CN116934546A - Police condition detection method and device, electronic equipment and storage medium - Google Patents
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Abstract
The application relates to a method, a device, electronic equipment and a storage medium for detecting alarm conditions, which relate to the technical field of computers and comprise the following steps: acquiring a first case basic letter of a target case entity; acquiring a target thinking guide diagram corresponding to a target case entity, wherein the target thinking guide diagram comprises N-level nodes, the front N-1-level nodes correspondingly acquire detection results of current-level nodes and/or prompt information of lower-level nodes, the prompt information is used for prompting a detection strategy corresponding to the lower-level nodes of a user, and the N-level nodes correspondingly acquire target detection results; and generating a target detection result corresponding to the target case entity based on the first case basic information of the target case entity and the target thinking guide graph corresponding to the target case entity. The method, the device, the electronic equipment and the storage medium for detecting the police situation can realize information management of case detection and improve case detection efficiency.
Description
Technical Field
The present application relates to the field of computer technologies, and in particular, to a method, an apparatus, an electronic device, and a storage medium for detecting a warning situation.
Background
The traditional case investigation system usually records the file condition of the case, can partially realize the informatization management of the case and realize the aim of the actual case, but often has no mature system in the case investigation direction to support, the sources of the information are mutually independent, the verification workload of the information is large, and the information collection is incomplete. Therefore, the investigation clue analysis is mainly performed by personal experience of the polices for data analysis. Along with the thinking that criminal investigation affairs advocate informatization leading investigation, at present combine together computer technology, case data information, three kinds of techniques of criminal investigation business to reach the purpose of quick case-breaking, with the problem that the traditional clue analysis and case-breaking technique have inefficiency.
Therefore, how to provide a case online detection processing method capable of realizing case detection informatization management and improving case detection efficiency is a technical problem to be solved at present.
Disclosure of Invention
In order to solve at least one of the above technical problems, the present application provides a method, an apparatus, an electronic device, and a storage medium for detecting a warning condition.
In a first aspect, the present application provides a method for detecting a warning condition, which adopts the following technical scheme:
A method for alert detection, comprising:
acquiring first case basic information of a target case entity;
acquiring a target thinking guide diagram corresponding to a target case entity, wherein the target thinking guide diagram comprises N-level nodes, the front N-1-level nodes correspondingly acquire detection results of current-level nodes and/or prompt information of lower-level nodes, the prompt information of the lower-level nodes is used for prompting a user of a detection strategy corresponding to the lower-level nodes, and the N-level nodes correspondingly acquire target detection results;
and generating a target detection result corresponding to the target case entity based on the first case basic information of the target case entity and the target thinking guide graph corresponding to the target case entity.
In one possible implementation manner, the previous N-1 level node correspondingly obtains a detection result of the current level node and prompt information of a lower level node, or the previous N-1 level node correspondingly obtains a detection result of the current level node; the generating a target detection result corresponding to the target case entity based on the first case basic information of the target case entity and the target thought guide graph corresponding to the target case entity includes:
acquiring second case basic information corresponding to a target case entity through the target thinking guide graph and based on the first case basic information, wherein the first case basic information and the second case basic information are used as entity characteristics of the target case entity;
Performing entity feature matching through the target thinking guide graph and based on the entity features of the target case entity to obtain a matching result, wherein the matching result comprises a history case matched with the entity features of the target case entity;
carrying out case serial-parallel prediction through the target thinking guide graph and based on the matching result to obtain a case serial-parallel prediction result;
and determining a target investigation result corresponding to the target case entity through the target thinking guide graph and based on the case serial-parallel prediction result.
In another possible implementation manner, based on the first case basic information, obtaining second case basic information corresponding to the target case entity includes:
acquiring second case basic information corresponding to a target case entity from a preset case system based on the first case basic information;
identifying whether the acquired second case basic information is sufficient;
if insufficient, generating and outputting prompt information, wherein the prompt information is used for prompting a user of second case basic information to be supplemented;
and acquiring second case basic information input by the user based on the prompt information.
In another possible implementation manner, performing entity feature matching based on the entity features of the target case entity to obtain a matching result, including:
Performing case type matching based on the entity characteristics of the target case entity to obtain a case type matching result, wherein the case type matching result comprises historical cases matched with the case type characteristics of the target case entity;
and carrying out case type matching based on a case type matching result to obtain the matching result, wherein the matching result comprises the historical cases matched with the case type characteristics and the case type characteristics of the target case entity.
In another possible implementation manner, based on the matching result, case serial-parallel prediction is performed, including:
and carrying out case serial-parallel prediction based on the matching result and through the entity characteristics of the target case entity.
In another possible implementation manner, based on the matching result and through the entity characteristics of the target case entity, case serial-parallel prediction is performed, including:
and if the entity characteristics of the target case entity comprise the service identification number, carrying out serial-parallel prediction based on the matching result and through the service identification number.
In another possible implementation manner, the determining, based on the case serial-parallel prediction result, the target detection result corresponding to the target case entity includes:
Carrying out suspicious data identification from the case serial-parallel prediction result;
if suspicious persons are identified, carrying out relationship strength calculation based on the suspicious persons to obtain the relationship person with the strongest relationship strength;
if the suspicious relation service identification number is identified, carrying out relation strength calculation based on the suspicious relation service identification number to obtain a relation person with the strongest relation strength;
if the suspicious vehicle is identified, calculating the relationship strength based on the suspicious vehicle information to obtain the relationship person with the strongest relationship strength.
