CN115346686A

CN115346686A - Relation map generation method and device, storage medium and electronic equipment

Info

Publication number: CN115346686A
Application number: CN202210970475.8A
Authority: CN
Inventors: 隋敏; 范林强; 蔡康宁
Original assignee: Yidu Cloud Beijing Technology Co Ltd
Current assignee: Yidu Cloud Beijing Technology Co Ltd
Priority date: 2022-08-12
Filing date: 2022-08-12
Publication date: 2022-11-15

Abstract

The disclosure relates to the technical field of computers, and provides a relation graph generation method and device, a computer storage medium and electronic equipment. Wherein, the method comprises the following steps: acquiring a flow regulation report of a case to be processed; analyzing the figure identification information of the personnel in the flow adjustment report to obtain candidate associated personnel information corresponding to the case to be processed; acquiring existing case information, and determining the associated case of the case to be processed according to the existing case information matched with the candidate associated personnel information; and correlating the case to be treated with the correlated case of the case to be treated to generate a relationship map for displaying the correlation relationship between the cases of infectious diseases. The scheme can automatically generate the map for displaying the incidence relation among cases of infectious diseases, and helps to improve the efficiency of infectious disease analysis.

Description

Relation graph generation method and device, storage medium and electronic equipment

Technical Field

The present disclosure relates to the field of computer technologies, and in particular, to a relationship graph generation method, a relationship graph generation apparatus, a computer-readable storage medium, and an electronic device.

Background

According to the incidence relation among the cases of the infectious diseases, the spreading condition of the infectious diseases can be analyzed, and the method has important value for preventing and treating the infectious diseases.

In the related technology, whether existing cases exist in the flow regulation report to be processed is mainly compared in a manual analysis mode to obtain the association relationship among the cases, and then a relationship map is drawn.

However, this manual analysis method is inefficient, and when the number of analyses is large, there is a high possibility that the manually added association relationship is missed, and the drawn relationship map is inaccurate.

It is to be noted that the information disclosed in the above background section is only for enhancement of understanding of the background of the present disclosure, and thus may include information that does not constitute prior art known to those of ordinary skill in the art.

Disclosure of Invention

The present disclosure is directed to a method and an apparatus for generating a relationship graph, a computer-readable storage medium, and an electronic device, which are capable of improving the problems of low efficiency and accuracy in generating a graph for showing an association relationship between cases of infectious diseases at least to some extent.

Additional features and advantages of the disclosure will be set forth in the detailed description which follows, or in part will be obvious from the description, or may be learned by practice of the disclosure.

According to a first aspect of the present disclosure, there is provided a relationship profile generation method for displaying an association relationship between cases of infectious disease, the method comprising: acquiring a flow regulation report of a case to be processed; analyzing the figure identification information in the flow adjustment report to obtain candidate associated personnel information corresponding to the case to be processed; acquiring existing case information, and determining the associated case of the case to be processed according to the existing case information matched with the candidate associated personnel information; and obtaining case association relations according to the case to be processed and the associated cases of the case to be processed, and generating a relation map for displaying the association relations among the cases of the infectious diseases based on the case association relations.

In an exemplary embodiment of the present disclosure, based on the foregoing scheme, the generating a relationship map for showing an association between cases of infectious diseases based on the case association includes: adding the association relationship to a case association relationship table; and generating a relation map for displaying the relation among the cases of the infectious diseases according to the case relation table.

In an exemplary embodiment of the present disclosure, based on the foregoing scheme, the method further includes: acquiring candidate associated personnel information corresponding to an existing case, and determining the existing case as a target existing case when the candidate associated personnel information corresponding to the existing case comprises the case to be processed; adding the case to be processed to the associated disease of the target existing case in the case association relation table

In an exemplary embodiment of the disclosure, based on the foregoing solution, after acquiring the report of the flow of the case to be processed, the method further includes: configuring a case unique identifier for the case to be processed; and adding the case unique identification of the case to be processed and the person identification of the case to be processed into a case information table so as to update the case information table.

In an exemplary embodiment of the present disclosure, based on the foregoing scheme, the acquiring existing case information includes: and acquiring the existing case information according to the person identifier corresponding to the unique case identifier in the case information table.

In an exemplary embodiment of the present disclosure, after analyzing the personal identification information in the flow adjustment report based on the foregoing scheme to obtain candidate associated person information corresponding to the case to be processed, the method further includes: generating a data record according to the unique case identification of the case to be processed and the person identification information of the candidate associated person corresponding to the case to be processed; and adding the data record to a case candidate associated personnel information table to update the case candidate associated personnel information table.

In an exemplary embodiment of the present disclosure, based on the foregoing scheme, the candidate related person information corresponding to the existing case includes: and acquiring candidate associated personnel information corresponding to the case unique identifier in the case candidate associated personnel information table according to the data record in the case candidate associated personnel information table.

In an exemplary embodiment of the disclosure, based on the foregoing scheme, the generating a relationship map for displaying an association relationship between cases of infectious diseases according to the case association relationship table includes: and generating a relationship map for displaying the association relationship among the cases of the infectious diseases by taking the person identifications corresponding to the cases in the case association relationship table as nodes and taking the case association relationship in the case association relationship table as connection logic among the nodes.

According to a second aspect of the present disclosure, there is provided a relationship profile generation apparatus for displaying an association relationship between cases of infectious diseases, the apparatus comprising: the system comprises a flow regulation report acquisition module, a flow regulation report acquisition module and a flow regulation report processing module, wherein the flow regulation report acquisition module is configured to acquire a flow regulation report of a case to be processed; the candidate associated person analysis module is configured to analyze the figure identification information in the flow regulation report to obtain candidate associated person information corresponding to the case to be processed; the associated case determining module is configured to acquire existing case information and determine an associated case of the to-be-processed case according to the existing case information matched with the candidate associated personnel information; the association module is configured to associate the case to be processed with an associated case of the case to be processed to obtain a case association relation; a relationship map generation module configured to generate a relationship map for showing an association relationship between cases of infectious diseases based on the case association relationship.

According to a third aspect of the present disclosure, there is provided a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the relationship map generation method as described in the first aspect of the above embodiments.

According to a fourth aspect of the embodiments of the present disclosure, there is provided an electronic apparatus including: a processor; and storage means for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to implement the relationship map generation method as described in the first aspect of the embodiments above.

