for judging the word with maximum study number of days is no more than the list that daily requirement recommends study to user
The corresponding total study number of days of word list subtractsIf be no more than, Solving Assignment Problem module will be in vector cnt
Element by descending order arrange, the subscript of preceding M element is recorded, according to record generate same day recommended user learn
Word list, return to study module；Recommend if it does, Solving Assignment Problem module request one-zero programming solves module and does
The feasibility inspection of scheme.If solution is feasible, Solving Assignment Problem module, which will receive one-zero programming and solve same day for sending of module, to be pushed away
The word list for recommending user's study, only needs this list being transmitted to study module at this time；If solution is infeasible, assignment problem
Solving module will receive from one-zero programming solution module about infeasible response is solved, and then Solving Assignment Problem module will
Information feeds back to cost matrix update module, makes corresponding update to cost matrix by cost matrix update module.
The one-zero programming solves module and is accomplished by one-zero programming solution module from total of Solving Assignment Problem module acquisition
Practise number of days and from entire learning process finish time reciprocal theSystem recommendation user between it
The word list of study converts these information to the constraint of mathematical optimization problem.Firstly, checking whether total learning time is less than
Study number of days needed for word with maximum study number of days: if so, directly report Solving Assignment Problem module solution is infeasible,
It does not continue to solve one-zero programming problem.Then, it establishes corresponding one-zero programming problem and solves.If can not find feasible solution,
The solution that Solving Assignment Problem module is found out is infeasible, will solve situation report Solving Assignment Problem module, it is enabled to notify cost square
Battle array update module updates cost matrix.If having found feasible solution, same day recommended user study is directly extracted from solution
Word list returns to Solving Assignment Problem module.
Advantage is the present invention compared with prior art:
(1) word assisted learning system of the invention can obtain in time real-time word difficulty information and use by feedback mechanism
Family learning ability information makes system at runtime can be more smart to system output progress according to global word and user's study situation
Quasi- adaptive adjustment.As described in technical solution of the invention, system collects user after the completion of the learning behavior of user
About the feedback information of learning effect, learns time consumed by each word in list and user including user and surveyed in word
Situation of answering in examination, and using all user's learning records summarize adjust output；And existing word mnemonic(al) product exists
In user's use process it is universal only after study feedback user to two tag along sorts of word Grasping level (" grasp " and
" not grasping "), and single user behavioral data acts only on single user itself.Therefore, information of the present invention is collected and feedback mechanism institute
Specifically, the actual amount of data applied to single user output is more huge, as a result, anti-in the present invention for the information of collection
Infeed mechanism is more fine, accurate, has good adaptivity.
(2) the intelligent decision module in word assistant learning system of the invention is based on quantitative analysis, provides intelligence and determines
Plan, the study provided suggest that study schedule that can be current with user accurately matches.Intelligent decision module is to something lost in the present invention
Forget theoretical application mode and be different from numerous prior arts: in conjunction with by being obtained in system feedback when present invention application Forgetting Theory
Word difficulty and user's learning ability calculate different user to various words using the forgetting curve quantification in Forgetting Theory
Grasp situation；And the prior art mostly all users learn any word when all directly using Chinese mugwort this great Forgetting Theory of guest in mention
Memory cycle out.Since the memory cycle in Chinese mugwort this great Forgetting Theory of guest is some specific according to this great memory of Chinese mugwort guest
What the experimental result of meaningless monogram proposed, thus this memory cycle to different abilities user and different difficulty
The applicability of word be unable to get guarantee.In contrast, the present invention is based on the quantification calculation methods of user and word data
It can adjust in time by feedback mechanism in decision inaccuracy, be obtained and the more matched study of user's study schedule in next day
It is recommended that.
Detailed description of the invention
Fig. 1 is the composition block diagram of present system；
Fig. 2 is the present invention for being fitted the function schematic diagram of forgetting curve (also known as " qualification curve ")；
Fig. 3 is the internal flow chart of the intelligent decision unit of present system client.
Specific embodiment
The following describes the present invention in detail with reference to the accompanying drawings and embodiments.