In another possible implementation manner, the obtaining the target mind map corresponding to the target case entity includes any one of the following:
acquiring a target thinking guide diagram corresponding to a target case entity based on first case basic information of the target case entity;
when the selection operation of the user for the mind map is detected, determining the target mind map corresponding to the target case entity based on the selection operation.
In a second aspect, the present application provides a device for detecting a warning condition, which adopts the following technical scheme:
an alarm condition detection device, comprising:
the first acquisition module is used for acquiring first case basic information of the target case entity;
The second acquisition module is used for acquiring a target thinking guide diagram corresponding to a target case entity, wherein the target thinking guide diagram comprises N-level nodes, the front N-1 level node correspondingly acquires a detection result of a current level node and/or prompt information of a lower level node, the prompt information of the lower level node is used for prompting a user of a detection strategy corresponding to the lower level node, and the N-level node correspondingly acquires a target detection result;
the generation module is used for generating a target detection result corresponding to the target case entity based on the first case basic information of the target case entity and the target thought guide graph corresponding to the target case entity.
In one possible implementation manner, the previous N-1 level node correspondingly obtains a detection result of the current level node and prompt information of a lower level node, or the previous N-1 level node correspondingly obtains a detection result of the current level node; the generation module is specifically configured to, when generating a target detection result based on the first case basic information of the target case entity and the target thought guide graph corresponding to the target case entity:
acquiring second case basic information corresponding to a target case entity through the target thinking guide graph and based on the first case basic information, wherein the first case basic information and the second case basic information are used as entity characteristics of the target case entity;
Performing entity feature matching through the target thinking guide graph and based on the entity features of the target case entity to obtain a matching result, wherein the matching result comprises a history case matched with the entity features of the target case entity;
carrying out case serial-parallel prediction through the target thinking guide graph and based on the matching result to obtain a case serial-parallel prediction result;
and determining a target investigation result corresponding to the target case entity through the target thinking guide graph and based on the case serial-parallel prediction result.
In another possible implementation manner, the generating module is specifically configured to, when acquiring the second case basic information corresponding to the target case entity based on the first case basic information:
acquiring second case basic information corresponding to a target case entity from a preset case system based on the first case basic information;
identifying whether the acquired second case basic information is sufficient;
if insufficient, generating and outputting prompt information, wherein the prompt information is used for prompting a user of second case basic information to be supplemented;
and acquiring second case basic information input by the user based on the prompt information.
In another possible implementation manner, the generating module is specifically configured to, when performing entity feature matching based on the entity feature of the target case entity to obtain a matching result:
performing case type matching based on the entity characteristics of the target case entity to obtain a case type matching result, wherein the case type matching result comprises historical cases matched with the case type characteristics of the target case entity;
and carrying out case type matching based on the case type matching result to obtain the matching result, wherein the matching result comprises historical cases matched with case type characteristics and case type characteristics of the target case entity.
In another possible implementation manner, the generating module is specifically configured to, when performing case serial-parallel prediction based on the matching result:
and carrying out case serial-parallel prediction based on the matching result and through the entity characteristics of the target case entity.
In another possible implementation manner, the generating module is specifically configured to, when performing case serial-parallel prediction based on the matching result and through the entity characteristics of the target case entity:
and if the entity characteristics of the target case entity comprise the service identification number, carrying out serial-parallel prediction based on the matching result and through the service identification number.
In another possible implementation manner, the generating module is specifically configured to, when determining, based on a case serial-parallel prediction result, a target investigation result corresponding to the target case entity:
carrying out suspicious data identification from the case serial-parallel prediction result;
if suspicious persons are identified, carrying out relationship strength calculation based on the suspicious persons to obtain the relationship person with the strongest relationship strength;
if the suspicious relation service identification number is identified, carrying out relation strength calculation based on the suspicious relation service identification number to obtain a relation person with the strongest relation strength;
if the suspicious vehicle is identified, calculating the relationship strength based on the suspicious vehicle information to obtain the relationship person with the strongest relationship strength.
In another possible implementation manner, the second obtaining module is specifically configured to, when obtaining the target mind map corresponding to the target case entity, any one of the following:
acquiring a target thinking guide diagram corresponding to a target case entity based on first case basic information of the target case entity;
when the selection operation of the user for the mind map is detected, determining the target mind map corresponding to the target case entity based on the selection operation.
In a third aspect, the present application provides an electronic device, which adopts the following technical scheme:
an electronic device, the electronic device comprising:
at least one processor;
a memory;
at least one application program, wherein the at least one application program is stored in the memory and configured to be executed by the at least one processor, the at least one application program configured to: executing the alarm condition detection method.
In a fourth aspect, the present application provides a computer readable storage medium, which adopts the following technical scheme:
a computer-readable storage medium, comprising: a computer program is stored that can be loaded by a processor and that performs the above-described alert detection method.
In summary, the present application includes at least one of the following beneficial technical effects:
compared with the related technology, the method, the device, the electronic equipment and the storage medium acquire the first case basic information of the target case entity and the target thinking guide diagram corresponding to the target case entity, and can acquire case detection results corresponding to each level of node and/or detection strategies of the lower level of node based on the first case basic information of the target case entity and through detection thought of each level of node in the target thinking guide diagram because the target thinking guide diagram comprises N levels of nodes, and further can finally acquire the target detection results corresponding to the target case entity to assist in rapid case breaking, thereby realizing case investigation informatization management and further improving case investigation efficiency.
