CN111708821B - Method, device and storage medium for determining personnel intimacy - Google Patents
Method, device and storage medium for determining personnel intimacy Download PDFInfo
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Abstract
The invention provides a method and a device for determining personnel intimacy and a storage medium. The method comprises the following steps: determining one or more sensitivity levels corresponding to data features between a target person and a person to be detected, wherein the sensitivity levels are improved along with the increase of the influence degree of the data features on the affinity; determining the grade weight of each sensitivity grade according to the number of the data characteristics corresponding to each sensitivity grade in one or more sensitivity grades; and determining the intimacy between the target personnel and the personnel to be detected according to the data characteristics between the target personnel and the personnel to be detected and the grade weights of one or more sensitive grades corresponding to the data characteristics. The invention solves the problem that the determination of personnel affinity is not accurate enough, thereby achieving the effect of accurately analyzing the personnel affinity.
Description
Technical Field
The present invention relates to the field of data mining, and in particular, to a method and apparatus for determining personnel affinity, and a storage medium.
Background
The control of the intimacy between personnel has a very important role in the development of public safety management.
At present, in the aspect of personnel intimacy calculation based on public safety data, a machine learning method or a rule-based method is mainly adopted for calculating intimacy among personnel aiming at behavior feature data such as liveness, classmates and the like in the public safety data.
However, the sensitivity of the influence of different behavioral characteristics on the affinity of the person is actually different among the persons of the subject, and the determination of the affinity of the person is not accurate in the related art.
Disclosure of Invention
The embodiment of the invention provides a method and a device for determining personnel affinity and a storage medium, which are used for at least solving the problem that the determination of the personnel affinity is not accurate enough in the related technology.
According to an embodiment of the present invention, there is provided a method for determining a person's affinity, including: determining one or more sensitivity levels corresponding to data features between a target person and a person to be detected, wherein the sensitivity levels are improved along with the increase of the influence degree of the data features on the affinity; determining the grade weight of each sensitivity grade according to the number of the data characteristics corresponding to each sensitivity grade in one or more sensitivity grades; and determining the intimacy between the target personnel and the personnel to be detected according to the data characteristics between the target personnel and the personnel to be detected and the grade weights of one or more sensitive grades corresponding to the data characteristics.
In at least one exemplary embodiment, before determining the one or more sensitivity levels corresponding to the data characteristics between the target person and the person to be detected, the method further includes: all supported types of data features are classified into a plurality of sensitivity levels according to the sensitivity level of the influence of the different types of data features on the affinity, wherein the plurality of sensitivity levels comprise the one or more sensitivity levels.
In at least one exemplary embodiment, determining the class weight for each sensitivity class according to the number of data features corresponding to each sensitivity class of the one or more sensitivity classes includes: determining a basic weight according to the number of the data features corresponding to each of one or more sensitivity levels; and determining the grade weight of each sensitivity grade according to the basic weight and the number of the data features corresponding to each sensitivity grade.
In at least one exemplary embodiment, determining the base weight according to the number of data features corresponding to each of the one or more sensitivity levels includes: the basis weight W is determined according to the following formula:
degree＝N 1 W+N 2 N 1 W+N 3 N 2 N 1 W+…+N K N K-1 N K-2 W...N 1 w, wherein the degree is a preset affinity normalization value, N i And K is the total number of the one or more sensitivity levels, and i is less than or equal to K.
In at least one exemplary embodiment, determining the class weight of each sensitivity class according to the base weight and the number of data features corresponding to each sensitivity class includes: determining a level weight W of an ith sensitivity level from low to high i ＝N i *...*N 1 * W, where N j And for the number of the data features corresponding to the ith sensitivity level, i is less than or equal to K, wherein K is the total number of the one or more sensitivity levels.
In at least one exemplary embodiment, determining the intimacy between the target person and the person to be detected according to the data characteristics between the target person and the person to be detected and the grade weights of one or more sensitivity grades corresponding to the data characteristics includes: for each data characteristic between the target person and the person to be detected, determining a intimacy value corresponding to the data characteristic according to the category to which the data characteristic belongs and the grade weight of the sensitivity grade corresponding to the data characteristic; and merging the intimacy values corresponding to each data characteristic to determine the intimacy between the target personnel and the personnel to be detected.
In at least one exemplary embodiment, for each data feature between the target person and the person to be detected, determining, according to a class to which the data feature belongs and a class weight of a sensitivity class corresponding to the data feature, an affinity value corresponding to the data feature includes: for each data feature between the target person and the person to be detected, determining a corresponding intimacy value of the data feature by using a first intimacy formula or a second intimacy formula according to the category of the data feature, wherein the first intimacy formula is used for determining the corresponding intimacy value of the data feature when the category of the data feature is deterministic, and the second intimacy formula is used for determining the corresponding intimacy value of the data feature when the category of the data feature is non-deterministic; the first affinity formula is: c=a×w c Wherein C is the affinity value corresponding to the data feature, A is the influence constant corresponding to the data feature, W c A grade weight of the sensitive grade corresponding to the data characteristic; the second affinity formula is: c= (1-1/m) W c Wherein C is the intimacy value corresponding to the data feature, m is the occurrence frequency of the uncertain behavior corresponding to the data feature, W c And the grade weight of the sensitivity grade corresponding to the data characteristic is given.
In at least one exemplary embodiment, the impact constant a corresponding to the data feature increases as the degree of impact of the deterministic relationship expressed by the data feature on the affinity increases.
In at least one exemplary embodiment, combining the affinity value corresponding to each data feature to determine the affinity between the target person and the person to be detected includes: and adding the intimacy value corresponding to each data characteristic, and determining the added result as intimacy between the target person and the person to be detected.
In at least one exemplary embodiment, after determining the intimacy between the target person and the person to be detected according to the data characteristics between the target person and the person to be detected and the grade weights of one or more sensitivity grades corresponding to the data characteristics, the method further includes: and screening, sorting, displaying and/or reporting the information of the personnel to be detected according to the intimacy between the target personnel and the personnel to be detected.
In at least one exemplary embodiment, the screening, sorting, displaying and/or reporting the information of the person to be detected according to the affinity between the target person and the person to be detected includes at least one of: screening the information of the personnel to be detected according to the intimacy between the target personnel and the personnel to be detected, and determining target associated personnel, wherein the target associated personnel comprise: the intimacy degree of the person to be detected is higher than a preset threshold value, or the person to be detected ranked in the top N positions of the intimacy degree of the person to be detected is ranked, wherein N is a positive integer; sorting the information of the personnel to be detected according to the intimacy between the target personnel and the personnel to be detected to obtain a personnel list, wherein the personnel list is arranged according to the intimacy descending order; controlling and displaying the intimacy between the target personnel and the personnel to be detected; and uploading the intimacy information between the target personnel and the personnel to be detected to a management platform.
According to another embodiment of the present invention, there is provided a person affinity determining apparatus including: the sensitivity level determining module is used for determining one or more sensitivity levels corresponding to the data characteristics between the target person and the person to be detected, wherein the sensitivity levels are improved along with the increase of the influence degree of the data characteristics on the affinity; the weight determining module is used for determining the grade weight of each sensitive grade according to the number of the data features corresponding to each sensitive grade in one or more sensitive grades; and the affinity determining module is used for determining the affinity between the target personnel and the personnel to be detected according to the data characteristics between the target personnel and the personnel to be detected and the grade weights of one or more sensitive grades corresponding to the data characteristics.
In at least one example embodiment, the apparatus further comprises: and the sensitivity level classification module is used for classifying all the supported data features into a plurality of sensitivity levels according to the sensitivity degree of the influence of the data features of different types on the intimacy, wherein the plurality of sensitivity levels comprise the one or more sensitivity levels.
In at least one example embodiment, the weight determination module includes: the basic weight determining unit is used for determining basic weights according to the number of the data features corresponding to each of one or more sensitivity levels; and the grade weight determining unit is used for determining the grade weight of each sensitive grade according to the basic weight and the number of the data features corresponding to each sensitive grade.
In at least one example embodiment, the affinity determination module includes: the single affinity determining unit is used for determining an affinity value corresponding to each data characteristic between the target person and the person to be detected according to the category to which the data characteristic belongs and the grade weight of the sensitive grade corresponding to the data characteristic; and the intimacy combining and determining unit is used for combining intimacy values corresponding to each data characteristic so as to determine intimacy between the target personnel and the personnel to be detected.
In at least one example embodiment, the apparatus further comprises: and the processing module is used for screening, sorting, displaying and/or reporting the information of the personnel to be detected according to the intimacy between the target personnel and the personnel to be detected.
According to a further embodiment of the invention, there is also provided a storage medium having stored therein a computer program, wherein the computer program is arranged to perform the steps of any of the method embodiments described above when run.
According to a further embodiment of the invention there is also provided a data analysis device comprising a memory having stored therein a computer program and a processor arranged to run the computer program to perform the steps of any of the method embodiments described above.
According to the invention, one or more sensitive grades corresponding to the data characteristics between the target personnel and the personnel to be detected are determined, the grade weight of each sensitive grade is determined according to the quantity of the data characteristics corresponding to each sensitive grade in the one or more sensitive grades, and the intimacy between the target personnel and the personnel to be detected is determined according to the data characteristics between the target personnel and the personnel to be detected and the grade weight of the one or more sensitive grades corresponding to the data characteristics. Because the influence of the characteristic data of different sensitivity levels on the actual intimacy is different, the intimacy between the personnel is determined according to the sensitivity level and the weight, the problem that the determination of the intimacy of the personnel is not accurate enough can be solved, and more reasonable and accurate personnel intimacy analysis and calculation are realized.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiments of the invention and together with the description serve to explain the invention and do not constitute a limitation on the invention. In the drawings:
FIG. 1 is a flow chart of a method of determining personal affinity according to embodiment 1 of the present invention;
fig. 2 is a block diagram of the configuration of a person affinity determination device according to embodiment 2 of the present invention;
fig. 3 is a first exemplary structural block diagram of a person affinity determination device according to embodiment 2 of the present invention;
fig. 4 is a second exemplary structural block diagram of a person affinity determination device according to embodiment 2 of the present invention;
fig. 5 is a third exemplary structural block diagram of a person affinity determination device according to embodiment 2 of the present invention;
fig. 6 is a fourth exemplary structural block diagram of a person affinity determination device according to embodiment 2 of the present invention;
fig. 7 is a process flow chart of a method of determining personal affinity according to embodiment 4 of the present invention.
Detailed Description
The invention will be described in detail hereinafter with reference to the drawings in conjunction with embodiments. It should be noted that, in the case of no conflict, the embodiments and features in the embodiments may be combined with each other.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order.
Example 1
In this embodiment, a method for determining a person's intimacy is provided, fig. 1 is a flowchart of a method for determining a person's intimacy according to embodiment 1 of the present invention, as shown in fig. 1, the flowchart includes the steps of:
step S102, determining one or more sensitivity levels corresponding to data features between a target person and a person to be detected, wherein one or more data features exist between the target person and the person to be detected, each data feature corresponds to one sensitivity level, and the sensitivity level is improved along with the increase of the influence degree of the data features on the affinity;
step S104, determining the grade weight of each sensitive grade according to the number of the data characteristics corresponding to each sensitive grade in one or more sensitive grades;
and step S106, determining the intimacy between the target personnel and the personnel to be detected according to the data characteristics between the target personnel and the personnel to be detected and the grade weights of one or more sensitive grades corresponding to the data characteristics.
Through the steps, one or more sensitive grades corresponding to the data characteristics between the target personnel and the personnel to be detected are determined, the grade weight of each sensitive grade is determined according to the quantity of the data characteristics corresponding to each sensitive grade in the one or more sensitive grades, and the intimacy between the target personnel and the personnel to be detected is determined according to the data characteristics between the target personnel and the personnel to be detected and the grade weight of the one or more sensitive grades corresponding to the data characteristics. Because the influence of the characteristic data of different sensitivity levels on the actual intimacy is different, the intimacy between the personnel is determined according to the sensitivity level and the weight, the problem that the determination of the intimacy of the personnel is not accurate enough can be solved, and more reasonable and accurate personnel intimacy analysis and calculation are realized.
Alternatively, the execution subject of the above steps may be a data analysis device, a data server, a data analysis platform, or the like, but is not limited thereto.
In at least one exemplary embodiment, before step S102, the method may further include:
all supported types of data features are classified into a plurality of sensitivity levels according to the sensitivity level of the influence of the different types of data features on the affinity, wherein the plurality of sensitivity levels comprise the one or more sensitivity levels.
By the method, various data features supported by the system can be divided into corresponding sensitivity levels according to the sensitivity degree of the influence of the data features on the affinity, so that the calculation of the affinity is convenient.
In at least one exemplary embodiment, step S104 may include:
step S1041, determining a basic weight according to the number of the data features corresponding to each of the one or more sensitivity levels.
In at least one exemplary embodiment, step S1041 may include: the basis weight W is determined according to the following formula:
degree＝N 1 W+N 2 N 1 W+N 3 N 2 N 1 W+…+N K N K-1 N K-2 W...N 1 w, wherein the degree is a preset affinity normalization value, N i And K is the total number of the one or more sensitivity levels, and i is less than or equal to K.
Step S1042, determining a level weight of each sensitivity level according to the basic weight and the number of the data features corresponding to each sensitivity level.
In at least one exemplary embodiment, step S1042 may include: determining a level weight W of an ith sensitivity level from low to high i ＝N i *...*N 1 * W, where N i And for the number of the data features corresponding to the ith sensitivity level, i is less than or equal to K, wherein K is the total number of the one or more sensitivity levels.
In at least one exemplary embodiment, step S106 may include:
step S1061, for each data feature between the target person and the person to be detected, determining an affinity value corresponding to the data feature according to the class to which the data feature belongs and the class weight of the sensitivity class corresponding to the data feature.
In at least one exemplary embodiment, step S1061 may include:
for each data feature between the target person and the person to be detected, determining a corresponding affinity value of the data feature by using a first affinity formula or a second affinity formula according to the category of the data feature, wherein the first affinity formula is used for determining the corresponding affinity value of the data feature when the category of the data feature is deterministic, and the second affinity formula is used for determining the corresponding affinity value of the data feature when the category of the data feature is non-deterministic.
The first affinity formula may be: c=a×w c Wherein C is the affinity value corresponding to the data feature, A is the influence constant corresponding to the data feature, W c And the grade weight of the sensitivity grade corresponding to the data characteristic is given. In at least one exemplary embodiment, the impact constant a corresponding to the data feature increases as the degree of impact of the deterministic relationship expressed by the data feature on the affinity increases.
The second affinity formula may be: c= (1-1/m) W c Wherein C is the intimacy value corresponding to the data feature, m is the occurrence frequency of the uncertain behavior corresponding to the data feature, W c And the grade weight of the sensitivity grade corresponding to the data characteristic is given.
Step S1062, merging the affinity values corresponding to each data feature to determine the affinity between the target person and the person to be detected.
In at least one exemplary embodiment, step S1062 may include:
and adding the intimacy value corresponding to each data characteristic, and determining the added result as intimacy between the target person and the person to be detected.
After step S106, it may further include:
and step S108, screening, sorting, displaying and/or reporting the information of the personnel to be detected according to the intimacy between the target personnel and the personnel to be detected.
In at least one example embodiment, step S108 may include at least one of:
step S1081, screening the information of the person to be detected according to the intimacy between the target person and the person to be detected, and determining a target associated person, where the target associated person includes: and the intimacy degree of the person to be detected is higher than a preset threshold value, or the person to be detected ranked in the top N positions of the intimacy degree of the person to be detected, wherein N is a positive integer. For example, the method can be applied to the aspect of investigation of important persons, for example, the information of travel, relatives and the like of the important persons is utilized for the important persons, the affinity between the important persons and surrounding related persons is calculated by using the affinity calculation method of the embodiment, and the persons with higher affinity to the important persons are provided for public safety management institutions for reference.
Step S1082, sorting the information of the personnel to be detected according to the intimacy degree between the target personnel and the personnel to be detected, and obtaining a personnel list, wherein the personnel list is arranged according to the intimacy degree descending order. For example, the method can be applied to public safety data processing, based on a personnel database, the intimacy degree between the personnel and surrounding related personnel is calculated by using the intimacy degree calculation method of the embodiment according to the information of travel, relatives and the like of important attention personnel provided by a public safety management organization, and the intimacy degree calculation result is provided for the public safety management organization for reference.
Step S1083, controlling and displaying the intimacy between the target person and the person to be detected. For example, the method can be applied to public safety data processing, based on a personnel database, the intimacy degree between the personnel and surrounding related personnel is calculated by using the intimacy degree calculation method of the embodiment according to the information of travel, relatives and the like of important attention personnel provided by a public safety management organization, and the intimacy degree calculation result is displayed on a screen.
And step S1084, uploading the intimacy information between the target personnel and the personnel to be detected to a management platform. For example, the method can be applied to public safety data processing, based on a personnel database, aiming at important attention personnel provided by a public safety management organization, the intimacy degree calculation method of the embodiment is used for calculating the intimacy degree between the personnel and surrounding related personnel by utilizing information such as travel, relatives and the like of the personnel, and the intimacy degree calculation result is uploaded to a management platform for reference of the whole public safety management system.
From the description of the above embodiments, it will be clear to a person skilled in the art that the method according to the above embodiments may be implemented by means of software plus the necessary general hardware platform, but of course also by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) comprising instructions for causing a terminal device (which may be a mobile phone, a computer, a server, or a network device, etc.) to perform the method according to the embodiments of the present invention.
Example 2
In this embodiment, a device for determining personnel affinity is further provided, and the device is used to implement the foregoing embodiments and preferred embodiments, and is not described in detail. As used below, the term "module" may be a combination of software and/or hardware that implements a predetermined function. While the means described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware, is also possible and contemplated.
Fig. 2 is a block diagram of a person's intimacy determination device according to embodiment 2 of the invention, which device, as shown in fig. 2, includes:
the sensitivity level determining module 22 is configured to determine one or more sensitivity levels corresponding to data features between a target person and a person to be detected, where one or more data features exist between the target person and the person to be detected, and each data feature corresponds to one sensitivity level, and the sensitivity level increases as the influence degree of the data feature on the affinity increases;
a weight determining module 24, configured to determine a class weight of each sensitivity class according to the number of data features corresponding to each sensitivity class in the one or more sensitivity classes;
And the affinity determining module 26 is configured to determine the affinity between the target person and the person to be detected according to the data feature between the target person and the person to be detected and the grade weight of one or more sensitivity grades corresponding to the data feature.
By the device, one or more sensitive grades corresponding to the data characteristics between the target person and the person to be detected are determined, the grade weight of each sensitive grade is determined according to the number of the data characteristics corresponding to each sensitive grade in the one or more sensitive grades, and the intimacy between the target person and the person to be detected is determined according to the data characteristics between the target person and the person to be detected and the grade weight of the one or more sensitive grades corresponding to the data characteristics. Because the influence of the characteristic data of different sensitivity levels on the actual intimacy is different, the intimacy between the personnel is determined according to the sensitivity level and the weight, the problem that the determination of the intimacy of the personnel is not accurate enough can be solved, and more reasonable and accurate personnel intimacy analysis and calculation are realized.
Alternatively, the above-described apparatus may be provided to a data analysis device, such as a data server, a data analysis platform, or the like, but is not limited thereto.
Fig. 3 is a first exemplary structural block diagram of a person affinity determination device according to embodiment 2 of the present invention, as shown in fig. 3, and in at least one exemplary embodiment, the device further includes:
the sensitivity level classification module 32 is configured to classify all supported types of data features into a plurality of sensitivity levels according to the sensitivity level of the influence of the different types of data features on the affinity, where the plurality of sensitivity levels includes the one or more sensitivity levels.
By the device, various data features supported by the system can be divided into corresponding sensitivity levels according to the sensitivity degree of the influence of the data features on the affinity, so that the calculation of the affinity is convenient.
Fig. 4 is a second exemplary structural block diagram of a person affinity determination device according to embodiment 2 of the present invention, as shown in fig. 4, in at least one exemplary embodiment, the weight determination module 24 includes:
the base weight determining unit 242 is configured to determine a base weight according to the number of data features corresponding to each of the one or more sensitivity levels.
In at least one exemplary embodiment, the basis weight determining unit 242 may determine the basis weight W according to the following formula:
degree＝N 1 W+N 2 N 1 W+N 3 N 2 N 1 W+…+N K N K-1 N K-2 W...N 1 w, wherein the degree is a preset affinity normalization value, N i And K is the total number of the one or more sensitivity levels, and i is less than or equal to K.
The level weight determining unit 244 is configured to determine a level weight of each sensitivity level according to the base weight and the number of data features corresponding to each sensitivity level.
In at least one example embodiment, the rank weight determination unit 244 may determine the rank weight W for the i-th sensitivity rank from low to high i ＝N i *...*N 1 * W, where N i And for the number of the data features corresponding to the ith sensitivity level, i is less than or equal to K, wherein K is the total number of the one or more sensitivity levels.
Fig. 5 is a third exemplary structural block diagram of a person affinity determination device according to embodiment 2 of the present invention, as shown in fig. 5, in at least one exemplary embodiment, the affinity determination module 26 includes: a single affinity determination unit 262 and an affinity merge determination unit 264.
And a single-item affinity determining unit 262, configured to determine, for each data feature between the target person and the person to be detected, an affinity value corresponding to the data feature according to a class to which the data feature belongs and a class weight of a sensitivity class corresponding to the data feature.
In at least one exemplary embodiment, the single item affinity determination unit 262 may perform the following operations:
for each data feature between the target person and the person to be detected, determining a corresponding affinity value of the data feature by using a first affinity formula or a second affinity formula according to the category of the data feature, wherein the first affinity formula is used for determining the corresponding affinity value of the data feature when the category of the data feature is deterministic, and the second affinity formula is used for determining the corresponding affinity value of the data feature when the category of the data feature is non-deterministic.
The first affinity formula may be: c=a×w c Wherein C is the affinity value corresponding to the data feature, A is the influence constant corresponding to the data feature, W c And the grade weight of the sensitivity grade corresponding to the data characteristic is given. In at least one exemplary embodiment, the impact constant a corresponding to the data feature increases as the degree of impact of the deterministic relationship expressed by the data feature on the affinity increases.
The second affinity formula may be: c= (1-1/m) W c Wherein C is the intimacy value corresponding to the data feature, m is the occurrence frequency of the uncertain behavior corresponding to the data feature, W c And the grade weight of the sensitivity grade corresponding to the data characteristic is given.
And an affinity combination determining unit 264, configured to combine the affinity values corresponding to each data feature to determine the affinity between the target person and the person to be detected.
In at least one exemplary embodiment, the affinity combination determination unit 264 may add the affinity values corresponding to each data feature, and determine the result of the addition as the affinity between the target person and the person to be detected.
Fig. 6 is a fourth exemplary structural block diagram of a person affinity determination device according to embodiment 2 of the present invention, as shown in fig. 6, and in at least one exemplary embodiment, the device may further include:
And the processing module 62 is configured to screen, sort, display and/or report the information of the personnel to be detected according to the intimacy between the target personnel and the personnel to be detected.
In at least one example embodiment, the processing module 62 may be configured to perform at least one of:
(1) Screening the information of the personnel to be detected according to the intimacy between the target personnel and the personnel to be detected, and determining target associated personnel, wherein the target associated personnel comprise: and the intimacy degree of the person to be detected is higher than a preset threshold value, or the person to be detected ranked in the top N positions of the intimacy degree of the person to be detected, wherein N is a positive integer. For example, the method can be applied to the aspect of investigation of important persons, for example, the information of travel, relatives and the like of the important persons is utilized for the important persons, the affinity between the important persons and surrounding related persons is calculated by using the affinity calculation method of the embodiment, and the persons with higher affinity to the important persons are provided for public safety management institutions for reference.
(2) And ordering the information of the personnel to be detected according to the intimacy between the target personnel and the personnel to be detected to obtain a personnel list, wherein the personnel list is arranged according to the intimacy descending order. For example, the method can be applied to public safety data processing, based on a personnel database, the intimacy degree between the personnel and surrounding related personnel is calculated by using the intimacy degree calculation method of the embodiment according to the information of travel, relatives and the like of important attention personnel provided by a public safety management organization, and the intimacy degree calculation result is provided for the public safety management organization for reference.
(3) And controlling and displaying the intimacy between the target personnel and the personnel to be detected. For example, the method can be applied to public safety data processing, based on a personnel database, the intimacy degree between the personnel and surrounding related personnel is calculated by using the intimacy degree calculation method of the embodiment according to the information of travel, relatives and the like of important attention personnel provided by a public safety management organization, and the intimacy degree calculation result is displayed on a screen.
(4) And uploading the intimacy information between the target personnel and the personnel to be detected to a management platform. For example, the method can be applied to public safety data processing, based on a personnel database, aiming at important attention personnel provided by a public safety management organization, the intimacy degree calculation method of the embodiment is used for calculating the intimacy degree between the personnel and surrounding related personnel by utilizing information such as travel, relatives and the like of the personnel, and the intimacy degree calculation result is uploaded to a management platform for reference of the whole public safety management system.
It should be noted that each of the above modules may be implemented by software or hardware, and for the latter, it may be implemented by, but not limited to: the modules are all located in the same processor; alternatively, the above modules may be located in different processors in any combination.
Example 3
An embodiment of the invention also provides a storage medium having a computer program stored therein, wherein the computer program is arranged to perform the steps of any of the method embodiments described above when run.
Alternatively, in the present embodiment, the above-described storage medium may be configured to store a computer program for performing the steps of:
step S1, determining one or more sensitivity levels corresponding to data features between a target person and a person to be detected, wherein one or more data features exist between the target person and the person to be detected, each data feature corresponds to one sensitivity level, and the sensitivity level is improved along with the increase of the influence degree of the data features on the affinity;
step S2, determining the grade weight of each sensitive grade according to the number of the data features corresponding to each sensitive grade in one or more sensitive grades;
and step S3, determining the intimacy between the target personnel and the personnel to be detected according to the data characteristics between the target personnel and the personnel to be detected and the grade weights of one or more sensitive grades corresponding to the data characteristics.
Alternatively, in the present embodiment, the storage medium may include, but is not limited to: a usb disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a removable hard disk, a magnetic disk, or an optical disk, or other various media capable of storing a computer program.
An embodiment of the invention also provides a data analysis device comprising a memory having stored therein a computer program and a processor arranged to run the computer program to perform the steps of any of the method embodiments described above.
Optionally, the electronic apparatus may further include a transmission device and an input/output device, where the transmission device is connected to the processor, and the input/output device is connected to the processor.
Alternatively, in the present embodiment, the above-described processor may be configured to execute the following steps by a computer program:
step S1, determining one or more sensitivity levels corresponding to data features between a target person and a person to be detected, wherein one or more data features exist between the target person and the person to be detected, each data feature corresponds to one sensitivity level, and the sensitivity level is improved along with the increase of the influence degree of the data features on the affinity;
Step S2, determining the grade weight of each sensitive grade according to the number of the data features corresponding to each sensitive grade in one or more sensitive grades;
and step S3, determining the intimacy between the target personnel and the personnel to be detected according to the data characteristics between the target personnel and the personnel to be detected and the grade weights of one or more sensitive grades corresponding to the data characteristics.
Alternatively, specific examples in this embodiment may refer to examples described in the foregoing embodiments and optional implementations, and this embodiment is not described herein.
Example 4
This embodiment describes the processing procedure of the affinity determination scheme in detail taking the example that the data characteristics include "parent, spouse, brother" and "simultaneous travel".
According to the scheme, information such as parents, spouse, family and the like contained in public safety data is classified into sensitivity grades, specific weights are respectively given to the data with different sensitivity grades, so that the influence degree of the data with low sensitivity grades on the final affinity is smaller than that of the data with high sensitivity grades on the final affinity, and the affinity between two main personnel is calculated according to the weights of the data with different sensitivity grades between the two main personnel.
Fig. 7 is a process flow chart of a method for determining personal affinity according to embodiment 4 of the present invention, as shown in fig. 7, the rule-based public safety data personal affinity determination method includes the steps of:
step S701, public safety data sensitivity degree division. And grading the data characteristics of spouse, parents, family users, group users, peer, internet surfing and the like contained in the public safety data according to the sensitivity degree.
Step S702, basic weight calculation. Dividing public safety data into K grades according to the sensitivity degree, wherein each grade comprises N data characteristics, the basic weight is W, and the intimacy between two main personnel can be described as
degree＝N 1 W+N 2 N 1 W+N 3 N 2 N 1 W+…+N K N K-1 N K-2 W...N 1 W (1)
The above formula is made to be equal to the normalized value of the affinity (1 is taken in the embodiment), and the basic weight W is obtained by solving.
Step S703, each rank weight is calculated. The weight of each level is set to be the product of the number of data features contained in the current level and all the number of data features contained below the current level, multiplied by the base weight, e.gThe current level is level 3, comprising a data features, and levels 2 and 1 below the current level comprise, b and 1, respectively c And the weight of the current grade is a, b, c and W.
In step S704, final affinity is calculated by integrating public safety data features, where public safety data includes deterministic relationships such as parent relationship and couple relationship, and non-deterministic relationships such as travel-like and online-like, where deterministic relationships are set to different constants according to the influence degree on affinity, for example, parent-couple relationship is set to 1, family-family relationship is set to 0.8, family-family relationship is set to 0.6, where each constant value is required to be determined according to specific data, non-deterministic relationship takes a number of times, for example, M times the travel-like in N days, where constant value set by deterministic relationship is directly multiplied by weight of corresponding level, non-deterministic relationship takes a difference value of reciprocal and 1 multiplied by weight of corresponding level, for example, the same-line relationship is performed 3 times in N days, and corresponding weight is 0.6, and then its value is 0.6 (1-1/3). And calculating the intimacy value corresponding to each data characteristic by the method.
Step S705, summing the affinity values corresponding to each data feature as a final affinity value.
Based on the above method, for easy understanding, this embodiment takes the public security data including the characteristics of parents, spouse, brothers and co-travel data as an example, and the scheme will be described in detail based on practical examples.
Step S701', public safety data sensitivity degree division. The data features are classified according to the sensitivity level, and the data features are classified into parent, spouse and brother grades and the same trip grade sequentially from high to low.
Step S702', basic weight calculation. Dividing the public safety data features into 2 level layers, wherein each level layer from high to low comprises 3 and 1 data features, and solving the formula 1 to obtain the basic weight of 1/4.
Step S703', each rank weight is calculated. The weight of the "simultaneous going" rank is that the data feature number contained in the rank is multiplied by the basic weight, i.e., 1*1/3=1/3, and the weight of the "parent, partner, sibling" rank is that the product of the data feature number 3 contained in the rank and the data feature number 1 contained in the "simultaneous going" rank lower than the rank is multiplied by the basic weight, i.e., 3×1×1/3=1.
Steps S704'-S705' integrate public safety data features. The value of the two main body personnel is set to be 1 if the two main body personnel are in parent, spouse and brother relations, otherwise, the value is set to be 0, and assuming that the two main body personnel a and b travel together for 2 times in N days and are in spouse relations, the affinity value of the 'same travel' grade is 1/3 (1-1/2) =1/6, the affinity of the 'parent, spouse and brother' grade is 1*1 =1, and the final affinity value of the a and b is 1/6+1=7/6; assuming that two subject persons c and d are likewise traveling 2 times within N days, the "same travel" rating has an affinity value of 1/3 x (1-1/2) =1/6, not one of the parent, spouse, sibling relationships, and the "parent, spouse, sibling" rating has an affinity of 1*0 =0, with a final affinity value between c and d of 1/6+0 =1/6.
The scheme provides that information such as parents, spouse, family, group user and the like contained in public safety data are subjected to sensitivity grading, and the intimacy between two main body personnel is calculated according to the interaction degree of different sensitivity grade data between the two main body personnel.
It will be appreciated by those skilled in the art that the modules or steps of the invention described above may be implemented in a general purpose computing device, they may be concentrated on a single computing device, or distributed across a network of computing devices, they may alternatively be implemented in program code executable by computing devices, so that they may be stored in a memory device for execution by computing devices, and in some cases, the steps shown or described may be performed in a different order than that shown or described, or they may be separately fabricated into individual integrated circuit modules, or multiple modules or steps within them may be fabricated into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.
The above description is only of the preferred embodiments of the present invention and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the principle of the present invention should be included in the protection scope of the present invention.
Claims (11)
1. A method for determining personal affinity, comprising:
determining one or more sensitivity levels corresponding to data features between a target person and a person to be detected, wherein the sensitivity levels are improved along with the increase of the influence degree of the data features on the affinity;
determining the grade weight of each sensitivity grade according to the number of the data characteristics corresponding to each sensitivity grade in one or more sensitivity grades;
determining the intimacy between the target person and the person to be detected according to the data characteristics between the target person and the person to be detected and the grade weights of one or more sensitive grades corresponding to the data characteristics;
wherein, according to the data characteristics between the target person and the person to be detected and the grade weights of one or more sensitive grades corresponding to the data characteristics, determining the intimacy between the target person and the person to be detected includes: for each data feature between the target person and the person to be detected, determining a corresponding intimacy value of the data feature by using a first intimacy formula or a second intimacy formula according to the category of the data feature, wherein the first intimacy formula is used for determining the corresponding intimacy value of the data feature when the category of the data feature is deterministic, and the second intimacy formula is used for determining the corresponding intimacy value of the data feature when the category of the data feature is non-deterministic; combining the intimacy values corresponding to each data characteristic to determine the intimacy between the target personnel and the personnel to be detected;
Wherein the first parentThe density formula is: c=a×w c Wherein C is the affinity value corresponding to the data feature, A is the influence constant corresponding to the data feature, W c A grade weight of the sensitive grade corresponding to the data characteristic;
wherein, the second affinity formula is: c= (1-1/m) W c Wherein C is the intimacy value corresponding to the data feature, m is the occurrence frequency of the uncertain behavior corresponding to the data feature, W c And the grade weight of the sensitivity grade corresponding to the data characteristic is given.
2. The method of claim 1, further comprising, prior to determining the one or more sensitivity levels corresponding to the data characteristics between the target person and the person to be detected:
all supported types of data features are classified into a plurality of sensitivity levels according to the sensitivity level of the influence of the different types of data features on the affinity, wherein the plurality of sensitivity levels comprise the one or more sensitivity levels.
3. The method of claim 1, wherein determining the class weight for each sensitivity class based on the number of data features corresponding to each sensitivity class of the one or more sensitivity classes comprises:
Determining a basic weight according to the number of the data features corresponding to each of one or more sensitivity levels;
and determining the grade weight of each sensitivity grade according to the basic weight and the number of the data features corresponding to each sensitivity grade.
4. A method according to claim 3, wherein determining the basis weight based on the number of data features corresponding to each of the one or more sensitivity levels comprises:
the basis weight W is determined according to the following formula:
degree＝N 1 W+N 2 N 1 W+N 3 N 2 N 1 W+…+N K N K-1 N K-2 W…N 1 w, wherein,
the degree is a preset intimacy normalization value, N i And K is the total number of the one or more sensitivity levels, and i is less than or equal to K.
5. A method according to claim 3, wherein determining the class weight for each sensitivity class based on the base weight and the number of data features to which each sensitivity class corresponds comprises:
determining a level weight W of an ith sensitivity level from low to high i ＝N i *…*N 1 * W, where N i And for the number of the data features corresponding to the ith sensitivity level, i is less than or equal to K, wherein K is the total number of the one or more sensitivity levels.
6. The method of claim 1, wherein the impact constant a for the data feature increases as the degree of impact of the deterministic relationship expressed by the data feature on intimacy increases.
7. The method of claim 1, wherein combining the affinity value for each data feature to determine the affinity between the target person and the person to be detected comprises:
and adding the intimacy value corresponding to each data characteristic, and determining the added result as intimacy between the target person and the person to be detected.
8. The method according to any one of claims 1-7, wherein after determining the intimacy between the target person and the person to be detected according to the data characteristics between the target person and the person to be detected and the grade weights of one or more sensitivity grades corresponding to the data characteristics, further comprises:
and screening, sorting, displaying and/or reporting the information of the personnel to be detected according to the intimacy between the target personnel and the personnel to be detected.
9. The method of claim 8, wherein the screening, sorting, displaying and/or reporting of the information of the person to be detected based on the affinity between the target person and the person to be detected comprises at least one of:
Screening the information of the personnel to be detected according to the intimacy between the target personnel and the personnel to be detected, and determining target associated personnel, wherein the target associated personnel comprise: the intimacy degree of the person to be detected is higher than a preset threshold value, or the person to be detected ranked in the top N positions of the intimacy degree of the person to be detected is ranked, wherein N is a positive integer;
sorting the information of the personnel to be detected according to the intimacy between the target personnel and the personnel to be detected to obtain a personnel list, wherein the personnel list is arranged according to the intimacy descending order;
controlling and displaying the intimacy between the target personnel and the personnel to be detected;
and uploading the intimacy information between the target personnel and the personnel to be detected to a management platform.
10. A person affinity determination apparatus, comprising:
the sensitivity level determining module is used for determining one or more sensitivity levels corresponding to the data characteristics between the target person and the person to be detected, wherein the sensitivity levels are improved along with the increase of the influence degree of the data characteristics on the affinity;
The weight determining module is used for determining the grade weight of each sensitive grade according to the number of the data features corresponding to each sensitive grade in one or more sensitive grades;
the affinity determining module is used for determining the affinity between the target person and the person to be detected according to the data characteristics between the target person and the person to be detected and the grade weights of one or more sensitive grades corresponding to the data characteristics;
the intimacy determining module is used for determining intimacy between the target person and the person to be detected in the following mode: for each data feature between the target person and the person to be detected, determining a corresponding intimacy value of the data feature by using a first intimacy formula or a second intimacy formula according to the category of the data feature, wherein the first intimacy formula is used for determining the corresponding intimacy value of the data feature when the category of the data feature is deterministic, and the second intimacy formula is used for determining the corresponding intimacy value of the data feature when the category of the data feature is non-deterministic; combining the intimacy values corresponding to each data characteristic to determine the intimacy between the target personnel and the personnel to be detected;
Wherein, the first affinity formula is: c=a×w c Wherein C is the affinity value corresponding to the data feature, A is the influence constant corresponding to the data feature, W c A grade weight of the sensitive grade corresponding to the data characteristic;
wherein, the second affinity formula is: c= (1-1/m) W c Wherein C is the intimacy value corresponding to the data feature, m is the occurrence frequency of the uncertain behavior corresponding to the data feature, W c And the grade weight of the sensitivity grade corresponding to the data characteristic is given.
11. A storage medium having a computer program stored therein, wherein the computer program is arranged to perform the method of any of claims 1 to 9 when run.
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| CN110020025A (en) * | 2017-09-28 | 2019-07-16 | 阿里巴巴集团控股有限公司 | A kind of data processing method and device |
| CN111049988A (en) * | 2019-12-23 | 2020-04-21 | 随手(北京)信息技术有限公司 | Intimacy prediction method, system, equipment and storage medium for mobile equipment |
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| CN110020025A (en) * | 2017-09-28 | 2019-07-16 | 阿里巴巴集团控股有限公司 | A kind of data processing method and device |
| CN109522489A (en) * | 2018-11-27 | 2019-03-26 | 杭州中奥科技有限公司 | The determination method, apparatus and intelligent terminal of personage's cohesion |
| CN111049988A (en) * | 2019-12-23 | 2020-04-21 | 随手(北京)信息技术有限公司 | Intimacy prediction method, system, equipment and storage medium for mobile equipment |
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