As shown in Figure 1.Present system is made of client and server.Client is responsible for sending user's to server
Study request, receives the operation result of study module in server, and according to this result, passes through patterned study circle
Face, auxiliary user carry out word study.Server disposition has two core cells of storage unit and intelligent decision unit, and is equipped with
Test module and study module, respond the request of user's different phase before learning.Implementation steps are as follows:
Step 1: user issues study request by client, and server receives this request, judges user information data
Whether user recent learning ability information is had in library；If user system for the first time log in or User Information Database in user
It is not updated within learning ability information one week or more, then calls test module before to test user's learning ability, go to
Step 2；If simultaneously non-first time logs in user, and user's learning ability information in user information database is updated in one day
It crosses, jumps directly to step 3；
Step 2: calling user's learning ability of test module test user before learning, utilize the group of words in word database
Volume, investigates user's word learning ability, obtains test result；Test volume is designed based on item response theory, using shellfish
This current learning ability of analysis method estimating subscriber's of leaf；After obtaining test result, test result is on the one hand fed back into client
It allows user to know, test result is on the other hand passed to storage unit, for updating User Information Database and word database；
Step 3: study module responds the study request of user, and user it is expected that the word list of study is sent as request
To intelligent decision unit；Intelligent decision unit responds this request, initializes, and reads user information from storage unit
And user it is expected the relevant information of the word in the word list of study, is used for intelligent decision；
Step 4: intelligent decision unit calls cost matrix update module, is assessed using forgetting curve and is pushed away on different opportunitys
Recommend different words to improve user's learning efficiency effect, then call Solving Assignment Problem module, using cost matrix as
Input, runs the Hungary Algorithm for solving assignment problem, calculates the inverse that user learns requested word list, between day last, system daily requirement recommends the word list of study to user for it.Later, intelligent decision list
Whether study number of days needed for word of the member first judgement with maximum study number of days is more than that daily requirement is recommended to learn to user
The corresponding total study number of days of word list subtractsIf it does, then by calculated word list and cost square
Battle array is input to one-zero programming and solves in module, and the feasibility of module check solution is solved by one-zero programming, if solution is infeasible, intelligence
Decision package calls cost matrix update module, updates cost corresponding to the word in cost matrix with maximum study number of days
Value, reruns Solving Assignment Problem module, and check again for solving result, repeatedly until the solution acquired is feasible.Then,
Intelligent decision module provides the word list that system daily requirement recommends study to user, and the same day is needed to recommend to learn to user
The word list of habit is sent to study module.
Step 5: study module receives the word list for recommending study on the same day from intelligent decision module, uses html language
Speech generates the study page comprising word and education resource, and the graphical study interface of client is back to by http agreement,
The word list of study is recommended to be transmitted to learning effect feedback module as learning records the same day simultaneously, the education resource includes
The audio of Chinese paraphrase and word pronunciation；
Step 6: study is completed, and calls learning effect feedback module, collects feedback information of the user about learning effect, and
Use these information update User Information Databases and word database.
Each module is described in detail below:
1. storage unit includes User Information Database and word database.
Storage content and meaning in User Information Database are listed below:
(1) user's unique identifying number UID: for distinguishing different user, and the filing to different user information.
(2) the learned word record sheet of user: each user has learned a word record in User Information Database
Table, be stored in word record sheet each word that user learnt for distinguishing the word unique identifying number of various words
GWID, and record the study date for the first time of each word.Each word is held in the learned word record sheet of user of single user
There is unique identifying number WID.It uses (UID, WID) sequence even, UID can be traced back in User Information Database correspond to user and learn
It practises WID and corresponds to the learning records during word.In actual deployment system, if the word record sheet of user is full, can not continue
The new word that will learn of addition user will then learn for the first time date earliest word and leave out from table, together in word record sheet
When removed users information database in the word occasionally traced back to of (UID, WID) sequence can be used.
(3) user's learning records table: each user has user's learning records table in User Information Database, uses
First pass learns length of time used in each word when learning record user's last time.For determining user, in this table
Information word identification number WID index can be used.
(4) user's test result table: each user has user's test result table in User Information Database, uses
In each word test result of the record at the end of user's last time learns.For determining user, the information in this table can
To use word identification number WID index.
(5) user's learning ability value table: this is a global positive floating type array, and for each user is respectively worth in array
Habit ability is demarcated, and customer identification number UID index can be used in the information in this table.
Storage content and meaning in word database are listed below:
(1) word unique identifying number GWID: for distinguishing different words, and the filing to various words information.
GWID and WID used in User Information Database is different, and GWID is the overall identification number in word database, and WID is single
Local identities number of the word in the learned word record sheet of user.
(2) the learning records table of word: each word has a learning records table, list item three in word database
Tuple (UID learns the used time for the first time, test result 0-1 amount), wherein UID is customer identification number, can be used for user information data
User's learning ability value is traced in library；" learning the used time for the first time " and identification number are in user's learning records table of the user of UID
The time recorded in the corresponding list item of GWID word is equivalent；" test result 0-1 amount " and identification number are the user of UID
User's test result table in the test result that is recorded of list item corresponding with GWID word be equivalent.In actual deployment system
When, if word learning records table is full, the list item for entering table earliest is removed, new list item is then added.
(3) word difficulty value table: this is a global positive floating type array, and the difficulty value for each word is respectively worth in array
It demarcates, word identification number GWID index can be used in the information in this table.
The learned word record sheet of user, user in the User Information Database and word database of storage unit test knot
Fruit table, user's learning ability value table and word learning records table when client triggers feedback operation, are passed according to from client
The packet content come is updated.
User's learning ability value in User Information Database and the word difficulty value in word database are run for the first time
It is calculated when system using following formula:
(1) word difficulty value is expressed as bw, indicate that the word difficulty value of w-th of word is bw, the value range of subscript w is
1,2 ..., W, W indicate that user learns the total words in request.It is determined using following formula:
bwSyllable number contained by letter number+0.3* contained by=0.7*
Then all word difficulties in word library are normalized:
bw=(bw-min(bi))/(max(bi)-min(bi))
In formula, max (b) indicates the difficulty in word database with the word of maximum difficulty value, and min (b) indicates single
There is the difficulty of the word of minimum difficulty value in word database.