Drawings
FIG. 1 is a flow chart of a method for alarm detection according to an embodiment of the present application;
FIG. 2a is a flowchart illustrating another method for alarm detection according to an embodiment of the present application;
fig. 2b is a schematic diagram corresponding to a prompt message provided in an embodiment of the present application for prompting a user to input basic information of a second case;
FIG. 2c is a schematic illustration of the thought of a telecommunications fraud case provided by an embodiment of the present application;
FIG. 3 is a schematic diagram of an apparatus for alarm detection according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
The present application will be described in further detail with reference to the accompanying drawings.
The present embodiment is only for explanation of the present application and is not to be construed as limiting the present application, and modifications to the present embodiment, which may not creatively contribute to the present application as required by those skilled in the art after reading the present specification, are all protected by patent laws within the scope of claims of the present application.
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments of the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
In addition, the term "and/or" herein is merely an association relationship describing an association object, and means that three relationships may exist, for example, a and/or B may mean: a exists alone, A and B exist together, and B exists alone. In this context, unless otherwise specified, the term "/" generally indicates that the associated object is an "or" relationship.
Embodiments of the application are described in further detail below with reference to the drawings.
The embodiment of the application provides a warning condition detection method which is executed by electronic equipment, wherein the electronic equipment can be a server or terminal equipment, and the server can be an independent physical server, a server cluster or a distributed system formed by a plurality of physical servers, or a cloud server for providing cloud computing service. The terminal device may be a smart phone, a tablet computer, a notebook computer, a desktop computer, etc., but is not limited thereto, and the terminal device and the server may be directly or indirectly connected through a wired or wireless communication manner, which is not limited herein.
Further, as shown in fig. 1, the method may include:
Step S101, acquiring first case basic information of a target case entity.
For the embodiment of the application, the first case basic information of the target case entity input by the user is acquired, and in the embodiment of the application, the first case basic information of the target case entity input by the user in a voice or text mode can be acquired.
The first case basic information of the target case entity may include: at least one of name of the case report person, reason for reporting the case, etc.
Step S102, obtaining a target thinking guide diagram corresponding to the target case entity.
The target thinking guide graph comprises N-level nodes, the front N-1-level nodes correspondingly obtain detection results of the current-level nodes and/or prompt information of lower-level nodes, the prompt information of the lower-level nodes is used for prompting a detection strategy corresponding to the lower-level nodes of a user, and the N-level nodes correspondingly obtain target detection results. In the embodiment of the application, each node can represent an entity, and the entity can be used for guiding the electronic equipment to carry out alarm condition detection.
For example, the target thinking guide graph comprises 4-level nodes, each level node can represent an entity, the electronic equipment is guided to carry out alarm condition detection, the first 1-3 levels of nodes correspondingly obtain detection results of each level of nodes and/or prompt information of lower level of nodes, and the 4-level nodes correspondingly obtain target detection results.
Specifically, in the embodiment of the present application, the obtaining the target thought guide map corresponding to the target case entity may specifically include: based on the first case basic information of the target case entity, acquiring a target mind map corresponding to the target case entity, or determining the target mind map corresponding to the target case entity based on the selection operation when the selection operation of the user on the mind map is detected. In the embodiment of the application, when the first case basic information of the target case entity is obtained, the case type corresponding to the first case basic information can be determined, the target thinking guide diagram corresponding to the target case entity can be determined based on the determined case type, and the target thinking guide diagram corresponding to the target case entity can be determined based on the selection operation of the user.
It should be noted that, step S101 may be performed before step S102, may be performed after step S102, or may be performed simultaneously with step S102, which is not limited in the embodiment of the present application, and fig. 1 is only one possible implementation and is not limited to the embodiment of the present application.
Step S103, generating a target detection result based on the first case basic information of the target case entity and the target thinking guide diagram corresponding to the target case entity.
For the embodiment of the application, after the first case basic information of the target case entity and the target thinking guide diagram corresponding to the target case entity are obtained, the electronic equipment is guided to carry out alarm condition detection according to the entity corresponding to each level of node, so as to obtain the detection result corresponding to each level of node and/or the prompt information corresponding to the next level of node, and the detection result corresponding to the last level of node is the target detection result. In the embodiment of the application, only the target investigation result corresponding to the target case entity can be directly output, and the investigation result corresponding to each level node in the N-1 level node and/or the prompt information of the lower level node and the investigation result corresponding to the N level node, namely the target investigation result corresponding to the target case entity, can be output.
It should be noted that, if the first N-1 level node of the target thinking guide graph can correspondingly obtain the investigation result of the current level node and the prompt information of the next level node, or the first N-1 level node of the target thinking guide graph can correspondingly obtain the investigation result of the current level node, in the process of generating the target investigation result based on the first case basic information of the target case entity and the target thinking guide graph corresponding to the target case entity, the electronic device can be guided to carry out alert detection to obtain the target investigation result; if the first N-1 level node of the target thinking guide graph only correspondingly obtains the prompt information of the lower level node, the user can also carry out alarm condition detection based on the prompt information, and finally, a target investigation result corresponding to the target case is obtained.
Further, in the embodiment of the application, based on the first case basic information of the target case entity and the target thinking guide diagram corresponding to the target case entity, in the process of generating the target investigation result, as each level of nodes in the target thinking guide diagram can correspondingly generate each level of the investigation result, instead of only giving clues or prompt information, the user (police officer) searches from other systems again, so that the time of the user (police officer) can be saved, and the efficiency of case investigation can be further improved.
Further, compared with the related technology, the embodiment of the application provides a warning situation detection method, and compared with the related technology, the method and the device for detecting the warning situation, the first case basic information of the target case entity and the target thinking guide diagram corresponding to the target case entity are obtained, and because the target thinking guide diagram comprises N-level nodes, based on the first case basic information of the target case entity and through the detection thought of each level of nodes in the target thinking guide diagram, the case detection result corresponding to each level of nodes and/or the detection policy of the lower level of nodes can be obtained, and further, the target detection result corresponding to the target case entity can be finally obtained to assist in rapid case breaking, thereby realizing case detection informatization management and further improving case detection efficiency.
