CN111708821A - Method and device for determining personnel intimacy and storage medium - Google Patents
Method and device for determining personnel intimacy and storage medium Download PDFInfo
- Publication number
- CN111708821A CN111708821A CN202010568708.2A CN202010568708A CN111708821A CN 111708821 A CN111708821 A CN 111708821A CN 202010568708 A CN202010568708 A CN 202010568708A CN 111708821 A CN111708821 A CN 111708821A
- Authority
- CN
- China
- Prior art keywords
- person
- data
- intimacy
- sensitivity
- detected
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
- G06F16/2465—Query processing support for facilitating data mining operations in structured databases
Landscapes
- Engineering & Computer Science (AREA)
- Databases & Information Systems (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Software Systems (AREA)
- Probability & Statistics with Applications (AREA)
- Mathematical Physics (AREA)
- Computational Linguistics (AREA)
- Data Mining & Analysis (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Fuzzy Systems (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention provides a method and a device for determining the intimacy degree of a person and a storage medium. The method comprises the following steps: 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 intimacy; determining the grade weight of each sensitivity grade according to the quantity of the data characteristics corresponding to each sensitivity grade in one or more sensitivity grades; and 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 weight of one or more sensitivity grades corresponding to the data characteristics. By the method and the device, the problem that the determination of the intimacy degree of the personnel is not accurate enough is solved, and the effect of accurately analyzing the intimacy degree of the personnel is further achieved.
Description
Technical Field
The invention relates to the field of data mining, in particular to a method and a device for determining personnel intimacy and a storage medium.
Background
The control of the intimacy between the persons plays an important role in the development of the work of public safety management.
At present, in the aspect of carrying out personnel intimacy calculation based on public safety data, the intimacy among personnel is mainly calculated by adopting a machine learning method or a rule-based method aiming at behavior characteristic data of the same residence, the same row and the like in the public safety data.
However, the sensitivity of the influence of different behavior characteristics among the subjects on the intimacy degree of the person is actually different, and the determination of the intimacy degree of the person in the related art is not accurate.
Disclosure of Invention
The embodiment of the invention provides a method and a device for determining the intimacy degree of a person and a storage medium, which are used for at least solving the problem that the determination of the intimacy degree of the person in the related technology is not accurate enough.
According to an embodiment of the present invention, there is provided a method for determining human intimacy, including: 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 intimacy; determining the grade weight of each sensitivity grade according to the quantity of the data characteristics corresponding to each sensitivity grade in one or more sensitivity grades; and 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 weight of one or more sensitivity grades corresponding to the data characteristics.
In at least one exemplary embodiment, before determining one or more sensitivity levels corresponding to data characteristics between the target person and the person to be detected, the method further includes: and classifying all supported types of data features into a plurality of sensitivity levels according to the sensitivity degrees of the different types of data features on the influence of intimacy, wherein the plurality of sensitivity levels comprise the one or more sensitivity levels.
In at least one example embodiment, determining a rank weight for each sensitivity level based on the number of data features corresponding to each sensitivity level of the one or more sensitivity levels comprises: determining a basis weight according to the number of the data features corresponding to each sensitivity level in 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 example embodiment, determining the basis weight based on the number of the data features corresponding to each of the one or more sensitivity levels comprises: determining the basis weight W according to the following formula:
degree＝N1W+N2N1W+N3N2N1W+…+NKNK-1NK-2W...N1w, wherein the degree is a preset normalized value of intimacy density, NiAnd 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 example embodiment, determining a level weight for each sensitivity level based on the base weight and the number of data features corresponding to each sensitivity level comprises: determining a level weight W for the ith sensitivity level from low to highi＝Ni*...*N1W, wherein, NjAnd i is less than or equal to K which is the total number of the one or more sensitivity levels corresponding to the number of the data features corresponding to the ith sensitivity level.
In at least one exemplary embodiment, determining the intimacy degree 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 level weight of the one or more sensitivity levels corresponding to the data feature includes: 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 category of the data feature and the level weight of the sensitivity level corresponding to the data feature; and combining the intimacy values corresponding to each data characteristic to determine the intimacy between the target person and the person to be detected.
In at least one exemplary embodiment, for each data feature between the target person and the person to be detected, determining the affinity value corresponding to the data feature according to the category to which the data feature belongs and the level weight of the sensitivity level corresponding to the data feature includes: for each data characteristic between the target person and the person to be detected,determining an affinity value corresponding to the data feature by using a first affinity formula or a second affinity formula according to the category to which the data feature belongs, wherein the affinity value corresponding to the data feature is determined by using the first affinity formula when the category to which the data feature belongs is a deterministic relationship, and the affinity value corresponding to the data feature is determined by using the second affinity formula when the category to which the data feature belongs is a non-deterministic relationship; the first intimacy formula is: c ═ A × WcWherein C is the intimacy value corresponding to the data characteristic, A is the influence constant corresponding to the data characteristic, and WcThe grade weight of the sensitivity grade corresponding to the data characteristic is obtained; the second affinity formula is: c ═ 1-1/m × WcWherein C is the intimacy value corresponding to the data characteristic, m is the occurrence frequency of the non-definite behavior corresponding to the data characteristic, and WcAnd the data characteristics are corresponding to the sensitivity levels of the grade weight.