(2) test result of the calculating of user's learning ability value θ dependent on test module before learning.Test module is defeated before learning
Result includes the word vector a of test, and the 0-1 vector scr for indicating test result out.Use item response theory
In Maximum Likelihood Estimation Method, using two-parameter logistic Item Response Pattern function:
X in formulaiIndicate that user answers questions the test question about i-th of word, P (xi=1 | θ) when indicating known θ, user answers questions
The probability of the test question of i-th of word；P(xi=0 | θ) when indicating known θ, user answers the general of the test question of wrong i-th of word
Rate.Likelihood function known to as a result:
Function I () is indicative function, takes 1 when the proposition in bracket is true, if false, taking 0；scriIndicate vector scr
I-th of component, scriValue be that 1 expression user answers questions the test question of i-th of word, answer wrong i-th of word for 0 expression user
Test question, i takes all over 1,2 ..., and A, A indicate word number contained by word vector a.Then logarithm is taken to above-mentioned likelihood function, and
Derivation, enabling derivative is 0, makes the maximum ability value θ of likelihood function using Newton-Raphson solution by iterative method.
When the learning records item number of assistant learning system reaches certain quantity (being greater than 1000), using EM algorithm,
Word difficulty is regarded as " hidden variable " in EM algorithm, user's learning ability value is " model parameter " in EM algorithm, EM algorithm fortune
Prior probability required for during calculating and conditional probability are directly estimated (occur using practical using the record in database
Frequency Estimation probability).
2. test module is used to test user's learning ability of user before learning, rolled up using the group of words in word database,
User's word learning ability is investigated, investigated as a result, the specific implementation process is as follows:
(1) a word quantity V for word test is specified by system manager.If system manager does not provide this
One quantity, then taking the default value of word quantity is V=100.
(2) User Information Database in storage unit is read, the ability value θ of active user is inquired by the UID of user.
If inquiry failure, taking θ is the median of all user's learning ability values.
(3) the empty array that a capacity is V is created, array is for storing the word that will be used for user's horizontal checkout
GWID。
(4) 4V word is randomly selected from word database, according to item response theory, uses user's learning ability value
θ and word difficulty bj, j=1,2 ..., 4V calculate word for the maximum information function I of userj(θ), calculation formula is such as
Under:
(5) the maximum information functional value of each word is arranged by descending order, first 0.6V taken out in arrangement is single
Word then rounds up if 0.6V is not integer, then places them into the empty array that the capacity created in (3) is V, then from
0.4V word is randomly selected in last 2.4V word in arrangement, if 2.4V is not integer, is rounded downwards, if 0.4V
It is not integer, is then rounded downwards, is then placed in the array created in (3) in remaining vacancy.
(6) array created in (3) is returned into client, as word test content.
3. study module is a module for communicating between server and client, it receives the study from client
Request, is then transmitted to intelligent decision module for this request, finishes to the solution of intelligent decision module, and study module, which receives, to be solved
Obtained same day recommends the word list of study, by word list word and corresponding education resource (including Chinese is dispelled misgivings
With the audio of word pronunciation) use html language generation word to learn the page, the graphical of client is back to by http agreement
Learn interface, while recommending the word list of study to be transmitted to learning effect feedback module as learning records the same day.
4. intelligent decision unit is responsible for providing the daily word sequence for recommending study for meeting the theoretical rule of forgetting curve, side
User is helped efficiently to learn word.Intelligent decision unit is asked by cost matrix update module, Solving Assignment Problem module and one-zero programming
Module composition is solved, is implemented as follows:
Cost matrix update module is responsible for calculating and updating cost matrix.Cost matrix is indicated with letter C, is a shape
For, element is the matrix of positive integer.The element representation that the i-th row jth arranges in C matrix is cij, its table
Show that the date by user's last time study word i is arranged in reciprocal the from entire learning process finish timeIt when, user oneself reaches the qualification of word i when the study of all words finishes to allow
To γcOr more, learn the smallest cumulative learning number of days, also known as cost required for word i.The above i=1,2 ..., W,When calling cost matrix update module for the first time daily, cost matrix update module is according to following
Step is realized:
(1) cost matrix update module obtains the qualification threshold value that user's expectation reaches from the study request of user
γ, user it is expected the word number M and word list to be learned that learn daily；With capital W indicate user request in
Word number in the word list of study, and use subscript 1,2 ..., index of the W as the word in word list.Then from
The difficulty b of current user capability value θ and each word are obtained in storage unitw, w=1,2 ..., W.
(2) the function prof (w, t, N) of a forgetting curve for being fitted in forgetting curve theory is specified.It can be by being
System administrator voluntarily specifies, or uses default value:
In function, w is the index number of word, and t is to be passed through using the time for starting to learn first word by starting point
Learning time (abstract is shown in the definition of learning time), N indicate until time t, user has learnt the number of word w, dw(t)
Indicate using learning time t as terminating point, with the last time learn word w at the beginning of for starting point, after study when
Between, Sw(N) be forgetting curve memory firmness parameter, Sw(N)=αNSw(0), wherein α is renewal rate, from storage unit
Obtaining minimum study times N * needed for grasping the word that difficulty is median (0.5) (if can not obtain, can use default value
4) following method of determination, is then provided:
Remember firmness initial parameter values Sw(0) it is determined by user's learning ability value and word difficulty, the determination of default
Formula are as follows:
Sw(0)=θ (1-bw)
In formula, subscript w indicates word, takes all over 1,2 ..., all values of W, and W is that the word that user learns in request is total
Number.
