CN117611412A - Event early warning method, device, equipment and medium - Google Patents

Event early warning method, device, equipment and medium Download PDF

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CN117611412A
CN117611412A CN202311527038.XA CN202311527038A CN117611412A CN 117611412 A CN117611412 A CN 117611412A CN 202311527038 A CN202311527038 A CN 202311527038A CN 117611412 A CN117611412 A CN 117611412A
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event
event data
target area
early warning
index
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陆军
蔡承源
李猛
燕立洁
刘磊
钟瑞峰
罗根照
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Beijing Softong Intelligent Technology Co ltd
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Abstract

The application discloses an event early warning method, device, equipment and medium. According to each event data of the target area, determining the efficiency index of the target area on event processing; carrying out semantic analysis on each event data, and determining topics and aimed objects of each event data; and generating early warning information according to the efficacy index and topics and objects corresponding to the event data. According to the technical scheme, comprehensive consideration is carried out from the event processing capability and the specific event situation respectively, so that early warning and intervention of potential hot events or hot events are realized, various key events are reduced, and the living satisfaction of residents is improved.

Description

Event early warning method, device, equipment and medium
Technical Field
The application relates to the technical field of smart city management, in particular to an event early warning method, device, equipment and medium.
Background
Along with the informatization development of cities and the popularization of the Internet, various data resources in society have the characteristics of multiple propagation channels, high propagation speed and large propagation range. On one hand, the wide information source can facilitate the management work of city managers on cities; on the other hand, the spreading of public opinion also puts a certain pressure on the management work of city managers. Therefore, city managers need to pay attention to various events in time so as to intervene in advance and reduce the occurrence of various key events.
At present, the processing scheme of event early warning is generally to extract the elements of each complaint work order so as to count the event complaint quantity of the same public opinion event and early warn the public opinion event that the complaint quantity reaches a preset trigger threshold. In the scheme, the triggering conditions for early warning are single, and the potential hot events cannot be early warned in time, so that the satisfaction degree of residents on cities is reduced.
Therefore, how to provide a technical scheme capable of timely early warning of a potential hot event or a hot event is a technical problem to be solved by those skilled in the art.
Disclosure of Invention
The application provides an event early warning method, an event early warning device, event early warning equipment and event early warning media, wherein the event early warning method, the event early warning device, the event early warning equipment and the event early warning media respectively comprehensively consider the event processing capacity and the specific event situation so as to realize early warning and intervention of potential hot events or hot events, reduce the occurrence of various key events and improve the life satisfaction of residents.
According to an aspect of the present application, there is provided an event early warning method, including:
determining the efficiency index of the target area for event processing according to each event data of the target area;
carrying out semantic analysis on each event data, and determining topics and aimed objects of each event data;
and generating early warning information according to the efficacy index and topics and objects corresponding to the event data.
According to another aspect of the present application, there is provided an event early warning apparatus, the apparatus comprising:
the efficiency index determining module is used for determining the efficiency index of the target area for event processing according to each event data of the target area;
the event information extraction module is used for carrying out semantic analysis on each event data and determining topics and aimed objects of each event data;
and the event early warning module is used for generating early warning information according to the efficacy index and topics and objects corresponding to the event data.
According to another aspect of the present application, there is provided an event early warning apparatus, the apparatus comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,
the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the event early warning method of any one of the embodiments of the present application.
According to another aspect of the present application, there is provided a computer readable storage medium storing computer instructions for causing a processor to execute an event early warning method according to any embodiment of the present application.
According to the technical scheme, the efficiency index of the target area for event processing is determined according to the event data of the target area; carrying out semantic analysis on each event data, and determining topics and aimed objects of each event data; generating according to the efficacy index and topics and objects corresponding to the event data
And (5) early warning information. According to the technical scheme, comprehensive consideration is carried out from the event processing capability and the specific event situation respectively, so that early warning and intervention of potential hot events or hot events are realized, various key events are reduced, and the living satisfaction of residents is improved.