In at least one exemplary embodiment, the influence constant a corresponding to the data feature increases as the degree of influence of the deterministic relationship expressed by the data feature on the intimacy increases.
In at least one exemplary embodiment, merging the affinity values corresponding to each data feature to determine the affinity between the target person and the person to be detected includes: and adding the intimacy values corresponding to each data characteristic, and determining the added result as the intimacy between the target person and the person to be detected.
In at least one exemplary embodiment, after determining the intimacy degree 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 level weight of the one or more sensitivity levels corresponding to the data feature, the method further includes: and screening, sorting, displaying and/or reporting the information of the personnel to be detected according to the intimacy degree between the target personnel and the personnel to be detected.
In at least one exemplary embodiment, the processing of screening, sorting, displaying and/or reporting the information of the person to be detected according to the intimacy 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 comprises: the affinity with the target person is higher than a preset threshold value, or the affinity with the target person is ranked at the top N positions of the to-be-detected persons, wherein N is a positive integer; sequencing 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 in a descending order; controlling and displaying the intimacy between the target person and the person to be detected; and uploading the intimacy information between the target person and the person to be detected to a management platform.
According to another embodiment of the present invention, there is provided an apparatus for determining intimacy degree of person, 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 intimacy; the weight determining module is used for determining the grade weight of each sensitivity grade according to the number of the data features corresponding to each sensitivity grade in one or more sensitivity grades; and the intimacy determining module is used for 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 weight of one or more sensitivity grades corresponding to the data characteristics.
In at least one example embodiment, the apparatus further comprises: and the sensitivity level dividing module is used for dividing all the supported types of data features into a plurality of sensitivity levels according to the sensitivity degrees of the different types of data features on the influence of intimacy degree, wherein the sensitivity levels comprise 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 a basic weight according to the number of the data features corresponding to each sensitivity level in one or more sensitivity levels; and the grade weight determining unit is used for 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 example embodiment, the affinity determination module includes: the individual intimacy degree determining unit is used for determining an intimacy degree value corresponding to each data feature between the target person and the person to be detected according to the category of the data feature and the grade weight of the sensitivity grade corresponding to the data feature; and the intimacy combining and determining unit is used for combining the intimacy values corresponding to the data characteristics so as to determine the intimacy between the target person and the person 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 degree between the target personnel and the personnel to be detected.
According to a further embodiment of the present invention, there is also provided a storage medium having a computer program stored therein, wherein the computer program is arranged to perform the steps of any of the above method embodiments when executed.
According to yet another embodiment of the present invention, there is also provided a data analysis device, comprising a memory in which a computer program is stored and a processor arranged to run the computer program to perform the steps of any of the above method embodiments.
According to the invention, one or more sensitivity levels corresponding to the data characteristics between the target person and the person to be detected are determined, the level weight of each sensitivity level is determined according to the number of the data characteristics corresponding to each sensitivity level in the one or more sensitivity levels, 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 level weights of the one or more sensitivity levels corresponding to the data characteristics. Because the influence of the characteristic data of different sensitivity levels on the actual intimacy is different, the weight is determined according to the sensitivity levels, and the intimacy between the personnel is determined according to the weight, so that the problem that the determination of the intimacy of the personnel is not accurate enough can be solved, and more reasonable and accurate analysis and calculation of the intimacy of the personnel 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 embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:
fig. 1 is a flowchart of a method of determining human intimacy degree according to embodiment 1 of the present invention;
fig. 2 is a block diagram of the structure of a person intimacy degree determination apparatus according to embodiment 2 of the present invention;
fig. 3 is a first exemplary configuration block diagram of a person intimacy degree determination apparatus according to embodiment 2 of the present invention;
fig. 4 is a second exemplary configuration block diagram of the person intimacy degree determination apparatus according to embodiment 2 of the present invention;
fig. 5 is a third exemplary configuration block diagram of the person intimacy degree determination apparatus according to embodiment 2 of the present invention;
fig. 6 is a fourth exemplary configuration block diagram of the person intimacy degree determination apparatus according to embodiment 2 of the present invention;
fig. 7 is a process flow chart of a method of determining intimacy degree of person according to embodiment 4 of the present invention.
Detailed Description
The invention will be described in detail hereinafter with reference to the accompanying drawings in conjunction with embodiments. It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order.