Fig. 2 is when selecting default function as forgetting curve function, and functional value can in user's actual use systematic procedure
A kind of situation of change that can occur.
(3) cost matrix C: the element c in cost matrix C is calculatedijCalculation formula it is as follows:
Wherein
Then, calculated cost matrix is stored and is used to store original cost matrix and current into intelligent decision unit
In the temporary storage cell of cost matrix.
Above step is the step of cost matrix update module calculates initial cost matrix when study request arrives.
Cost matrix update module is also responsible for responding the request for updating cost matrix from Solving Assignment Problem module.What is be likely to occur asks
Condition of pleading and corresponding matrix update method are as follows:
Situation 1: the solution of Solving Assignment Problem unit finishes, if the total study number of days T acquired, which is less than, has maximum study
Study number of days needed for the word of number of days, the then mode for updating cost matrix are as follows:
It is i that setting tool, which has the call number of the word of maximum study number of days,max(if multiple words all have maximum study number of days,
The word for then taking call number small), this word is in the daily word list for recommending study that Solving Assignment Problem module acquires
Positioned at DmaxIn it study list, then the corresponding element in current cost Matrix C is updated according to the following formula:
J is integer
Then total study number of days T is recalculated according to new cost matrix, if still hadOn then continuing
The increment operator of formula, until
Situation 2: not meeting situation 1, but the report of Solving Assignment Problem module, which claims one-zero programming to solve module, can not find often
The solution of repeated word is all not present in the word list of one day recommended user study.So first record current total study number of days
T0, then execute following formula description operation:
J is integer
And new total study number of days T is recalculated according to updated cost matrix.If T < T0+ 1, then continue on
The increment operator of formula, until T=T0+1。
Solving Assignment Problem module receives the cost matrix that cost matrix update module provides, using cost matrix as defeated
Enter, call Hungary Algorithm, obtain: one for indicating assignment schemeThe negated negative integer of each element of dimension
The each element of vector sol and the W dimension of value takes the vector cnt of positive integer value.Positive integer value in the vector sol does not repeat mutually,
The value sol of i-th of component of vector soliIt indicates: if soliIt is not 0, then reciprocal theIt is pushed away
It recommends in the word list of user's study comprising serial number soliWord；If soliIt is 0, then without meaning.The vector cnt table
Show the study number of days of each word accumulation, that is, the numerical value of i-th of component of vector cnt indicates that user learns the serial number i in request
Word need study number of days value.Then, the judgement of Solving Assignment Problem module has needed for the word of maximum study number of days
Study number of days whether be no more than daily requirement to user recommend study the corresponding total study number of days of word list subtractIf it does, Solving Assignment Problem module request one-zero programming solves the feasibility inspection that module does suggested design
It looks into.
One-zero programming solves module and is responsible for when Solving Assignment Problem module can not determine whether solution is feasible, and auxiliary is assigned and asked
Topic solves the feasibility of module judgement solution.One-zero programming solve module from Solving Assignment Problem module obtain total study number of days T and
For indicating reciprocal the from entire learning process finish timeSystem recommendation user learns between it
The vector sol of the word list of habit, and the vector cnt for indicating each word cumulative learning number of days.Then, one-zero programming is asked
Solution module checks whether the solution that Solving Assignment Problem module obtains is feasible in accordance with the following steps:
(1) check whether total learning time T is less than with study number of days needed for the maximum word for learning number of days, if so,
Then directly report Solving Assignment Problem module solution is infeasible, does not continue to solve one-zero programming problem.If it is not, then entering in next step.
(2) it is as follows to establish corresponding one-zero programming problem:
find xw,t, w=1,2 ..., W；T=1,2 ..., T
xw,t∈{0,1}.
In above formula, xw,tIt is 0-1 variable, xw,t=0 indicates that the word that call number is w did not recommended the word of study at the t days
In list, xw,t=1 indicates in the word list that the word that call number is w recommended study at the t days, cntwIndicate vector cnt's
W-th of component, θwIt is determined by following formula:
(3) established one-zero programming mode input is solved into integer programming solver.Integer programming solver can be with
Existing integer programming on the market is selected to solve the function intlinprog in module, such as MATLAB, due to not special
Objective function requirement, directly can set 0 for objective function using when this class function.If can not find feasible solution, appointment is reported
Problem solver module " has called one-zero programming to solve function verifying, to solve infeasible ".If having found feasible solution, appointment is reported
Problem solver module " Xie Kehang ", and the x that will be acquiredW, tIt is sent to Solving Assignment Problem module.
When Solving Assignment Problem module self judges or learns the daily recommendation found out by one-zero programming solution module judgement
User study word list be it is feasible, then the word list that same day recommended user learns is sent to study module, specifically
Realization divides following two situation:
Situation 1:At this moment Solving Assignment Problem module can be certainly
Row is judged to solve feasible.Then, Solving Assignment Problem module is arranged the element in vector cnt by descending order, by preceding M
The word index number of a element is recorded, and is generated same day recommended user using the corresponding word of these word index number and learnt
Word list, be sent to study module.