As can be seen from the foregoing technical solutions, the relationship graph generation method, the relationship graph generation apparatus, and the computer-readable storage medium and the electronic device for implementing the relationship graph generation method in the exemplary embodiment of the present disclosure have at least the following advantages and positive effects:

in the technical solutions provided by some embodiments of the present disclosure, candidate associated person information corresponding to a case to be processed can be obtained by analyzing person identification information in a circulation report of the case to be processed; then, the candidate associated person information and the existing case information can be matched, the associated case of the case to be processed is determined according to the existing case successfully matched, the case to be processed and the associated case of the case to be processed are associated to obtain a case association relation, and finally, a relation map for displaying the association relation among cases of infectious diseases can be generated according to the case association relation. Compared with the prior art, on one hand, the relationship map for displaying the association relationship among the cases of the infectious diseases can be automatically generated by analyzing and processing the flow regulation reports of the cases, so that the generation efficiency of the case association relationship map can be improved, and the analysis efficiency of the transmission link of the infectious diseases can be assisted to be improved; on the other hand, the method and the device can automatically match the associated case with the case to be processed, and can improve the comprehensiveness of the determined associated relation, so that the accuracy of generating the case associated relation map can be improved, and the accuracy of analyzing the transmission link of the infectious disease can be improved in an auxiliary manner.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure. It is to be understood that the drawings in the following description are merely exemplary of the disclosure, and that other drawings may be derived from those drawings by one of ordinary skill in the art without the exercise of inventive faculty.

Fig. 1 is a schematic diagram illustrating an exemplary system structure to which the relationship map generation method and apparatus of the present disclosure may be applied in an exemplary embodiment;

FIG. 2 illustrates a flow diagram of a relationship graph generation method in an exemplary embodiment of the present disclosure;

fig. 3 is a flow chart illustrating a method of updating a case candidate associated people information table in an exemplary embodiment of the disclosure;

fig. 4 illustrates a flow diagram of a method of determining an associated case of a pending case in an exemplary embodiment of the disclosure;

fig. 5 is a flowchart illustrating a method for updating a case associated with an existing case in a case associated information table according to a case to be processed in an exemplary embodiment of the present disclosure;

fig. 6 illustrates a schematic diagram of a case association map generated in an exemplary embodiment of the present disclosure;

FIG. 7 is a schematic diagram illustrating an exemplary embodiment of a relationship graph generation apparatus according to the present disclosure;

fig. 8 shows a schematic structural diagram of an electronic device in an exemplary embodiment of the present disclosure.

Detailed Description

Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the disclosure. One skilled in the relevant art will recognize, however, that the subject matter of the present disclosure can be practiced without one or more of the specific details, or with other methods, components, devices, steps, and the like. In other instances, well-known technical solutions have not been shown or described in detail to avoid obscuring aspects of the present disclosure.

The terms "a," "an," "the," and "said" are used in this specification to denote the presence of one or more elements/components/parts/etc.; the terms "comprising" and "having" are intended to be inclusive and mean that there may be additional elements/components/etc. other than the listed elements/components/etc.; the terms "first" and "second", etc. are used merely as labels, and are not limiting on the number of their objects.

Furthermore, the drawings are merely schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus their repetitive description will be omitted. Some of the block diagrams shown in the figures are functional entities and do not necessarily correspond to physically or logically separate entities.

In the related technology, the name of a person appearing in an infectious disease flow regulation report is mainly analyzed manually, then the name of the person is compared with case information in a system to check whether a case with the same name exists or not, the association relationship among the cases is added manually, and after the association relationship among all the cases is added, an association relationship map is drawn.

However, the method for manually determining and adding the association relationship between cases is inefficient, and when the amount of data to be analyzed is large, the possibility of omission is high, so that the drawn association relationship map is inaccurate, and the accuracy of analyzing the transmission link of the infectious disease based on the association relationship map is affected.

In order to solve the above problem, the present disclosure provides a method and an apparatus for generating a relationship graph, which may be applied to a system architecture of an exemplary application environment shown in fig. 1.

As shown in fig. 1, system architecture 100 may include terminal device 101, network 102, and server 103. Network 102 is the medium used to provide communication links between terminal devices 101 and server 103. Network 102 may include various connection types, such as wired, wireless communication links, or fiber optic cables, among others. The terminal device 101 may be, but is not limited to, a smart phone, a tablet computer, a notebook computer, a desktop computer, and the like.

It should be understood that the number of terminal devices, networks, and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation. For example, the server 103 may be an independent physical server, a server cluster or a distributed system formed by a plurality of physical servers, or a cloud server providing basic cloud computing services such as a cloud service, a cloud database, cloud computing, a cloud function, cloud storage, a network service, cloud communication, a middleware service, a domain name service, a security service, a CDN, and a big data and artificial intelligence platform.

The relationship graph generation method provided by the embodiment of the present disclosure may be executed in the server 103, and accordingly, the relationship graph generation apparatus may be disposed in the server 103. The relationship graph generation method provided by the embodiment of the present disclosure may also be executed in the terminal device 101, and accordingly, the relationship graph generation apparatus may be disposed in the terminal device 101. Of course, the relationship map generation method may be partially executed in the server 103, partially executed in the terminal device 101, or the relationship map generation apparatus may be partially provided in the server 103, partially provided in the terminal device 101, which is not particularly limited in this exemplary embodiment.

For example, in an exemplary embodiment, the user may send case information of the case to be processed to the server 103 through the terminal device 10, where the case information includes at least one of a name and identification card information of the case to be processed, and also includes an infectious disease circulation report of the case to be processed. Server 103 may parse the infectious disease call report to obtain the name and/or identification card information included in the infectious disease call report. And matching the name and/or the identity card information included in the infectious disease call report with the name and/or the identity card information of the existing case to obtain an associated case having an association relationship with the case to be processed, adding the association relationship between the case to be processed and the associated case corresponding to the case to a case association relationship table, sending the case association relationship in the case association relationship table to the terminal device 101, drawing a case association relationship map by the terminal device 101 according to the received case association relationship, and displaying the case association relationship map in a graphical user interface of the terminal device 101.

However, it is easily understood by those skilled in the art that the foregoing application scenarios are only for example, and the exemplary embodiment is not limited thereto.