Example 1
In this embodiment, a method for determining a human intimacy degree is provided, and fig. 1 is a flowchart of a method for determining a human intimacy degree according to embodiment 1 of the present invention, as shown in fig. 1, the flowchart includes the following steps:
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 levels are improved along with the increase of the influence degree of the data features on intimacy;
step S104, determining the grade weight of each sensitivity grade according to the quantity of the data characteristics corresponding to each sensitivity grade in one or more sensitivity grades;
and S106, 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.
Through the steps, one or more sensitivity levels corresponding to the data characteristics between the target person and the person to be detected are determined, the level weight of each sensitivity level is determined according to the number of the data characteristics corresponding to each sensitivity level in the one or more sensitivity levels, 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 level weights of the one or more sensitivity levels corresponding to the data characteristics. Because the influence of the characteristic data of different sensitivity levels on the actual intimacy is different, the weight is determined according to the sensitivity levels, and the intimacy between the personnel is determined according to the weight, so that the problem that the determination of the intimacy of the personnel is not accurate enough can be solved, and more reasonable and accurate analysis and calculation of the intimacy of the personnel are realized.
Optionally, the executing subject of the above steps may be, but is not limited to, a data analysis device, a data server, a data analysis platform, and the like.
In at least one exemplary embodiment, before step S102, the method may further include:
and classifying all supported types of data features into a plurality of sensitivity levels according to the sensitivity degrees of the different types of data features on the influence of intimacy, wherein the plurality of sensitivity levels comprise the one or more sensitivity levels.
By the method, various data characteristics supported by the system can be divided into corresponding sensitivity levels according to the sensitivity of the data characteristics on the influence of the intimacy degree, so that the intimacy degree can be calculated conveniently.
In at least one exemplary embodiment, step S104 may include:
step S1041, determining a basis weight according to the number of the data features corresponding to each sensitivity level in the one or more sensitivity levels.
In at least one exemplary embodiment, step S1041 may include: determining the basis weight W according to the following formula:
degree＝N1W+N2N1W+N3N2N1W+…+NKNK-1NK-2W...N1w, wherein the degree is a preset normalized value of intimacy density, NiAnd K is the total number of the one or more sensitivity levels, and i is less than or equal to K.
Step S1042, 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, step S1042 may include: determining a level weight W for the ith sensitivity level from low to highi＝Ni*...*N1W, wherein, NiAnd i is less than or equal to K which is the total number of the one or more sensitivity levels corresponding to the number of the data features corresponding to the ith sensitivity level.
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 category to which the data feature belongs and the grade weight of the sensitivity grade corresponding to the data feature.
In at least one exemplary embodiment, step S1061 may include:
determining, for each data feature between the target person and the person to be detected, an affinity value corresponding to the data feature by using a first affinity formula or a second affinity formula according to a category to which the data feature belongs, wherein the affinity value corresponding to the data feature is determined by using the first affinity formula when the category to which the data feature belongs is a deterministic relationship, and the affinity value corresponding to the data feature is determined by using the second affinity formula when the category to which the data feature belongs is a non-deterministic relationship.
The first affinity formula may be: c ═ A × WcWherein C is the intimacy value corresponding to the data characteristic, A is the influence constant corresponding to the data characteristic, and WcAnd the data characteristics are corresponding to the sensitivity levels of the grade weight. In at least one exemplary embodiment, the influence constant a corresponding to the data feature increases as the degree of influence of the deterministic relationship expressed by the data feature on the intimacy increases.
The second affinity formula may be: c ═ 1-1/m × WcWherein C is the intimacy value corresponding to the data characteristic, m is the occurrence frequency of the non-definite behavior corresponding to the data characteristic, and WcAnd the data characteristics are corresponding to the sensitivity levels of the grade weight.
Step S1062, merging the intimacy values corresponding to each data feature to determine the intimacy between the target person and the person to be detected.
In at least one exemplary embodiment, step S1062 may include:
and adding the intimacy values corresponding to each data characteristic, and determining the added result as the intimacy between the target person and the person to be detected.
After step S106, the method may further include:
and S108, screening, sorting, displaying and/or reporting the information of the personnel to be detected according to the intimacy degree between the target personnel and the personnel to be detected.
In at least one exemplary embodiment, step S108 may include at least one of:
step S1081, 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 related personnel, wherein the target related personnel comprise: and the intimacy degree of the personnel to be detected with the target personnel is higher than a preset threshold value, or the ranking of the intimacy degree of the personnel to be detected with the target personnel is arranged at the top N, wherein N is a positive integer. For example, the method may be applied to the aspect of examining key-point persons, for example, for key-point persons, the intimacy degree calculation method of the present embodiment is used to calculate the intimacy degree between the key-point persons and the surrounding related persons by using the information of their traveling, relatives, and the like, and the persons with higher intimacy degree with the key-point persons are provided to the public safety management institution for reference.
