CN112668800A - Information processing method, apparatus, medium, and device - Google Patents
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Abstract
One or more embodiments of the present specification provide an information processing method including: acquiring related information related to the virus-involved personnel according to the identity of the virus-involved personnel, wherein the identity of the virus-involved personnel is unique; performing statistical analysis on the associated information according to a preset intelligent algorithm to obtain an analysis result, and constructing a relationship map of suspected personnel according to the analysis result; and determining the identity of the suspected personnel according to the relationship map, and outputting a list of the suspected personnel with the virus-related behavior. The invention can intelligently analyze and discover potential virus-related personnel, form a grey list and provide powerful guarantee for virus-related management and control.
Description
Technical Field
One or more embodiments of the present disclosure relate to the field of data processing technologies, and in particular, to an information processing method, apparatus, medium, and device.
Background
In recent years, the trend of people involved in the virus in China is increased to cause various worries. At the present stage of the ministry of public security, only a small amount of information of the dominant drug-involved personnel is mastered, and the information of the recessive drug-involved personnel is really few and less. At the present stage, the society is networked, people can not make an interaction with the network at any time in daily life, and each person can form a series of data one word at a time. In this context, it becomes particularly important to obtain useful information by configuring data collision and machine learning algorithm models.
The problem that virus-related personnel are difficult to control exists in many regions throughout the country, the fundamental reason is determined by the characteristics of virus-addicts and the mobility of modern social personnel, and the control is particularly difficult when a large number of personnel go out of office due to economic differences as inland. In order to solve the problems, under the background of current big data and AI, a big data analysis thinking is applied, and the establishment of a control model of virus-related personnel becomes a key research direction for maintaining the stability of information.
Therefore, how to predict and recommend the hidden information of the virus-related personnel and how to obtain the data of the personnel in contact with the virus-related personnel according to the network information of the virus-related personnel so as to find out the information of potential suspect persons which is not mastered by the public security is a problem to be solved urgently in the industry.
Disclosure of Invention
In view of this, one or more embodiments of the present disclosure are directed to an information processing method, an information processing apparatus, an information processing medium, and an information processing device, so as to solve the problem that the control accuracy of potential virus-related personnel is not high at present.
In view of the above object, one or more embodiments of the present specification provide an information processing method including:
acquiring related information related to the virus-involved personnel according to the identity of the virus-involved personnel, wherein the identity of the virus-involved personnel is unique;
performing statistical analysis on the associated information according to a preset intelligent algorithm to obtain an analysis result, and constructing a relationship map of suspected personnel according to the analysis result;
and determining the identity of the suspected personnel according to the relationship map, and outputting a list of the suspected personnel with the virus-related behavior.
With reference to the above description, in another possible implementation manner of the embodiment of the present invention, the performing statistical analysis on the association information according to a preset intelligent algorithm to obtain an analysis result, and constructing a relationship graph of the suspected person according to the analysis result includes:
performing binary classification and logistic regression classification on the associated information, and analyzing by adopting a machine learning algorithm, wherein the method comprises the following steps:
determining an optimal objective function:
wherein z denotes a linear function, g (z) is a probability value of a last output sample class, and when a set threshold value is 0.5, g (z) results in 1 when being greater than or equal to 0.5 and results in 0 when being less than 0.5;
after classification, determining an optimal linear function model:
wherein x is an input identity of a related person, theta is an optimal parameter of x, and T is a parameter matrix;
combining said equations (1) and (2) to construct a prediction function and determine a loss function:
P(y|x；θ)＝(hθ(x))y(1-hθ(x))1-yformula (4)
Wherein P is the probability value of the sample data,
determining a log-likelihood function:
equation (5) returns the category 1 or 0 of the input sample data, where 1 represents suspect and 0 is not suspect.
With reference to the foregoing description, in another possible implementation manner of the embodiment of the present invention, the association information includes:
at least one of mobile phone information, WeChat information, QQ information, Internet surfing personnel information, railway network information and accommodation information of the virus-involved personnel.
In another possible implementation manner of the embodiment of the present invention, in combination with the above description, the method further includes:
performing correlation collision with the correlation information of the selected non-virus-related personnel according to the correlation information of the virus-related personnel;
and outputting a suspected personnel list with the virus-related behavior according to the collision result.
