CN109408727A - User based on Multidimensional Awareness data pays close attention to information intelligent recommended method and system - Google Patents
User based on Multidimensional Awareness data pays close attention to information intelligent recommended method and system Download PDFInfo
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Abstract
The present invention provides a kind of, and the user based on Multidimensional Awareness data pays close attention to information intelligent recommended method and system, method includes the following steps: S1, is written information recommendation library for the multidimensional data of headend equipment acquisition；S2 records the retrieval information of user and is stored in Data analysis library, forms a plurality of retrieval record, and every retrieval record includes user name, the characteristic value of searched targets object, retrieval number and retrieval time；S3 is recorded according to the retrieval that user name is inquired in Data analysis library, and is ranked up by attention rate of the user to the target object in each retrieval record to retrieval record, and a part retrieval record that sequence is forward is taken；S4, according to the characteristic value of the target object in the retrieval record of selection, related information recommends the relevant information in library and is pushed to user.The present invention can push the relevant information of the high target object of user's attention rate in real time, reduce user's operation amount, improve recall precision.
Description
Technical field
The present invention relates to smart city management domains more particularly to a kind of user based on Multidimensional Awareness data to pay close attention to information
Intelligent recommendation method and system.
Background technique
With the fast development of technology of Internet of things, smart city construction has been inexorable trend, more and more public security systems
Internet of Things control platform is built, the Multidimensional Awareness data of headend equipment acquisition are collected, investigation of handling a case is to social security point
The dependence of position is increasing, but carries out inquiry to the information in Internet of Things control platform and rely on substantially MS manual search, due to controlling
Pacify the increasing of point, data volume constantly expands, and the data for causing user to need to check become more, and inquiry velocity is slow, if with
Family is retrieved one by one checks that not only inefficiency also will cause user's dislike.
Summary of the invention
The user that the purpose of the present invention is to provide a kind of based on Multidimensional Awareness data pay close attention to information intelligent recommended method and
System, it is intended to rely on MS manual search for solving existing user and inquire a large amount of public security point data, inquiry velocity slowly, efficiency
Low problem.
The present invention is implemented as follows:
On the one hand, the present invention provides a kind of user's concern information intelligent recommended method based on Multidimensional Awareness data, including
Following steps:
Information recommendation library is written in the multidimensional data of headend equipment acquisition by S1；
S2 records the retrieval information of user and is stored in Data analysis library, forms a plurality of retrieval record, every retrieval record packet
User name, the characteristic value of searched targets object, retrieval number and retrieval time are included, wherein retrieval number should for the user search
The total degree of target object, retrieval time are the time that user last time retrieves the target object；
S3 is recorded according to the retrieval that user name is inquired in Data analysis library, and by user to the mesh in each retrieval record
The attention rate for marking object is ranked up retrieval record, takes a part retrieval record that sequence is forward；
S4, according to the characteristic value of the target object in the retrieval record of selection, related information recommends the relevant information in library
And it is pushed to user.
Further, in the step S1, the multidimensional data of headend equipment acquisition includes that portrait captures data, vehicle snapshot
Data and MAC capture data.
Further, the step S1 further include:
Analysis in real time is carried out to the data that headend equipment acquires according to information of deploying to ensure effective monitoring and control of illegal activities and generates alarm or abnormal data, is write together
Enter information recommendation library.
Further, in the step S2, searched targets object is if face object, then characteristic value is that face passes through face
PERSONID after algorithm, if Vehicle Object, then characteristic value is license plate number, and if MAC object, then characteristic value is corresponding
MAC value.
Further, retrieval is remembered by attention rate of the user to the target object in each retrieval record in the step S3
Record, which is ranked up, to be specifically included:
S3.1 is from the near to the distant ranked up retrieval record with the rule of retrieval number descending according to retrieval time, obtains
The M1 item retrieval record for sorting forward；
S3.2 calculates each target object for the M1 item retrieval record that step S3.1 is obtained by attention-degree analysis model
User attention rate Q is ranked up this M1 item retrieval record according to user's attention rate Q descending, and takes the forward M2 item that sorts again
Retrieval record.