Step S1082, the information of the personnel to be detected is sequenced according to the intimacy between the target personnel and the personnel to be detected, and a personnel list is obtained, wherein the personnel list is arranged according to the intimacy in a descending order. For example, the method may be applied to public security data processing, based on a personnel database, for a person of major concern provided by a public security management organization, using information of his trip, relatives, and the like, using the intimacy degree calculation method of the present embodiment to calculate intimacy degree between the person and surrounding related persons, and providing the intimacy degree calculation result to the public security management organization for reference.
And S1083, controlling and displaying the intimacy between the target person and the person to be detected. For example, the method may be applied to public safety data processing, based on a personnel database, the intimacy degree between the person and the surrounding related personnel is calculated by using the intimacy degree calculation method of the present embodiment according to the information of the person who is mainly concerned provided by the public safety administration, and the intimacy degree calculation result is displayed on the screen.
And S1084, uploading the intimacy information between the target person and the person to be detected to a management platform. For example, the method may be applied to public security data processing, based on a personnel database, for a key attention person provided by a public security management organization, the intimacy degree between the key attention person and the surrounding related person is calculated by using the intimacy degree calculation method of the present embodiment by using information of travel, relatives, and the like of the key attention person, and the intimacy degree calculation result is uploaded to a management platform for reference use by the whole public security management system.
Through the above description of the embodiments, those skilled in the art can clearly understand that the method according to the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but the former is a better implementation mode in many cases. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (e.g., ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, or a network device) to execute the method according to the embodiments of the present invention.
Example 2
In this embodiment, a device for determining the intimacy degree of a person is also provided, and the device is used to implement the foregoing embodiments and preferred embodiments, and the description of the device is omitted. As used below, the term "module" may be a combination of software and/or hardware that implements a predetermined function. Although the means described in the embodiments below are preferably implemented in software, an implementation in hardware, or a combination of software and hardware is also possible and contemplated.
Fig. 2 is a block diagram showing the structure of an apparatus for determining intimacy degree of person according to embodiment 2 of the present invention, as shown in fig. 2, the apparatus including:
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, each data feature corresponds to one sensitivity level, and the sensitivity levels are improved as the degree of influence of the data features on intimacy increases;
the weight determining module 24 is configured to determine a level weight of each sensitivity level according to the number of the data features corresponding to each sensitivity level in one or more sensitivity levels;
the intimacy degree determining module 26 is configured to determine the intimacy degree 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 level weight of the one or more sensitivity levels corresponding to the data feature.
By the device, one or more sensitivity levels corresponding to the data characteristics between the target person and the person to be detected are determined, the level weight of each sensitivity level is determined according to the number of the data characteristics corresponding to each sensitivity level in the one or more sensitivity levels, 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 level weights of the one or more sensitivity levels corresponding to the data characteristics. Because the influence of the characteristic data of different sensitivity levels on the actual intimacy is different, the weight is determined according to the sensitivity levels, and the intimacy between the personnel is determined according to the weight, so that the problem that the determination of the intimacy of the personnel is not accurate enough can be solved, and more reasonable and accurate analysis and calculation of the intimacy of the personnel are realized.
Alternatively, the above-mentioned apparatus may be disposed in a data analysis device, such as a data server, a data analysis platform, etc., but is not limited thereto.
Fig. 3 is a first exemplary block diagram of a device for determining intimacy degree of a person according to embodiment 2 of the present invention, as shown in fig. 3, and in at least one exemplary embodiment, the device further includes:
a sensitivity ranking module 32, configured to rank all the supported types of data features into multiple sensitivity rankings according to sensitivity degrees of different types of data features on influence of affinity, where the multiple sensitivity rankings include the one or more sensitivity rankings.
By the device, various data characteristics supported by the system can be divided into corresponding sensitivity levels according to the sensitivity of the data characteristics on the influence of the intimacy degree, so that the intimacy degree can be calculated conveniently.
Fig. 4 is a second exemplary block diagram of the apparatus for determining the intimacy degree of a person according to embodiment 2 of the present invention, and as shown in fig. 4, in at least one exemplary embodiment, the weight determining module 24 includes:
the basic weight determining unit 242 is configured to determine a basic weight according to the number of the data features corresponding to each sensitivity level in the one or more sensitivity levels.
In at least one exemplary embodiment, the base weight determining unit 242 may determine the base weight W according to the following formula:
degree＝N1W+N2N1W+N3N2N1W+…+NKNK-1NK-2W...N1w, wherein the degree is a preset normalized value of intimacy density, NiAnd K is the total number of the one or more sensitivity levels, and i is less than or equal to K.
A level weight determining unit 244, configured to determine a level weight of each sensitivity level according to the base weight and the number of the data features corresponding to each sensitivity level.
In at least one exemplary embodiment, the rank weight determination unit 244 may determine the rank weight W for the ith sensitivity rank from low to highi＝Ni*...*N1W, wherein, NiAnd i is less than or equal to K which is the total number of the one or more sensitivity levels corresponding to the number of the data features corresponding to the ith sensitivity level.
