CN106504105A - A kind of user's virtual community construction device and method based on the degree of belief factor - Google Patents
A kind of user's virtual community construction device and method based on the degree of belief factor Download PDFInfo
- Publication number
- CN106504105A CN106504105A CN201710004815.0A CN201710004815A CN106504105A CN 106504105 A CN106504105 A CN 106504105A CN 201710004815 A CN201710004815 A CN 201710004815A CN 106504105 A CN106504105 A CN 106504105A
- Authority
- CN
- China
- Prior art keywords
- data
- user
- degree
- belief
- module
- 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.)
- Pending
Links
- 238000010276 construction Methods 0.000 title claims abstract description 23
- 238000000034 method Methods 0.000 title claims description 34
- 238000004458 analytical method Methods 0.000 claims abstract description 51
- 238000012545 processing Methods 0.000 claims abstract description 36
- 230000003993 interaction Effects 0.000 claims description 29
- 238000000605 extraction Methods 0.000 claims description 26
- 230000008569 process Effects 0.000 claims description 26
- 230000008447 perception Effects 0.000 claims description 22
- 230000006854 communication Effects 0.000 claims description 21
- 238000004891 communication Methods 0.000 claims description 20
- 230000006399 behavior Effects 0.000 claims description 19
- 238000007405 data analysis Methods 0.000 claims description 18
- 238000004140 cleaning Methods 0.000 claims description 11
- 239000000284 extract Substances 0.000 claims description 10
- 238000007726 management method Methods 0.000 claims description 10
- 238000011002 quantification Methods 0.000 claims description 8
- 239000000463 material Substances 0.000 claims description 7
- 238000013139 quantization Methods 0.000 claims description 6
- 230000008878 coupling Effects 0.000 claims description 4
- 238000010168 coupling process Methods 0.000 claims description 4
- 238000005859 coupling reaction Methods 0.000 claims description 4
- 238000001914 filtration Methods 0.000 claims description 4
- 230000002452 interceptive effect Effects 0.000 claims description 3
- 238000004445 quantitative analysis Methods 0.000 claims description 3
- 238000010223 real-time analysis Methods 0.000 claims 1
- 230000006872 improvement Effects 0.000 description 8
- 230000000694 effects Effects 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 3
- 238000004364 calculation method Methods 0.000 description 2
- 230000008859 change Effects 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000001228 spectrum Methods 0.000 description 2
- 238000013459 approach Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000007423 decrease Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000000556 factor analysis Methods 0.000 description 1
- 238000013467 fragmentation Methods 0.000 description 1
- 238000006062 fragmentation reaction Methods 0.000 description 1
- 230000005055 memory storage Effects 0.000 description 1
- 238000002360 preparation method Methods 0.000 description 1
- 238000012546 transfer Methods 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—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/01—Social networking
Abstract
The invention discloses a kind of user's virtual community construction device based on the degree of belief factor, including：Data acquisition module；Data processing module；Degree of belief analysis module；User's Virtual Community Management module.User's virtual community construction device based on the degree of belief factor of the present invention, user data just can effectively be gathered by the setting of data acquisition module, by the setting of data processing module, just Treatment Analysis can be carried out to the data for collecting effectively, by the setting of degree of belief analysis module, the degree of belief factor just effectively can be extracted, build trust model, by user's Virtual Community Management module, user's virtual community can just be built, and virtual community is safeguarded, so can just strengthen the mutual exchange between student and learn from each other, collaborative study is effectively achieved.
Description
Technical field
The present invention relates to the ubiquitous learning system application of movement, specially a kind of user's virtuality based on the degree of belief factor
Community's construction device and method.
Background technology
With the continuous development of information technology, the extensive application of 4G network communication skills, human society is from the interconnection of computer
Net period has striden into the epoch that movement is mutually netted, and intelligent mobile terminal not only provides the facility of online for people, is also long-range height
Development Deng education provides more easily approach, and more people can be carried out anywhere or anytime using the time of fragmentation
Open ubiquitous study.However, the ubiquitous learning system of movement is present, user's feeling of lonely is strong, and between user, shortage is exchanged；Between user
Degree of belief is not high, lacks reliable communication channelss；In system, curriculum information overload, student's study are got lost, and lack effectively guiding etc.
Problem, and then cause the decline of student learning interest, learning quality and the learning efficiency that a large amount of levels differ, how to student
Set up unobstructed, the reliable channel of communication and guide efficient mutual assistance urgently to be resolved hurrily in having learnt into the ubiquitous learning system of movement
Problem.