Fig. 2 shows a flow chart of a relationship profile generation method for displaying an association relationship between cases of infectious diseases in an exemplary embodiment of the present disclosure. Referring to fig. 2, the method includes:

step S210, acquiring a flow regulation report of a case to be processed;

step S220, analyzing the figure identification information in the flow regulation report to obtain candidate associated person information corresponding to the case to be processed;

step S230, acquiring existing case information, and determining the associated case of the case to be processed according to the existing case information matched with the candidate associated personnel information;

step S240, the case to be processed and the associated case of the case to be processed are associated to obtain a case association relation;

step S250, generating a relation map for displaying the relation among the cases of the infectious disease based on the case relation.

In the technical solution provided by the embodiment shown in fig. 2, candidate related persons corresponding to the case to be processed can be obtained by analyzing the person identifier in the circulation report of the case to be processed; then, the candidate associated personnel corresponding to the case to be processed and the existing case can be matched, the associated case of the case to be processed is determined according to the existing case which is successfully matched, then the case to be processed and the associated case of the case to be processed are associated to obtain a case association relation, and finally, a map for displaying the association relation between cases of infectious diseases can be generated according to the case association relation. Compared with the related art, on one hand, the relationship map for displaying the association relationship among the cases of the infectious diseases can be automatically generated by analyzing and processing the flow regulation reports of the cases, so that the generation efficiency of the case association relationship map can be improved, and the analysis efficiency of the transmission link of the infectious diseases can be assisted to be improved; on the other hand, the method and the device can automatically match the associated case with the case to be processed, and can improve the comprehensiveness of the determined associated relation, so that the accuracy of generating the case associated relation map can be improved, and the accuracy of analyzing the transmission link of the infectious disease can be improved in an auxiliary manner.

The following detailed description of the various steps in the example shown in fig. 2:

in step S210, a flow report of the case to be processed is acquired.

In an exemplary embodiment, the circulation report records the infectious disease circulation information of the case to be processed, such as the name, identification card, mobile phone number, activity track and contacted person of the case to be processed in the last period of time. The report of the epidemiology can be determined by the relevant staff performing an epidemiological survey of the cases of the infectious disease.

In an exemplary embodiment, a case of an infectious disease may be understood as a person who has been confirmed to have an infectious disease, i.e., a person who has been diagnosed with an infectious disease.

Next, in step S220, the personal identification information in the flow adjustment report is analyzed to obtain candidate related staff information corresponding to the case to be processed.

In an exemplary embodiment, the personal identification information includes at least one of a name and identification card information. The candidate related person information includes at least one of a name and identification card information of a candidate related person corresponding to the case to be processed.

Wherein the candidate associated person may be understood as a person who has been contacted with the object to be streamed in the streaming report, such as a colleague, a friend, a relative, etc. of the object to be streamed. Some of the persons who have come into contact with the regulated subject may be closely-bound persons for the infectious disease (i.e., have not been diagnosed), and some may be cases of the infectious disease (i.e., have been diagnosed with the disease).

That is, the candidate related persons may include close contact persons and confirmed persons who have been in contact with the case to be treated.

In the present disclosure, according to the circulation report of the infectious disease, the candidate related persons need to be subjected to screening by sun to determine the contact relationship between the confirmed persons of the infectious disease, and further, a relationship map for representing the contact relationship between cases of the infectious disease is generated. Therefore, researchers can be assisted to analyze the spreading condition of the infectious diseases and the like according to the relation graph, and the analysis efficiency and the analysis accuracy of the spreading condition of the infectious diseases are improved.

For example, after the flow adjustment report is obtained, the personal identification information of the adjusted object in the flow adjustment report may be analyzed first, and the personal identification information of the adjusted object in the flow adjustment report may be determined as the personal identification information of the case to be processed. In general, the first personal identification information appearing in a style report may be determined to be the personal identification information of the object being style.

Or the character identification information of the object to be streamed can be determined according to the information of the value corresponding to the preset keyword in the streaming report. For example, there are many flow adjustment items in a flow adjustment report, and each flow adjustment item is displayed by storing in the form of a keyword and its corresponding value. For example, the word "name of the current case" is the corresponding key word of a circulation item, and the specific name of the current case, for example, "zhang san" is the corresponding value of the key word of the circulation item, i.e., "name of the current case". Therefore, the information of the value corresponding to the keyword "name of the current case" can be determined as the personal identification information of the object to be streamed, that is, the personal identification information of the case to be processed. Of course, the personal identification information of the streamed object may also be represented by other keywords, which is not particularly limited in this exemplary embodiment. The method can also directly upload the figure identification information of the case to be processed and the flow regulation report corresponding to the figure information identification, so that the figure identification information of the case to be processed can be directly determined.

Since there may be the person identification information of the to-be-adjusted object, that is, the case to be processed, in the adjustment report, after the person identification information in the adjustment report is analyzed, the person identification information of the to-be-adjusted object may be removed, so as to obtain the candidate related person information.

Illustratively, the names of people included in the flow chart report of the case to be processed can be analyzed through natural language processing technology, such as named entity recognition, the identity card information included in the flow chart report can be analyzed through a regular matching mode, and the analyzed names and/or identity card information can be used as the person identification information.

Taking the example that the person identification information includes name and identification card information, when the name and identification card information of the same person are counted in the flow chart report, the name and identification card information can be recorded in a direct splicing manner, and if the identification card number of Zhang III is 123456789, the flow chart report can be recorded in a format of "Zhang III 123456789". Therefore, whether the two represent the same object can be determined according to whether the analyzed adjacent name and identity card information has interval information.

For example, when there is no interval information between the analyzed adjacent names and identification cards, it can be confirmed that the name and identification card information represent the same object, and then the name and identification card information can be combined to be used as the personal identification information of a candidate related person; when the analyzed name and identity card information has interval information, the name and identity card information can be confirmed to respectively represent the person identification information of different candidate associated persons, and the analyzed name and identity card information are stored in an array in a key value pair mode, so that a candidate associated person information array corresponding to each case to be processed is obtained.

In other words, each element in the array of candidate associated person information includes two key-value pairs, namely a first key-value pair consisting of a name and its corresponding value, and a second key-value pair consisting of an identity card and its corresponding value. If a certain candidate associated person only has name information, the value corresponding to the identity card is null, and if only the identity card information exists, the value corresponding to the name is null.

Of course, it is also possible to parse only names present in the callout report to generate an array of candidate associated people from the names. It is also possible to analyze only the identity card existing in the flow adjustment report to generate the candidate associated person information array according to the identity card, which is not particularly limited in the present exemplary embodiment.

Illustratively, after the person identification information in the flow adjustment report is analyzed to obtain the candidate associated person information corresponding to the to-be-processed case, the case candidate associated person information table may be updated according to the candidate associated person information corresponding to the to-be-processed case. Fig. 3 is a flowchart illustrating a method of updating a case candidate associated person information table in an exemplary embodiment of the disclosure. Referring to fig. 3, the method may include steps S310 to S320. Wherein:

in step S310, a data record is generated according to the case unique identifier of the case to be processed and the candidate related staff information corresponding to the case to be processed.

For example, a case unique identifier can be assigned to the pending case, and the case unique identifier is used to distinguish different pending cases. For example, after the flow adjustment report of the case to be processed is acquired, a random number may be generated, and the random number may be used as the case unique identifier of the case to be processed. Of course, the unique identifier of the case may be generated for the to-be-processed case in other manners, as long as the generated unique identifier of the case can uniquely represent one case, and this exemplary embodiment is not particularly limited thereto.

By configuring the unique identification of the case for the case to be processed, the unique identification of the case can distinguish the cases with the same name but different objects under the condition that the cases have the same name but cannot obtain the identity numbers of the cases.

For example, after the flow adjustment report of the case to be processed is obtained, the unique identifier of the case may be configured for the case to be processed, and the flow adjustment report of the case to be processed is analyzed to obtain the person identifier information of the candidate associated person of the case to be processed. And then, storing the person identification information of the candidate associated person corresponding to the case to be processed in the array to obtain the candidate associated person information array of the case to be processed. If there are 3 candidate associated persons corresponding to a certain to-be-processed case, there are 3 elements in the candidate associated person information array of the to-be-processed case, and each element is used for recording the name and the identity card of the corresponding candidate associated person. And generating a data record according to the unique case identifier corresponding to the case to be processed and the candidate associated personnel information array corresponding to the unique case identifier.

Next, in step S320, the data record is added to the case candidate related person information table to update the case candidate related person information table.

For example, the data record generated in step S310 may be added to the candidate related person information table to update the case candidate related person information table. Namely, the candidate related personnel information corresponding to the case to be processed is added to the case candidate related personnel information table, and after the candidate related personnel information is successfully added, the case to be processed becomes the existing case in the case candidate related personnel information table.

Based on the above steps S310 to S320, a case candidate associated person information table can be maintained by processing the flow adjustment report for each case to be processed.

That is, in the present disclosure, the case candidate related person information table may be understood as a data table for storing personal identification information of persons who have been in contact with each case of infectious disease. That is, the case candidate related person information table may store the case unique identifier of the infectious disease case and the candidate related person information array corresponding to the infectious disease case. After the names and/or the identity cards of the candidate associated personnel of the to-be-processed case are analyzed from the flow regulation report of each to-be-processed case, the case unique identifier configured for the to-be-processed case and the candidate associated personnel information array corresponding to the to-be-processed case can be used as the same data record to be associated, and then the data record is stored in a case candidate associated personnel information table. Thus, by referring to the case candidate related information table, the candidate related person information for each case can be obtained.

The case candidate related staff information table can be used for updating the case association relation table in the subsequent embodiment, and the specific updating process is explained in detail in the embodiment shown in fig. 5 below.

Next, with continued reference to fig. 2, in step S230, existing case information is acquired, and a case associated with the to-be-processed case is determined according to the existing case information matched with the candidate associated person information. In an exemplary embodiment, after the personal identification information of each to-be-processed case is determined, a case information table may be maintained by the case unique identifier configured for each to-be-processed case and the personal identification information of each to-be-processed case.

That is, the case information table can be understood as a data table for storing identification information of cases of infectious diseases, and it is possible to know which existing cases of infectious diseases exist from the case information table. In other words, the case currently stored in the case information table can be understood as the existing case of the infectious disease.

For example, after the personal identification information of the to-be-processed case is obtained, a case unique identifier may be configured for the personal identification information of the to-be-processed case, such that a random number is generated as described above, and the random number is used as the case unique identifier corresponding to the personal identification information of the to-be-processed case. The correspondence of the case unique identifier and the person identification information of each to-be-processed case may be added to the case information table to maintain one case information table.

For example, a data record may be generated based on the case unique identifier of the case to be processed, the name of the case to be processed, and the identification card information, and then the data record may be added to the case information table, so that the maintained case information table may be updated with the corresponding data record of each case to be processed.

After the case unique identifier of the case to be processed and the person identifier corresponding to the case to be processed are added to the case information table, the case to be processed can become an existing case in the case information table.

In other words, in step S230, the existing case information may be acquired from the case information table. Specifically, the personal identification information corresponding to the unique identifier of each case may be obtained from the case information table to obtain the existing case information, i.e., the existing case information in step S230 may be understood as the personal identification information currently stored in the case information table.

Next, a specific embodiment of step S230 will be described with reference to fig. 4. Fig. 4 shows a flowchart of a method of determining an associated case of a pending case in an exemplary embodiment of the present disclosure. Referring to fig. 4, the method may include steps S410 to S440. Wherein:

in step S410, matching the personal identification information of the existing case in the case information table with the personal identification information of the candidate related person corresponding to the case to be processed;

in step S420, it is determined whether the matching is successful, and if the matching is successful, the process goes to step S430, otherwise, the process goes to step S440;

in step S430, determining that the existing case is a related case of the to-be-processed case;

in step S440, no processing is performed.

For example, the person identification information in the case information table may be understood as existing case information, the first person identification information in the case information table may be acquired, and then the first person identification information may be matched with the second person identification information corresponding to the resolved candidate related person information. And determining the existing case indicated by the first person identification information successfully matched with the second person identification information as the associated case of the case to be processed.

When the matching is performed, the first person identification information and the second person identification information of the same type are matched, for example, the name of the existing case is matched with the name of the candidate related person, and the identity card of the existing case is matched with the identity card of the candidate related person.

In an exemplary embodiment, a similarity between the first personal identification information and the second personal identification information may be determined through a machine learning model, and when the similarity is greater than a preset value, the first personal identification information and the second personal identification information are considered to be successfully matched, otherwise, the matching fails. Of course, whether the first personal information and the second personal information match each other may also be determined in other manners, and this exemplary embodiment is not particularly limited in this respect.