Fig. 5 is a third exemplary block diagram of the structure of the apparatus for determining the intimacy degree of a person according to embodiment 2 of the present invention, as shown in fig. 5, and in at least one exemplary embodiment, the intimacy degree determining module 26 includes: a single item affinity determination unit 262 and an affinity-combination determination unit 264.
And the individual intimacy degree determining unit 262 is used for determining, for each data feature between the target person and the person to be detected, an intimacy degree value corresponding to the data feature according to the category to which the data feature belongs and the grade weight of the sensitivity grade corresponding to the data feature.
In at least one example embodiment, the singleton affinity determination unit 262 may perform the following operations:
determining, for each data feature between the target person and the person to be detected, an affinity value corresponding to the data feature by using a first affinity formula or a second affinity formula according to a category to which the data feature belongs, wherein the affinity value corresponding to the data feature is determined by using the first affinity formula when the category to which the data feature belongs is a deterministic relationship, and the affinity value corresponding to the data feature is determined by using the second affinity formula when the category to which the data feature belongs is a non-deterministic relationship.
The first affinity formula may be: c ═ A × WcWherein C is the intimacy value corresponding to the data characteristic, A is the influence constant corresponding to the data characteristic, and WcAnd the data characteristics are corresponding to the sensitivity levels of the grade weight. In at least one exemplary embodiment, the data features correspond toThe influence constant a increases with increasing degree of influence of the deterministic relationship expressed by the data features on the intimacy.
The second affinity formula may be: c ═ 1-1/m × WcWherein C is the intimacy value corresponding to the data characteristic, m is the occurrence frequency of the non-definite behavior corresponding to the data characteristic, and WcAnd the data characteristics are corresponding to the sensitivity levels of the grade weight.
An affinity combining and 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 block diagram of a device for determining intimacy degree of a person 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:
the processing module 62 is configured to perform screening, sorting, displaying and/or reporting processing on the information of the to-be-detected person according to the intimacy between the target person and the to-be-detected person.
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 comprises: and the intimacy degree of the personnel to be detected with the target personnel is higher than a preset threshold value, or the ranking of the intimacy degree of the personnel to be detected with the target personnel is arranged at the top N, wherein N is a positive integer. For example, the method may be applied to the aspect of examining key-point persons, for example, for key-point persons, the intimacy degree calculation method of the present embodiment is used to calculate the intimacy degree between the key-point persons and the surrounding related persons by using the information of their traveling, relatives, and the like, and the persons with higher intimacy degree with the key-point persons are provided to the public safety management institution for reference.
(2) And sequencing 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 in a descending order. For example, the method may be applied to public security data processing, based on a personnel database, for a person of major concern provided by a public security management organization, using information of his trip, relatives, and the like, using the intimacy degree calculation method of the present embodiment to calculate intimacy degree between the person and surrounding related persons, and providing the intimacy degree calculation result to the public security management organization for reference.
(3) And controlling and displaying the intimacy between the target person and the person to be detected. For example, the method may be applied to public safety data processing, based on a personnel database, the intimacy degree between the person and the surrounding related personnel is calculated by using the intimacy degree calculation method of the present embodiment according to the information of the person who is mainly concerned provided by the public safety administration, and the intimacy degree calculation result is displayed on the screen.
(4) And uploading the intimacy information between the target person and the person to be detected to a management platform. For example, the method may be applied to public security data processing, based on a personnel database, for a key attention person provided by a public security management organization, the intimacy degree between the key attention person and the surrounding related person is calculated by using the intimacy degree calculation method of the present embodiment by using information of travel, relatives, and the like of the key attention person, and the intimacy degree calculation result is uploaded to a management platform for reference use by the whole public security management system.
It should be noted that, the above modules may be implemented by software or hardware, and for the latter, the following may be implemented, but not limited to: the modules are all positioned in the same processor; alternatively, the modules are respectively located in different processors in any combination.
Example 3
Embodiments of the present invention also provide a storage medium having a computer program stored therein, wherein the computer program is arranged to perform the steps of any of the above method embodiments when executed.
Alternatively, in the present embodiment, the storage medium may be configured to store a computer program for executing 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 levels are improved along with the increase of the influence degree of the data features on intimacy;
step S2, determining the grade weight of each sensitivity grade according to the quantity of the data characteristics corresponding to each sensitivity grade in one or more sensitivity grades;
step S3, 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 weight of one or more sensitivity grades corresponding to the data characteristics.
Optionally, in this embodiment, the storage medium may include, but is not limited to: various media capable of storing computer programs, such as a usb disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic disk, or an optical disk.
Embodiments of the present invention also provide a data analysis device comprising a memory having a computer program stored therein and a processor arranged to run the computer program to perform the steps of any of the above method embodiments.