Situation 2:But one-zero programming solves module that found out can
Row solution.Solving Assignment Problem module solves the variable x that module is sent from one-zero programmingw,t, w=1,2 ..., W；T=1,
2,...,T.Then construct word index number set I=w | xw,1=1, w=1,2 ..., W }, and use the word in set I
The corresponding word of call number generates the word list of same day recommended user study, is sent to study module.
5. learning the study request that request module collects user, and the study of user request is sent to server, specifically
Realization process is as follows:
(1) study request module inquiry user needs the word list learnt and needs after study to be achieved ripe
Practice degree.
(2) after receiving response of the user about word list and desired qualification, study request module is assisted using http
The identification number of the response of user and user is packaged into study request data package by view, is transmitted to server.
6. graphical study interface is with the operation result from intelligent decision module that study module is passed back from server
User is assisted to carry out word study by patterned study interface for foundation, the specific implementation process is as follows:
(1) graphically study interface passes through what http agreement learnt from the study module of server reception same day recommended user
Word list.
(2) user starts this study, the graphical word column for learning boundary's user oriented and showing same day recommended user study
Word and its education resource in table.Education resource includes that the Chinese of word dispels misgivings and English equivalents and other helps to learn
The word learning stuff of habit.
7. learning effect feedback module receives together with graphical study interface in learning process and comes from server middle school
The corresponding of module is practised, feedback information of the user about learning effect is collected simultaneously, the feedback information being collected into is fed back into service
Storage unit in device, for updating storage User Information Database and word database in unit, specific implementation process is such as
Under:
(1) learning effect feedback module receives same day recommended user study from the study module of server by http agreement
Word sequence.
(2) shaping array of the word with this study marked as index built in learning effect feedback module.User
When learning a certain word w (w=1,2 ..., W, W are contained word numbers in study request), learning effect feedback module records the same day
User learns the time of the accumulative consumption of this word.
(3) after the study of this word, learning effect feedback module arranges word test, and word test result is remembered
Record is in 0-1 array of the word marked as index, specific implementation are as follows: arranges the word list random ordering in this study request
Column, word is then successively taken out from word list, executes operation: by equiprobability random selection " only showing Chinese paraphrase ", " only
Display word itself ", " only playing pronunciation ", after selecting, according to selected mode, word is presented to the user, and is provided two and selected
Item " understanding ", " not recognizing " open simultaneously timer, setting time 5 seconds, start countdown.If used before countdown terminates
Family has selected " to recognize ", then the corresponding position of this word in 0-1 array is set 1；If user selects before countdown terminates
" not recognizing ", or user does not make a choice yet after countdown, then by the corresponding position of this word in 0-1 array
Set 0.
(4) by user learn the same day recommend study word accumulative elapsed time and user to the test knots of these words
Fruit is packaged into data packet, is back to server, is received by the storage unit in server.
Claims (5)
1. a kind of word assistant learning system of the quantification with learning cycle characterized by comprising client and service
Device；
The client includes: study request module, graphical study interface and learning effect feedback module；Learn request module
It is responsible for sending the study request of user to server, receives the operation result of study module in server；Graphical study interface
According to the operation result from intelligent decision module that study module in server is passed back, pass through patterned study circle
Face, auxiliary user carry out word study；Learning effect feedback module receives together with graphical study interface in learning process
The response of study module in server, is collected simultaneously feedback information of the user about learning effect, and the feedback information refers to
User learns the test result carried out after each word the time it takes, and study to user's learning outcome；It will receive
The feedback information and corresponding user and word collected is bound into a data packet, feeds back to the storage unit in server, uses
In updating storage User Information Database and word database in unit；
The server disposition has test module and study module before storage unit, intelligent decision unit,；To user's not same order
The request of section responds；
The storage unit, it is responsible to receive to learn by oneself the feedback letter of the learning effect feedback module in preceding test module and client
It ceases, the User Information Database and word database inside updating unit；User Information Database is responsible for recording the study of user
History, it is described study history, that is, user learned word, learn each word when the time it takes and user word test in
Test result；Word database is responsible for recording the case where each word is learnt, the aptitude tests knot of the user including learning word
Fruit, each user word in study consumed by the time summarize and to the inferred results of word difficulty；
The intelligent decision unit receives the study request comprising word list to be learned for carrying out self-learning module, single from storage
Member obtains user's learning ability, word difficulty and the user's learning records that user reflects in learning process, and is based on these
Data provide the word list of same day recommendation study for user；The intelligent decision unit include: cost matrix update module,
Solving Assignment Problem module, one-zero programming solve module；The cost matrix update module is used for the calculating of initial cost matrix,
And cost matrix is modified during solving the daily word list for recommending study；Solving Assignment Problem module will generation
Valence matrix runs the Hungary Algorithm for solving assignment problem as input, calculates and learns requested word column in user
The inverse of table, between day last, system daily requirement recommends the word list of study to user, and is falling for it
NumberIt is recommended to the daily requirement provided between day last to user under the word list of study, each word institute
The study number of days needed, wherein W indicates that user learns the total words in request, and it is every that M indicates that user learns to specify in request
The word number that day can learn；One-zero programming solves module dedicated for solving one-zero programming problem, when with maximum study number of days
Word needed for study number of days be greater than daily requirement to user recommend study the corresponding total study number of days of word list subtractWhen, the daily requirement that Solving Assignment Problem module is obtained word list recommended to the user is adjusted as input
With one-zero programming problem solver module, to verify the feasibility for the word list that Solving Assignment Problem module obtains；
Test module before is rolled up for testing user's learning ability of user using the group of words in word database, right
User's word learning ability is tested, and test result is obtained；On the one hand test result is fed back to client allows user to know,
On the other hand test result is passed to storage unit, for updating User Information Database and word database；
The study module is the module that server is used to communicate with client, it is not when user information needs to update
Receive the study request from client, this request is then transmitted to intelligent decision module, is solved to intelligent decision module
It finishes, study module receives the word list for recommending study on the same day for solving and obtaining, by this word and corresponding html language
Speech generates word and learns the page, the graphical study interface of client is back to by http agreement, while will recommend on the same day to learn
The word list of habit is transmitted to learning effect feedback module as learning records；The education resource includes that Chinese is dispelled misgivings and word reading
The audio of sound.