With reference to the foregoing description, in another possible implementation manner of the embodiment of the present invention, the performing a correlation collision with the correlation information of the selected non-virus-related person according to the correlation information of the virus-related person includes:
determining the identity of non-virus-related personnel related to the virus-related personnel from the related information of the virus-related personnel, and determining the related information of the non-virus-related personnel according to the identity;
and performing correlation collision on the correlation information of the related non-virus-involved persons to obtain the important features of the suspected persons, wherein the correlation collision at least comprises one of union set, intersection set, difference set, deviation and data cleaning of the correlation information.
In another possible implementation manner of the embodiment of the present invention, in combination with the above description, the method further includes:
determining whether the risk degree of the suspected personnel is greater than a risk threshold value or not by combining the correlation collision result of the suspected personnel and the correlation information with higher activity of the suspected personnel;
and triggering alarm information when the risk degree of the suspected personnel is greater than a risk threshold value, and sending the alarm to an intranet.
In a second aspect, the present invention also provides an information processing apparatus, including:
the information acquisition module is used for acquiring related information related to the virus-related personnel according to the identification of the virus-related personnel, and the identification of the virus-related personnel has uniqueness;
the statistical analysis module is used for performing statistical analysis on the associated information according to a preset intelligent algorithm to obtain an analysis result and constructing a relationship map of suspected personnel according to the analysis result;
and the output display module is used for determining the identity of suspected personnel according to the relationship map and outputting a list of suspected personnel with the virus-related behavior.
The above apparatus, further comprising:
the collision module is used for performing correlation collision with the correlation information of the selected non-virus-related personnel according to the correlation information of the virus-related personnel; and
and outputting a suspected personnel list with the virus-related behavior according to the collision result.
In a third aspect, the present invention further provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, the information processing method is implemented.
In a fourth aspect, the present invention also provides a non-transitory computer-readable storage medium storing computer instructions for causing the computer to execute the above-described information processing method.
As can be seen from the above, the information processing method, apparatus, medium, and device provided in one or more embodiments of the present disclosure perform comprehensive analysis of a preset algorithm on various kinds of associated information of the virus-related information, so that the control capability of the virus-related personnel and the groups of the virus-related personnel can be effectively improved, and the requirements of the society on the virus-related personnel are met; the coverage rate of virus-involved persons who are not checked is quickly and effectively improved, and the case occurrence of virus-involved groups is maximally assisted and inhibited; the workload of manual analysis processing of the drug-related cases is reduced, the phenomenon of information leakage management of the drug-related personnel is reduced, and the working cost and time cost of police personnel are greatly reduced.
Drawings
In order to more clearly illustrate one or more embodiments or prior art solutions of the present specification, the drawings that are needed in the description of the embodiments or prior art will be briefly described below, and it is obvious that the drawings in the following description are only one or more embodiments of the present specification, and that other drawings may be obtained by those skilled in the art without inventive effort from these drawings.
FIG. 1 is a schematic diagram of a basic flow of an information method according to one or more embodiments of the present disclosure;
FIG. 2 is a schematic relational map of one or more embodiments of the disclosure;
FIG. 3 is a basic diagram of an information processing apparatus according to one or more embodiments of the present disclosure;
FIG. 4 is a schematic diagram of an information handling system according to one or more embodiments of the present disclosure;
fig. 5 is a schematic structural diagram of an electronic device according to one or more embodiments of the present disclosure.
Detailed Description
For the purpose of promoting a better understanding of the objects, aspects and advantages of the present disclosure, reference is made to the following detailed description taken in conjunction with the accompanying drawings.
It is to be noted that unless otherwise defined, technical or scientific terms used in one or more embodiments of the present specification should have the ordinary meaning as understood by those of ordinary skill in the art to which this disclosure belongs. The use of "first," "second," and similar terms in one or more embodiments of the specification is not intended to indicate any order, quantity, or importance, but rather is used to distinguish one element from another. The word "comprising" or "comprises", and the like, means that the element or item listed before the word covers the element or item listed after the word and its equivalents, but does not exclude other elements or items. The terms "connected" or "coupled" and the like are not restricted to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "upper", "lower", "left", "right", and the like are used merely to indicate relative positional relationships, and when the absolute position of the object being described is changed, the relative positional relationships may also be changed accordingly.