In other words, for each candidate related person in the candidate related person information corresponding to the to-be-processed case, the following processing may be performed to determine the related case of the to-be-processed case: and matching the personal identification information of the current candidate associated person with the personal identifications of all cases in the case information table one by one, and determining a case as the associated case of the case to be processed when the matching of the personal identification information of a certain case in the case information table and the personal identification information of the current candidate associated person is successful.

The identity card information can be preferentially used for matching in the matching process, and names are used for matching when the identity card information cannot be used for matching. For example, when both the candidate related person and the existing case have identification card information, the candidate related person and the existing case may be matched using the identification card information, and when either of the candidate related person and the existing case does not have identification card information, the candidate related person and the existing case may be matched using a name. Thus, the influence of different cases of the same name on the matching result can be reduced as much as possible.

Next, with continued reference to fig. 2, in step S240, the case to be processed and the associated case of the case to be processed are associated to obtain a case association relationship.

Illustratively, after determining the associated case of the case to be processed, the case unique identifiers of all the associated cases of the case to be processed may be stored in the same array, so as to obtain the associated case array of the case to be processed. And then, generating a data record according to the unique case identification of the case to be processed and the associated case array of the case to be processed, so as to associate the case to be processed and the associated case of the case to be processed according to the data record. The data record may characterize the existence of an association between the case to be processed and the case in the array of associated cases.

Next, in step S250, a relationship map for showing the relationship between cases of infectious diseases is generated based on the case relationship.

Illustratively, the generating a relationship profile for displaying relationships between cases of infectious diseases based on the case relationships comprises: adding the association relationship to a case association relationship table; and generating a relationship map for displaying the relationship among the cases of the infectious diseases according to the case relationship table.

For example, the case association table may include two fields of a case ID (Identity) and an associated case ID. The unique identification of the case to be processed is used as a value corresponding to a field of case ID, and the associated case array corresponding to the case to be processed is used as a value corresponding to a field of associated case ID to form a data record. The data record is used for representing the association relationship between the case corresponding to the case ID and the case corresponding to the associated case ID, and then the data record is added into the case association relationship table.

That is, the case relation table can be understood as a data table for storing information on other cases with which each case has been exposed. For example, if case a appears in the flow report of case B, then case a and case B are described as having been in contact, case a may be stored in the case association table as an associated case for case B.

In an exemplary embodiment, after the above steps S210 to S240 are performed on all the to-be-processed cases, the association relationship between all the to-be-processed cases and the corresponding associated cases may be stored in the case association relationship table. Then, a relationship map showing the relationship between cases of infectious diseases can be generated from the case relationship table.

In an exemplary scenario, taking a case to be processed as case a, an existing case as B, C, D, E, and finally determining associated cases of the case to be processed a as B and E, a record "case ID: a; associated cases: [ B, E ] ". Since case a is processed after case B and case E, that is, case a is not an existing case when case B and case E are processed, even if case a exists among candidate related persons of case B and case E, information of case a is missing in the determined related case of case B and case E.

Further, if there is a case a in the candidate related persons of the existing case C, but the information of the case C is missing in the report of the flow adjustment of the case a due to negligence in the flow adjustment, that is, there is no case C in the candidate related persons of the analyzed case a, then the case C is missing in the finally determined related case of the case a. Meanwhile, since case a is processed after case C, that is, when case C is processed, case a is not already an existing case, case a is also missing in the related case of case C. That is, the association between case a and case C is eventually lost.

Based on the above, the associated case array of the existing case can be updated in the case association relation table according to the case to be processed. Therefore, omission of the association relationship among the cases can be avoided, and the comprehensiveness and the accuracy of the case association relationship stored in the case association relationship table are improved.

Fig. 5 is a flowchart illustrating a method for updating a case associated with an existing case in a case association information table according to a case to be processed in an exemplary embodiment of the disclosure. Referring to fig. 5, the method may include steps S510 to S520. Wherein:

in step S510, candidate related person information of an existing case is obtained, and when the candidate related person information corresponding to the existing case includes the case to be processed, the existing case is determined to be a target existing case.

Illustratively, the acquiring the candidate related person information corresponding to the existing case includes: and acquiring candidate associated personnel information corresponding to the case unique identifier in the case candidate associated personnel information table according to the data record in the case candidate associated personnel information table.

For example, candidate related person information of an existing case may be acquired from the case candidate related person information table, and for a candidate related person information array corresponding to a unique identifier of each case in the case candidate related person information table, each person identifier in the candidate related person information array may be respectively matched with the person identifier information of the case to be processed. And if the person identification information of a certain candidate related person is successfully matched with the person identification information of the case to be processed, the case indicated by the case unique identification corresponding to the candidate related person is the target existing case.

If such a data record "case unique identifier" exists in the candidate related person information table: 123; candidate associated person information array: if the name of the case to be processed is wang five, the name of the case to be processed is successfully matched with the name wang five in the candidate related personnel information array, and the case indicated by the case unique identifier 123 is the existing case of the target case.

After the target existing case is determined, in step S520, the case to be processed is added to the associated case of the target existing case in the case association relationship table, so as to update the case association relationship table.

For example, after the existing target case is determined, the unique case identifier of the case to be processed may be added to the associated case array corresponding to the existing target case in the case association table, so as to update the associated case of the existing target case.

Continuing to use the case to be processed as case a, the existing case is B, C, D, E, the associated cases of case a are B and E, and case a exists in the candidate associated persons of case C, through the above steps S510 to S520, since case a exists in the candidate associated persons of case C, case a can be successfully matched with case a existing in the candidate associated persons of case C, that is, case C will also become the target existing case, that is, case a can be added in the associated case of case C, and when case C is processed, the associated cases of case C obtained are case F and case H, that is, such a record "case ID" exists in the updated case association relationship table: c; associated cases: [ F, H, A ] ". That is, in the case relation table, there is a relation between case C and case a. Obviously, even if the report of the flow regulation of the case A has errors, the incidence relation between the case C and the case A is obtained, so that the accuracy and comprehensiveness of the incidence relation determination are improved.

For example, one specific embodiment of step S250 may be to generate a map showing the relationship between cases of infectious diseases according to the case relationship table updated through the above steps S510 to S520.