Further, the attention-degree analysis model in the step S3.2 are as follows:
Wherein DNNumber of days for the time interval current time of last time searched targets object is poor, NNFor the inspection of target object
Rope number, S are coefficient.
Further, the information that user is pushed in the step S4 includes candid photograph, alarm and abnormal data information.
On the other hand, the present invention also provides a kind of, and the user based on Multidimensional Awareness data pays close attention to information intelligent recommender system,
Including Data write. module, retrieval record collection module, retrieval record ordering module and info push module；
Information recommendation library is written in the multidimensional data that the Data write. module is used to acquire headend equipment；
The retrieval record collection module is used to record the retrieval information of user and is stored in Data analysis library, forms a plurality of inspection
Suo Jilu, every retrieval record include user name, the characteristic value of searched targets object, retrieve number and retrieval time, wherein
The total degree that number is the user search target object is retrieved, retrieval time is that user last time retrieves the target object
Time；
The retrieval that the retrieval record ordering module is used to be inquired in Data analysis library according to user name records, and presses user
The attention rate of target object in each retrieval record is ranked up retrieval record, takes a part retrieval note that sequence is forward
Record；
The info push module is used for the characteristic value of the target object in the retrieval record according to selection, and related information pushes away
It recommends the relevant information in library and is pushed to user.
Further, the retrieval record ordering module is specifically used for:
Retrieval record is ranked up with the rule of retrieval number descending from the near to the distant according to retrieval time, sequence is obtained and leans on
Preceding M1 item retrieves record；
The user attention rate Q of each target object of above-mentioned M1 item retrieval record, root are calculated by attention-degree analysis model
This M1 item retrieval record is ranked up according to user's attention rate Q descending, and takes the M2 item retrieval record for sorting forward again.
Further, the attention-degree analysis model are as follows:
Wherein DNNumber of days for the time interval current time of last time searched targets object is poor, NNFor the inspection of target object
Rope number, S are coefficient.
Compared with prior art, the invention has the following advantages:
This user based on Multidimensional Awareness data provided by the invention pays close attention to information intelligent recommended method and system, can
The relevant information of the high target object of push user's attention rate in real time, avoids user from retrieving one by one, can reduce use
Family operating quantity improves recall precision, and the attention rate of target object is retrieved according to the history of user and recorded to judge, the property of can refer to
Relatively strong, accuracy is high.
Detailed description of the invention
Fig. 1 is that a kind of user based on Multidimensional Awareness data provided in an embodiment of the present invention pays close attention to information intelligent recommended method
Flow chart；
Fig. 2 is that a kind of user based on Multidimensional Awareness data provided in an embodiment of the present invention pays close attention to information intelligent recommender system
Block diagram.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts all other
Embodiment shall fall within the protection scope of the present invention.
As shown in Figure 1, the embodiment of the present invention mentions a kind of user's concern information intelligent recommendation side based on Multidimensional Awareness data
Method, comprising the following steps:
Information recommendation library is written in the multidimensional data of headend equipment acquisition by S1；
S2 records the retrieval information of user and is stored in Data analysis library, forms a plurality of retrieval record, every retrieval record packet
User name, the characteristic value of searched targets object, retrieval number and retrieval time are included, wherein retrieval number should for the user search
The total degree of target object, retrieval time are the time that user last time retrieves the target object；
S3 is recorded according to the retrieval that user name is inquired in Data analysis library, and by user to the mesh in each retrieval record
The attention rate for marking object is ranked up retrieval record, takes a part retrieval record that sequence is forward；
S4, according to the characteristic value of the target object in the retrieval record of selection, related information recommends the relevant information in library
And it is pushed to user.