Optionally, the electronic apparatus may further include a transmission device and an input/output device, wherein the transmission device is connected to the processor, and the input/output device is connected to the processor.
Optionally, in this embodiment, the 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 levels are improved along with the increase of the influence degree of the data features on intimacy;
step S2, determining the grade weight of each sensitivity grade according to the quantity of the data characteristics corresponding to each sensitivity grade in one or more sensitivity grades;
step S3, 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 weight of one or more sensitivity grades corresponding to the data characteristics.
Optionally, the specific examples in this embodiment may refer to the examples described in the above embodiments and optional implementation manners, and this embodiment is not described herein again.
Example 4
The present embodiment describes in detail the processing procedure of the intimacy degree determination scheme, taking as an example data characteristics including "parent, spouse, brother" and "same trip".
According to the scheme, information of parents, spouses, family households and group households and the like contained in the public safety data is subjected to sensitivity grade division, specific weights are respectively given to data with different sensitivity grades, so that the influence degree of the data with low sensitivity grade on the final intimacy degree is constantly smaller than the influence degree of the data with high sensitivity grade on the final intimacy degree, and finally the intimacy degree between two main persons is calculated according to the weights of the data with different sensitivity grades between the two main persons.
Fig. 7 is a process flow chart of a method for determining human intimacy degree according to embodiment 4 of the present invention, and as shown in fig. 7, the method for determining human intimacy degree based on public safety data based on rules includes the following steps:
and step S701, dividing the sensitivity degree of the public safety data. And grading the data characteristics of spouse, parents, family households, group households, lines, networks and the like contained in the public security data according to the sensitivity degree.
Step S702, calculating a basis weight. Dividing the public security data into K levels according to the sensitivity degree, wherein each level comprises N data characteristics, the basic weight is W, and the intimacy between two subject persons can be described as
degree＝N1W+N2N1W+N3N2N1W+…+NKNK-1NK-2W...N1W (1)
The above formula is made to be identical to the normalized value of the intimacy degree (1 in this embodiment), and the basic weight W is obtained by solving.
In step S703, each level weight is calculated. The weight of each level is set as the product of the number of data features contained in the current level and the number of data features contained in all levels lower than the current level, and then multiplied by the basic weight, for example, the current level is 3 levels containing a data features, and the levels 2 and 1 lower than the current level contain b andcand the weight of the current grade is a, b, c and W.
Step S704, calculating final intimacy by integrating public security data characteristics, wherein the public security data comprises deterministic relationships such as parental relationships, couple relationships and the like and non-deterministic relationships such as same trip, same internet and the like, the deterministic relationships are respectively set to be different constants according to the influence degree on intimacy, for example, the parental and spouse relationship is set to 1, the family relationship is set to 0.8, the family relationship is set to 0.6, wherein each constant value is determined according to specific data, the non-deterministic relationship is a number of the constant values, for example, M times for the same row in N days, wherein the constant value of the deterministic relationship setting is directly multiplied by the weight of the corresponding level, the non-deterministic relationship is multiplied by the difference of the reciprocal thereof with 1 and the weight of the corresponding level, such as a peer relationship, the same row was performed 3 times in N days, and the corresponding weight was 0.6, which is 0.6 x (1-1/3). And calculating the relative density value corresponding to each data characteristic by the method.
In step S705, the affinity values corresponding to each data feature are added and summed to obtain a final affinity value.
Based on the above method, for convenience of understanding, the present embodiment takes the common security data containing the characteristics of the parent, spouse, brother and same row data as an example, and details the scheme based on the practical example are described.
And step S701', dividing the sensitivity degree of the public safety data. The data characteristics are graded according to the sensitivity degree, and the proposal sequentially grades the data characteristics into a parent grade, a spouse grade and a brother grade and a same trip grade from high to low.
Step S702', calculating the basic weight. Dividing the public safety data features into 2 level hierarchies, wherein each level hierarchy from high to low comprises 3 and 1 data features, and solving formula 1 to obtain 1/4 as a basis weight.
Step S703', each level weight is calculated. The weight of the "same row" level is the multiplication of the data characteristic number contained in the level and the basic weight, namely 1 × 1/3 ═ 1/3, and the weight of the "parent, spouse, brother" level is the multiplication of the data characteristic number 3 contained in the level and the data characteristic number 1 contained in the "same row" level lower than the level and the basic weight, namely 3 × 1 × 1/3 ═ 1.
Steps S704 '-S705', integrate the public safety data features. If the two subject persons are in a parent, spouse and brother relationship, the value is set to 1, otherwise, the value is set to 0, assuming that the two subject persons a and b travel 2 times in the same row within N days and are in a spouse relationship, the affinity value of the "same row" grade is 1/3 (1-1/2) ═ 1/6, and the affinity value of the "parent, spouse and brother" grade is 1 × 1 ═ 1, then the final affinity value of a and b is 1/6+1 ═ 7/6; assuming that two subject persons c and d are also traveling 2 times in the same row within N days, the affinity value of the "same row" rating is 1/3 × 1/6 (1-1/2), and is not one of the parent, spouse, and brother relationships, the affinity value of the "parent, spouse, and brother" rating is 1 × 0 — 0, and the final affinity value between c and d is 1/6+0 — 1/6.