In an exemplary embodiment, after all the cases to be processed are processed to obtain the case association relationship table, it may be further verified manually whether the case association relationship exists. For example, for a case with the same name but without an identification card number, since two cases cannot be distinguished by name, there may be a case of correlation error, at this time, the correlated case of the case with the same name may be manually checked and screened to ensure the accuracy and comprehensiveness of the case correlation relationship stored in the final case correlation relationship table.

It should be noted that, compared with the identification card information, the name information of the case is the case information that is easier to acquire, so that the influence of the duplicate case on the accuracy of the determined case association relationship can be avoided by a manual verification method even if the identification card information cannot be acquired, and the accuracy of the determination of the case association relationship is further ensured.

And all the association relations are generated by automatic analysis, and the manual work only participates in the verification of the association relations of the duplicate cases, so that the efficiency of determining the association relations of the cases can be greatly improved compared with the mode of directly determining the association relations manually.

For example, the user may enter case information of a plurality of cases to be processed for which association needs to be determined, and the case information may include information such as names, identification numbers, telephone numbers, and flow reports of the cases to be processed. After the user has finished entering, the above steps S210 to S240 and steps S510 to S520 may be respectively performed on each piece of to-be-processed case information, so as to obtain a case association table corresponding to a plurality of to-be-processed cases. Then, manually checking and checking the associated cases of the duplicate cases in the case association relationship table, and if errors are found, modifying, namely manually deleting or adding the associated cases in the case association relationship table, thereby obtaining the manually checked case association relationship table. And drawing an association relationship map between cases according to the case association relationship table after manual verification.

For example, another specific implementation manner of step S250 may be to generate a graph for showing the association relationship between cases with the person identifier corresponding to the case in the case association relationship table as a node and the case association relationship in the case association relationship table as a connection logic between the nodes.

For example, a plurality of case unique identifier pairs having an association relationship may be generated according to the case unique identifier in the case association relationship table and the case unique identifier in the associated case array corresponding to the case unique identifier. And for each case unique identification pair with the association relationship, searching for the person identifications corresponding to the two case unique identifications in the case unique identification pair from the case information table, then searching whether a node corresponding to the person identification exists in the graph, if so, judging whether the two case unique identifications are connected, if so, continuously processing the next case unique identification pair with the association relationship, and if not, adding the node corresponding to the person identification in the currently processed case unique identification pair in the graph, and connecting the nodes corresponding to the person identifications of the two case unique identifications in the currently processed case unique identification pair.

If the person identifications corresponding to the two case unique identifications in the currently processed case unique identification pair both exist in the map, but the person identifications are not connected, the person identifications and the person identifications are directly connected, and then the next case unique identification pair with the association relation is processed continuously. Until all the case unique identification pairs with the association relation are processed, a map of the association relation between the cases can be generated.

The generated case association relationship graph can be as shown in fig. 6, that is, each node in the graph represents a case, name and/or identity card information of the case is shown, and all data in the case relationship table is used as connection logic between the nodes. In fig. 6, two cases with duplicate names are shown, and the identity card information of the two cases is different, namely 'XX 1' and 'XX 2'.

It should be noted that, when multiple cases are renamed and there is no id information, the unique identifiers of the cases corresponding to the multiple cases may be directly identified as nodes corresponding to the cases in the graph to distinguish the renamed cases, if the cases are renamed and there is id information, the names and id information of the cases are used as nodes, if the cases are not renamed, the names may be directly used as nodes, the identifiers of the nodes in the graph may be determined by self-definition according to actual conditions, as long as objects represented by different nodes can be distinguished, which is not particularly limited in the exemplary embodiment.

In an exemplary application scenario, a transmission chain map of infectious diseases can also be generated according to the case relation table. For example, the diagnosis time of each case may be added to the case association table, then all cases are sorted according to the precedence order of the diagnosis times of the cases, and then the one-way arrow is connected between the cases with the association relationship according to the association relationship in the case association table, where the one-way arrow points from the case with the earlier diagnosis time to the case with the later diagnosis time, thereby generating the transmission chain map of infectious diseases.

In an exemplary application scenario, a user may enter case information of a plurality of cases to be processed for which association needs to be determined, and the case information may include information such as names, identification numbers, telephone numbers, and flow reports of the cases to be processed. After the user enters the information, each piece of case information can be processed respectively, and specifically, the following processing procedures can be executed for each piece of case information: a case ID (i.e., the above-mentioned case unique identifier) is generated for the currently processed case information, and the case ID, name, and identification number are stored in the case information table. Analyzing the flow regulation report of the currently processed case information by using a natural language processing technology, analyzing a plurality of groups of names and identity card information, storing the plurality of groups of names and identity card information into an array to obtain a case candidate associated personnel array, and storing the case ID, the flow regulation report and the case candidate associated personnel array into a case candidate associated personnel information table. Then, all existing cases in the case information table are inquired, matching is respectively carried out on the existing cases and case candidate associated persons in the case candidate associated person array corresponding to the currently processed case, whether the names and/or the identity card information are consistent or not is judged, if yes, matching is successful, all the existing cases successfully matched are determined to be the associated cases of the currently processed case, case IDs of all the associated cases of the currently processed case are stored in the array to obtain an associated case ID array, and data are formed according to the case ID corresponding to the currently processed case and the associated case ID array and are added into the case association relation table.

Traversing each case in the case candidate associated personnel information table, judging whether the name and/or the identity number of the currently processed case is contained in the case candidate associated personnel array corresponding to each case in the case candidate associated personnel information table, and if so, adding a case ID corresponding to the currently processed case in the case associated relation array for the associated case ID array of the currently traversed case so as to establish the associated relation between the currently traversed case in the case candidate associated personnel information table and the currently processed case.

After all the entered cases are processed, the generated case association relationship can be manually verified whether exists indeed, so that the case association relationship table is verified. Then, a case association map can be drawn according to the case association table obtained after manual verification, for example, each node in the map represents a case, the vicinity of each node in the map can identify the name and/or identity card information of the case represented by the node, and then, all data in the case association table is used as the connection logic between the nodes, and finally, the association map is generated.

As described above, the case candidate related person information table may further store a circulation report corresponding to the case. In this way, after the flow regulation report of a certain case is uploaded again, whether the flow regulation report uploaded again is different from the flow regulation report in the case candidate associated person information table or not can be compared to determine whether the newly uploaded flow regulation report needs to be analyzed or not so as to update the case association relationship of the case.

Meanwhile, the flow report is stored in the case candidate associated personnel information table, so that the judgment on whether the case association relation needs to be updated or not can be realized, the flow report, the name of the case, the identity card information and the like can be stored separately, and the query efficiency of the name of the case and the identity card information is improved.

Illustratively, the method can also be directly interfaced with the dispatching system, and the dispatching report of the case to be processed is directly obtained from the dispatching system without manual uploading, so as to further improve the efficiency.

According to the method and the device, the case association relationship map can be automatically generated according to the flow report of the case through an automatic processing flow, and the generation efficiency of the case association relationship map is improved. And the false determination of the incidence relation caused by manual operation is avoided, and the accuracy of the case incidence relation map is improved.

Those skilled in the art will appreciate that all or part of the steps implementing the above embodiments are implemented as computer programs executed by a CPU. The computer program, when executed by the CPU, performs the functions defined by the method provided by the present invention. The program may be stored in a computer readable storage medium, which may be a read-only memory, a magnetic or optical disk, or the like.

Furthermore, it should be noted that the above-mentioned figures are only schematic illustrations of the processes involved in the method according to exemplary embodiments of the invention and are not intended to be limiting. It will be readily understood that the processes shown in the above figures are not intended to indicate or limit the chronological order of the processes. In addition, it is also readily understood that these processes may be performed synchronously or asynchronously, e.g., in multiple modules.

Fig. 7 shows a schematic structural diagram of a relationship graph generation apparatus for displaying an association relationship between cases of infectious diseases in an exemplary embodiment of the present disclosure, the apparatus 700 may include: a flow regulation report acquisition module 710, a candidate associated personnel analysis module 720, an associated case determination module 730, an association module 740, and a relationship map generation module 750. Wherein:

a reconciliation report acquisition module 710 configured to acquire case information of a case to be processed, the case information including a reconciliation report of the case to be processed;

a candidate associated person parsing module 720, configured to parse the person identifiers of the persons included in the flow adjustment report to obtain candidate associated persons corresponding to the to-be-processed case;

the associated case determining module 730 is configured to acquire existing case information and determine an associated case of the to-be-processed case according to the existing case information matched with the candidate associated person information;

a correlation module 740 configured to correlate the to-be-processed case with a correlated case of the to-be-processed case to obtain a case correlation relationship;

a relationship map generation module 750 configured to generate a relationship map for showing a relationship between cases of infectious diseases based on the case relationship.

In some exemplary embodiments of the present disclosure, based on the foregoing embodiments, the relationship drag generation module 750 may be further specifically configured to: adding the association relationship to a case association relationship table; and generating a relationship map for displaying the relationship among the cases of the infectious diseases according to the case relationship table.

In some exemplary embodiments of the present disclosure, based on the foregoing embodiments, the apparatus may further include an association update module, and the association update module may be configured to: acquiring candidate associated personnel information corresponding to an existing case, and determining the existing case as a target existing case when the candidate associated personnel information corresponding to the existing case comprises the case to be processed; and in the case association relation table, adding the case to be processed into the associated case of the target existing case so as to update the case association relation table.

In some exemplary embodiments of the present disclosure, based on the foregoing embodiments, the map generating module may be further configured to: and generating a map for displaying the association relationship among the cases of the infectious diseases according to the updated case association relationship table.

In some exemplary embodiments of the present disclosure, based on the foregoing embodiments, the apparatus further comprises a case information table updating module, which may be specifically configured to: configuring a case unique identifier for the case to be processed; and adding the case unique identification of the case to be processed and the person identification information of the case to be processed into a case information table so as to update the case information table.

In some exemplary embodiments of the present disclosure, based on the foregoing embodiments, the associated case determination module 730 may further include an existing case information obtaining unit, which may be configured to: and acquiring the existing case information according to the person identifier corresponding to the unique case identifier in the case information table.

In some exemplary embodiments of the present disclosure, based on the foregoing embodiments, the apparatus further includes a case candidate associated person information table generating module, which may be specifically configured to: generating a data record according to the case unique identifier of the case to be processed and the candidate associated personnel information corresponding to the case to be processed; and adding the data record into a case candidate associated personnel information table to update the case candidate associated personnel information table.

In some exemplary embodiments of the present disclosure, based on the foregoing embodiments, the acquiring information of candidate related persons corresponding to an existing case includes: and acquiring candidate associated personnel information corresponding to the case unique identifier in the case candidate associated personnel information table according to the data record in the case candidate associated personnel information table.

In some exemplary embodiments of the present disclosure, based on the foregoing embodiments, the person identification includes at least one of name and identification card information.

In some exemplary embodiments of the present disclosure, based on the foregoing embodiments, the relationship map generation module 750 may be specifically configured to: and generating a map for displaying the association relationship among the cases of the infectious diseases by taking the person identification corresponding to the case in the case association relationship table as a node and taking the case association relationship in the case association relationship table as a connection logic among the nodes.

The specific details of each module or unit in the above-mentioned relationship map generation apparatus have been described in detail in the corresponding relationship map generation method, and therefore are not described herein again.

It should be noted that although in the above detailed description several modules or units of the device for action execution are mentioned, such a division is not mandatory. Indeed, the features and functionality of two or more modules or units described above may be embodied in one module or unit, according to embodiments of the present disclosure. Conversely, the features and functions of one module or unit described above may be further divided into embodiments by a plurality of modules or units.

Moreover, although the steps of the methods of the present disclosure are depicted in the drawings in a particular order, this does not require or imply that the steps must be performed in this particular order, or that all of the depicted steps must be performed, to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step execution, and/or one step broken down into multiple step executions, etc.

Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which may be a personal computer, a server, a mobile terminal, or a network device, etc.) to execute the method according to the embodiments of the present disclosure.

In an exemplary embodiment of the present disclosure, there is also provided a computer storage medium capable of implementing the above method. On which a program product capable of implementing the above-described method of the present specification is stored. In some possible embodiments, various aspects of the disclosure may also be implemented in the form of a program product comprising program code for causing a terminal device to perform the steps according to various exemplary embodiments of the disclosure as described in the "exemplary methods" section above of this specification, when the program product is run on the terminal device.

Embodiments of the present disclosure may also include a program product for implementing the above method, which may employ a portable compact disc read only memory (CD-ROM) and include program code, and may be run on a terminal device, such as a personal computer. However, the program product of the present disclosure is not limited thereto, and in this document, a readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.

