CN113314233A - Event tracking processing method, system, equipment and medium - Google Patents
Event tracking processing method, system, equipment and medium Download PDFInfo
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Abstract
The invention provides an event tracing processing method, a system, equipment and a medium, comprising the following steps: constructing an event set to be monitored, wherein each event factor in the event set to be monitored comprises one or more corresponding key features; creating block data comprising a plurality of data nodes based on data records of a plurality of data acquisition points in a defined area, wherein each data node corresponds to a data acquisition point at a different geographic position; searching real-time event records in a set time interval from the block data according to the key features of the event set to be monitored, and comparing the real-time event records with historical synchronous event records to obtain abnormal events; positioning a resident geographical position of a target object according to the abnormal event, and starting event early warning if a common target object contained in the resident geographical position exceeds a set threshold value; the invention can automatically and quickly track the security event and provide timely early warning.
Description
Technical Field
The present invention relates to the field of big data processing, and in particular, to a method, a system, a device, and a medium for processing event tracking.
Background
At present, aiming at emergent sanitary safety events, a quick and effective tracking early warning mechanism is lacked, data summarization statistics mostly depends on manual work, the processing efficiency is low, and the reliability is insufficient. And because the processing data volume is large, the detail characteristics are often ignored during data statistics, so that the accuracy of the data result is not high, and how to accurately and quickly monitor and track the specific event becomes a problem which needs to be solved at present.
Disclosure of Invention
In view of the problems in the prior art, the invention provides an event tracking processing method, system, device and medium, which mainly solve the problems of low automation degree and insufficient accuracy of the existing event monitoring and tracking.
In order to achieve the above and other objects, the present invention adopts the following technical solutions.
An event tracing processing method, comprising:
constructing an event set to be monitored, wherein each event factor in the event set to be monitored comprises one or more corresponding key features;
creating block data comprising a plurality of data nodes based on data records of a plurality of data acquisition points in a defined area, wherein each data node corresponds to a data acquisition point at a different geographic position;
searching real-time event records in a set time interval from the block data according to the key features of the event set to be monitored, and comparing the real-time event records with historical synchronous event records to obtain abnormal events;
and positioning a resident geographical position of the target object according to the abnormal event, and starting event early warning if a common target object contained in the resident geographical position exceeds a set threshold value.
Optionally, constructing the set of events to be monitored includes:
acquiring event description information and extracting key features from the event description information;
and associating the key features with time nodes corresponding to events to serve as event factors in the event set to be monitored.
Optionally, searching a real-time event record in a set time interval from the block data according to the key features of the event set to be monitored, and comparing the real-time event record with a historical synchronous event record to obtain an abnormal event, including:
sequentially connecting key features of single event factors in the event set to be monitored to obtain a key feature sequence;
taking the case records in the block data, the similarity of which with the key feature sequence reaches a set threshold value, as the real-time event records, and acquiring the number of the real-time event records and the distribution of each data node in the block data;
and determining abnormal data nodes according to the distribution, and/or comparing the number of the real-time event records with the average value of historical synchronous number, and judging whether the real-time event records are abnormal or not to obtain abnormal events.
Optionally, determining an abnormal data node according to the distribution includes:
if the proportion of the real-time event record quantity of one or more data nodes to the quantity of all real-time event records in the block data exceeds a set quantity threshold value, judging that the corresponding data node is abnormal, and acquiring the geographical position information of the abnormal data node;
and when the number of the abnormal data nodes is multiple, classifying the abnormal data nodes adjacent to the geographic position into one class to obtain one or more abnormal areas.
Optionally, locating the resident geographic location of the target object according to the abnormal event includes:
acquiring the identity information of the target object corresponding to the abnormal event, wherein the identity information comprises: name, identity address and mobile phone;
acquiring a first target area according to identity information of each target object, wherein the first target area is determined by a plurality of target objects with same-level identity addresses, and the same-level addresses comprise: the same village, the same cell and/or the same county city;
and if the first target area does not exist, acquiring the resident area of each target object according to the identity information of the target object, and acquiring one or more common target objects corresponding to the resident area, wherein the resident area is determined by a mobile phone of the target object.
Optionally, the residence area is determined by a mobile phone of the target object, and includes:
and according to the coverage range of one or more base stations, acquiring the resident area of the target object.
Optionally, the obtaining the exception event further comprises:
and carrying out consensus comparison on the real-time event record in the current block data and historical synchronous event records contained in the plurality of block data, and if the number of the feedback abnormal block data exceeds two thirds of the number of all the block data participating in the comparison, judging that the current real-time event record is abnormal.