It should be understood that the description of this section is not intended to identify key or critical features of the embodiments of the application or to delineate the scope of the application. Other features of the present application will become apparent from the description that follows.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of an event early warning method according to a first embodiment of the present application;
fig. 2 is a flowchart of an event early warning method provided in a second embodiment of the present application;
fig. 3 is a schematic structural diagram of an event early warning device according to a third embodiment of the present application;
fig. 4 is a schematic structural diagram of a device for implementing an event early warning method according to an embodiment of the present application.
Detailed Description
In order to make the present application solution better understood by those skilled in the art, the following description will be made in detail and with reference to the accompanying drawings in the embodiments of the present application, it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, shall fall within the scope of the present application.
It should be noted that the terms "first," "second," "third," "fourth," and the like in the description and claims of the present application and in the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that embodiments of the present application described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Example 1
Fig. 1 is a flowchart of an event early warning method provided in an embodiment of the present application, where the embodiment may be suitable for a situation of counting and early warning a hot event that may occur in a certain area, the method may be performed by an event early warning device, where the event early warning device may be implemented in a form of hardware and/or software, and the event early warning device may be configured in a device with data processing capability. As shown in fig. 1, the method includes:
s110, determining the efficiency index of the target area for event processing according to each event data of the target area.
The target area may be a country, province, city or designated area, and may be determined according to actual requirements.
The event can be obtained through government hotline, intelligent metropolitan area management, network public opinion, public mailbox, business systems and the like in the target area. Specifically, after the event is acquired, the event features may be extracted to acquire event data. Event data may be event-related data such as occurrence time, occurrence area, event details, event body object, processing state, processing time, and the like of an event.
The performance index may be the processing capacity of each event-carrying unit in the target area for the event. The higher the performance index, the more powerful the event handling capability, and vice versa.
In the scheme, the efficiency index can be comprehensively evaluated from various aspects such as on-schedule handling, appeal resolution, standard handling and the like of each event. Specifically, the performance index may be calculated according to a certain calculation rule according to data related to handling each event, such as a processing state, a processing time, and the like. The method for determining the efficiency index according to the embodiment of the invention is not limited, and can be formulated according to the actual requirements of different areas.
Optionally, before determining the performance index of the target area for event processing according to each event data of the target area, the method further includes: acquiring incremental event data of a target area through a target channel; and synchronizing the incremental event data to a dynamic event library at fixed time through a data center station to obtain event data of a target area.
The target channel may be government hotline, smart city management, network public opinion, online business systems, community gridding members, etc.
Wherein the incremental event data may be event change data. Specifically, if the dynamic event library has event data which is the same as the acquired new event data, the incremental event data may be the change data of the event, such as change of the handling state and handling time; if the event data which is the same as the acquired new event data does not exist in the dynamic event library, the incremental event data can be the new event data.
In the scheme, event acquisition channels in a target area can be firstly combed, event data are acquired through the target channels, and incremental event data are uploaded to a dynamic event library at regular time through a data center so as to analyze and process each event data later.
Optionally, determining, according to each event data, an efficiency index of the target area for event processing, including: counting the event data, and determining the total carrying quantity, the junction quantity, the total acceptance quantity, the on-time handling quantity, the off-time handling quantity, the total overdue time duration, the total evaluation quantity, the evaluation satisfaction quantity and the evaluation dissatisfaction quantity of the target area; determining a response index of the target area to event processing according to the total underwriting number and the transaction number; determining an overdue index of the target area for event processing according to the total acceptance quantity, the on-time handling quantity, the off-time handling quantity and the total overdue duration; determining a satisfaction index of the target area for event processing according to the total evaluation quantity, the evaluation satisfaction quantity and the evaluation dissatisfaction quantity; and determining the efficacy index of the target area according to the response index, the overdue index and the satisfaction index.
The response index is used for representing the transaction rate of the target area on event processing; the overdue index is used for indicating the punctual rate of the target area on event processing; the satisfaction index is used to indicate the satisfaction of the residents in the target area with respect to the event processing.
In the scheme, corresponding weights can be respectively distributed to the response index, the overdue index and the satisfaction index according to the actual demand of the target area, and the efficiency index of the target area is obtained.