Further, the target mind map may include N levels of nodes, each level of node may correspond to a warning situation detection mode, and the warning situation detection mode is used for guiding the electronic device to perform warning situation detection, in the embodiment of the present application, the warning situation detection mode may be represented by a behavior entity, and in one possible implementation manner, for a telecom fraud case, the warning situation detection mode corresponding to the first level of node may include: according to the embodiment of the application, after obtaining the first case basic information, the electronic device may obtain second case basic information corresponding to the target case entity according to the guidance of the corresponding level node in the target thinking guide graph, that is, the following step S1031 is corresponding, and the alert condition detection mode corresponding to the second level node may include: in the embodiment of the present application, after obtaining the first case basic information and the second case basic information (i.e., the physical characteristics of the target case entity), the electronic device may perform the physical characteristic matching according to the guidance of the corresponding level node in the target thinking guide graph, so as to obtain a matching result, that is, corresponding to the following step S1032, where the alert condition detection mode corresponding to the third level node may include: in the embodiment of the present application, after obtaining the matching result, the electronic device may conduct case serial-parallel prediction according to guidance of the corresponding level node in the target mind map to obtain a case serial-parallel prediction result, that is, corresponding to the following step S1033, a case serial-parallel prediction mode corresponding to the fourth level node may include: through the target thinking guide graph and based on the case serial-parallel prediction result, the target detection result is determined, and in the embodiment of the application, after the case serial-parallel prediction result is obtained, the electronic device can determine the target detection result corresponding to the telecommunication fraud case according to the guidance of the corresponding level node in the target thinking guide graph, that is, the following step S1034 is corresponding.
Specifically, as described above, the target mind map corresponding to the target case entity is used to guide the electronic device to execute the following steps S1031-S1034, that is, the generating, in step S103, the target detection result corresponding to the target case entity based on the first case basic information of the target case entity and the target mind map corresponding to the target case entity may specifically include: step S1031, step S1032, step S1033, and step S1034, as shown in fig. 2a, wherein,
step S1031, obtaining second case basic information corresponding to the target case entity through the target thinking guide diagram and based on the first case basic information.
For the embodiment of the application, after the first case basic information input by the user is obtained, the second case basic information corresponding to the target case entity input by the user can be obtained; and after the first case basic information input by the user is obtained, second case basic information corresponding to the target case entity can be directly obtained from other systems.
Specifically, after the first case basic information input by the user is obtained, the second case basic information corresponding to the target case entity input by the user may be obtained, which specifically includes: after the first case basic information input by the user is obtained, the electronic equipment is guided to identify whether the first case basic information is sufficient, if not, prompt information is generated and output to prompt the user to input second case basic information corresponding to the target case entity, and then after the second case basic information input by the user is obtained, the second case basic information corresponding to the target case entity input by the user is directly obtained. For example, after the first case basic information (name of the case report person and reason of the case report) input by the user is obtained, the guiding electronic device recognizes that the first case basic information is insufficient, and then outputs prompt information to prompt the user to input second case basic information (for example, prompt the user to input a case occurrence place and a case occurrence time), where a form corresponding to prompt information prompting the user to input the second case basic information corresponding to the target case entity is shown in fig. 2 b.
Further, after the first case basic information input by the user is obtained, second case basic information corresponding to the target case entity input by the user may be obtained, and specifically further include: after the first case basic information input by the user is obtained, the electronic equipment is guided to generate and output prompt information through the target thinking guide graph so as to prompt the user to input second case basic information corresponding to the target case entity. For example, the first case basic information may include: the name of the case report person, the reason of the case report, and the case report identity information, the second case basic information may include: when the first case basic information (namely, name of case report person, reason of case report and identity information of case report person) input by the user is obtained, the prompt information is output to prompt the user to input the second case information (namely, case place and case time).
Specifically, after the first case basic information input by the user is obtained, obtaining second case basic information corresponding to the target case entity from other systems may specifically include: after the first case basic information input by the user is obtained, the corresponding electronic equipment can be guided to identify whether the first case basic information is sufficient or not through the target thinking guide graph, and if the first case basic information is insufficient, the electronic equipment is guided to acquire second case basic information corresponding to the target case entity from other systems; or after the first case basic information input by the user is obtained, the electronic equipment is directly guided to obtain second case basic information corresponding to the target case entity from other systems through the target thinking guide graph.
Specifically, based on the target case entity, acquiring the second case basic information corresponding to the target case entity may specifically include: acquiring second case basic information corresponding to a target case entity from a preset case system based on the first case basic information; identifying whether the acquired second case basic information is sufficient; if insufficient, generating and outputting prompt information; and acquiring second case basic information input by the user based on the prompt information. That is, in the embodiment of the present application, after the second case basic information corresponding to the target case entity is obtained from the preset system, the electronic device may be guided to identify the second case basic information through the target thought guide graph, so as to determine whether the second case basic information is sufficient, and if not, the electronic device may be further guided to generate and output the prompt information through the target thought guide graph, so as to prompt the user to continuously input the second case basic information.
Step S1032, performing entity feature matching through the target thinking guide graph and based on the entity features of the target case entity to obtain a matching result.