An event trace processing system, comprising:
the event creating module to be monitored is used for constructing an event set to be monitored, and each event factor in the event set to be monitored comprises one or more corresponding key features;
the block data creating module is used for creating block data comprising a plurality of data nodes based on data records of a plurality of data acquisition points in a defined area, wherein each data node corresponds to a data acquisition point at a different geographic position;
the abnormal acquisition module is used for searching real-time event records in a set time interval from the block data according to the key features of the event set to be monitored, and comparing the real-time event records with historical synchronous event records to acquire abnormal events;
and the target tracking early warning module is used for positioning a resident geographical position of a target object according to the abnormal event, and starting event early warning if a common target object contained in the resident geographical position exceeds a set threshold value.
An event trace processing device comprising:
one or more processors; and
one or more machine readable media having instructions stored thereon that, when executed by the one or more processors, cause the apparatus to perform the event tracing processing method.
A machine-readable medium having stored thereon instructions, which when executed by one or more processors, cause an apparatus to perform the event tracing processing method.
As described above, the event trace processing method, system, device, and medium according to the present invention have the following advantageous effects.
By constructing the event set to be monitored, abnormal event tracking monitoring is carried out aiming at specific events and specific areas, abnormal identification and target object tracking are automatically completed, and accuracy and efficiency of event monitoring and processing are improved.
Drawings
Fig. 1 is a flowchart illustrating an event tracing processing method according to an embodiment of the present invention.
FIG. 2 is a block diagram of an event tracking processing system according to an embodiment of the present invention.
Fig. 3 is a schematic structural diagram of an apparatus according to an embodiment of the present invention.
Detailed Description
The embodiments of the present invention are described below with reference to specific embodiments, and other advantages and effects of the present invention will be easily understood by those skilled in the art from the disclosure of the present specification. The invention is capable of other and different embodiments and of being practiced or of being carried out in various ways, and its several details are capable of modification in various respects, all without departing from the spirit and scope of the present invention. It is to be noted that the features in the following embodiments and examples may be combined with each other without conflict.
It should be noted that the drawings provided in the following embodiments are only for illustrating the basic idea of the present invention, and the components related to the present invention are only shown in the drawings rather than drawn according to the number, shape and size of the components in actual implementation, and the type, quantity and proportion of the components in actual implementation may be changed freely, and the layout of the components may be more complicated.
Referring to fig. 1, the present invention provides an event tracing processing method, which includes steps S01-S04.
Step S01, constructing an event set to be monitored, wherein each event factor in the event set to be monitored comprises one or more corresponding key features;
step S02, creating block data containing a plurality of data nodes based on the data records of a plurality of data acquisition points in the defined area, wherein each data node corresponds to a data acquisition point at a different geographic position;
step S03, searching real-time event records in a set time interval from the block data according to the key characteristics of the event set to be monitored, and comparing the real-time event records with historical synchronous event records to obtain abnormal events;
and step S04, positioning the resident geographic position of the target object according to the abnormal event, and starting event early warning if the common target object contained in the resident geographic position exceeds a set threshold value.
In step S01 of the present embodiment, the set of events to be monitored may include: acquiring event description information, and extracting key features from the event description information; and associating the key features with the time nodes corresponding to the events to be used as event factors in the event set to be monitored. Illustratively, taking influenza as an example, the descriptive information corresponding to the influenza can be expressed as "general symptoms are acute onset, weakness symptom exists in prodromal period, general poisoning symptoms such as high fever, chills, headache, general muscle and joint ache and the like appear very quickly, and local symptoms such as nasal obstruction, rhinorrhea, sore throat, dry cough, discomfort after sternum, flushing face, conjunctival congestion and the like can be accompanied or not accompanied". Based on the universal description information of the event to be monitored, symptoms corresponding to the flu can be extracted as key features. Such key features may include: high fever, aversion to cold, chills, headache, etc. Further, time nodes with a large spread of influenza recorded over the past few years or more may be associated with the corresponding key features as event factors. The recording time node can provide data reference for early warning of subsequent events according to the number of cases and the change trend of the corresponding time node. Of course, the event set to be monitored may also include other events, such as high-threat virus infection, food safety event, and other public health events, and may be flexibly set according to practical applications. The time description information can be sorted based on the symptoms of historical events and adjusted by a panel of experts to ensure that the description information is accurate and reliable. The feature extraction may adopt a conventional neural network, and the specific feature extraction process is not described herein again.
In step S02 of this embodiment, the plurality of tiles may be divided according to regions, such as a district or a county, and the specific dividing manner may be adjusted according to the actual application requirement, which is not limited herein. And after the block division is completed, constructing block data by taking the data acquisition points in the blocks as data nodes. Each data acquisition point in the block can perform data encryption sharing in a public key-private key pair mode. Illustratively, the data acquisition points may include hospitals, health stations, clinics, and the like. And storing the historical case data of each data acquisition point in the corresponding data node so as to access the case data in each data node through any data node in the block data. And simultaneously recording the geographical position information of the corresponding data acquisition points by each data node. To locate the abnormal event based on the geographical location information. In another embodiment, data communication can be established between different block data to realize data sharing of the block area.