Illustratively, a target area A is illustrated, which uses the following formula to determine the target area's performance index: city efficiency index = (10-number of untimely transactions x 0.1) + (5-total timeout period x 0.1) + (number of office workers/number of support) x 5+ (number of untimely transactions/total number of support) x 20+ (1-number of evaluation dissatisfaction/total number of support) x 60.
The technical scheme has the beneficial effects that the efficiency index is determined by calculating the event data, the management capacity of the target area is embodied, and effective data support is provided for early warning of the event in the target area.
S120, carrying out semantic analysis on each event data, and determining topics and aimed objects of each event data.
Wherein, the topic may be the subject of the event, and the object to which the topic is directed may be the subject of the event. For example, if certain event data is a drug a price increase, the topic may be the drug a price increase, and the target to which the topic is directed may be the drug a.
In the scheme, semantic analysis can be performed on each event data through an NLP (Natural Language Processing ) type algorithm, topics and aimed objects of each event data are obtained, and the topics and the aimed objects are associated with each event data.
It should be noted that one event may be associated with a plurality of topics, and one event may also be associated with a plurality of targeted objects.
S130, generating early warning information according to the efficacy index and topics and objects corresponding to the event data.
When the efficiency index becomes low, it means that the management ability of the target area becomes poor, and satisfaction of residents in the target area with the target area also decreases, and the occurrence frequency and influence degree of various kinds of key events become larger. Therefore, when the efficiency index is lower, the response sensitivity to various topics and objects is correspondingly improved so as to intervene various events in advance, reduce the occurrence of key events, improve the efficiency index and improve the satisfaction of residents to a target area.
The early warning information may include early warning event information and processing unit information. After the early warning information is generated, the early warning event can be sent to a corresponding processing unit, and the early warning event can be processed in time.
Optionally, generating early warning information according to the performance index, topics corresponding to each event data, and a main body, including: generating early warning information if at least one of the following exists: the efficiency index is smaller than a first preset threshold, and the number of event data corresponding to the same topic is larger than a first number threshold; the efficiency index is smaller than a second preset threshold value, and the number of event data corresponding to the same object is larger than a second number threshold value; the number of event data corresponding to the same topic is larger than a third number threshold in the current period, and the number of event data corresponding to the same topic is smaller than a fourth number threshold in the previous period.
The first item can be early warning of a hot spot event, the second item can be early warning of a hot spot object, and the third item can be early warning of a potential hot spot event.
For example, if city X has 10 different citizens feeding back events on the same topic within 2 days, and the performance index of city X in nearly 2 days is lower than 80 minutes, a hot event early warning is generated; if city X complains about the same object more than 10 times within 5 days, and the efficiency index of city X in 5 days is lower than 80 minutes, generating hot spot object early warning; if the topic event rank of citizen complaints in the city X is the first five, the topic rank is outside the first five in the last week, and the efficiency index of the city X in the near 14 days is lower than 80 minutes, the potential hot event early warning is generated.
Optionally, the first preset threshold and the second preset threshold are determined according to population information of the target area.
It will be appreciated that as the population increases in the target area, the greater the amount of events that the resident feeds back or complaints, the corresponding decrease in performance index. Thus, the threshold for the performance index may be determined based on the population of the target area.
The technical scheme has the beneficial effect that the accuracy of event early warning can be improved.
The embodiment of the invention provides an event early warning method, which comprises the steps of determining the efficiency index of a target area on event processing according to each event data of the target area; carrying out semantic analysis on each event data, and determining topics and aimed objects of each event data; and generating early warning information according to the efficacy index and topics and objects corresponding to the event data. According to the technical scheme, comprehensive consideration is carried out from the event processing capability and the specific event situation respectively, so that early warning and intervention of potential hot events or hot events are realized, various key events are reduced, and the living satisfaction of residents is improved.
Example two
Fig. 2 is a flowchart of an event early warning method according to a second embodiment of the present application, which is optimized based on the foregoing embodiment. As shown in fig. 2, the method of this embodiment specifically includes the following steps:
s210, determining the efficiency index of the target area for event processing according to each event data of the target area.
S220, carrying out semantic analysis on each event data, and determining keywords corresponding to each event data.
Specifically, the event data may be segmented, i.e., the event data is divided into discrete language units, and may be represented in the form of vectors, such as an event title, event location information, event start time, event end time, and the like.