Technical solution of the present invention can push the relevant information of the high target object of user's attention rate in real time, avoid user one
Item one is retrieved, and user's operation amount can be reduced, and improves recall precision, and the attention rate of target object going through according to user
History retrieval record is to judge, the property of can refer to is stronger, and accuracy is high.
Above steps is described in detail below.
In one embodiment, in the step S1, headend equipment can be the fence for being deployed in target area,
WIFI fence, vehicle bayonet etc., target area can be city or the region of other ranges, the multidimensional data of headend equipment acquisition
Data, vehicle snapshot data and MAC capture data etc. are captured including portrait, the data of acquisition receive write-in letter by kafka
Breath recommends library.
In one embodiment, the step S1 further include: the data that headend equipment acquires are carried out according to information is deployed to ensure effective monitoring and control of illegal activities
Analysis generates alarm or abnormal data in real time, information recommendation library is written together, to can obtain corresponding report when user search
Alert or abnormal data, facilitates and is analyzed.
In one embodiment, in the step S2, target is recorded when a user retrieves a target object for the first time
Characteristics of objects value V, retrieval time T are retrieved times N (N=1), and simultaneously information recommendation library is written in user name P, wherein searched targets pair
As if face object, then characteristic value V is face by the PERSONID after face algorithm, if Vehicle Object, then characteristic value V
For license plate number, if MAC object, then characteristic value V is corresponding MAC value, and features described above value, which can facilitate, carries out target object
It distinguishes.When one target object of a user (n+1)th time retrieval, updated according to searched targets characteristics of objects value V and user name P
Corresponding N value is n+1 in information recommendation library, and T is (n+1)th retrieval time.
In one embodiment, user is pressed in the step S3 to the attention rate pair of the target object in each retrieval record
Retrieval record, which is ranked up, to be specifically included:
S3.1 is from the near to the distant ranked up retrieval record with the rule of retrieval number descending according to retrieval time, specifically
It can be first ranked up from the near to the distant according to retrieval time T, be ranked up further according to retrieval times N descending, it is forward to obtain sequence
M1 item retrieve record；
S3.2 calculates each target object for the M1 item retrieval record that step S3.1 is obtained by attention-degree analysis model
User attention rate Q is ranked up this M1 item retrieval record according to user's attention rate Q descending, and takes the forward M2 item that sorts again
Retrieval record, wherein M1 and M2 is natural number and M1 > M2, the range that remaining data do not consider as stale data in push
It is interior.
Further, the attention-degree analysis model in the step S3.2 are as follows:
Wherein DNNumber of days for the time interval current time of last time searched targets object is poor, NNFor the inspection of target object
Rope number, S are coefficient, and value is the decimal between 0 to 1, preferably 0.6..
Above-described embodiment can accurately obtain the higher target object of user's attention rate by two minor sorts and screening, and
By the screening of first time, the amount of calculation of second step can be reduced, improves computational efficiency.
In one embodiment, the information that user is pushed in the step S4 includes candid photograph, alarm and abnormal data letter
Alarm and abnormal data are pushed to user, facilitate user to understand related data situation, even if capturing useful information by breath.
It illustrates below and above-described embodiment is specifically described.