2. a kind of word assistant learning system of quantification with learning cycle according to claim 1, feature exist
In: the cost matrix update module that is accomplished by of the cost matrix update module is responsible for calculating cost matrix, and cost matrix is used
Letter C indicates, is that a shape is, element is the matrix of positive integer, the i-th row column in C matrix
The element representation of j is cij, it indicates that the date by user's last time study word i is arranged at the end of the entire learning process
Reciprocal the carvedIt when, user is in order to allow oneself to the qualification of word i in all words
Study reaches γ when finishingcOr more, learn the smallest cumulative learning number of days, also known as cost required for word i, the above pass
It in the narration for the element that the i-th row jth arranges in C matrix, takes all over 1 to all integers between W, including 1 and W, j take and arrive all over 1Between all integers, including 1 He
The qualification in forgetting curve theory for being fitted the function of forgetting curve by being calculated, the choosing of forgetting curve function
With negative exponent function or models of negative index functions；Learn run cost matrix update module for the first time after request arrives in user,
Cost matrix update module will calculate cost matrix according to the function for being used to be fitted forgetting curve in theory completely, and will calculate
Cost matrix separately backed up as initial cost matrix, if Solving Assignment Problem module is due to can not judge whether solution feasible
Solution is sent to one-zero programming and solves module, and one-zero programming infeasible, the cost matrix update module at this time that solves module discovery solution
It is responsible for updating cost matrix: if the total study number of days acquired is less than study day needed for the word with maximum study number of days
Number, then cost matrix update module, which increases, has the word of maximum study number of days corresponding in currently assigned scheme in cost matrix
Study number under date, every time plus 1, until total study number of days can be not less than maximum study number of days；If the total study acquired
Study number of days needed for number of days is not less than the word with maximum study number of days, but solution is still infeasible, then cost matrix then cost
Matrix update module, which increases, has the word of maximum study number of days under the currently assigned scheme corresponding date in cost matrix
Learn number, every time plus 1, until total study number of days is 1 more than total study number of days before updating.
3. a kind of word assistant learning system of quantification with learning cycle according to claim 1, feature exist
In: the Solving Assignment Problem module is accomplished by Solving Assignment Problem module and receives the generation that cost matrix update module provides
Valence matrix calls Hungary Algorithm, obtain using cost matrix as input: one for indicating assignment schemeThe each element that each element of dimension takes the vector sol and W of nonnegative integral value to tie up takes the vector cnt of positive integer value；Institute
It states the positive integer value in vector sol not repeat mutually, the value sol of i-th of component of vector soliIt indicates: if soliIt is not 0, then
Reciprocal theIt include serial number sol in the word list of it recommended user's studyiWord；If
soliIt is 0, then without meaning；The vector cnt indicates the study number of days of each word accumulation, that is, i-th of component of vector cnt
Numerical value indicates that user learns the value for learning number of days that the word of the serial number i in request needs；Then, Solving Assignment Problem module
Whether study number of days needed for judging the word with maximum study number of days is no more than the list that daily requirement recommends study to user
The corresponding total study number of days of word list subtractsIf be no more than, Solving Assignment Problem module will be in vector cnt
Element by descending order arrange, the subscript of preceding M element is recorded, according to record generate same day recommended user learn
Word list, return to study module；Recommend if it does, Solving Assignment Problem module request one-zero programming solves module and does
The feasibility inspection of scheme；If solution is feasible, Solving Assignment Problem module, which will receive one-zero programming and solve same day for sending of module, to be pushed away
The word list for recommending user's study, only needs this list being transmitted to study module at this time；If solution is infeasible, assignment problem
Solving module will receive from one-zero programming solution module about infeasible response is solved, and then Solving Assignment Problem module will
Information feeds back to cost matrix update module, makes corresponding update to cost matrix by cost matrix update module.