For the embodiment of the application, after the entity characteristics of the target case entity are obtained, determining the next-stage node in the target thinking guide graph, and guiding the electronic equipment to carry out entity characteristic matching based on the next-stage node. In the embodiment of the application, the first case basic information and the second case basic information are used as the entity characteristics of the target case entity. In the embodiment of the application, after the entity characteristics of the target case entity are obtained, the electronic equipment is guided to carry out entity characteristic matching with the historical case so as to obtain a matching result. In the embodiment of the application, the matching result comprises a history case matched with the entity characteristics of the target case entity.
Specifically, the entity characteristics of the target case entity may include: in the embodiment of the present application, based on the entity characteristics of the target case entity, the matching of the entity characteristics is performed to obtain a matching result, which may specifically include: case type matching is carried out based on the entity characteristics of the target case entity, so that a case type matching result is obtained, wherein the case type matching result comprises historical cases matched with the case type characteristics of the target case entity; and carrying out case type matching based on the case type matching result to obtain a matching result, wherein the matching result comprises historical cases matched with case type characteristics and case type characteristics of the target case entity.
For example, the case type feature may be a fraud case type, the case type feature may be a telecom fraud case type, and after obtaining the fraud case type and the telecom fraud case type contained in the entity feature of the target case entity, the electronic device is guided to match the historical case with the fraud case type from the historical cases, and then match the historical case with the telecom fraud case type from the historical cases with the fraud case type obtained by matching, that is, finally select the historical case with the fraud case type and the telecom fraud case type from the historical cases.
And step S1033, carrying out case serial-parallel prediction through the target thinking guide graph and based on the matching result, and obtaining a case serial-parallel prediction result.
For the embodiment of the application, after the matching result is obtained, determining the next-stage node based on the target thinking guide graph, and guiding the electronic equipment to conduct case serial-parallel prediction based on the next-stage node so as to obtain the case serial-parallel result. That is, after the historical cases matched with the case type features and the case category features of the target case entity are obtained through the above embodiment, the electronic device is guided to perform case serial-parallel prediction based on the matched historical cases based on the target thinking guide graph, so as to obtain a case serial-parallel prediction result.
Specifically, in the embodiment of the present application, based on the matching result, case serial-parallel prediction may specifically include: and carrying out case serial-parallel prediction based on the matching result and through the entity characteristics of the target case entity. In the embodiment of the application, the matching result comprises historical cases matched with the entity characteristics of the target case entity, each historical case can be used as a historical case entity, each historical case entity comprises the entity characteristics of the historical case entity, and the entity characteristics are matched based on the entity characteristics of the target case entity and the entity characteristics of each historical case entity so as to perform case serial-parallel prediction to obtain the historical case entity which is in serial-parallel connection with the target case entity.
For example, the physical characteristics of the target case entity and the physical characteristics of each history case entity include: case category characteristics and case making means characteristics, the history case entity includes: history case entity 1, history case entity 2, and history case entity 3; and carrying out entity characteristic matching on the case category characteristics and the case making means characteristics corresponding to the target case entity and the case category characteristics and the case making means characteristics corresponding to each historical case entity (the historical case entity 1, the historical case entity 2 and the historical case entity 3) so as to carry out case serial-parallel prediction to obtain the historical case entities carrying out case parallel prediction with the target case entity, such as the historical case entity 1 and the historical case entity 2.
Specifically, if the entity characteristics of the target case entity include the service identification number, performing case serial-parallel prediction based on the matching result and through the entity characteristics of the target case entity may specifically include: and carrying out serial-parallel prediction based on the matching result and through the service identification number. In the embodiment of the application, when the entity characteristics of the target case contain the service identification number entity characteristics, the serial-parallel prediction can be preferentially performed according to the service identification number entity characteristics and the history cases contained in the matching result. In an embodiment of the present application, the service identification number entity features may include: identity card number features and bank card number features.
Further, when the physical characteristics of the target case include the service identification number physical characteristics and other physical characteristics (for example, case category characteristics and case making means characteristics), case serial-parallel prediction may be performed only according to the service identification number physical characteristics, case serial-parallel prediction may also be performed according to other physical characteristics, and case serial-parallel prediction may also be performed according to the service identification number physical characteristics and other physical characteristics.
Step S1034, determining a target investigation result corresponding to the target case entity through the target thinking guide diagram and based on the case serial-parallel prediction result.
For the embodiment of the application, after the case serial-parallel prediction result is obtained, a corresponding next-stage node is determined based on the target thinking guide graph, and the electronic equipment is guided based on the next-stage node to determine the target investigation result corresponding to the target case entity based on the case serial-parallel prediction result.
For the embodiment of the present application, the target detection result may include: suspicious data (e.g., suspicious personal, suspicious relationship service identification numbers, suspicious vehicles, etc.), and those having the strongest relationship with the suspicious data.
Specifically, determining, based on the case serial-parallel prediction result, a target investigation result corresponding to the target case entity may specifically include: step S10341 (not shown), step S10342 (not shown), step S10343 (not shown), and step S10344 (not shown), wherein,
step S10341, identifying suspicious data from the case serial-parallel prediction result.
For the embodiment of the application, the case serial-parallel prediction result comprises: after the case serial-parallel prediction result is obtained, the electronic equipment is guided to identify suspicious data from the case serial-parallel prediction result so as to identify suspicious personnel, suspicious relation service identification numbers and/or suspicious vehicles.
Step S10342, if suspicious persons are identified, calculating the relationship strength based on the suspicious persons to obtain the relationship person with the strongest relationship strength.
Specifically, in the embodiment of the application, if the suspicious person is identified, the electronic equipment is guided to calculate the relationship strength based on the suspicious person, so as to obtain the relationship person with the strongest relationship strength with the identified suspicious person, and the relationship person with the strongest relationship strength is output. In the embodiment of the application, the number of the relational personnel with the strongest relation strength finally obtained can be one or at least two.