Assuming that there are following information recommendation libraries, comprising: vehicle snapshot library:
| License plate number | Capture the time | Point title | Body color | Vehicle speed per hour | ........... |
| a | Time1 | Name1 | Color1 | Speed1 | ........... |
| a | Time2 | Name2 | Color1 | Speed2 | ........... |
| a | Time3 | Name3 | Color1 | Speed3 | ........... |
| b | Time4 | Name4 | Color2 | Speed4 | ........... |
| c | Time5 | Name5 | Color3 | Speed5 | ........... |
Vehicle is deployed to ensure effective monitoring and control of illegal activities library of alarming:
| License plate number | Capture the time | Point title | Body color | Vehicle speed per hour | ........... |
| a | Time1 | Name1 | Color1 | Speed1 | ........... |
| a | Time2 | Name2 | Color1 | Speed2 | ........... |
| a | Time3 | Name3 | Color1 | Speed3 | ........... |
| b | Time4 | Name4 | Color2 | Speed4 | ........... |
| c | Time5 | Name5 | Color3 | Speed5 | ........... |
Face information recommends library:
| PERSONID | Capture the time | Gender | Age | ........... |
| ID1 | Time1 | Male | Age1 | ........... |
| ID2 | Time2 | Male | Age2 | ........... |
| ID3 | Time3 | Male | Age3 | ........... |
Face warning message recommends library:
| PERSONID | Time of fire alarming | Gender | Age | ........... |
| ID1 | Time1 | Male | Age1 | ........... |
| ID2 | Time2 | Male | Age2 | ........... |
| ID3 | Time3 | Male | Age3 | ........... |
MAC information bank:
| MAC | Capture time | Field strength | Site name | ........... |
| Mac1 | Time1 | Power1 | Name1 | ........... |
| Mac2 | Time2 | Power2 | Name2 | ........... |
| Mac3 | Time3 | Power3 | Name3 | ........... |
| Mac4 | Time4 | Power4 | Name4 | ........... |
MAC warning message recommends library:
| MAC | Time of fire alarming | Field strength | Site name | ........... |
| Mac1 | Time1 | Power1 | Name1 | ........... |
| Mac2 | Time2 | Power2 | Name2 | ........... |
| Mac3 | Time3 | Power3 | Name3 | ........... |
| Mac4 | Time4 | Power4 | Name4 | ........... |
The retrieval record of user P1 is recorded in Data analysis library:
| SEQ | P | V | N | T |
| 1 | P1 | V1 | N1 | T1 |
| 2 | P1 | V2 | N2 | T2 |
| 3 | P1 | V3 | N3 | T3 |
| 4 | P1 | V4 | N4 | T4 |
| 5 | P1 | V5 | N5 | T5 |
| 6 | P1 | V6 | N6 | T6 |
| 7 | P1 | V7 | N7 | T7 |
| 8 | ||||
| ... | ... | ... | ... | ... |
| 88 | P1 | V8 | N8 | T8 |
| 89 | P1 | V9 | N9 | T9 |
| 90 | P1 | V10 | N10 | T10 |
It is first arranged from the near to the distant according to retrieval time T and arranges to obtain preceding M1 (M1=30) item further according to retrieval times N descending
Data:
According to attention rate modelAttention rate is calculated, and according to pass
Note degree descending is arranged to obtain preceding M2 (M2=10) data:
| SEQ | P | V | N | T |
| 9 | P1 | V9 | N9 | T9 |
| 2 | P1 | V2 | N2 | T2 |
| 8 | P1 | V8 | N8 | T8 |
| 4 | P1 | V4 | N4 | T4 |
| 23 | P1 | V23 | N23 | T23 |
| 6 | P1 | V6 | N6 | T6 |
| 1 | P1 | V1 | N1 | T1 |
| 20 | P1 | V20 | N20 | T20 |
| 16 | P1 | V16 | N16 | T16 |
| 7 | P1 | V7 | N7 | T7 |
The information of vehicles in information recommendation library finally is respectively associated with the characteristic value V in result above and recommends library and vehicle report
License plate number, face information in alert information recommendation library recommend library and face warning message to recommend PERSIONID, MAC letter in library
Breath recommends library and MAC warning message that the corresponding recommendation information of MAC inquiry in library is recommended to be pushed to user.
Based on the same inventive concept, the present invention also provides a kind of, and user's concern information intelligent based on Multidimensional Awareness data pushes away
System is recommended, a kind of user based on Multidimensional Awareness data of the principle and above-described embodiment solved the problems, such as due to the system pays close attention to information
Intelligent recommendation method is similar, therefore the implementation of the system may refer to the implementation of preceding method, and overlaps will not be repeated.
As shown in Fig. 2, for a kind of user's concern information intelligent based on Multidimensional Awareness data provided in an embodiment of the present invention
Recommender system, for executing above method embodiment, the system include Data write. module 11, retrieval record collection module 12,
Retrieve record ordering module 13 and info push module 14.
Information recommendation library is written in the multidimensional data that the Data write. module 11 is used to acquire headend equipment；
The retrieval record collection module 12 is used to record the retrieval information of user and is stored in Data analysis library, is formed a plurality of
Retrieval record, every retrieval record include user name, the characteristic value of searched targets object, retrieve number and retrieval time,
Middle retrieval number is the total degree of the user search target object, and retrieval time is that user last time retrieves the target pair
The time of elephant；
The retrieval that the retrieval record ordering module 13 is used to be inquired in Data analysis library according to user name records, and presses and use
Family is ranked up the attention rate of the target object in each retrieval record to retrieval record, takes a part retrieval that sequence is forward
Record；
The info push module 14 is used for the characteristic value of the target object in the retrieval record according to selection, related information
Recommend the relevant information in library and is pushed to user.
In one embodiment, the multidimensional data of the headend equipment acquisition includes that portrait captures data, vehicle snapshot number
Accordingly and MAC captures data.
Preferably, the Data write. module 11 is also used to carry out in fact the data that headend equipment acquires according to information is deployed to ensure effective monitoring and control of illegal activities
The raw alarm of time-division division or abnormal data, are written information recommendation library together.
In one embodiment, the searched targets object is if face object, then characteristic value is that face is calculated by face
PERSONID after method, if Vehicle Object, then characteristic value is license plate number, and if MAC object, then characteristic value is corresponding MAC
Value.
In one embodiment, the retrieval record ordering module 13 is specifically used for:
Retrieval record is ranked up with the rule of retrieval number descending from the near to the distant according to retrieval time, sequence is obtained and leans on
Preceding M1 item retrieves record；
The user attention rate Q of each target object of above-mentioned M1 item retrieval record, root are calculated by attention-degree analysis model
This M1 item retrieval record is ranked up according to user's attention rate Q descending, and takes the M2 item retrieval record for sorting forward again.
Further, the attention-degree analysis model are as follows:
Wherein DNNumber of days for the time interval current time of last time searched targets object is poor, NNFor the inspection of target object
Rope number, S are coefficient.
In one embodiment, it includes candid photograph, alarm and exception that the info push module 14, which is pushed to the information of user,
Data information.
Those of ordinary skill in the art will appreciate that all or part of the steps in the various methods of embodiment is can to lead to
Program is crossed to instruct relevant hardware and complete, which can be stored in a computer readable storage medium, storage medium
It may include: read-only memory (ROM, Read Only Memory), random access memory (RAM, RandomAccess
Memory), disk or CD etc..
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, all in essence of the invention
Within mind and principle, any modification, equivalent replacement, improvement and so on be should all be included in the protection scope of the present invention.
Claims (10)
1. a kind of user based on Multidimensional Awareness data pays close attention to information intelligent recommended method, which comprises the following steps:
Information recommendation library is written in the multidimensional data of headend equipment acquisition by S1；
S2 records the retrieval information of user and is stored in Data analysis library, forms a plurality of retrieval record, every retrieval record includes using
Name in an account book, the characteristic value of searched targets object, retrieval number and retrieval time, wherein retrieval number is the user search target
The total degree of object, retrieval time are the time that user last time retrieves the target object；
S3 is recorded according to the retrieval that user name is inquired in Data analysis library, and by user to the target pair in each retrieval record
The attention rate of elephant is ranked up retrieval record, takes a part retrieval record that sequence is forward；
S4, according to the characteristic value of the target object in the retrieval record of selection, related information is recommended the relevant information in library and is pushed away
Give user.
2. the user based on Multidimensional Awareness data pays close attention to information intelligent recommended method as described in claim 1, it is characterised in that:
In the step S1, the multidimensional data of headend equipment acquisition includes that portrait captures data, vehicle snapshot data and MAC capture number
According to.
3. the user based on Multidimensional Awareness data pays close attention to information intelligent recommended method as described in claim 1, which is characterized in that
The step S1 further include:
Analysis in real time is carried out to the data that headend equipment acquires according to information of deploying to ensure effective monitoring and control of illegal activities and generates alarm or abnormal data, together write-in letter
Breath recommends library.
4. the user based on Multidimensional Awareness data pays close attention to information intelligent recommended method as described in claim 1, it is characterised in that:
In the step S2, searched targets object is if face object, then characteristic value is that face passes through the PERSONID after face algorithm,
If Vehicle Object, then characteristic value is license plate number, and if MAC object, then characteristic value is corresponding MAC value.
5. the user based on Multidimensional Awareness data pays close attention to information intelligent recommended method as described in claim 1, which is characterized in that
Specific packet is ranked up to retrieval record by attention rate of the user to the target object in each retrieval record in the step S3
It includes:
S3.1 is from the near to the distant ranked up retrieval record with the rule of retrieval number descending according to retrieval time, obtains sequence
Forward M1 item retrieves record；
S3.2 calculates the user of each target object for the M1 item retrieval record that step S3.1 is obtained by attention-degree analysis model
Attention rate Q is ranked up this M1 item retrieval record according to user's attention rate Q descending, and takes the M2 item retrieval for sorting forward again
Record.
6. the user based on Multidimensional Awareness data pays close attention to information intelligent recommended method as claimed in claim 5, which is characterized in that
Attention-degree analysis model in the step S3.2 are as follows:
Wherein DNNumber of days for the time interval current time of last time searched targets object is poor, NNFor the retrieval time of target object
Number, S is coefficient.
7. the user based on Multidimensional Awareness data pays close attention to information intelligent recommended method as described in claim 1, it is characterised in that:
The information that user is pushed in the step S4 includes candid photograph, alarm and abnormal data information.
8. a kind of user based on Multidimensional Awareness data pays close attention to information intelligent recommender system, it is characterised in that: be written including data
Module, retrieval record collection module, retrieval record ordering module and info push module；
Information recommendation library is written in the multidimensional data that the Data write. module is used to acquire headend equipment；
The retrieval record collection module is used to record the retrieval information of user and is stored in Data analysis library, forms a plurality of retrieval note
Record, every retrieval record includes user name, the characteristic value of searched targets object, retrieval number and retrieval time, wherein retrieving
Number is the total degree of the user search target object, retrieval time be user last time retrieve the target object when
Between；
The retrieval that the retrieval record ordering module is used to be inquired in Data analysis library according to user name records, and by user to each
The attention rate of target object in a retrieval record is ranked up retrieval record, takes a part retrieval record that sequence is forward；
The info push module is used for the characteristic value of the target object in the retrieval record according to selection, and related information recommends library
In relevant information and be pushed to user.
9. the user based on Multidimensional Awareness data pays close attention to information intelligent recommender system as claimed in claim 8, which is characterized in that
The retrieval record ordering module is specifically used for:
Retrieval record is ranked up with the rule of retrieval number descending from the near to the distant according to retrieval time, it is forward to obtain sequence
M1 item retrieval record；
The user attention rate Q that each target object of above-mentioned M1 item retrieval record is calculated by attention-degree analysis model, according to
Family attention rate Q descending is ranked up this M1 item retrieval record, and takes the M2 item retrieval record for sorting forward again.
10. the user based on Multidimensional Awareness data pays close attention to information intelligent recommender system as claimed in claim 9, feature exists
In the attention-degree analysis model are as follows:
Wherein DNNumber of days for the time interval current time of last time searched targets object is poor, NNFor the retrieval time of target object
Number, S is coefficient.
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