The invention relates to an information processing method, a device, a medium and equipment, which are mainly applied to a scene needing comprehensive analysis on potential virus-involved personnel, and the basic idea is as follows: the method has the advantages that the relevant information of the related personnel, such as the exchange information, the hotel information, the trip information and the like, is comprehensively analyzed through a preset algorithm, the grey list of potential virus-related personnel is determined, valuable social security information is provided for public security organs, assistance is provided for inhibiting case events of virus-related groups, the workload of manual analysis processing of the virus-related cases can be greatly reduced, the phenomenon of information leakage management of the virus-related personnel is reduced, and the working cost and the time cost of police officers are greatly reduced.
It should be noted that the method of one or more embodiments of the present disclosure may be performed by a single device, such as a computer or server. The method of the embodiment can also be applied to a distributed scene and completed by the mutual cooperation of a plurality of devices. In this distributed scenario, one of the multiple devices may only perform one or more steps of the method according to one or more embodiments of the present disclosure, and the multiple devices interact with each other to complete the information processing method.
It should be noted that the above description describes certain embodiments of the present disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
Fig. 1 is a basic flowchart of an information processing method according to an exemplary embodiment of the present invention, and in conjunction with fig. 1, the information processing method according to the present invention includes the following steps:
in step 110, acquiring related information related to the person involved in the virus according to the identity of the person involved in the virus, wherein the identity of the person involved in the virus has uniqueness;
the identity of the virus-involved person can be an identity card number of the virus-involved person, and the identity has unique identification, and in a specific safety system, the identity can be a string of characters subjected to masking processing, so that the identity can be associated with a specific certain virus-involved person one by one, even if the identity has the uniqueness.
The related information is generally mobile phone information, WeChat information, QQ information, Internet access personnel information, railway network information, accommodation information and the like of virus-related personnel, and in comprehensive analysis, the clothes and eating and accommodation related information can be used as the related information, such as a delivery address during shopping at a shopping website, a delivery contact, a contact for making a call, a contact of WeChat or QQ and other types of instant messaging software, user information of nearby machine information during Internet access, identity information of other accommodation personnel in a hotel during accommodation and the like.
In step 120, performing statistical analysis on the associated information according to a preset intelligent algorithm to obtain an analysis result, and constructing a relationship map of suspected personnel according to the analysis result;
the predetermined intelligent algorithm specifically includes the following processes for classifying, normalizing, optimizing and determining log-likelihood functions of the data.
In step 130, the identity of the suspected person is determined according to the relationship map, and a list of suspected persons with the virus-related behavior is output.
In the implementation manner of the exemplary embodiment of the present invention, the srcpackageid is a unique identifier for a person inside the system, and is an electronic special identifier inside the public security, that is, the identity identifier, when the output probability (P) of a non-drug addict in machine learning by using the features is greater than 0.5, the person is assumed to be a suspected drug addict recommended by the model, that is, the predicted value is 1, and the output probability (P) is less than 0.5, and the person is assumed to be a non-drug addict, that is, the predicted value is 0.
The characteristics are digital marks set for the drug addicts, and for example, different user behavior characteristics, user action tracks, frequent location and the like of the drug addicts and the non-drug addicts can be used as characteristics for machine learning.
More specifically, when the action track of one drug addict is completely the same as that of another drug addict, the machine may determine that there is a high probability of a relapse illegal action of the two drug addicts, or the same merchant often purchases the same article for multiple times by multiple drug addicts, and the merchant may be determined as a suspected drug addict or other illegal person by the machine, and so on.
And compiling a list of potential virus-related personnel with a predicted value of 1 and outputting a grey list, so that relevant organs or departments can perform targeted safety maintenance work.