And step S10343, if the suspicious relationship service identification number is identified, carrying out relationship strength calculation based on the suspicious relationship service identification number to obtain the relationship person with the strongest relationship strength.
Specifically, in the embodiment of the application, if the suspicious relationship service identification number is identified, the electronic equipment is guided to calculate the relationship strength based on the suspicious relationship service identification number, so as to obtain the relationship person with the strongest relationship strength with the identified suspicious relationship service identification number. In the embodiment of the application, the number of the relational personnel with the strongest relation strength finally obtained can be one or at least two.
And step S10344, if the suspicious vehicle is identified, calculating the relationship strength based on the suspicious vehicle information to obtain the relationship person with the strongest relationship strength.
Specifically, in the embodiment of the application, if the suspicious vehicle is identified, the electronic equipment is guided to perform relationship strength calculation based on the identified suspicious vehicle information, so as to obtain the relationship person with the strongest relationship with the identified suspicious vehicle. In the embodiment of the application, the number of the relational personnel with the strongest relation strength finally obtained can be one or at least two.
It should be noted that, all of the steps S10342, S10343, and S10344 may be performed, that is, when the suspicious person, the suspicious relationship service identification number, and the suspicious vehicle are identified from the case serial-parallel result, the steps S10342, S10343, and S10434 may be performed, where the steps S10342, S10343, and S10434 may be performed simultaneously or may not be performed simultaneously, and when the steps S10342, S10343, and S10434 are not performed simultaneously, the execution sequence of the steps S10342, S10343, and S10434 is not limited in the embodiment of the present application; step S10342, step S10343, and step S10344 may be performed only by one or two steps, for example, if only suspicious persons are identified, step S10342 may be performed, if suspicious persons and suspicious vehicles are identified, step S10342 and step S10344 may be performed, in the embodiment of the present application, step S10342 may be performed before step S10344, may be performed after step S10344, or may be performed simultaneously with step S10344.
Further, on the basis of the above embodiment, a manner of guiding the telecom fraud case to perform alert detection by using the mind map is described in detail, where the mind map may include three levels of nodes, and the behavior entity corresponding to the first level of nodes is used to guide the electronic device to obtain complete case basic information, for example, obtain second case basic information based on the first case basic information, where the level of nodes correspondingly obtain the physical characteristics of the target case; the behavior entity corresponding to the second-level node is used for guiding the electronic equipment to perform serial-parallel detection (including case serial-parallel detection through the service mark number and/or case-like serial-parallel detection), namely if the entity behavior feature of the target case contains the service mark number, the electronic equipment can be guided to perform serial-parallel detection based on the service mark number, and the serial-parallel detection can also be performed according to the case type and/or the case making means; and the behavior entity corresponding to the third-level node is used for guiding the electronic equipment to determine a detection clue, namely, if the suspicious crime personnel are identified from the case serial-parallel result, performing close relation calculation to obtain the relation personnel with the strongest relation strength, if the suspicious relation service identification number is identified from the case serial-parallel result, performing close relation calculation to obtain the relation personnel with the strongest relation strength, and if the suspicious motor vehicle is identified from the case serial-parallel result, performing close relation calculation to obtain the relation personnel with the strongest relation, wherein the thinking guide diagram corresponding to the telecommunication fraud case is shown in fig. 2 b.
The foregoing embodiments describe a method for detecting a warning situation from the aspect of a method flow, and the following embodiments describe a device for detecting a warning situation from the aspect of a device structure, which are described in detail in the following embodiments.
An embodiment of the present application provides a device for detecting an alarm condition, as shown in fig. 3, the device 30 for detecting an alarm condition may include: a first acquisition module 31, a second acquisition module 32, and a generation module 33, wherein,
the first obtaining module 31 is configured to obtain first case basic information of the target case entity.
The second obtaining module 32 is configured to obtain a target mind map corresponding to the target case entity, where the target mind map includes N level nodes, the first N-1 level node corresponds to obtain a detection result of the current level node and/or a prompt message of a lower level node, the prompt message of the lower level node is used to prompt a user for a detection policy corresponding to the lower level node, and the nth level node corresponds to obtain the target detection result.
The generating module 33 is configured to generate a target detection result corresponding to the target case entity based on the first case basic information of the target case entity and the target thought guide map corresponding to the target case entity.
In one possible implementation manner of the embodiment of the application, the front N-1 level node correspondingly obtains the investigation result of the current level node and the prompt information of the lower level node, or the front N-1 level node correspondingly obtains the investigation result of the current level node; the generating module 33 is specifically configured to, when generating the target detection result corresponding to the target case entity based on the first case basic information of the target case entity and the target thought guide graph corresponding to the target case entity:
Acquiring second case basic information corresponding to a target case entity through the target thinking guide graph and based on the first case basic information, wherein the first case basic information and the second case basic information are used as entity characteristics of the target case entity;
carrying out entity characteristic matching through the target thinking guide graph based on the entity characteristics of the target case entity to obtain a matching result, wherein the matching result comprises a history case matched with the entity characteristics of the target case entity;
carrying out case serial-parallel prediction through the target thinking guide graph and based on the matching result to obtain a case serial-parallel prediction result;
and determining a target investigation result corresponding to the target case entity through the target thinking guide graph and based on the case serial-parallel prediction result.