S230, performing cluster analysis on the keywords, and determining topics and aimed objects of the event data.
Specifically, a Density-based clustering algorithm (Density-BasedSpatial Clustering of Applications with Noise, DBSCAN) may cluster multiple keywords to determine topics and objects for each event data. The clustering method and the clustering device can also be used for clustering the plurality of reference characteristic data through other clustering algorithms, the embodiment of the invention is not limited to the clustering method and the clustering method can be determined according to actual needs.
The technical scheme has the beneficial effects that the keywords corresponding to the event data can be clustered to obtain a plurality of keyword sets. Therefore, when the reference event data associated with the target event data is determined later, the reference event data associated with the target event data can be determined quickly from a plurality of keyword sets with smaller numbers, and the processing efficiency of determining the event is improved.
S240, generating early warning information according to the efficacy index and topics and objects corresponding to the event data.
The embodiment of the invention provides an event early warning method, which determines the efficiency index of a target area on event processing according to each event data of the target area; carrying out semantic analysis on each event data, and determining keywords corresponding to each event data; performing cluster analysis on each keyword to determine topics and main bodies corresponding to each event data; and generating early warning information according to the efficacy index and topics and objects corresponding to the event data. According to the technical scheme, natural language processing is carried out on the event data to grasp the attention degree of various events, so that potential hot events or hot events can be early warned and intervened in advance, the occurrence of various key events is reduced, and the living satisfaction degree of residents is improved.
Based on the foregoing embodiments, optionally, after generating the early warning information according to the performance index and the keywords corresponding to each event data, the method further includes: and generating a thermodynamic diagram of the target area according to the early warning information and the event data.
Specifically, a thermodynamic diagram of the early warning event can be generated on the map of the target area according to the feedback or complaint times of each early warning event and the occurrence position of each early warning event. The arrangement has the advantages that the distribution and the attention heat of each early warning event in the target area can be intuitively known, early warning events are effectively interventional in advance, various key events are reduced, and the living satisfaction of residents is improved.
Example III
Fig. 3 is a schematic structural diagram of an event early warning device according to a third embodiment of the present application. As shown in fig. 3, the apparatus includes:
the performance index determining module 310 is configured to determine, according to each event data of a target area, a performance index of the target area for event processing;
the event information extraction module 320 is configured to perform semantic analysis on each event data, and determine a topic and a targeted object of each event data;
the event early warning module 330 is configured to generate early warning information according to the performance index, topics and objects corresponding to the event data.
The embodiment of the invention provides an event early warning device, which determines the efficiency index of a target area for event processing according to each event data of the target area; carrying out semantic analysis on each event data, and determining topics and aimed objects of each event data; and generating early warning information according to the efficacy index and topics and objects corresponding to the event data. According to the technical scheme, comprehensive consideration is carried out from the event processing capability and the specific event situation respectively, so that early warning and intervention of potential hot events or hot events are realized, various key events are reduced, and the living satisfaction of residents is improved.
Further, the device further comprises:
the incremental event data acquisition module is used for acquiring the incremental event data of the target area through the target channel before determining the efficiency index of the target area on event processing according to each event data of the target area;
and the incremental event data synchronization module is used for synchronizing the incremental event data to the dynamic event library at fixed time through the data center station to obtain event data of the target area.
Further, the performance index determination module 310 includes:
the event data statistics unit is used for counting the event data and determining the total underwriting quantity, the transaction quantity, the total acceptance quantity, the on-time transaction quantity, the non-on-time transaction quantity, the total overdue time length, the total evaluation quantity, the evaluation satisfaction quantity and the evaluation dissatisfaction quantity of the target area;
the response index determining unit is used for determining the response index of the target area to event processing according to the total underwriting number and the transaction number;
the overdue index determining unit is used for determining the overdue index of the target area for event processing according to the total accepted quantity, the on-time transacted quantity, the un-on-time transacted quantity and the total overdue duration;
a satisfaction index determination unit configured to determine a satisfaction index of the target area for event processing, based on the total evaluation number, the evaluation satisfaction number, and the evaluation dissatisfaction number;