In an implementation manner of the exemplary embodiment of the present invention, the performing statistical analysis on the associated information according to a preset intelligent algorithm to obtain an analysis result, and constructing a relationship graph of suspected persons according to the analysis result includes:
performing binary classification and logistic regression classification on the associated information, and analyzing by adopting a machine learning algorithm, wherein the method comprises the following steps:
determining an optimal objective function:
wherein z denotes a linear function, g (z) is a probability value of a last output sample class, and when a set threshold value is 0.5, g (z) results in 1 when being greater than or equal to 0.5 and results in 0 when being less than 0.5;
after classification, determining an optimal linear function model:
wherein x is an input identity of a related person, theta is an optimal parameter of x, and T is a parameter matrix;
combining said equations (1) and (2) to construct a prediction function and determine a loss function:
P(y|x；θ)＝(hθ(x))y(1-hθ(x))1-yformula (4)
Wherein P is the probability value of the sample data,
determining a log-likelihood function:
equation (5) returns the category 1 or 0 of the input sample data, where 1 represents suspect and 0 is not suspect.
In a more specific implementation manner of the exemplary embodiment of the present invention, the association information may be information in the following tables 1 to 10:
TABLE 1
When the associated information is the mobile phone information, it is shown in table 2 below:
TABLE 2
| Name (I) | srcpackageid (identification) | Mobile phone number |
| A permit | 0200-a040-7jh0-09ks-0421 | 1574896**** |
| Wang (PZQ DXW) | 0300-a040-7jh0-09ks-0421 | 1824042**** |
When the associated information is the mobile phone address book information, it is shown in table 3 below:
TABLE 3
| Name (I) | srcpackageid (identification) | Personal mobile phone number | Opposite side mobile phone number |
| Plum | 0200-a040-7jh0-09ks-0421 | 1574896**** | 1541532**** |
| Liu (PZQ DXW) | 0300-a040-7jh0-09ks-0421 | 1824042**** | 1379770**** |
When the associated information is the mobile phone call record information, it is shown in the following table 4:
TABLE 4
| Name (I) | srcpackageid (identification) | Calling number | Called number |
| King | 2200-a040-7jh0-05ks-0421 | 1587633**** | 1524534**** |
| Song Dynasty | 4300-a040-7jh2-09ks-7421 | 1874042**** | 1388977**** |
When the associated information is the mobile phone WeChat information, the following table 5 shows:
TABLE 5
| srcpackageid (identification) | WeChat account | Remarks for note |
| 3200-bj93-7ks0-05ks-0902 | D7GJLW2W | Is free of |
| 3301-b093-8jh2-08ks-7862 | TY5YNP6E | Repeat suction of the person |
When the associated information is the information of the mobile phone WeChat friend, the following table 6 shows:
TABLE 6
| srcpackageid (identification) | WeChat account | Friend WeChat account |
| 9200-bj93-7ks0-05ks-0782 | D7G***** | WH7OW***** |
| 3301-yhd3-8893-08ks-7902 | TY5****** | AJJW****** |
When the associated information is the mobile phone WeChat member table information, the following table 7 shows:
TABLE 7
| srcpackageid (identification) | WeChat account | WeChat group account |
| 9000-bj93-7ks0-05ks-0893 | D7G***** | 15Y3NU*****776 |
| 4501-yhd3-8893-08ks-7893 | TY5****** | 145AJJW******09 |
When the associated information is the mobile phone QQ information, it is shown in table 8 below:
TABLE 8
| srcpackageid (identification) | QQAccount number | Remarks for note |
| 6701-7j93-78s0-05ks-6723 | 12911******* | Is free of |
| 8201-7093-8jh2-08ks-8921 | 93657***** | Is free of |
When the associated information is the information of the QQ friend of the mobile phone, it is shown in table 9 below:
TABLE 9
| srcpackageid (identification) | Personal QQ Account number | Friend QQ account |
| 0450-bj93-7ks0-0jks-0892 | 129112***** | 747075*** |
| 7801-juy3-9883-08ks-7902 | 936575**** | 133845****** |
When the associated information is information of the mobile phone QQ group members, it is shown in table 10 below:
watch 10
When the associated information is the internet surfing information of the internet bar of the virus-related personnel, the table 11 shows that:
TABLE 11
When the related information is the lodging information of the person involved in the virus, it is shown in the following table 12:
TABLE 12
When the related information is trip information of the virus-related person, it is shown in table 13 below:
watch 13
In an implementation manner of the exemplary embodiment of the present invention, the various types of related information may be stored in a data storage, and when acquiring data, the data may be acquired according to a big data environment stored by different police classes through the public security data.
In one implementation manner of the exemplary embodiment of the present invention, according to the associated information of the person involved in the virus, the associated information of the selected non-person involved in the virus is subjected to associated collision;
the associated collision is a collision result obtained after the characteristics related to the drug-taking personnel are associated with the characteristics related to the non-drug-taking personnel, and the collision result can be used for determining the likelihood probability among specific personnel so as to finally guide the law enforcement personnel to carry out corresponding law enforcement activities according to the collision result.
And outputting a suspected personnel list with the virus-related behavior according to the collision result.
In an implementation manner of the exemplary embodiment of the present invention, the performing a correlation collision with the correlation information of the selected non-virus-related person according to the correlation information of the virus-related person includes:
determining the identity of non-virus-related personnel related to the virus-related personnel from the related information of the virus-related personnel, and determining the related information of the non-virus-related personnel according to the identity;
and performing correlation collision on the correlation information of the related non-virus-involved persons to obtain the important features of the suspected persons, wherein the correlation collision at least comprises one of union set, intersection set, difference set, deviation and data cleaning of the correlation information.
The suspected personnel information obtained after the associated collision includes the following table 14:
TABLE 14
The output results are shown in table 15:
watch 15
In one implementation of the exemplary embodiments of this invention, the triggering of the dangerous alarm information for the suspected person is further included, and the process includes:
determining whether the risk degree of the suspected personnel is greater than a risk threshold value or not by combining the correlation collision result of the suspected personnel and the correlation information with higher activity of the suspected personnel;
and triggering alarm information when the risk degree of the suspected personnel is greater than a risk threshold value, and sending the alarm to an intranet.
In one embodiment of the exemplary embodiment of the present invention, the relationship map is shown in fig. 2, which can be displayed by a relationship map display device, when obtaining basic information data (basic information of the virus-related personnel), behavior trace data (railway data, lodging data, and internet surfing data) of the virus-related personnel (see tables 11-13), the frequency of contact between highly suspected virus-related personnel information and the virus-related personnel (frequency of riding, frequency of lodging and frequency of internet surfing) output according to the preset intelligent algorithm of the present invention, to obtain the information of the close relationship between the virus-related personnel, to form the relationship map of the suspected virus-related personnel, wherein the center of the map is the virus-inhaling personnel, the arrow points to other persons associated with the virus-inhaling personnel, the specific relationship network analysis can be performed for the virus-related personnel according to the arrow points and the relationship between the virus-inhaling personnel, and the relationship between different virus-inhaling personnel can be combined, to facilitate further relational analysis.
The method of the invention can combine a large amount of data analysis and information platform data according to the actual data analysis and working experience, describe the personal characteristics, group characteristics and behavior characteristics of the suspected persons by a statistical analysis method in the data analysis process, so as to obtain the suspected suspicion of the unscented non-persons and provide an accurate decision for the suspected persons.
Fig. 3 is a schematic structural diagram of an information processing apparatus according to an embodiment of the present invention, which may be implemented by software and/or hardware, generally integrated in an intelligent terminal, and may be implemented by an information processing method. As shown in the figure, the present embodiment may provide an information processing apparatus based on the above embodiments, which mainly includes an information collecting module 310, a statistical analysis module 320, and an output display module 330.
The information acquisition module 310 is configured to acquire, according to an identity of a person involved in a virus, associated information related to the person involved in the virus, where the identity of the person involved in the virus is unique;
the statistical analysis module 320 is configured to perform statistical analysis on the association information according to a preset intelligent algorithm to obtain an analysis result, and construct a relationship map of the suspected person according to the analysis result;
the output display module 330 is configured to determine an identity of a suspected person according to the relationship graph, and output a list of suspected persons with a virus-related behavior.
More specifically, the information processing apparatus of the present invention can be further expressed as the information processing system shown in fig. 4, the data collector 1 corresponds to the information collecting module 310, the virus-related analyzer corresponds to the statistical analysis module 320, the relationship diagram displayer corresponds to the output display module 330, and the data storage is used for storing various collected information.
For convenience of description, the above devices are described as being divided into various modules by functions, and are described separately. Of course, the functionality of the modules may be implemented in the same one or more software and/or hardware implementations in implementing one or more embodiments of the present description.
The apparatus in the foregoing embodiment is used to implement the corresponding information processing method in any of the foregoing embodiments, and has the beneficial effects of the corresponding method embodiment, which are not described herein again.
Based on the same inventive concept, corresponding to any of the above-mentioned embodiments, one or more embodiments of the present specification further provide an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, the information processing method according to any of the above-mentioned embodiments is implemented.
Fig. 5 is a schematic diagram illustrating a more specific hardware structure of an electronic device according to this embodiment, where the electronic device may include: a processor 1010, a memory 1020, an input/output interface 1030, a communication interface 1040, and a bus 1050. Wherein the processor 1010, memory 1020, input/output interface 1030, and communication interface 1040 are communicatively coupled to each other within the device via bus 1050.
The processor 1010 may be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an Application Specific Integrated Circuit (ASIC), or one or more Integrated circuits, and is configured to execute related programs to implement the technical solutions provided in the embodiments of the present disclosure.
The Memory 1020 may be implemented in the form of a ROM (Read Only Memory), a RAM (Random Access Memory), a static storage device, a dynamic storage device, or the like. The memory 1020 may store an operating system and other application programs, and when the technical solution provided by the embodiments of the present specification is implemented by software or firmware, the relevant program codes are stored in the memory 1020 and called to be executed by the processor 1010.
The input/output interface 1030 is used for connecting an input/output module to input and output information. The i/o module may be configured as a component in a device (not shown) or may be external to the device to provide a corresponding function. The input devices may include a keyboard, a mouse, a touch screen, a microphone, various sensors, etc., and the output devices may include a display, a speaker, a vibrator, an indicator light, etc.
The communication interface 1040 is used for connecting a communication module (not shown in the drawings) to implement communication interaction between the present apparatus and other apparatuses. The communication module can realize communication in a wired mode (such as USB, network cable and the like) and also can realize communication in a wireless mode (such as mobile network, WIFI, Bluetooth and the like).
It should be noted that although the above-mentioned device only shows the processor 1010, the memory 1020, the input/output interface 1030, the communication interface 1040 and the bus 1050, in a specific implementation, the device may also include other components necessary for normal operation. In addition, those skilled in the art will appreciate that the above-described apparatus may also include only those components necessary to implement the embodiments of the present description, and not necessarily all of the components shown in the figures.
The electronic device of the foregoing embodiment is used to implement the corresponding information processing method in any of the foregoing embodiments, and has the beneficial effects of the corresponding method embodiment, which are not described herein again.
Based on the same inventive concept, corresponding to any of the above-described embodiment methods, one or more embodiments of the present specification further provide a non-transitory computer-readable storage medium storing computer instructions for causing the computer to execute the information processing method according to any of the above-described embodiments.
Computer-readable media of the present embodiments, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device.
The computer instructions stored in the storage medium of the foregoing embodiment are used to enable the computer to execute the information processing method according to any one of the foregoing embodiments, and have the beneficial effects of the corresponding method embodiment, which are not described herein again.
Those of ordinary skill in the art will understand that: the discussion of any embodiment above is meant to be exemplary only, and is not intended to intimate that the scope of the disclosure, including the claims, is limited to these examples; within the spirit of the present disclosure, features from the above embodiments or from different embodiments may also be combined, steps may be implemented in any order, and there are many other variations of different aspects of one or more embodiments of the present description as described above, which are not provided in detail for the sake of brevity.
In addition, well-known power/ground connections to Integrated Circuit (IC) chips and other components may or may not be shown in the provided figures, for simplicity of illustration and discussion, and so as not to obscure one or more embodiments of the disclosure. Furthermore, devices may be shown in block diagram form in order to avoid obscuring the understanding of one or more embodiments of the present description, and this also takes into account the fact that specifics with respect to implementation of such block diagram devices are highly dependent upon the platform within which the one or more embodiments of the present description are to be implemented (i.e., specifics should be well within purview of one skilled in the art). Where specific details (e.g., circuits) are set forth in order to describe example embodiments of the disclosure, it should be apparent to one skilled in the art that one or more embodiments of the disclosure can be practiced without, or with variation of, these specific details. Accordingly, the description is to be regarded as illustrative instead of restrictive.