The scheme provides that information of parents, spouses, family households and group households and the like contained in the public security data is subjected to sensitivity level division, and the intimacy between two main personnel is calculated according to the interaction degree of data with different sensitivity levels between the two main personnel.
It will be apparent to those skilled in the art that the modules or steps of the present invention described above may be implemented by a general purpose computing device, they may be centralized on a single computing device or distributed across a network of multiple computing devices, and alternatively, they may be implemented by program code executable by a computing device, such that they may be stored in a storage device and executed by a computing device, and in some cases, the steps shown or described may be performed in an order different than that described herein, or they may be separately fabricated into individual integrated circuit modules, or multiple ones of them may be fabricated into a single integrated circuit module. Thus, the present invention is not limited to any specific combination of hardware and software.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the principle of the present invention should be included in the protection scope of the present invention.
Claims (13)
1. A method for determining a person's intimacy, comprising:
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 intimacy;
determining the grade weight of each sensitivity grade according to the quantity of the data characteristics corresponding to each sensitivity grade in one or more sensitivity grades;
and 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 weight of one or more sensitivity grades corresponding to the data characteristics.
2. The method of claim 1, wherein prior to determining one or more sensitivity levels corresponding to data characteristics between the target person and the person to be detected, further comprising:
and classifying all supported types of data features into a plurality of sensitivity levels according to the sensitivity degrees of the different types of data features on the influence of intimacy, wherein the plurality of sensitivity levels comprise the one or more sensitivity levels.
3. The method of claim 1, wherein determining a rank weight for each sensitivity level based on the number of data features corresponding to each sensitivity level of one or more sensitivity levels comprises:
determining a basis weight according to the number of the data features corresponding to each sensitivity level in 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. The method of claim 3, wherein determining a basis weight based on the number of data features corresponding to each of the one or more sensitivity levels comprises:
determining the basis weight W according to the following formula:
degree＝N1W+N2N1W+N3N2N1W…+NKNK-1NK-2W…N1w, wherein the degree is a preset normalized value of intimacy density, NiAnd K is the total number of the one or more sensitivity levels, and i is less than or equal to K.
5. The method of claim 3, wherein determining a level weight for each sensitivity level based on the base weight and the number of data features corresponding to each sensitivity level comprises:
determining a level weight W for the ith sensitivity level from low to highi＝Ni*…*N1W, wherein, NiAnd i is less than or equal to K which is the total number of the one or more sensitivity levels corresponding to the number of the data features corresponding to the ith sensitivity level.
6. The method of claim 1, wherein determining the intimacy between the target person and the person to be detected according to the data characteristic between the target person and the person to be detected and the rating weight of the one or more sensitivity levels corresponding to the data characteristic comprises:
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 category of the data feature and the level weight of the sensitivity level corresponding to the data feature;
and combining the intimacy values corresponding to each data characteristic to determine the intimacy between the target person and the person to be detected.
7. The method according to claim 6, wherein for each data feature between the target person and the person to be detected, determining the affinity value corresponding to the data feature according to the category to which the data feature belongs and the grade weight of the sensitivity grade corresponding to the data feature comprises:
determining, for each data feature between the target person and the person to be detected, an affinity value corresponding to the data feature by using a first affinity formula or a second affinity formula according to a category to which the data feature belongs, wherein the affinity value corresponding to the data feature is determined by using the first affinity formula when the category to which the data feature belongs is a deterministic relationship, and the affinity value corresponding to the data feature is determined by using the second affinity formula when the category to which the data feature belongs is a non-deterministic relationship;
the first intimacy formula is: c ═ A × WcWherein C is the intimacy value corresponding to the data characteristic, A is the influence constant corresponding to the data characteristic, and WcThe grade weight of the sensitivity grade corresponding to the data characteristic is obtained;
the second affinity formula is: c ═ 1-1/m × WcWherein C is the intimacy value corresponding to the data characteristic, m is the occurrence frequency of the non-definite behavior corresponding to the data characteristic, and WcAnd the data characteristics are corresponding to the sensitivity levels of the grade weight.
8. The method of claim 7, wherein the influence constant A corresponding to the data feature increases with the degree of influence of the deterministic relationship expressed by the data feature on the intimacy degree.
9. The method of claim 6, wherein combining the affinity values corresponding to each data feature to determine the affinity between the target person and the person to be detected comprises:
and adding the intimacy values corresponding to each data characteristic, and determining the added result as the intimacy between the target person and the person to be detected.