and the efficacy index determining unit is used for determining the efficacy index of the target area according to the response index, the overdue index and the satisfaction index.
Further, the event information extraction module 320 includes:
the keyword extraction unit is used for carrying out semantic analysis on each event data and determining keywords corresponding to each event data;
the topic object determining unit is used for carrying out cluster analysis on the keywords and determining topics and aimed objects of the event data.
Further, the event early warning module 330 is specifically configured to:
generating early warning information if at least one of the following exists:
the efficiency index is smaller than a first preset threshold, and the number of event data corresponding to the same topic is larger than a first number threshold;
the efficiency index is smaller than a second preset threshold value, and the number of event data corresponding to the same object is larger than a second number threshold value;
the number of event data corresponding to the same topic is larger than a third number threshold in the current period, and the number of event data corresponding to the same topic is smaller than a fourth number threshold in the previous period.
Further, the first preset threshold and the second preset threshold are determined according to population information of the target area.
Further, the device further comprises:
and the thermodynamic diagram generating module is used for generating thermodynamic diagrams of the target area according to the early warning information and the event data after generating the early warning information according to the efficiency index and the keywords corresponding to the event data.
The event early warning device provided by the embodiment of the application can execute the event early warning method provided by any embodiment of the application, and has the corresponding functional modules and beneficial effects of the execution method.
Example IV
Fig. 4 shows a schematic of the structure of a device 10 that may be used to implement embodiments of the present application. Devices are intended to represent various forms of digital computers, such as laptops, desktops, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The device may also represent various forms of mobile apparatuses such as personal digital processing, cellular telephones, smart phones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing apparatuses. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the application described and/or claimed herein.
As shown in fig. 4, the apparatus 10 includes at least one processor 11, and a memory, such as a Read Only Memory (ROM) 12, a Random Access Memory (RAM) 13, etc., communicatively connected to the at least one processor 11, wherein the memory stores a computer program executable by the at least one processor, and the processor 11 may perform various suitable actions and processes according to the computer program stored in the Read Only Memory (ROM) 12 or the computer program loaded from the storage unit 18 into the Random Access Memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the device 10 can also be stored. The processor 11, the ROM 12 and the RAM 13 are connected to each other via a bus 14. An input/output (I/O) interface 15 is also connected to bus 14.
The various components in the device 10 are connected to the I/O interface 15, including: an input unit 16 such as a keyboard, a mouse, etc.; an output unit 17 such as various types of displays, speakers, and the like; a storage unit 18 such as a magnetic disk, an optical disk, or the like; and a communication unit 19 such as a network card, modem, wireless communication transceiver, etc. The communication unit 19 allows the device 10 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.
The processor 11 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various processors running machine learning model algorithms, digital Signal Processors (DSPs), and any suitable processor, controller, microcontroller, etc. The processor 11 performs the various methods and processes described above, such as the event pre-warning method.
In some embodiments, the event alert method may be implemented as a computer program tangibly embodied on a computer-readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program may be loaded and/or installed onto the device 10 via the ROM 12 and/or the communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the event early warning method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the event early warning method by any other suitable means (e.g., by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.
A computer program for carrying out the methods of the present application may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions/acts specified in the flowchart and/or block diagram block or blocks to be implemented. The computer program may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of this application, a computer-readable storage medium may be a tangible medium that can contain, or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, the computer readable storage medium may be a machine readable signal medium. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, 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.
To provide for interaction with a user, the systems and techniques described here can be implemented on a device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and pointing device (e.g., a mouse or trackball) by which a user can provide input to the device. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), blockchain networks, and the internet.
The computing system may include clients and servers. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical hosts and VPS service are overcome.
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps described in the present application may be performed in parallel, sequentially, or in a different order, so long as the desired results of the technical solutions of the present application are achieved, and the present application is not limited herein.
The above embodiments do not limit the scope of the application. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application are intended to be included within the scope of the present application.

Claims (10)

1. An event early warning method, characterized in that the method comprises the following steps:
determining the efficiency index of the target area for event processing according to each event data of the target area;
carrying out semantic analysis on each event data, and determining topics and aimed objects of each event data;
and generating early warning information according to the efficacy index and topics and objects corresponding to the event data.
2. The method of claim 1, wherein prior to determining the target zone performance index for event processing based on each event data of the target zone, the method further comprises:
acquiring incremental event data of a target area through a target channel;
and synchronizing the incremental event data to a dynamic event library at fixed time through a data center station to obtain event data of a target area.
3. The method of claim 1, wherein determining an efficacy index of the target area for event processing based on each of the event data comprises:
counting the event data, and determining the total carrying quantity, the junction quantity, the total acceptance quantity, the on-time handling quantity, the off-time handling quantity, the total overdue time duration, the total evaluation quantity, the evaluation satisfaction quantity and the evaluation dissatisfaction quantity of the target area;
determining a response index of the target area to event processing according to the total underwriting number and the transaction number;
determining an overdue index of the target area for event processing according to the total acceptance quantity, the on-time handling quantity, the off-time handling quantity and the total overdue duration;
determining a satisfaction index of the target area for event processing according to the total evaluation quantity, the evaluation satisfaction quantity and the evaluation dissatisfaction quantity;
and determining the efficacy index of the target area according to the response index, the overdue index and the satisfaction index.
4. The method of claim 1, wherein performing semantic analysis on each of the event data to determine topics and targeted objects for each of the event data comprises:
carrying out semantic analysis on each event data to determine keywords corresponding to each event data;
and carrying out cluster analysis on the keywords, and determining topics and aimed objects of the event data.
5. The method of claim 1, wherein generating pre-warning information based on the performance index, topics and subjects corresponding to each of the event data, comprises:
generating early warning information if at least one of the following exists:
the efficiency index is smaller than a first preset threshold, and the number of event data corresponding to the same topic is larger than a first number threshold;
the efficiency index is smaller than a second preset threshold value, and the number of event data corresponding to the same object is larger than a second number threshold value;
the number of event data corresponding to the same topic is larger than a third number threshold in the current period, and the number of event data corresponding to the same topic is smaller than a fourth number threshold in the previous period.
6. The method of claim 5, wherein the first preset threshold and the second preset threshold are determined based on demographic information of the target area.
7. The method of claim 1, wherein after generating the pre-warning information based on the performance index and the keywords corresponding to each of the event data, the method further comprises:
and generating a thermodynamic diagram of the target area according to the early warning information and the event data.
8. An event early warning device, the device comprising:
the efficiency index determining module is used for determining the efficiency index of the target area for event processing according to each event data of the target area;
the event information extraction module is used for carrying out semantic analysis on each event data and determining topics and aimed objects of each event data;
and the event early warning module is used for generating early warning information according to the efficacy index and topics and objects corresponding to the event data.
9. An electronic device, the device comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,
the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the event early warning method of any one of claims 1-7.
10. A computer readable storage medium storing computer instructions for causing a processor to perform the event early warning method of any one of claims 1 to 7.
CN202311527038.XA 2023-11-15 2023-11-15 Event early warning method, device, equipment and medium Pending CN117611412A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202311527038.XA CN117611412A (en) 2023-11-15 2023-11-15 Event early warning method, device, equipment and medium

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202311527038.XA CN117611412A (en) 2023-11-15 2023-11-15 Event early warning method, device, equipment and medium

Publications (1)

Publication Number Publication Date
CN117611412A true CN117611412A (en) 2024-02-27

Family

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Family Applications (1)

Application Number Title Priority Date Filing Date
CN202311527038.XA Pending CN117611412A (en) 2023-11-15 2023-11-15 Event early warning method, device, equipment and medium

Country Status (1)

Country Link
CN (1) CN117611412A (en)

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