While the present disclosure has been described in conjunction with specific embodiments thereof, many alternatives, modifications, and variations of these embodiments will be apparent to those of ordinary skill in the art in light of the foregoing description. For example, other memory architectures (e.g., dynamic ram (dram)) may use the discussed embodiments.
It is intended that the one or more embodiments of the present specification embrace all such alternatives, modifications and variations as fall within the broad scope of the appended claims. Therefore, any omissions, modifications, substitutions, improvements, and the like that may be made without departing from the spirit and principles of one or more embodiments of the present disclosure are intended to be included within the scope of the present disclosure.
Claims (10)
1. An information processing method characterized by comprising:
acquiring related information related to the virus-involved personnel according to the identity of the virus-involved personnel, wherein the identity of the virus-involved personnel is unique;
performing statistical analysis on the associated information according to a preset intelligent algorithm to obtain an analysis result, and constructing a relationship map of suspected personnel according to the analysis result;
and determining the identity of the suspected personnel according to the relationship map, and outputting a list of the suspected personnel with the virus-related behavior.
2. The method according to claim 1, wherein the performing statistical analysis on the associated information according to a preset intelligent algorithm to obtain an analysis result, and constructing a relationship map of the suspected person according to the analysis result comprises:
performing binary classification and logistic regression classification on the associated information, and analyzing by adopting a machine learning algorithm, wherein the method comprises the following steps:
determining an optimal objective function:
wherein z denotes a linear function, g (z) is a probability value of a last output sample class, and when a set threshold value is 0.5, g (z) results in 1 when being greater than or equal to 0.5 and results in 0 when being less than 0.5;
after classification, determining an optimal linear function model:
wherein x is an input identity of a related person, theta is an optimal parameter of x, and T is a parameter matrix;
combining said equations (1) and (2) to construct a prediction function and determine a loss function:
P(y|x；θ)＝(hθ(x))y(1-hθ(x))1-yformula (4)
Wherein P is the probability value of the sample data,
determining a log-likelihood function:
equation (5) returns the category 1 or 0 of the input sample data, where 1 represents suspect and 0 is not suspect.
3. The method of claim 1, wherein the association information comprises:
at least one of mobile phone information, WeChat information, QQ information, Internet surfing personnel information, railway network information and accommodation information of the virus-involved personnel.
4. The method of claim 1, further comprising:
performing correlation collision with the correlation information of the selected non-virus-related personnel according to the correlation information of the virus-related personnel;
and outputting a suspected personnel list with the virus-related behavior according to the collision result.
5. The method of claim 4, wherein the performing the correlation collision with the correlation information of the selected non-virus-related person according to the correlation information of the virus-related person comprises:
determining the identity of non-virus-related personnel related to the virus-related personnel from the related information of the virus-related personnel, and determining the related information of the non-virus-related personnel according to the identity;
and performing correlation collision on the correlation information of the related non-virus-involved persons to obtain the important features of the suspected persons, wherein the correlation collision at least comprises one of union set, intersection set, difference set, deviation and data cleaning of the correlation information.
6. The method of claim 5, further comprising:
determining whether the risk degree of the suspected personnel is greater than a risk threshold value or not by combining the correlation collision result of the suspected personnel and the correlation information with higher activity of the suspected personnel;
and triggering alarm information when the risk degree of the suspected personnel is greater than a risk threshold value, and sending the alarm to an intranet.
7. An information processing apparatus characterized in that the apparatus comprises:
the information acquisition module is used for acquiring related information related to the virus-related personnel according to the identification of the virus-related personnel, and the identification of the virus-related personnel has uniqueness;
the statistical analysis module is used for performing statistical analysis on the associated information according to a preset intelligent algorithm to obtain an analysis result and constructing a relationship map of suspected personnel according to the analysis result;
and the output display module is used for determining the identity of suspected personnel according to the relationship map and outputting a list of suspected personnel with the virus-related behavior.
8. The apparatus of claim 7, further comprising:
the collision module is used for performing correlation collision with the correlation information of the selected non-virus-related personnel according to the correlation information of the virus-related personnel; and
and outputting a suspected personnel list with the virus-related behavior according to the collision result.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the information processing method according to any one of claims 1 to 6 when executing the program.
10. A non-transitory computer-readable storage medium storing computer instructions for causing a computer to execute the information processing method according to any one of claims 1 to 6.
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