4. a kind of word assistant learning system of quantification with learning cycle according to claim 1, feature exist
In: the one-zero programming, which solves module and is accomplished by one-zero programming and solves module and obtain from Solving Assignment Problem module, always learns day
Number and from entire learning process finish time reciprocal theSystem recommendation user learns between it
Word list, these information are converted to the constraint of mathematical optimization problem, firstly, checking whether total learning time is less than and has
Study number of days needed for the word of maximum study number of days: if so, directly report Solving Assignment Problem module solution is infeasible, no longer
Continue to solve one-zero programming problem；Then it establishes corresponding one-zero programming problem and solves, if can not find feasible solution, appointment is asked
The solution that topic solution module is found out is infeasible, will solve situation report Solving Assignment Problem module, and enable its that cost matrix is notified to update
Module updates cost matrix；If having found feasible solution, the word column of same day recommended user study are directly extracted from solution
Table returns to Solving Assignment Problem module.
5. a kind of word assisted learning method of the quantification with learning cycle, which comprises the following steps:
Step 1: user issues study request by client, and server receives this request, judges in User Information Database
Whether user recent learning ability information is had；If user system for the first time log in or User Information Database in user study
It is not updated within ability information one week or more, then calls test module before to test user's learning ability, go to step
2；If simultaneously non-first time logs in user, and user's learning ability information in user information database is updated in one day, directly
It connects and jumps to step 3；
Step 2: user's learning ability of test module test user before learning is called, is rolled up using the group of words in word database,
User's word learning ability is investigated, test result is obtained；Test volume is designed based on item response theory, using Bayes
The current learning ability of analysis method estimating subscriber's；After obtaining test result, test result is on the one hand fed back into client and allows use
Family is known, test result is on the other hand passed to storage unit, for updating User Information Database and word database；
Step 3: study module responds the study request of user, and user it is expected that the word list of study is sent to intelligence as request
It can decision package；Intelligent decision unit responds this request, initializes, from storage unit read user information and
User it is expected the relevant information of the word in the word list of study, is used for intelligent decision；
Step 4: intelligent decision unit calls cost matrix update module, is recommended not using forgetting curve assessment on different opportunitys
With word to improve user's learning efficiency effect, then call Solving Assignment Problem module, using cost matrix as input,
The Hungary Algorithm for solving assignment problem is run, the inverse that user learns requested word list is calculated
, between day last, system daily requirement recommends the word list of study to user for it；Later, intelligent decision unit first judges
Whether study number of days needed for the word with maximum study number of days is more than that daily requirement recommends the word list learnt to user
Corresponding total study number of days subtractsIf it does, then calculated word list and cost matrix are input to
One-zero programming solves in module, and the feasibility of module check solution, if solution is infeasible, intelligent decision unit are solved by one-zero programming
Cost matrix update module is called, updates cost value corresponding to the word in cost matrix with maximum study number of days, again
Solving Assignment Problem module is run, and checks again for solving result, repeatedly until the solution acquired is feasible.Then, it intelligently determines
Plan module provides the word list that system daily requirement recommends study to user, and is needed to recommend to user the list of study the same day
Word list is sent to study module；
Step 5: study module receives the word list for recommending study on the same day from intelligent decision module, raw using html language
At the study page comprising word and education resource, the graphical study interface of client is back to by http agreement, simultaneously
The word list of study is recommended to be transmitted to learning effect feedback module as learning records the same day, the education resource includes Chinese
The audio of paraphrase and word pronunciation；
Step 6: study is completed, and calls learning effect feedback module, collects feedback information of the user about learning effect, and use
These information update User Information Databases and word database.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910693170.5A CN110473435B (en) | 2019-07-30 | 2019-07-30 | Word auxiliary learning system and method with quantification of learning period |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910693170.5A CN110473435B (en) | 2019-07-30 | 2019-07-30 | Word auxiliary learning system and method with quantification of learning period |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110473435A true CN110473435A (en) | 2019-11-19 |
| CN110473435B CN110473435B (en) | 2021-07-20 |
Family
ID=68509892
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910693170.5A Active CN110473435B (en) | 2019-07-30 | 2019-07-30 | Word auxiliary learning system and method with quantification of learning period |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110473435B (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111260965A (en) * | 2020-01-17 | 2020-06-09 | 宇龙计算机通信科技(深圳)有限公司 | Word stock generation method and related device |
| CN111752756A (en) * | 2020-06-24 | 2020-10-09 | 厦门靠谱云股份有限公司 | Method for setting database backup strategy through autonomous learning |
| CN111861372A (en) * | 2020-06-19 | 2020-10-30 | 北京国音红杉树教育科技有限公司 | Method and system for testing word mastering degree |
| CN111861816A (en) * | 2020-06-19 | 2020-10-30 | 北京国音红杉树教育科技有限公司 | Method and equipment for calculating word memory strength in language translation learning |
| CN112364152A (en) * | 2020-11-09 | 2021-02-12 | 上海束水智能科技有限公司 | Response type learning assistance method, system and equipment |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20050008271A (en) * | 2003-07-15 | 2005-01-21 | 박진우 | E-learning System Using Fogetting Curve |
| CN101201812A (en) * | 2006-12-14 | 2008-06-18 | 英业达股份有限公司 | System and method for executive auxiliary learning of language word by computer |
| CN103413478A (en) * | 2013-07-09 | 2013-11-27 | 复旦大学 | Word memory intelligent learning method and system thereof |
| CN104077930A (en) * | 2014-05-13 | 2014-10-01 | 李国胜 | Powerful memorizing and learning method based on mobile terminal and mobile terminal |
| CN104134374A (en) * | 2014-05-06 | 2014-11-05 | 天津工业大学 | Electronic dictionary method of dynamically evaluating master degree based on scheduling of words and phrases |
| JP2015206835A (en) * | 2014-04-17 | 2015-11-19 | 株式会社エレナ | learning system |
-
2019
- 2019-07-30 CN CN201910693170.5A patent/CN110473435B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20050008271A (en) * | 2003-07-15 | 2005-01-21 | 박진우 | E-learning System Using Fogetting Curve |
| CN101201812A (en) * | 2006-12-14 | 2008-06-18 | 英业达股份有限公司 | System and method for executive auxiliary learning of language word by computer |
| CN103413478A (en) * | 2013-07-09 | 2013-11-27 | 复旦大学 | Word memory intelligent learning method and system thereof |
| JP2015206835A (en) * | 2014-04-17 | 2015-11-19 | 株式会社エレナ | learning system |
| CN104134374A (en) * | 2014-05-06 | 2014-11-05 | 天津工业大学 | Electronic dictionary method of dynamically evaluating master degree based on scheduling of words and phrases |
| CN104077930A (en) * | 2014-05-13 | 2014-10-01 | 李国胜 | Powerful memorizing and learning method based on mobile terminal and mobile terminal |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111260965A (en) * | 2020-01-17 | 2020-06-09 | 宇龙计算机通信科技(深圳)有限公司 | Word stock generation method and related device |
| CN111260965B (en) * | 2020-01-17 | 2021-11-16 | 宇龙计算机通信科技(深圳)有限公司 | Word stock generation method and related device |
| CN111861372A (en) * | 2020-06-19 | 2020-10-30 | 北京国音红杉树教育科技有限公司 | Method and system for testing word mastering degree |
| CN111861816A (en) * | 2020-06-19 | 2020-10-30 | 北京国音红杉树教育科技有限公司 | Method and equipment for calculating word memory strength in language translation learning |
| CN111861372B (en) * | 2020-06-19 | 2023-12-26 | 北京国音红杉树教育科技有限公司 | Method and system for testing word mastering degree |
| CN111861816B (en) * | 2020-06-19 | 2024-01-16 | 北京国音红杉树教育科技有限公司 | Method and equipment for calculating word memory strength in language inter-translation learning |
| CN111752756A (en) * | 2020-06-24 | 2020-10-09 | 厦门靠谱云股份有限公司 | Method for setting database backup strategy through autonomous learning |
| CN112364152A (en) * | 2020-11-09 | 2021-02-12 | 上海束水智能科技有限公司 | Response type learning assistance method, system and equipment |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110473435B (en) | 2021-07-20 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110473435A (en) | A kind of the word assistant learning system and method for the quantification with learning cycle | |
| US11379489B2 (en) | Digital assistant extension automatic ranking and selection | |
| CN110473438A (en) | A kind of word assistant learning system and method based on quantitative analysis | |
| US20190354887A1 (en) | Knowledge graph based learning content generation | |
| CN109360457A (en) | A kind of topic method for pushing, storage medium and application system | |
| CN111651676B (en) | Method, device, equipment and medium for performing occupation recommendation based on capability model | |
| Wong | Sequence based course recommender for personalized curriculum planning | |
| CN109472305A (en) | Answer quality determines model training method, answer quality determination method and device | |
| US10929781B1 (en) | Systems and methods for determining training parameters for dialog generation | |
| CN111126552A (en) | Intelligent learning content pushing method and system | |
| CN111460101A (en) | Knowledge point type identification method and device and processor | |
| CN110866209A (en) | Online education data pushing method and system and computer equipment | |
| WO2023045193A1 (en) | Self-adaptive testing-based user capability grading method and apparatus, device, and medium | |
| CN113705792B (en) | Personalized recommendation method, device, equipment and medium based on deep learning model | |
| CN111405054A (en) | Intelligent teaching assistant system and method | |
| CN112015992A (en) | Intelligent word recitation plan generation method | |
| CN109800880B (en) | Self-adaptive learning feature extraction system based on dynamic learning style information and application | |
| EL MEZOUARY et al. | An evaluation of learner clustering based on learning styles in MOOC course | |
| CN108875027A (en) | Learning functionality recommended method, device, private tutor's machine and the storage medium of private tutor's machine | |
| CN113535911B (en) | Reward model processing method, electronic device, medium and computer program product | |
| KR102329611B1 (en) | Pre-training modeling system and method for predicting educational factors | |
| JP2023098155A (en) | Computer program, information processing device, and information processing method | |
| CN113094404A (en) | Big data acquisition multi-core parameter self-adaptive time-sharing memory driving method and system | |
| JP2017207691A (en) | Correct answer ratio prediction method of multiple-choice question | |
| CN112365302A (en) | Product recommendation network training method, device, equipment and medium |
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 |