The program product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

A computer readable signal medium may include a propagated data signal with readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A readable signal medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.

Program code embodied on a readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

Program code for carrying out operations for the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).

In addition, in an exemplary embodiment of the present disclosure, an electronic device capable of implementing the above method is also provided.

As will be appreciated by one skilled in the art, aspects of the present disclosure may be embodied as a system, method or program product. Accordingly, various aspects of the present disclosure may be embodied in the form of: an entirely hardware embodiment, an entirely software embodiment (including firmware, microcode, etc.) or an embodiment combining hardware and software aspects that may all generally be referred to herein as a "circuit," module "or" system.

An electronic device 800 according to this embodiment of the disclosure is described below with reference to fig. 8. The electronic device 800 shown in fig. 8 is only an example and should not bring any limitations to the functionality and scope of use of the embodiments of the present disclosure.

As shown in fig. 8, electronic device 800 is in the form of a general purpose computing device. The components of the electronic device 800 may include, but are not limited to: the at least one processing unit 810, the at least one memory unit 820, a bus 830 that couples various system components including the memory unit 820 and the processing unit 810, and a display unit 840.

Wherein the storage unit stores program code that is executable by the processing unit 810 to cause the processing unit 810 to perform steps according to various exemplary embodiments of the present disclosure as described in the "exemplary methods" section above in this specification. For example, the processing unit 810 may perform the various steps as shown in fig. 2 to 5.

The storage unit 820 may include readable media in the form of volatile memory units such as a random access memory unit (RAM) 8201 and/or a cache memory unit 8202, and may further include a read only memory unit (ROM) 8203.

The storage unit 820 may also include a program/utility 8204 having a set (at least one) of program modules 8205, such program modules 8205 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination thereof may comprise an implementation of a network environment.

Bus 830 may be any of several types of bus structures including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

The electronic device 800 may also communicate with one or more external devices 900 (e.g., keyboard, pointing device, bluetooth device, etc.), with one or more devices that enable a user to interact with the electronic device 800, and/or with any devices (e.g., router, modem, etc.) that enable the electronic device 800 to communicate with one or more other computing devices. Such communication may occur via input/output (I/O) interfaces 850. Also, the electronic device 800 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the internet) via the network adapter 860. As shown, the network adapter 860 communicates with the other modules of the electronic device 800 via the bus 830. It should be appreciated that although not shown, other hardware and/or software modules may be used in conjunction with the electronic device 800, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.

Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which may be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the embodiments of the present disclosure.

Furthermore, the above-described figures are merely schematic illustrations of processes included in methods according to exemplary embodiments of the present disclosure, and are not intended to be limiting. It will be readily understood that the processes shown in the above figures are not intended to indicate or limit the chronological order of the processes. In addition, it is also readily understood that these processes may be performed, for example, synchronously or asynchronously in multiple modules.

Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.

Claims

1. A method of generating a relationship profile for displaying associations between cases of infectious disease, the method comprising:

acquiring a flow regulation report of a case to be processed;

analyzing the figure identification information in the flow adjustment report to obtain candidate associated personnel information corresponding to the case to be processed;

acquiring existing case information, and determining the associated case of the case to be processed according to the existing case information matched with the candidate associated personnel information;

correlating the case to be processed with the correlated case of the case to be processed to obtain a case correlation relationship;

and generating a relation map for displaying the relation among the cases of the infectious diseases based on the case relation.

2. The relationship profile generation method according to claim 1, wherein generating a relationship profile for displaying relationships between cases of infectious disease based on the case relationships comprises:

adding the association relationship to a case association relationship table;

and generating a relationship map for displaying the relationship among the cases of the infectious diseases according to the case relationship table.

3. The relationship graph generation method according to claim 2, further comprising:

acquiring candidate associated personnel information corresponding to an existing case, and determining the existing case as a target existing case when the candidate associated personnel information corresponding to the existing case comprises the case to be processed;

and in the case association relation table, adding the case to be processed into the associated case of the target existing case so as to update the case association relation table.

4. The relationship map generation method according to claim 3, wherein after acquiring the report of the flow of the case to be treated, the method further comprises:

configuring a case unique identifier for the case to be processed;

adding the unique case identification of the case to be processed and the person identification of the case to be processed into a case information table so as to update the case information table;

the acquiring the existing case information comprises:

and acquiring the existing case information according to the person identification corresponding to the case unique identification in the case information table.

5. The relationship graph generation method according to claim 4, wherein after the person identification information in the flow adjustment report is analyzed to obtain the candidate associated person information corresponding to the case to be processed, the method further comprises:

generating a data record according to the unique case identification of the case to be processed and the candidate associated personnel information corresponding to the case to be processed;

and adding the data record to a case candidate associated personnel information table to update the case candidate associated personnel information table.

6. The relationship map generation method according to claim 5, wherein the obtaining of candidate related person information corresponding to an existing case comprises:

and acquiring candidate associated personnel information corresponding to the case unique identifier in the case candidate associated personnel information table according to the data record in the case candidate associated personnel information table.

7. The relationship profile generation method according to any one of claims 2 to 6, wherein generating a relationship profile showing an association between cases of infectious disease from the case association relationship table includes:

and generating a relationship map for displaying the association relationship among the cases of the infectious diseases by taking the person identifications corresponding to the cases in the case association relationship table as nodes and taking the case association relationship in the case association relationship table as connection logic among the nodes.

8. A relationship profile generation apparatus, wherein the profile is used to show an association between cases of infectious disease, the apparatus comprising:

the system comprises a flow regulation report acquisition module, a flow regulation report acquisition module and a flow regulation report processing module, wherein the flow regulation report acquisition module is configured to acquire a flow regulation report of a case to be processed;

the candidate associated personnel analysis module is configured to analyze the figure identification information in the flow regulation report to obtain candidate associated personnel information corresponding to the case to be processed;

the associated case determining module is configured to acquire existing case information and determine an associated case of the to-be-processed case according to the existing case information matched with the candidate associated personnel information;

the association module is configured to associate the case to be processed with an associated case of the case to be processed to obtain a case association relation;

a relationship map generation module configured to generate a relationship map for showing an association relationship between cases of infectious diseases based on the case association relationship.

9. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the method according to any one of claims 1 to 7.

10. An electronic device, comprising:

one or more processors;

storage means for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to carry out the method of any one of claims 1 to 7.