Content of the invention
In view of the shortcomings of the prior art, it is an object of the invention to provide a kind of user based on the degree of belief factor is empty
Intend community's construction device and method, strengthen mutually exchange, mutual assistance study by building reliable user's virtual community, in order to solve
The problem proposed in above-mentioned background technology.
For achieving the above object, the invention provides following technical scheme：A kind of user based on the degree of belief factor is virtual
Community's construction device, including：
Data acquisition module, for gathered data, which is coupled with outside mobile terminal and is communicated, the outside mobile terminal of collection
User basic information, course essential information, user mutual behavior information and mobile awareness data, collection will be above-mentioned after completing
Information is compiled into user data package signal output；
Data processing module, for processing to data, which is coupled with data acquisition module, to receive and parse through user
Data packet signal, obtains user basic information, course essential information, user mutual behavior information and mobile awareness data, and right
Above- mentioned information carries out quantization storage after being processed, the data after being processed；
Degree of belief analysis module, for calculating the degree of belief factor and building trust metric model, which is coupled to data processing mould
Block, to be communicated with data processing module, is called the data after processing, and calculates the degree of belief factor according to data, according to degree of belief
The factor builds trust metric model, and the degree of belief analysis module is further coupled to data acquisition module and is sent with receiving data acquisition module
User data package；
User's Virtual Community Management module, for building and managing virtual community, is coupled to degree of belief analysis module, with
Degree of belief analysis module communicates, and calls degree of belief factor data and reaLtime user data bag, according to degree of belief factor data and reality
When user data package build communities of users.
As a further improvement on the present invention, the data processing module includes：
Data cleansing part, is coupled to data acquisition module, the user data package letter exported with receiving data acquisition module
Number, by data packet signal of the user data package signal after interference signal filtering after output cleaning；
Characteristic extraction part, is coupled to data cleansing part, with the data that receiving data is cleaned after the cleaning of part output
Bag signal, carries out frequency range selection to the data packet signal, chooses the signal of the frequency range and exports extraction packet；
Characteristic quantification part, coupling and characteristic extraction part, to receive the extraction packet of characteristic extraction part output, and
To extracting packet quantitative analysiss, discrete data point is obtained, for the degree of belief analysis module analytical calculation degree of belief factor.
As a further improvement on the present invention, the data cleansing part and characteristic extraction part are wave filter, described
Characteristic quantification part is band filter.
As a further improvement on the present invention, the degree of belief analysis module includes perception data analysis module, interaction number
Module and trust model creation module, the perception data analysis module, interaction data are built according to analysis module, the degree of belief factor
Analysis module, the degree of belief factor build module and trust model creation module with data processing module and data acquisition module coupling
Connect, in order to the data after the real time data and process of receiving data processing module respectively and data acquisition module output, and pass through
Perception data analysis module carries out perception analysis to the data after real time data and process, obtains perception data, by interaction number
Analysis is interacted to the data after real time data and process according to analysis module, interaction data is obtained, by degree of belief factor structure
Modeling block to process after data be analyzed calculatings, the acquisition degree of belief factor, by trust model creation module by degree of belief
The factor is combined with the data after real time data and process, obtains trust model.
As a further improvement on the present invention, user's Virtual Community Management module includes：
Communities of users builds module, is coupled to degree of belief analysis module, calls the trust model in degree of belief analysis module,
Initial trust degree between user is calculated according to trust model, according to the degree of belief between user by multiple customer mobile terminals
Connection communication, constitutes communities of users；
Community's interaction module, is arranged in communities of users, connects with each member communication in the mobile terminal of communities of users
Connect, in order to provide the information interaction between the member of communities of users；
Mutual-aid community study module, with community's interaction module couples, is stored with learning materials, in order to community
Interaction module conveys learning materials；
Community's dynamic adjusting module, is coupled to degree of belief analysis module, calls the trust model in degree of belief analysis module,
Real-time degree of belief between user is calculated according to trust model, and number of members in communities of users is adjusted according to real-time degree of belief
Amount.
As a further improvement on the present invention, the customer mobile terminal is basic for be stored with user basic information, course
The mobile phone of information, user mutual behavior information and mobile awareness data.
Another aspect of the present invention provides a kind of user's virtual community construction method based on the degree of belief factor, including as follows
Step：
Step one, using the particular attribute of mobile terminal device, gathers source of new data, and new data source includes that user is basic
Information, course essential information, user mutual behavior information and mobile awareness data, data acquisition；
Step 2, carries out cleaning, screens and feature extraction to the Various types of data collected in step one, finally quantified
Storage, completes data processing；
Step 3, to the perception data in the data after step 2 process, the analysis of interbehavior dataware, extracts degree of belief
The factor, and corresponding trust metric model is built according to the degree of belief factor, complete trust metric model structure；
Step 4, in conjunction with the degree of belief factor is obtained in step 3, is used using the interactive information between user, resource and is commented
Valence mumber evidence, the live establishment user's virtual community of dynamic study, complete user's virtual community and build；
Step 5, according to the further community's behavior in real time of user, enters Mobile state adjustment, builds more to the member in community
Stable Learning Community, completes the dynamic adjustment of virtual community, and wherein step 5 constantly circulates adjustment.Structure as the present invention
The extraction step for extracting the degree of belief factor in further improvements in methods, step 3 (203) is as follows：
A, Internet is arranged to input layer (301), e-learning layer (302) and output layer (303), in setting network
Two users are respectively user i and user j, using input layer (301) extract positional distance between user i and user j (i,
J), user's interval degree (i, j) between user i and user j is extracted, the communication frequency (i, j) between user i and user j is extracted；
B, by the positional distance (i, j) for extracting, user's interval degree (i, j) and the communication frequency (i, j) are input to network science
Practise in layer (302), by the study and computing of e-learning layer (302), calculate the degree of belief factor.
Beneficial effects of the present invention, by the setting of data acquisition module, it is possible to effectively logical with customer mobile terminal
Letter, calls out user basic information, course essential information, user mutual behavior information and the movement of customer mobile terminal memory storage
Perception data, so just can effectively complete acquiring for data, afterwards by the setting of data processing module, it is possible to right
The data for collecting effectively are processed, and carry out quantization storage, call for other modules, then pass through after process is completed
The setting of degree of belief analysis module, it is possible to the data for effectively calling the process for quantifying to have stored to complete, completes according to process
Data calculate the degree of belief factor, trust metric model is effectively built according to the degree of belief factor afterwards, then empty by user
Intend community management module, the initial trust degree for each user being calculated using trust metric model builds communities of users, continues afterwards
The real-time degree of belief that each user is calculated using trust metric model, user's Virtual Community Management module can just pass through user's
Degree of belief is effectively have adjusted to the community member inside communities of users in real time, so just can effectively by mobile terminal
Learner effectively couple together, it is to avoid the low problem of the general study of movement is present in prior art the learning efficiency.
Description of the drawings
Fig. 1 is the module frame chart of the user's virtual community construction device based on the degree of belief factor of the present invention；
Fig. 2 is the flow chart of the user's virtual community construction method based on the degree of belief factor of the present invention；
Fig. 3 is the block diagram that the degree of belief factor is calculated in Fig. 2.
Specific embodiment
The present invention is described in further detail below in conjunction with the embodiment given by accompanying drawing.
Referring to figs. 1 to shown in 3, a kind of user's virtual community construction device based on the degree of belief factor of the present embodiment is wrapped
Include：
Data acquisition module 101, for gathered data, which is coupled with outside mobile terminal and is communicated, and collection is outside mobile
The user basic information 1011 of terminal, course essential information 1012, user mutual behavior information 1013 and mobile awareness data, adopt
Above- mentioned information is compiled into user data package signal output after completing by collection；
Data processing module 102, for processing to data, which is coupled with data acquisition module 101, to receive and solve
Analysis user data package signal, obtains user basic information 1011, course essential information 1012,1013 and of user mutual behavior information
Mobile awareness data, and quantization storage, the data after being processed after processing, are carried out to above- mentioned information；
Degree of belief analysis module 103, for calculating the degree of belief factor and building trust metric model, which is coupled to data processing
Module 102, to be communicated with data processing module 102, is called the data after processing, and calculates the degree of belief factor, root according to data
Trust metric model is built according to the degree of belief factor, the degree of belief analysis module 103 is further coupled to data acquisition module 101 to receive number
The user data package sent according to acquisition module；
User's Virtual Community Management module 104, for building and managing virtual community, is coupled to degree of belief analysis module
103, to communicate with degree of belief analysis module 103, degree of belief factor data and user data package is called, according to degree of belief factor number
According to building with user data package and adjustment communities of users, during community is built, first by data acquisition module 101 with
Mobile terminal is communicated, user basic information 1011, course essential information 1012 in collection mobile terminal, user mutual row
For information 1013 and mobile awareness data, the wherein data acquisition module 101 of the present embodiment is mobile terminal server, Ran Houtong
Cross 102 pairs of data for collecting of data processing module to process, the quantization stored after being processed after process is completed
Data, are analyzed calculating by degree of belief analysis module 103 afterwards to quantized data, obtain the degree of belief factor, build and trust
Degree model, afterwards by the setting of user's Virtual Community Management module 104 using the degree of belief between trust metric model calculating user,
User's virtual community is constructed according to the degree of belief between user, then proceedes to calculate the degree of belief between user, according to degree of belief
Member inside value adjustment communities of users, constantly optimizes communities of users, increases the learning interest of user, reduce the study of user
Feeling of lonely, the long-distance user community construction device of the present embodiment is by expanding data acquisition channel, expansion data acquisition range, number
According to analysis, extract the degree of belief factor, build trust metric model, scattered student is clustered, the lonely of user is released
Sense, while the user with same characteristic features is focused on together, carries out mutually exchange and common study.Finally, by data point
Analysis, data digging method, are protected in the data base during the Various types of data of curriculum implement example is sent to data acquisition module 101
Deposit, as the foundation of later stage community's dynamic adjustment, so avoid the problems that the general study of movement in prior art is present.
Used as a kind of improved specific embodiment, the data processing module 102 includes：
Data cleansing part 1021, is coupled to data acquisition module 101, with the use that receiving data acquisition module 101 is exported
User data bag signal, by data packet signal of the user data package signal after interference signal filtering after output cleaning；
Characteristic extraction part 1022, is coupled to data cleansing part 1021, cleans the output of part 1021 with receiving data
Data packet signal after cleaning, carries out frequency range selection to the data packet signal, chooses the signal of the frequency range and exports extraction data
Bag；
Characteristic quantification part 1023, coupling and characteristic extraction part 1022, to receive the output of characteristic extraction part 1022
Packet is extracted, and to extracting packet quantitative analysiss, obtains discrete data point, for 103 analytical calculation of degree of belief analysis module
The degree of belief factor, during electronic data transfer, often encloses interference signal, thus passes through data cleansing portion on signal
Divide 1021 setting just effectively can clean data, remove the interference signal of signal, pass through feature extraction unit afterwards
Points 1022 just can effectively from the effective information of substantial amounts of extracting data, and then characteristic quantification part 1023 will extract
Effectively information is quantified, and is stored after quantifying to complete so that information preferably can be called calculating,
Thus by the setting of data cleansing part 1021, characteristic extraction part 1022 and characteristic quantification part 1023, it is possible to effectively
Complete paired data process.
Used as a kind of improved specific embodiment, the data cleansing part 1021 and characteristic extraction part 1022 are
Wave filter, the characteristic quantification part 1022 are band filter, and data cleansing and feature extraction are that data signal is carried out
The process for filtering, thus the effect that just effectively can complete in the present embodiment to filter data signal using wave filter
Really, it is achieved that the effect to the cleaning of data, extraction and quantization, the process of so effective complete paired data.
Used as a kind of improved specific embodiment, the degree of belief analysis module 103 includes perception data analysis module
1031st, interaction data analysis module 1032, the degree of belief factor build module 1033 and trust model creation module 1034, the sense
Primary data analysis module 1031, interaction data analysis module 1032, the degree of belief factor are built module 1033 and are created with trust model
Module 1034 is coupled with data processing module 102 and data acquisition module 101, in order to receiving data processing module 102 respectively
Data after the real time data exported with data acquisition module 101 and process, and pass through 1031 pairs of realities of perception data analysis module
When data and the data after processing carry out perception analysis, obtain perception data, by interaction data analysis module 1032 pairs in real time
Data after data and process interact analysis, obtain interaction data, build 1033 pairs of process of module by the degree of belief factor
Data afterwards are analyzed calculating, obtain the degree of belief factor, by trust model creation module 1034 by the degree of belief factor and reality
When data and process after data combine, obtain trust model, degree of belief analysis module 103 work during, perceive number
Process will be analyzed to the data message that handles well according to analysis module, obtained perception data, learnt the study at ordinary times of user
During mobile awareness behavior, the interbehavior information of user is analyzed using interaction data analysis module 1032, is obtained
Know the usual interbehavior of user, and then be inferred to the usual preference of user, module is built by the degree of belief factor then
1033, according to usual interbehavior and the mobile awareness behavior of user, calculate the degree of belief factor, pass through trust model afterwards
Creation module 1034 just can effectively be created that trust model according to the degree of belief factor, so just can realize user's virtuality society
Area's management module 104 calculates the effect of the degree of belief between each user using trust model, and the structure for communities of users is provided
Basis is built, perception data analysis module 1031 wherein in the present embodiment is frequency spectrum perception device, perceives customer mobile terminal
Frequency spectrum change process, interaction data analysis module 1032 be communication processor, the degree of belief factor build module 1033 and trust
Model creation module is and adopts computer.
Used as a kind of improved specific embodiment, user's Virtual Community Management module 104 includes：
Communities of users builds module 1041, is coupled to degree of belief analysis module 103, calls in degree of belief analysis module 103
Trust model, the initial trust degree between user is calculated according to trust model, will be multiple according to the degree of belief between user
Customer mobile terminal connection communication, constitutes communities of users；
Community's interaction module 1042, is arranged in communities of users, logical with each member in the mobile terminal of communities of users
Letter connection, in order to provide the information interaction between the member of communities of users；
Mutual-aid community study module 1043, is coupled with community's interaction module 1042, is stored with learning materials, is used
To convey learning materials to community's interaction module 1042；
Community's dynamic adjusting module 1044, is coupled to degree of belief analysis module 103, calls in degree of belief analysis module 103
Trust model, the real-time degree of belief between user is calculated according to trust model, and user society is adjusted according to real-time degree of belief
Number of members in area, when communities of users is built, communities of users builds module 1041 and is similar to perception behavior, interbehavior
Similar user is divided, and then calculates the initial trust degree between user further according to trust model, by initial trust degree
It is attached in user profile, then above-mentioned user is coupled according to classification, the structure of communities of users is so just completed, is being coupled
During be the communication for realizing between each user by community's interaction module 1042, while utilizing mutual-aid community
Practise module 1043 and learning materials provided to community's interaction module 1042, be to provide to support in user learning communication process,
Constantly users to trust degree is recalculated finally by community's dynamic adjusting module 1044, filter the not high use of degree of belief
Family, it is ensured that in the academic environment of communities of users, wherein the present embodiment, communities of users build module 1041 and adopt server reality
Existing, community's interaction module 1042 adopts communication module, mutual-aid community study module 1043 to adopt memorizer, community's dynamic to adjust
Mould preparation block 1044 is integrated into communities of users and builds in 1041 server of module.
As a kind of improved specific embodiment, the customer mobile terminal is the user basic information 1011 that is stored with,
The mobile phone of course essential information 1012, user mutual behavior information 1013 and mobile awareness data, mobile phone are that current people use
Most mobile devices, thus with here can be effectively to collect the learning data of user, and need not be again
One mobile terminal of design is issued to user, reduces the cost of device.
Present invention also offers another kind of embodiment, a kind of user's virtual community construction method based on the degree of belief factor,
Comprise the steps：
Step one 201, using the particular attribute of mobile terminal device, gathers source of new data, and new data source includes user
Essential information 1011, course essential information 1012, user mutual behavior information 1013 and mobile awareness data, complete data and adopt
Collection；
Step 2 202, is carried out cleaning, is screened and feature extraction to the Various types of data collected in step one 201, most laggard
Row quantifies storage, completes data processing；
Step 3 203, to the perception data in the data after the process of step 2 202, the analysis of interbehavior dataware, extracts
The degree of belief factor, and corresponding trust metric model is built according to the degree of belief factor, complete trust metric model structure；
Step 4 204, is obtained the degree of belief factor in conjunction with step 3 203, is made using the interactive information between user, resource
User's virtual community is created with evaluating data, dynamic study fact, user's virtual community structure is completed；
Step 5 205, according to the further community's behavior in real time of user, enters Mobile state adjustment, structure to the member in community
More stable Learning Community is built, the dynamic adjustment of virtual community is completed, the wherein continuous circulation adjustment of step 5 205, by step
One 201 setting just can effectively complete the collection of data, just can effectively complete data by the setting of step 2 202
Process, just can effectively be calculated by the setting of step 3 203 and the degree of belief factor and construct trust model, by step
User's virtual community can be just set up out in rapid 4 204 setting, then by the setting of step 5 205, it is possible to effectively right
Communities of users is adjusted, it is to avoid the various problems occurred in the general study of movement in prior art.
As a kind of improved specific embodiment of construction method, carrying for the degree of belief factor in the step 3 203, is extracted
Take step as follows：
A, Internet is arranged to input layer 301, e-learning layer 302 and output layer 303, two in setting network use
Family is respectively user i and user j, extracts the positional distance (i, j) between user i and user j using input layer 301, extracts and uses
User's interval degree (i, j) between family i and user j, extracts the communication frequency (i, j) between user i and user j；
B, by the positional distance (i, j) for extracting, user's interval degree (i, j) and the communication frequency (i, j) are input to network science
Practise in layer 302, by the study and computing of e-learning layer 302, calculate the degree of belief factor, calculate the degree of belief factor it
Before, first positional distance (i, j) and user's interval degree (i, j) are inverted, positional distance (i, j) is transformed to 1/ positional distance
(i, j), interval degree (i, j) are transformed to 1/ interval degree (i, j), afterwards to the positional distance (i, j) of input, use in input layer 301
Family interval degree (i, j) and the communication frequency (i, j) equal additional weight value above, weighted value sum is 1, to three weighted values additional
Individual definite value, it is variate to select a weighted value, is left two weighted value sums and deducts variate for 1, then by whole weighted values
It is added after being multiplied with the value of positional distance (i, j), user's interval degree (i, j) and the communication frequency (i, j) and obtains the degree of belief factor, it
After judge now to obtain the degree of belief factor calculate whether correct, if correctly, increasing the value of variate, other two weighted values
Sum is reduced, if mistake, reduces the variate, and other two weighted value sums increase, and constantly variate are entered according to above-mentioned steps
Row adjustment, till variate is repeatedly unchanged, determines variate afterwards, and it is new change to select a value being left in two weighted values
Value, new variate deduct the variate for determining with remaining weighted value sum equal to 1, repeat above-mentioned calculating, and correctly stylish variate increases
Plus, remaining weighted value reduces, and the stylish variate of mistake reduces, and remaining weighted value increases, until new variate is repeatedly unchanged being
Only, so just effectively can realize one study calculate effect, just effectively can complete to three positional distances (i,
J), the determination of the weighted value of user's interval degree (i, j) and the communication frequency (i, j) data, it is ensured that the degree of belief factor that calculates
More accurate, this makes it possible to effectively calculate the accurate degree of belief factor.
In sum, a kind of user's virtual community construction device based on the degree of belief factor that the present invention is provided, will trust
The advanced achievements such as the degree factor, virtual community theory, data digging method are integrated in the module of method, by ubiquitous for movement study ring
Generalization study under border is changed into customer-centric, the AC system personalization mutual assistance study side based on mobile source of new data
Formula, so that effectively improve learning interest and the learning efficiency of learner.
The above is only the preferred embodiment of the present invention, and protection scope of the present invention is not limited merely to above-mentioned enforcement
Example, all technical schemes belonged under thinking of the present invention belong to protection scope of the present invention.It should be pointed out that for the art
Those of ordinary skill for, some improvements and modifications without departing from the principles of the present invention, these improvements and modifications
Should be regarded as protection scope of the present invention.
Claims (8)
1. a kind of user's virtual community construction device based on the degree of belief factor, it is characterised in that：Including：
Data acquisition module (101), for gathered data, which is coupled with outside mobile terminal and is communicated, and collection is outside mobile whole
The user basic information (1011) at end, course essential information (1012), user mutual behavior information (1013) and mobile awareness number
According to above- mentioned information is compiled into user data package signal output after completing by collection；
Data processing module (102), for processing to data, which is coupled with data acquisition module (101), to receive and solve
Analysis user data package signal, obtains user basic information (1011), course essential information (1012), user mutual behavior information
(1013) and mobile awareness data, and quantization storage, the data after being processed are carried out after processing to above- mentioned information；
Degree of belief analysis module (103), for calculating the degree of belief factor and building trust metric model, which is coupled to data processing mould
Block (102), to be communicated with data processing module (102), is called the data after processing, and calculates the degree of belief factor according to data,
According to the degree of belief factor build trust metric model, the degree of belief analysis module (103) be further coupled to data acquisition module (101) with
The user data package that receiving data acquisition module sends；User's Virtual Community Management module (104), virtual for building and managing
Community, is coupled to degree of belief analysis module (103), to communicate with degree of belief analysis module (103), calls degree of belief factor data
And user data package, built according to degree of belief factor data and user data package and adjustment communities of users.
2. the user's virtual community construction device based on the degree of belief factor according to claim 1, it is characterised in that：Described
Data processing module (102) includes：
Data cleansing part (1021), is coupled to data acquisition module (101), is exported with receiving data acquisition module (101)
User data package signal, by data packet signal of the user data package signal after interference signal filtering after output cleaning；
Characteristic extraction part (1022), is coupled to data cleansing part (1021), with receiving data cleaning part (1021) output
Cleaning after data packet signal, frequency range selection is carried out to the data packet signal, the signal of the frequency range is chosen and is exported extraction number
According to bag；
Characteristic quantification part (1023), coupling and characteristic extraction part (1022), to receive characteristic extraction part (1022) output
Extraction packet, and to extract packet quantitative analysiss, obtain discrete data point, for degree of belief analysis module (103) analyze
Calculate the degree of belief factor.
3. the user's virtual community construction device based on the degree of belief factor according to claim 2, it is characterised in that：Described
Data cleansing part (1021) and characteristic extraction part (1022) are wave filter, and described characteristic quantification part (1022) are band logical
Wave filter.
4. the user's virtual community construction device based on the degree of belief factor according to claim 1 or 2 or 3, its feature exist
In：Described degree of belief analysis module (103) include perception data analysis module (1031), interaction data analysis module (1032),
Degree of belief factor structure module (1033) and trust model creation module (1034), perception data analysis module (1031),
Interaction data analysis module (1032), the degree of belief factor build module (1033) with trust model creation module (1034) with number
Couple according to processing module (102) and data acquisition module (101), adopt in order to receiving data processing module (102) and data respectively
Collection module (101) real time data that exports and the data after processing, and by perception data analysis module (1031) to number in real time
Perception analysis are carried out according to the data after process, perception data is obtained, by interaction data analysis module (1032) to number in real time
Analysis is interacted according to the data after process, interaction data is obtained, module (1033) is built to processing by the degree of belief factor
Data afterwards are analyzed calculating, obtain the degree of belief factor, by trust model creation module (1034) by the degree of belief factor with
Data after real time data and process are combined, and obtain trust model.
5. the user's virtual community construction device based on the degree of belief factor according to claim 1 or 2 or 3, its feature exist
In：User's Virtual Community Management module (104) include：
Communities of users builds module (1041), is coupled to degree of belief analysis module (103), calls degree of belief analysis module (103)
Interior trust model, calculates the initial trust degree between user according to trust model, will be many according to the degree of belief between user
Individual customer mobile terminal connection communication, constitutes communities of users；
Community's interaction module (1042), is arranged in communities of users, with each member communication in the mobile terminal of communities of users
Connection, in order to provide the information interaction between the member of communities of users；
Mutual-aid community study module (1043), is coupled with community's interaction module (1042), is stored with learning materials, is used
To convey learning materials to community's interaction module (1042)；
Community's dynamic adjusting module (1044), is coupled to degree of belief analysis module (103), calls degree of belief analysis module (103)
Interior trust model, calculates the real-time degree of belief between user according to trust model, and adjusts user according to real-time degree of belief
Number of members in community.
6. the user's virtual community construction device based on the degree of belief factor according to claim 1 or 2 or 3, its feature exist
In：The customer mobile terminal is be stored with user basic information (1011), course essential information (1012), user mutual behavior
Information (1013) and the mobile phone of mobile awareness data.
7. a kind of user's virtual community construction method based on the degree of belief factor, it is characterised in that：Comprise the steps：
Step one (201), using mobile terminal device, gathers source of new data, and new data source includes user basic information
(1011), course essential information (1012), user mutual behavior information (1013) and mobile awareness data, data acquisition；
Step 2 (202), is carried out cleaning, is screened and feature extraction to the Various types of data collected in step one (201), most laggard
Row quantifies storage, completes data processing；
Step 3 (203), to the perception data in the data after step 2 (202) process, the analysis of interbehavior dataware, extracts
The degree of belief factor, and corresponding trust metric model is built according to the degree of belief factor, complete trust metric model structure；
Step 4 (204), is obtained the degree of belief factor in conjunction with step 3 (203), is made using the interactive information between user, resource
User's virtual community is created with evaluating data, dynamic study fact, user's virtual community structure is completed；
Step 5 (205), according to the further community's behavior in real time of user, enters Mobile state adjustment, builds to the member in community
More stable Learning Community, completes the dynamic adjustment of virtual community, wherein step 5 (205) constantly circulation adjustment.
8. user's virtual community construction method according to claim 7, it is characterised in that：Carry in step 3 (203)
The extraction step for taking the degree of belief factor is as follows：
A, Internet is arranged to input layer (301), e-learning layer (302) and output layer (303), two in setting network
User is respectively user i and user j, extracts the positional distance (i, j) between user i and user j using input layer (301), carries
User's interval degree (i, j) between family i and user j is taken, the communication frequency (i, j) between user i and user j is extracted；
B, by the positional distance (i, j) for extracting, user's interval degree (i, j) and the communication frequency (i, j) are input to e-learning layer
(302), in, by the study and computing of e-learning layer (302), the degree of belief factor is calculated.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710004815.0A CN106504105A (en) | 2017-01-04 | 2017-01-04 | A kind of user's virtual community construction device and method based on the degree of belief factor |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710004815.0A CN106504105A (en) | 2017-01-04 | 2017-01-04 | A kind of user's virtual community construction device and method based on the degree of belief factor |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN106504105A true CN106504105A (en) | 2017-03-15 |
Family
ID=58345052
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710004815.0A Pending CN106504105A (en) | 2017-01-04 | 2017-01-04 | A kind of user's virtual community construction device and method based on the degree of belief factor |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106504105A (en) |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090327484A1 (en) * | 2008-06-27 | 2009-12-31 | Industrial Technology Research Institute | System and method for establishing personal social network, trusty network and social networking system |
| CN102044009A (en) * | 2009-10-23 | 2011-05-04 | 华为技术有限公司 | Group recommending method and system |
| CN102523554A (en) * | 2011-11-28 | 2012-06-27 | 苏州英福迈升信息技术有限公司 | Virtual community application system based on radio-frequency identification (RFID) |
-
2017
- 2017-01-04 CN CN201710004815.0A patent/CN106504105A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090327484A1 (en) * | 2008-06-27 | 2009-12-31 | Industrial Technology Research Institute | System and method for establishing personal social network, trusty network and social networking system |
| CN102044009A (en) * | 2009-10-23 | 2011-05-04 | 华为技术有限公司 | Group recommending method and system |
| CN102523554A (en) * | 2011-11-28 | 2012-06-27 | 苏州英福迈升信息技术有限公司 | Virtual community application system based on radio-frequency identification (RFID) |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN104396188B (en) | System and method for carrying out basic reason analysis to mobile network property problem | |
| CN104424235B (en) | The method and apparatus for realizing user profile cluster | |
| CN108123931A (en) | Ddos attack defence installation and method in a kind of software defined network | |
| CN109768888A (en) | A kind of network service quality evaluation method, device, equipment and readable storage medium storing program for executing | |
| CN108520365A (en) | Education decision system based on big data analysis | |
| CN109743356B (en) | Industrial internet data acquisition method and device, readable storage medium and terminal | |
| CN102722577B (en) | The determination method and device of index changeable weight | |
| CN102111453A (en) | Method and system for extracting Internet user network behaviors | |
| CN109522822A (en) | A kind of video detecting method and device | |
| CN106878409A (en) | A kind of game data processing system and processing method | |
| CN105340311B (en) | The network equipment, network service prediction meanss and method | |
| CN108346004A (en) | A kind of water resource monitoring analysis system and method based on big data | |
| CN103605736B (en) | The processing method and processing device of conversion data | |
| CN108337324A (en) | A kind of card insertion intelligent cloud computing central processing unit system and its data processing method | |
| CN101399708B (en) | Method and device for establishing network performance model | |
| CN107105226B (en) | A kind of video quality evaluation device | |
| CN106790072A (en) | The recognition methods of malice entry address and device | |
| CN109726808B (en) | Neural network training method and device, storage medium and electronic device | |
| CN105550334B (en) | A kind of video recommendation method and device | |
| CN106504105A (en) | A kind of user's virtual community construction device and method based on the degree of belief factor | |
| CN101931986A (en) | Indication method of network energy efficiency, indicator and system | |
| CN109344333A (en) | A kind of internet big data analysis extracting method and system | |
| CN110971673B (en) | Computer device and method for acquiring user activity of deep learning platform | |
| CN109243549A (en) | A kind of intelligent follow-up method, device and server | |
| CN106570003A (en) | Data pushing method and apparatus |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20170315 |
|
| RJ01 | Rejection of invention patent application after publication |