In another possible implementation manner of the embodiment of the present application, when the generating module 33 obtains the second case basic information corresponding to the target case entity based on the first case basic information, the generating module is specifically configured to:
acquiring second case basic information corresponding to a target case entity from a preset case system based on the first case basic information;
identifying whether the acquired second case basic information is sufficient;
if the information is insufficient, generating and outputting prompt information, wherein the prompt information is used for prompting a user of second case basic information to be supplemented;
And acquiring second case basic information input by the user based on the prompt information.
In another possible implementation manner of the embodiment of the present application, the generating module 33 is specifically configured to, when performing entity feature matching based on the entity feature of the target case entity to obtain a matching result:
case type matching is carried out based on the entity characteristics of the target case entity, so that a case type matching result is obtained, wherein the case type matching result comprises historical cases matched with the case type characteristics of the target case entity;
and carrying out case type matching based on the case type matching result to obtain a matching result, wherein the matching result comprises historical cases matched with case type characteristics and case type characteristics of the target case entity.
In another possible implementation manner of the embodiment of the present application, the generating module 33 is specifically configured to:
and carrying out case serial-parallel prediction based on the matching result and through the entity characteristics of the target case entity.
In another possible implementation manner of the embodiment of the present application, the generating module 33 is specifically configured to, when performing case serial-parallel prediction based on the matching result and through the entity characteristics of the target case entity:
And if the entity characteristics of the target case entity contain the service identification numbers, carrying out serial-parallel prediction through the service identification numbers based on the matching result.
In another possible implementation manner of the embodiment of the present application, when determining the target investigation result corresponding to the target case entity based on the case serial-parallel prediction result, the generating module 33 is specifically configured to:
carrying out suspicious data identification from the case serial-parallel prediction result;
if suspicious persons are identified, carrying out relationship strength calculation based on the suspicious persons to obtain the relationship person with the strongest relationship strength;
if the suspicious relationship service identification number is identified, carrying out relationship strength calculation based on the suspicious relationship service identification number to obtain a relationship person with the strongest relationship strength;
if the suspicious vehicle is identified, calculating the relationship strength based on the suspicious vehicle information to obtain the relationship person with the strongest relationship strength.
In another possible implementation manner of the embodiment of the present application, the second obtaining module 32 is specifically configured to, when obtaining the target mind map corresponding to the target case entity, any one of the following:
acquiring a target thinking guide diagram corresponding to a target case entity based on first case basic information of the target case entity;
When the selection operation of the user for the mind map is detected, determining the target mind map corresponding to the target case entity based on the selection operation.
Compared with the related technology, the embodiment of the application acquires the first case basic information of the target case entity and the target thinking guide diagram corresponding to the target case entity, and the N-level nodes are contained in the target thinking guide diagram, so that the case detection result corresponding to each level of nodes and/or the detection strategy of the lower level of nodes can be obtained based on the first case basic information of the target case entity and through the detection thought of each level of nodes in the target thinking guide diagram, and further, the target detection result corresponding to the target case entity can be finally obtained to assist in quickly breaking cases, thereby realizing case detection information management and further improving case detection efficiency.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, and are not repeated herein.
In an embodiment of the present application, as shown in fig. 4, an electronic device is provided, as shown in fig. 4, and an electronic device 400 shown in fig. 4 includes: a processor 401 and a memory 403. Processor 401 is connected to memory 403, such as via bus 402. Optionally, the electronic device 400 may also include a transceiver 404. It should be noted that, in practical applications, the transceiver 404 is not limited to one, and the structure of the electronic device 400 is not limited to the embodiment of the present application.
The processor 401 may be a CPU (Central Processing Unit ), general purpose processor, DSP (Digital Signal Processor, data signal processor), ASIC (Application Specific Integrated Circuit ), FPGA (Field Programmable Gate Array, field programmable gate array) or other programmable logic device, transistor logic device, hardware components, or any combination thereof. Which may implement or perform the various exemplary logic blocks, modules and circuits described in connection with this disclosure. Processor 401 may also be a combination that implements computing functionality, such as a combination comprising one or more microprocessors, a combination of a DSP and a microprocessor, or the like.
Bus 402 may include a path to transfer information between the components. Bus 402 may be a PCI (Peripheral Component Interconnect, peripheral component interconnect standard) bus or EISA (Extended Industry Standard Architecture ) bus, among others. Bus 402 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one thick line is shown in fig. 4, but not only one bus or one type of bus.
The Memory 403 may be, but is not limited to, a ROM (Read Only Memory) or other type of static storage device that can store static information and instructions, a RAM (Random Access Memory ) or other type of dynamic storage device that can store information and instructions, an EEPROM (Electrically Erasable Programmable Read Only Memory ), a CD-ROM (Compact Disc Read Only Memory, compact disc Read Only Memory) or other optical disk storage, optical disk storage (including compact discs, laser discs, optical discs, digital versatile discs, blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer.
The memory 403 is used for storing application program codes for executing the inventive arrangements and is controlled to be executed by the processor 401. The processor 401 is arranged to execute application code stored in the memory 403 for implementing what is shown in the foregoing method embodiments.
Among them, electronic devices include, but are not limited to: mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and the like, and stationary terminals such as digital TVs, desktop computers, and the like. The electronic device shown in fig. 4 is only an example and should not be construed as limiting the functionality and scope of use of the embodiments of the application.
Embodiments of the present application provide a computer-readable storage medium having a computer program stored thereon, which when run on a computer, causes the computer to perform the corresponding method embodiments described above. Compared with the related art, the first case basic information of the target case entity and the target thinking guide diagram corresponding to the target case entity are obtained, and because the target thinking guide diagram comprises N levels of nodes, the case detection result corresponding to each level of nodes and/or the detection strategy of the lower level of nodes can be obtained based on the first case basic information of the target case entity and through the detection thought of each level of nodes in the target thinking guide diagram, and further the target detection result corresponding to the target case entity can be finally obtained to assist in rapid case breaking, thereby realizing case detection informatization management and further improving case detection efficiency.
It should be understood that, although the steps in the flowcharts of the figures are shown in order as indicated by the arrows, these steps are not necessarily performed in order as indicated by the arrows. The steps are not strictly limited in order and may be performed in other orders, unless explicitly stated herein. Moreover, at least some of the steps in the flowcharts of the figures may include a plurality of sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, the order of their execution not necessarily being sequential, but may be performed in turn or alternately with other steps or at least a portion of the other steps or stages.
The foregoing is only a partial embodiment of the present application, and it should be noted that it will be apparent to those skilled in the art that modifications and adaptations can be made without departing from the principles of the present application, and such modifications and adaptations are intended to be comprehended within the scope of the present application.
Claims (10)
1. A method for detecting an alert condition, comprising:
acquiring first case basic information of a target case entity;
acquiring a target thinking guide diagram corresponding to a target case entity, wherein the target thinking guide diagram comprises N-level nodes, the front N-1-level nodes correspondingly acquire detection results of current-level nodes and/or prompt information of lower-level nodes, the prompt information of the lower-level nodes is used for prompting a user of a detection strategy corresponding to the lower-level nodes, and the N-level nodes correspondingly acquire target detection results;
and generating a target detection result corresponding to the target case entity based on the first case basic information of the target case entity and the target thinking guide graph corresponding to the target case entity.
2. The method of claim 1, wherein the previous N-1 level node correspondingly obtains a investigation result of the current level node and a prompt message of a lower level node, or wherein the previous N-1 level node correspondingly obtains a investigation result of the current level node; the generating a target detection result corresponding to the target case entity based on the first case basic information of the target case entity and the target thought guide graph corresponding to the target case entity includes:
Acquiring second case basic information corresponding to a target case entity through the target thinking guide graph and based on the first case basic information, wherein the first case basic information and the second case basic information are used as entity characteristics of the target case entity;
performing entity feature matching through the target thinking guide graph and based on the entity features of the target case entity to obtain a matching result, wherein the matching result comprises a history case matched with the entity features of the target case entity;
carrying out case serial-parallel prediction through the target thinking guide graph and based on the matching result to obtain a case serial-parallel prediction result;
and determining a target investigation result corresponding to the target case entity through the target thinking guide graph and based on the case serial-parallel prediction result.
3. The method of claim 2, wherein obtaining second case basic information corresponding to a target case entity based on the first case basic information comprises:
acquiring second case basic information corresponding to a target case entity from a preset case system based on the first case basic information;
identifying whether the acquired second case basic information is sufficient;
If insufficient, generating and outputting prompt information, wherein the prompt information is used for prompting a user of second case basic information to be supplemented;
and acquiring second case basic information input by the user based on the prompt information.
4. A method according to claim 2 or 3, wherein performing entity feature matching based on the entity features of the target case entity to obtain a matching result comprises:
performing case type matching based on the entity characteristics of the target case entity to obtain a case type matching result, wherein the case type matching result comprises historical cases matched with the case type characteristics of the target case entity;
and carrying out case type matching based on the case type matching result to obtain the matching result, wherein the matching result comprises historical cases matched with case type characteristics and case type characteristics of the target case entity.
5. The method of claim 2, wherein performing case serial-parallel prediction based on the matching result comprises:
and carrying out case serial-parallel prediction based on the matching result and through the entity characteristics of the target case entity.
6. The method of claim 5, wherein the case serial-parallel prediction based on the matching result and through the entity characteristics of the target case entity comprises:
And if the entity characteristics of the target case entity comprise the service identification number, carrying out serial-parallel prediction based on the matching result and through the service identification number.
7. The method of claim 2, wherein determining a target investigation result corresponding to the target case entity based on the case serial-parallel prediction result comprises:
carrying out suspicious data identification from the case serial-parallel prediction result;
if suspicious persons are identified, carrying out relationship strength calculation based on the suspicious persons to obtain the relationship person with the strongest relationship strength;
if the suspicious relation service identification number is identified, carrying out relation strength calculation based on the suspicious relation service identification number to obtain a relation person with the strongest relation strength;
if the suspicious vehicle is identified, calculating the relationship strength based on the suspicious vehicle information to obtain the relationship person with the strongest relationship strength.
8. An apparatus for detecting an alert condition, comprising:
the first acquisition module is used for acquiring first case basic information of the target case entity;
the second acquisition module is used for acquiring a target thinking guide diagram corresponding to a target case entity, wherein the target thinking guide diagram comprises N-level nodes, the front N-1 level node correspondingly acquires a detection result of a current level node and/or prompt information of a lower level node, the prompt information of the lower level node is used for prompting a user of a detection strategy corresponding to the lower level node, and the N-level node correspondingly acquires a target detection result;
The generation module is used for generating a target detection result corresponding to the target case entity based on the first case basic information of the target case entity and the target thought guide graph corresponding to the target case entity.
9. An electronic device, comprising:
at least one processor;
a memory;
at least one application program, wherein the at least one application program is stored in the memory and configured to be executed by the at least one processor, the at least one application program configured to: a method of alarm detection according to any one of claims 1 to 7.
10. A computer readable storage medium having stored thereon at least one instruction, at least one program, code set, or instruction set, the at least one instruction, the at least one program, code set, or instruction set being loaded and executed by the processor to implement the method of alert detection as claimed in any one of claims 1 to 7.
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