10. The method according to any one of claims 1 to 9, wherein after determining the intimacy 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 ranking weight of the one or more sensitivity levels corresponding to the data feature, the method further comprises:
and screening, sorting, displaying and/or reporting the information of the personnel to be detected according to the intimacy degree between the target personnel and the personnel to be detected.
11. The method according to claim 10, wherein the processing of screening, sorting, displaying and/or reporting the information of the person to be detected according to the intimacy 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 comprises: the affinity with the target person is higher than a preset threshold value, or the affinity with the target person is ranked at the top N positions of the to-be-detected persons, wherein N is a positive integer;
sequencing 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 in a descending order;
controlling and displaying the intimacy between the target person and the person to be detected;
and uploading the intimacy information between the target person and the person to be detected to a management platform.
12. An apparatus for determining a human intimacy degree, 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 intimacy;
the weight determining module is used for determining the grade weight of each sensitivity grade according to the number of the data features corresponding to each sensitivity grade in one or more sensitivity grades;
and the intimacy determining module is used for 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 weight of one or more sensitivity grades corresponding to the data characteristics.
13. A storage medium, in which a computer program is stored, wherein the computer program is arranged to perform the method of any of claims 1 to 11 when executed.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010568708.2A CN111708821B (en) | 2020-06-19 | 2020-06-19 | Method, device and storage medium for determining personnel intimacy |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010568708.2A CN111708821B (en) | 2020-06-19 | 2020-06-19 | Method, device and storage medium for determining personnel intimacy |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111708821A true CN111708821A (en) | 2020-09-25 |
| CN111708821B CN111708821B (en) | 2023-07-14 |
Family
ID=72542719
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010568708.2A Active CN111708821B (en) | 2020-06-19 | 2020-06-19 | Method, device and storage medium for determining personnel intimacy |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111708821B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114894460A (en) * | 2022-05-10 | 2022-08-12 | 同济大学 | IMU-based method for monitoring and evaluating damage state of anti-seismic support and hanger |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| 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 |
| 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 |
-
2020
- 2020-06-19 CN CN202010568708.2A patent/CN111708821B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| 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 |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114894460A (en) * | 2022-05-10 | 2022-08-12 | 同济大学 | IMU-based method for monitoring and evaluating damage state of anti-seismic support and hanger |
| CN114894460B (en) * | 2022-05-10 | 2023-03-28 | 同济大学 | IMU-based method for monitoring and evaluating damage state of anti-seismic support and hanger |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111708821B (en) | 2023-07-14 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Patil et al. | Detecting experts on Quora: by their activity, quality of answers, linguistic characteristics and temporal behaviors | |
| Peng | Regional earthquake vulnerability assessment using a combination of MCDM methods | |
| Young et al. | A survey of methodologies for the treatment of missing values within datasets: Limitations and benefits | |
| US8548996B2 (en) | Ranking content items related to an event | |
| Fogués et al. | BFF: A tool for eliciting tie strength and user communities in social networking services | |
| CN107862022A (en) | Cultural resource commending system | |
| Sanderson et al. | Derivation and assessment of risk prediction models using case-cohort data | |
| CN110322356B (en) | Medical insurance abnormity detection method and system based on HIN mining dynamic multi-mode | |
| Chen et al. | Dynamic clustering collaborative filtering recommendation algorithm based on double-layer network | |
| KR20180086084A (en) | Device and Method on Making Highly Related Patent Set from Input Patent Set Based on Machine Learning Methodology Using Artificial Intelligence Technology | |
| Michelot et al. | Inference in MCMC step selection models | |
| CN113569162A (en) | Data processing method, device, equipment and storage medium | |
| Szádoczki et al. | Incomplete pairwise comparison matrices based on graphs with average degree approximately 3 | |
| Lohr | Design effects for a regression slope in a cluster sample | |
| Leal et al. | Trust-based modelling of multi-criteria crowdsourced data | |
| Fabrizi et al. | A hierarchical latent class model for predicting disability small area counts from survey data | |
| Ben Abdrabbah et al. | Social activities recommendation system for students in smart campus | |
| CN111708821A (en) | Method and device for determining personnel intimacy and storage medium | |
| US20210005298A1 (en) | Visualising clinical and genetic data | |
| JP4059970B2 (en) | Information source recommendation device | |
| Barhoum et al. | Composite performance indicators for helmet and seat-belt enforcement as imprecise data | |
| CN110729052A (en) | Old health data knowledge analysis method and system | |
| CN115391666A (en) | Hospital online recommendation method and device, computer equipment and storage medium | |
| Bhattacharyya et al. | Smart and Innovative Trends in Next Generation Computing Technologies: Third International Conference, NGCT 2017, Dehradun, India, October 30-31, 2017, Revised Selected Papers, Part I | |
| Nathoo et al. | A mixed mover–stayer model for spatiotemporal two-state processes |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |