CN107464196A - Student group is left school Forecasting Methodology and device - Google Patents
Student group is left school Forecasting Methodology and device Download PDFInfo
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Abstract
Left school Forecasting Methodology and device the invention discloses a kind of student group.Wherein, this method includes：It is determined that the student that leaves school；The cohesion left school by default student's cohesion network calculations between student, wherein, student's cohesion network is used to describe the cohesion between student；Determine whether that student group, which occurs, leaves school event according to the cohesion between the student that leaves school, wherein, student group event of leaving school is event that at least two students leave school.The present invention solve in the prior art can not look-ahead student group leave school the technical problem of event.
Description
Technical field
The present invention relates to computer internet field, left school Forecasting Methodology and dress in particular to a kind of student group
Put.
Background technology
There is the characteristics of mobility is big, individual difference is big in the student of school, and the atmosphere of school is more and more open now,
Whether statistic, which leaves school, becomes to become increasingly complex, even if having known the student that leaves school, it is also difficult to weighs whether the student that leaves school deposits
Leave school event in colony, left school event once student group occurs in the prior art, often there occurs after serious consequence
It can know or not be known always, and the student group event of leaving school pushes comes to shove, in the prior art also being capable of not prediction science
The method that raw colony leaves school.
For it is above-mentioned in the prior art can not look-ahead student group leave school event the problem of, not yet propose at present effective
Solution.
The content of the invention
Left school Forecasting Methodology and device the embodiments of the invention provide a kind of student group, at least to solve in the prior art
Can not look-ahead student group leave school the technical problem of event.
One side according to embodiments of the present invention, there is provided a kind of student group is left school Forecasting Methodology, including：It is determined that from
School student；The cohesion left school by default student's cohesion network calculations between student, wherein, student's cohesion network is used
Cohesion between student is described；Determine whether that student group, which occurs, leaves school event according to the cohesion between the student that leaves school,
Wherein, student group event of leaving school is the event left school of at least two students.
Another aspect according to embodiments of the present invention, additionally provide a kind of student group and leave school prediction meanss, including：First
Determining module, for determining the student that leaves school；Computing module, for by default student's cohesion network calculations leave school student it
Between cohesion, wherein, student's cohesion network is used to describe cohesion between student；Second determining module, for basis
The cohesion between student of leaving school determines whether to occur student group and left school event, wherein, the student group event of leaving school is at least
The event that two students leave school.
In embodiments of the present invention, by determining the student that leaves school；Left school by default student's cohesion network calculations
Cohesion between life, wherein, student's cohesion network is used to describe the cohesion between student；According between the student that leaves school
Cohesion determines whether that student group, which occurs, leaves school event, wherein, student group leaves school what event was left school at least two students
Event, it is achieved thereby that rationally student group can leave school event, real-time is good, disposes convenient technique effect, and then solve
In the prior art can not look-ahead student group leave school the technical problem of event.
Brief description of the drawings
Accompanying drawing described herein is used for providing a further understanding of the present invention, forms the part of the application, this hair
Bright schematic description and description is used to explain the present invention, does not form inappropriate limitation of the present invention.In the accompanying drawings：
Fig. 1 is that a kind of student group according to embodiments of the present invention is left school the schematic diagram of Forecasting Methodology；
Fig. 2 is that a kind of optional student group according to embodiments of the present invention is left school the schematic diagram of Forecasting Methodology；And
Fig. 3 is that a kind of student group according to embodiments of the present invention is left school the schematic diagrames of prediction meanss.
Embodiment
In order that those skilled in the art more fully understand the present invention program, below in conjunction with the embodiment of the present invention
Accompanying drawing, the technical scheme in the embodiment of the present invention is clearly and completely described, it is clear that described embodiment is only
The embodiment of a part of the invention, rather than whole embodiments.Based on the embodiment in the present invention, ordinary skill people
The every other embodiment that member is obtained under the premise of creative work is not made, it should all belong to the model that the present invention protects
Enclose.
It should be noted that term " first " in description and claims of this specification and above-mentioned accompanying drawing, "
Two " etc. be for distinguishing similar object, without for describing specific order or precedence.It should be appreciated that so use
Data can exchange in the appropriate case, so as to embodiments of the invention described herein can with except illustrating herein or
Order beyond those of description is implemented.In addition, term " comprising " and " having " and their any deformation, it is intended that cover
Cover it is non-exclusive include, be not necessarily limited to for example, containing the process of series of steps or unit, method, system, product or equipment
Those steps or unit clearly listed, but may include not list clearly or for these processes, method, product
Or the intrinsic other steps of equipment or unit.
Embodiment 1
According to embodiments of the present invention, there is provided a kind of student group leave school Forecasting Methodology embodiment of the method, it is necessary to illustrate
, can be held the step of the flow of accompanying drawing illustrates in the computer system of such as one group computer executable instructions
OK, although also, show logical order in flow charts, in some cases, can be with different from order herein
Perform shown or described step.
Fig. 1 is that student group according to embodiments of the present invention is left school Forecasting Methodology, as shown in figure 1, this method include it is as follows
Step：
Step S102, it is determined that the student that leaves school.
Specifically, determination is left school, student can include at least one following：It is determined that the name information for the student that leaves school, class's letter
Breath, specialized information, start time information of leaving school etc..Under normal circumstances, such as summer vacation either winter vacation or needs situation about asking for leave
Under, student can register information table of leaving school before leaving school, and the information such as name, initial time of leaving school are inserted in information table of leaving school,
Therefore information table can be left school by this to determine the student that leaves school, in addition, current student, which is substantially all, has such as hand
Some Intelligent mobile equipments such as machine, IPAD, computer, school would generally also provide wireless aps (i.e. wireless access points,
Wireless Access Point's writes a Chinese character in simplified form), and the above-mentioned Intelligent mobile equipment that student holds can be connected to school's wireless aps,
School's wireless aps can gather MAC (network interface physical address, the Media of the student's equipment for being connected to current school's wireless aps
Access Control or Medium Access Control's writes a Chinese character in simplified form) address, and distribute IP address (internet protocol address,
Internet Protocol Address' writes a Chinese character in simplified form), also, optionally, the online core switch record of school has student's
Internet log information, therefore, network playing by students daily record can be obtained by the online core switch of school, and by being connected to
Student's apparatus information acquiring student's positional information of school's wireless access points, believed by network playing by students daily record and student position
Cease to determine the student that leaves school.
Step S104, the cohesion between the student that left school by default student's cohesion network calculations, wherein, Xue Shengqin
Density network is used to describe the cohesion between student.
Specifically, student's cohesion network mentioned here can also be student's cohesion model, can specifically use
Numerical value describes the cohesion between student, the cohesion between student can also be carried out on the basis of the cohesion numerical value
Name, if for example, cohesion numerical value is less than the first numerical value, stranger is defined as, if cohesion numerical value is more than or equal to the
One numerical value but second value is less than, is then defined as recognizing, if cohesion numerical value is more than or equal to second value, defines preferably
Friend, wherein, the first numerical value is less than second value, except naming method in this, it should be noted that can also be other names side
Formula, a kind of name example is simply show herein.
Specifically, the student that leaves school determined in step S102 is isolated individual, it is to sentence only according to the student that leaves school
The disconnected student group that whether occurs is left school event, and the parent between the student that leaves school can be calculated according to default student's cohesion network
Density, left school event by cohesion to judge whether to occur student group.
Step S106, determine whether that student group, which occurs, leaves school event according to the cohesion between the student that leaves school, wherein, learn
Raw colony event of leaving school is event that at least two students leave school.
Specifically, by calculating the cohesion between the student that leaves school, you can whether draw has the student of high cohesion
The event together left school, left school event so as to predict student group.
In embodiments of the present invention, by determining the student that leaves school；Left school by default student's cohesion network calculations
Cohesion between life, wherein, student's cohesion network is used to describe the cohesion between student；According between the student that leaves school
Cohesion determines whether that student group, which occurs, leaves school event, wherein, student group leaves school what event was left school at least two students
Event, it is achieved thereby that rationally student group can leave school event, real-time is good, disposes convenient technique effect, and then solve
In the prior art can not look-ahead student group leave school the technical problem of event.
In a kind of optional embodiment, genetis method is determined whether according to the cohesion between the student that leaves school in step S106
The raw colony event of leaving school includes：
Step S202, determine whether that cohesion exceedes default cohesion threshold value according to the cohesion between the student that leaves school
Leave school student；
Step S204, in the case of the student that leaves school for thering is cohesion to exceed default cohesion threshold value, it is determined that student occurs
Colony leaves school event.
Specifically, by calculating the cohesion between the student that leaves school, if at least two cohesions for leaving school student surpass
Cross default cohesion threshold value, then illustrate that at least two student that leaves school has high close relationship, then can determine this at least two
The student that leaves school is the colony that leaves school, i.e., is left school event there occurs colony, herein it should be noted that in the thing it is determined that colony leaves school
In part leave school student when, can determine that two cohesions exceed the student that leaves school of default cohesion threshold value first, then see again
Whether the leave school student that with the cohesion of two the leave school student exceedes default cohesion threshold value is had, the like, so that it is determined that
Whom the student that colony leaves school in event has, wherein, presetting cohesion threshold value can be according to the self-defined setting of actual conditions.
In a kind of optional embodiment, the student that leaves school is determined in step S102, including：
Step S302, obtain network playing by students daily record and student's positional information；
Step S304, final time of each student in school is determined according to network playing by students daily record and student's positional information；
Step S306, the duration of leaving school of each student is determined according to final time of each student in school；
Step S308, it is determined that whether duration of leaving school exceedes predetermined threshold value；
Step S310, in the case where duration of leaving school exceedes predetermined threshold value, it is determined that leaving school student corresponding to duration to leave school
Student.
Specifically, according to network playing by students daily record and student's positional information determine each student school final time also
It is the initial time that each student leaves school, according to current time, with reference to final time of each student in school, it is possible to obtain
Each student duration of leaving school, when leaving school, duration exceedes predetermined threshold value, then assert student left school, i.e., the student for from
School student, wherein, predetermined threshold value can be according to the self-defined setting of actual conditions, for example, could be arranged to one day etc..
In a kind of optional embodiment, network playing by students daily record and student's positional information are obtained in step S302, including：Step
Rapid S402, network playing by students daily record is obtained by the online core switch of school, and connect by being connected to school's accessing wirelessly
Student's apparatus information acquiring student's positional information of access point.
Specifically, student's facility information includes the MAC Address and IP address of student's equipment, according to student's facility information
Learn student's positional information.
In a kind of optional embodiment, genetis method is determined whether according to the cohesion between the student that leaves school in step S106
The raw colony event of leaving school includes：
Step S502, according to the final time in school is identical or the student that leaves school in same time period between cohesion
Determine whether that cohesion exceedes the student that leaves school of default cohesion threshold value, wherein, school final time according to network playing by students
Daily record and student's positional information determine；
Step S504, in the case of the student that leaves school for thering is cohesion to exceed default cohesion threshold value, it is determined that student occurs
Colony leaves school event.
Specifically, judge whether that generation student group was left school in addition to the time except the cohesion according to the student that leaves school, in order to
Make judged result more accurate, the initial time of leaving school for the student that can be left school in combination with final time of the student in school of leaving school
Judged, left school in the same time or the student that leaves school that is left school in the same period in, if cohesion exceed it is default
The student that leaves school of cohesion threshold value, then it is more likely the colony that leaves school, colony more likely occurs and leaves school the time.
In a kind of optional embodiment, in step S104 by default student's cohesion network calculations leave school student it
Between cohesion before, method also includes：Step S108, build student's cohesion network；
Wherein, student's cohesion network is built in step S108 includes：
Step S602, that collects predetermined time period is connected to identical school wireless access points in same time
Pupilage information corresponding to student's facility information；
Step S604, pupilage information is trained using deep learning algorithm, obtains student's cohesion network.
Specifically, because school generally there are at least one school's wireless aps, when student is surfed the Net using school's wireless aps all
Real-name authentication is needed, the IP address information of provisional communication can be generated after certification, therefore, school's wireless aps can gather connection
It is corresponding to student's facility information of current school's wireless aps, including MAC information and IP address information, each IP address information
Student's id information, that is, pupilage information, therefore pupilage information is assured that according to IP address information, same
Time or being connected between the student of same school's wireless aps for same period typically can be assumed that as with certain parent
Close relation, thus can gather predetermined time period same time or same period to be connected to same school wireless
AP pupilage information, using the information as training data source, wherein, predetermined time period can be according to actual conditions certainly
Definition set, for example, it may be one month, the first quarter, half a year, 1 year etc., during which can every prefixed time interval collect one
Secondary data, such as every other day collect a data；Pass through connection of the deep learning algorithm to same time or same period
Pupilage information to same school's wireless aps is modeled, and trains a semantic network with space vector, i.e.,
Student's cohesion network, change the cohesion between student's cohesion network can expression student, and then student can also be obtained
Between similarity information, and be trained by constantly collecting new data, student's cohesion network can be continuous
Amendment, more accurately.
In a kind of optional embodiment, pupilage information is instructed using deep learning algorithm in step S604
Practice, including：
Step S702, pupilage information is trained using word2vec deep learning algorithm.
Specifically, a height that word is characterized as to real number value vector that word2vec is Google to increase income in year in 2013
Effect instrument, it utilizes the thought of deep learning, the processing to content of text can be reduced to K gts by training
In vector operation, and the similarity in vector space can be used for representing similarity on text semantic.Word2vec is exported
Term vector can be used to do the related work of many NLP, for example cluster, look for synonym, part of speech analysis etc..If change individual
Thinking, assign word as feature, then Word2vec cans can seek Feature Mapping to K gts for text data
Seek more profound character representation.
It is identical that being connected in same time for predetermined time period is collected in a kind of optional embodiment, in step S602
School's wireless access points student's facility information corresponding to pupilage information include：
Step S802, it is identical to collect being connected in same time for predetermined time period by school's wireless access points
School's wireless access points student's facility information, wherein, student's facility information includes IP address information；
Step S804, learned by the customer certification system of server according to corresponding to IP address acquisition of information IP address information
Raw identity information, wherein, customer certification system include at least one IP address information, at least one pupilage information and
Corresponding relation between at least one IP address information and at least one pupilage information.
Specifically, from above, school's wireless aps can gather the student's equipment letter for being connected to current school's wireless aps
Breath, including MAC information and IP address information, and these student's facility informations can be synchronized in the server of school, take
Business device includes customer certification system, is usually real name internet during network playing by students, therefore many is stored in customer certification system
Mapping relations between pupilage information, much IP address information and pupilage information and IP address information are namely learned
Corresponding relation between raw identity information and IP address information,, can according to the mapping of customer certification system by IP address information
With pupilage information corresponding to acquisition, and the pupilage information that same time or same period collect can be used as one
Data storage is in the server.
In a kind of specific embodiment, as shown in Fig. 2 Fig. 2 left-halfs are the prebuild mistakes of student's cohesion network
Journey, student side specifically refer to the mobile phone, IPAD, the Intelligent mobile equipment such as computer of student's carrying, AP1 ..., APN refer to school
Wireless aps, student can typically access school's wireless aps at school, and school's wireless aps can gather connected student's equipment
Student's facility information, including MAC information and IP address information, according to IP address information reflecting by school's customer certification system
Penetrate, it is possible to obtain pupilage information corresponding to IP address information, be connected to together by the same time for gathering a period of time
The pupilage information of one school's wireless aps, it can train to obtain student's cohesion model using word2vec；Fig. 2 right side
How point mainly determine to leave school the flow of student, and record has network playing by students daily record in school's Internet data core switch, leads to
These network collectors can be got by crossing network collector, with reference to IP address information, it may be determined that student's final online time,
Thus may determine that whether student leaves school, so that it is determined that the student that leaves school, it is determined that after the student that leaves school, with reference to student's cohesion net
Network, it can be determined that whether there is the student that leaves school of high cohesion in the student that leaves school, if, it may be determined that colony occurs and leaves school thing
Part.
Embodiment 2
According to embodiments of the present invention, there is provided a kind of student group is left school the product embodiments of prediction meanss, and Fig. 3 is basis
The student group of the embodiment of the present invention is left school prediction meanss, as shown in figure 3, the device includes the first determining module, computing module
With the second determining module, wherein, the first determining module, for determining to leave school student；Computing module, for passing through default student
The cohesion that cohesion network calculations are left school between student, wherein, student's cohesion network is used to describing intimate between student
Degree；Second determining module, left school event for determining whether to occur student group according to the cohesion left school between student, its
In, student group event of leaving school is the event left school of at least two students.
In embodiments of the present invention, the student that leaves school is determined by the first determining module；Computing module passes through default student
The cohesion that cohesion network calculations are left school between student, wherein, student's cohesion network is used to describing intimate between student
Degree；Second determining module determines whether that student group, which occurs, leaves school event according to the cohesion between the student that leaves school, wherein, student
Colony's event of leaving school is the event left school of at least two students, it is achieved thereby that rationally student group can leave school event, in real time
Property is good, disposes convenient technique effect, so solve in the prior art can not look-ahead student group leave school the skill of event
Art problem.
Herein it should be noted that above-mentioned first determining module, computing module and the second determining module correspond to embodiment 1
In step S102 to step S106, the example and application scenarios that above-mentioned module is realized with corresponding step be identical but unlimited
In the disclosure of that of above-described embodiment 1.It should be noted that above-mentioned module can be at such as one group as a part of of device
Performed in the computer system of computer executable instructions.
In a kind of optional embodiment, the second determining module includes the 3rd determining module and the 4th determining module, wherein,
3rd determining module, for determining whether that cohesion exceedes default cohesion threshold value according to the cohesion between the student that leaves school
Leave school student；4th determining module, in the case of the student that leaves school for thering is cohesion to exceed default cohesion threshold value, it is determined that
Generation student group is left school event.
Herein it should be noted that the step that above-mentioned 3rd determining module and the 4th determining module correspond in embodiment 1
S202 to step S204, above-mentioned module is identical with example and application scenarios that corresponding step is realized, but is not limited to above-mentioned reality
Apply the disclosure of that of example 1.It should be noted that above-mentioned module can be such as one group of computer can as a part of of device
Performed in the computer system of execute instruction.
In a kind of optional embodiment, the first determining module includes the first acquisition module, the 5th determining module, the 6th true
Cover half block, the 7th determining module and the 8th determining module, wherein, the first acquisition module, for obtaining network playing by students daily record and
Raw positional information；5th determining module, for determining each student in school according to network playing by students daily record and student's positional information
Final time；6th determining module, for determining leaving school for each student according to final time of each student in school
Duration；7th determining module, for determining whether duration of leaving school exceedes predetermined threshold value；8th determining module, for when leaving school
In the case that length exceedes predetermined threshold value, it is determined that leaving school student corresponding to duration as the student that leaves school.
Herein it should be noted that above-mentioned first acquisition module, the 5th determining module, the 6th determining module, the 7th determination
The step S302 to step S310 that module and the 8th determining module correspond in embodiment 1, above-mentioned module and corresponding step institute
The example of realization is identical with application scenarios, but is not limited to the disclosure of that of above-described embodiment 1.It should be noted that above-mentioned mould
Block can perform as a part of of device in the computer system of such as one group computer executable instructions.
In a kind of optional embodiment, the first acquisition module includes the second acquisition module, for the online by school
Core switch obtains network playing by students daily record, and by being connected to student's apparatus information acquiring of school's wireless access points
Student's positional information.
Herein it should be noted that above-mentioned second acquisition module correspond to embodiment 1 in step S402, above-mentioned module with
The example that corresponding step is realized is identical with application scenarios, but is not limited to the disclosure of that of above-described embodiment 1.Need to illustrate
, above-mentioned module can hold as a part of of device in the computer system of such as one group computer executable instructions
OK.
In a kind of optional embodiment, the second determining module includes the 9th determining module and the tenth determining module, wherein,
9th determining module, for according to the final time in school is identical or the student that leaves school in same time period between cohesion
Determine whether that cohesion exceedes the student that leaves school of default cohesion threshold value, wherein, school final time according to network playing by students
Daily record and student's positional information determine；Tenth determining module, in leave school for thering is cohesion to exceed default cohesion threshold value
In the case of life, the event it is determined that generation student group is left school.
Herein it should be noted that the step that above-mentioned 9th determining module and the tenth determining module correspond in embodiment 1
S502 to step S504, above-mentioned module is identical with example and application scenarios that corresponding step is realized, but is not limited to above-mentioned reality
Apply the disclosure of that of example 1.It should be noted that above-mentioned module can be such as one group of computer can as a part of of device
Performed in the computer system of execute instruction.
In a kind of optional embodiment, device also includes structure module, default for passing through in the first acquisition module
Before the cohesion that student's cohesion network calculations are left school between student, student's cohesion network is built；Wherein, module bag is built
Include the first collection module and the first training module, wherein, the first collection module, for collect predetermined time period when identical
Between be connected to pupilage information corresponding to student's facility information of identical school wireless access points；First training mould
Block, for being trained using deep learning algorithm to pupilage information, obtain student's cohesion network.
Herein it should be noted that above-mentioned structure module, the first collection module and the first training module correspond to embodiment 1
In step S108 and step S602 to step S604, above-mentioned the module example realized with corresponding step and application scenarios
It is identical, but it is not limited to the disclosure of that of above-described embodiment 1.It should be noted that above-mentioned module can as a part for device
To be performed in the computer system of such as one group computer executable instructions.
In a kind of optional embodiment, the first training module includes：Second training module, for using word2vec's
Deep learning algorithm is trained to pupilage information.
Herein it should be noted that above-mentioned second training module correspond to embodiment 1 in step S702, above-mentioned module with
The example that corresponding step is realized is identical with application scenarios, but is not limited to the disclosure of that of above-described embodiment 1.Need to illustrate
, above-mentioned module can hold as a part of of device in the computer system of such as one group computer executable instructions
OK.
In a kind of optional embodiment, the first collection module includes the second collection module and the 3rd acquisition module, wherein,
Second collection module is identical for collecting being connected in same time for predetermined time period by school's wireless access points
School's wireless access points student's facility information, wherein, student's facility information includes IP address information；3rd obtains mould
Block, for the customer certification system by server, the pupilage according to corresponding to IP address acquisition of information IP address information is believed
Breath, wherein, customer certification system includes at least one IP address information, at least one pupilage information and at least one
Corresponding relation between IP address information and at least one pupilage information.
Herein it should be noted that the step that above-mentioned second collection module and the 3rd acquisition module correspond in embodiment 1
S802 to step S804, above-mentioned module is identical with example and application scenarios that corresponding step is realized, but is not limited to above-mentioned reality
Apply the disclosure of that of example 1.It should be noted that above-mentioned module can be such as one group of computer can as a part of of device
Performed in the computer system of execute instruction.
Embodiment 3
According to embodiments of the present invention, there is provided a kind of product embodiments of storage medium, the storage medium include storage
Program, wherein, equipment where controlling storage medium when program is run performs above-mentioned student group and left school Forecasting Methodology method.
Embodiment 4
According to embodiments of the present invention, there is provided a kind of product embodiments of processor, the processor are used for operation program, its
In, program performs above-mentioned student group when running and left school Forecasting Methodology method.
Embodiment 5
According to embodiments of the present invention, there is provided a kind of product embodiments of terminal, the terminal include the first determining module, meter
Module, the second determining module and processor are calculated, wherein, the first determining module, for determining the student that leaves school；Computing module, it is used for
The cohesion left school by default student's cohesion network calculations between student, wherein, student's cohesion network is used to describe
Cohesion between student；Second determining module, for being determined whether student group occurs according to the cohesion between the student that leaves school
Body is left school event, wherein, student group event of leaving school is event that at least two students leave school；Processor, processor operation journey
Sequence, wherein, performed when program is run for the data exported from the first determining module, computing module and the second determining module above-mentioned
Student group is left school Forecasting Methodology method.
Embodiment 6
According to embodiments of the present invention, there is provided a kind of product embodiments of terminal, the terminal include the first determining module, meter
Module, the second determining module and storage medium are calculated, wherein, the first determining module, for determining the student that leaves school；Computing module, use
Cohesion between the student that left school by default student's cohesion network calculations, wherein, student's cohesion network is used to retouch
State the cohesion between student；Second determining module, for being determined whether student occurs according to the cohesion between the student that leaves school
Colony leaves school event, wherein, student group event of leaving school is event that at least two students leave school；Storage medium, for storing
Program, wherein, program operationally performs for the data exported from the first determining module, computing module and the second determining module
Above-mentioned student group is left school Forecasting Methodology method.
The embodiments of the present invention are for illustration only, do not represent the quality of embodiment.
In the above embodiment of the present invention, the description to each embodiment all emphasizes particularly on different fields, and does not have in some embodiment
The part of detailed description, it may refer to the associated description of other embodiment.
In several embodiments provided herein, it should be understood that disclosed technology contents, others can be passed through
Mode is realized.Wherein, device embodiment described above is only schematical, such as the division of the unit, Ke Yiwei
A kind of division of logic function, can there is an other dividing mode when actually realizing, for example, multiple units or component can combine or
Person is desirably integrated into another system, or some features can be ignored, or does not perform.Another, shown or discussed is mutual
Between coupling or direct-coupling or communication connection can be INDIRECT COUPLING or communication link by some interfaces, unit or module
Connect, can be electrical or other forms.
The unit illustrated as separating component can be or may not be physically separate, show as unit
The part shown can be or may not be physical location, you can with positioned at a place, or can also be distributed to multiple
On unit.Some or all of unit therein can be selected to realize the purpose of this embodiment scheme according to the actual needs.
In addition, each functional unit in each embodiment of the present invention can be integrated in a processing unit, can also
That unit is individually physically present, can also two or more units it is integrated in a unit.Above-mentioned integrated list
Member can both be realized in the form of hardware, can also be realized in the form of SFU software functional unit.
If the integrated unit is realized in the form of SFU software functional unit and is used as independent production marketing or use
When, it can be stored in a computer read/write memory medium.Based on such understanding, technical scheme is substantially
The part to be contributed in other words to prior art or all or part of the technical scheme can be in the form of software products
Embody, the computer software product is stored in a storage medium, including some instructions are causing a computer
Equipment (can be personal computer, server or network equipment etc.) perform each embodiment methods described of the present invention whole or
Part steps.And foregoing storage medium includes：USB flash disk, read-only storage (ROM, Read-OnlyMemory), arbitrary access are deposited
Reservoir (RAM, Random Access Memory), mobile hard disk, magnetic disc or CD etc. are various can be with store program codes
Medium.
Described above is only the preferred embodiment of the present invention, it is noted that for the ordinary skill people of the art
For member, under the premise without departing from the principles of the invention, some improvements and modifications can also be made, these improvements and modifications also should
It is considered as protection scope of the present invention.
Claims (10)
- The Forecasting Methodology 1. a kind of student group is left school, including：It is determined that the student that leaves school；By the cohesion between the student that left school described in default student's cohesion network calculations, wherein, student's cohesion Network is used to describe the cohesion between student；Determine whether that student group, which occurs, leaves school event according to the cohesion between the student that leaves school, wherein, the student group Body event of leaving school is the event left school of at least two students.
- 2. according to the method for claim 1, it is characterised in that determined whether according to the cohesion between the student that leaves school The generation student group event of leaving school includes：Determine whether that cohesion is left school described in exceeding default cohesion threshold value according to the cohesion between the student that leaves school Student；In the case where there is cohesion to exceed the student that left school described in default cohesion threshold value, it is determined that occur the student group from School event.
- 3. according to the method for claim 1, it is characterised in that it is determined that the student that leaves school, including：Obtain the network playing by students daily record and student's positional information；Final time of each student in school is determined according to the network playing by students daily record and student's positional information；The duration of leaving school of each student is determined according to final time of each the described student in school；It is determined that whether the duration of leaving school exceedes predetermined threshold value；In the case where the duration of leaving school exceedes predetermined threshold value, it is determined that the student corresponding to duration that leaves school is leave school It is raw.
- 4. according to the method for claim 3, it is characterised in that obtain the network playing by students daily record and student position letter Breath, including：The network playing by students daily record is obtained by the online core switch of school, and connect by being connected to school's accessing wirelessly Student's positional information described in student's apparatus information acquiring of access point.
- 5. the method according to claim 3 or 4, it is characterised in that determined according to the cohesion between the student that leaves school The student group event of leaving school, which whether occurs, to be included：According to the final time in school it is identical or in same time period described in the cohesion between student of leaving school determine whether There is the student that leaves school that cohesion exceedes default cohesion threshold value, wherein, the final time in school is according to the student Internet log and student's positional information determine；In the case where there is cohesion to exceed the student that left school described in default cohesion threshold value, it is determined that occur the student group from School event.
- 6. according to the method for claim 1, it is characterised in that by being left school described in default student's cohesion network calculations Before cohesion between student, methods described also includes：Build student's cohesion network；Building student's cohesion network includes：Collect student's facility information that identical school wireless access points are connected in same time of predetermined time period Corresponding pupilage information；The pupilage information is trained using deep learning algorithm, obtains student's cohesion network.
- 7. according to the method for claim 6, it is characterised in that the pupilage information is entered using deep learning algorithm Row training, including：The pupilage information is trained using word2vec deep learning algorithm.
- 8. according to the method for claim 6, it is characterised in that collects predetermined time period is connected to phase in same time Pupilage information corresponding to student's facility information of same school's wireless access points includes：By school's wireless access points collect predetermined time period same time be connected to identical school without Student's facility information of line access points, wherein, student's facility information includes IP address information；Pass through corresponding to customer certification system IP address information according to the IP address acquisition of information of server Raw identity information, wherein, the customer certification system includes at least one IP address information, at least one student Corresponding relation between identity information and at least one IP address information and at least one pupilage information.
- The prediction meanss 9. a kind of student group is left school, including：First determining module, for determining the student that leaves school；Computing module, for by the cohesion between the student that left school described in default student's cohesion network calculations, wherein, institute Student's cohesion network is stated to be used to describe the cohesion between student；Second determining module, the cohesion for being left school according between student determine whether to occur student group and left school thing Part, wherein, student group event of leaving school is the event left school of at least two students.
- 10. device according to claim 9, it is characterised in that second determining module includes：3rd determining module, it is default intimate to determine whether that cohesion exceedes for the cohesion between the student that left school according to The student that leaves school of degree threshold value；4th determining module, in the case where there is cohesion to exceed the student that left school described in default cohesion threshold value, it is determined that The generation student group is left school event.
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| CN201710660690.7A CN107464196A (en) | 2017-08-04 | 2017-08-04 | Student group is left school Forecasting Methodology and device |
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| CN201710660690.7A CN107464196A (en) | 2017-08-04 | 2017-08-04 | Student group is left school Forecasting Methodology and device |
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| CN110008866A (en) * | 2019-03-25 | 2019-07-12 | 联想(北京)有限公司 | A kind of data processing method and electronic equipment judging cohesion between student |
| CN117315591A (en) * | 2023-11-13 | 2023-12-29 | 安徽光谷智能科技股份有限公司 | Intelligent campus safety monitoring prediction management system |
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| CN104952137A (en) * | 2015-07-21 | 2015-09-30 | 华北理工大学 | Night-out detecting system for dormitory of college |
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| CN104952137A (en) * | 2015-07-21 | 2015-09-30 | 华北理工大学 | Night-out detecting system for dormitory of college |
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