In step S03 of the present embodiment, when performing an event search on one of the block data based on the key features in the event set to be monitored, the key features included in a single event factor in the event set to be monitored can be sequentially connected to form a key feature sequence corresponding to the event factor. Illustratively, the key signature sequence for influenza can be expressed as { high fever, aversion to cold, chills, headache, general muscle and joint soreness }. And further, comparing the key characteristic sequence with the case records of each data node in the block data, and if the similarity of the key characteristic sequence and the case records of each data node in the block data reaches a set threshold, judging the corresponding case record as a real-time event record. In this way, all real-time event records in the corresponding block data for a period of time (e.g., a month, a quarter, etc.) can be obtained. And counting the real-time event quantity distribution of each data node in the block data according to the quantity of the real-time event records. And comparing and identifying the events based on the key characteristics, so that the real-time event records can be more accurately acquired. The problem of inaccurate data caused by simple data classification is avoided. Illustratively, if all cold symptoms are recorded as cold in a general way, no symptom differentiation is performed, which may cause data misjudgment and affect the final data output result.
In one embodiment, the abnormal data nodes may be determined according to the real-time event number distribution of each data node. And if the proportion of the number of the real-time event records of one or more data nodes to the number of all the real-time event records in the block data exceeds a set number threshold, judging that the corresponding data node is abnormal.
In another embodiment, the corresponding abnormal data node may also be determined according to a difference between the number of real-time event records in the data node and a mean of the number of all real-time event records in the block data. Illustratively, the data node anomaly discrimination formula can be expressed as:
Ti=log(Pi-E)
wherein, TiA quantized value, P, representing the difference between the number of real-time event records in the ith data node and the mean of the number of all real-time event records in the block dataiThe number of real-time event records in the ith data node is E, and the average value of the number of all real-time event records in the block data is E.
Further, an anomaly discrimination threshold may be set if TiAnd if the value is larger than the abnormity judging threshold value, the corresponding data node is abnormal.
The geographical position information of all abnormal data nodes can be obtained through the steps. And when the number of the abnormal data nodes is multiple, classifying the abnormal data nodes adjacent to the geographic position into one class to obtain one or more abnormal areas. And judging the concentration ratio of the abnormal cases through the abnormal area. Data nodes in the abnormal area can be summarized and comprehensively analyzed, and the data analysis and processing efficiency is improved.
In an embodiment, the number of the real-time event records of each data node in the block data may also be compared with the average value of the historical synchronization number, and whether the real-time event records are abnormal or not is determined, so as to obtain an abnormal event.
Specifically, according to the time node of the occurred event recorded in the event set to be monitored, the event record corresponding to the time node can be selected as the comparison reference standard. And judging whether the current real-time event record reaches the historical event standard or not, and further determining the abnormality.
For example, the real-time event record in the current block data may be compared with the historical contemporaneous event records included in the plurality of block data in a consensus manner, and if the number of the block data with abnormal feedback exceeds two thirds of the number of all the block data participating in the comparison, the current real-time event record is determined to be abnormal.
In the process of consensus comparison, a plurality of representative block data can be selected from all the block data for consensus comparison. Comparing the number of the real-time event records in the current block data with the number of the historical contemporaneous event records in each selected block data, outputting a corresponding comparison result by each block, and judging that the real-time event records in the current block are abnormal if more than two-thirds of the results are abnormal; otherwise, if the abnormal result is less than two-thirds or more, the real-time event record in the current block is determined to be normal.
In another embodiment, when the abnormal data node in the current block data cannot be determined, that is, when the ratio of the number of the real-time event records of the data node to the number of all the real-time event records in the block data does not exceed the set number threshold, the abnormal block data may be determined by sharing and comparing the plurality of block data.
In step S04 of the present embodiment, an abnormal event in the block within a period of time can be obtained based on the above steps. The abnormal event corresponds to the case record of each data node in the block data. Identity information of the target object can be obtained according to the case record. Illustratively, the case records can be electronic medical records and the target object can be a patient for a visit. The identity information may include: name, identity address, mobile phone, etc.
In an embodiment, a first target area is obtained according to identity information of each target object, and the first target area is determined by a plurality of target objects having peer identity addresses, where the peer addresses include: the same village and town, the same cell and/or the same county and city. For example, information comparison can be performed according to the address of the identification card associated with the medical record of the patient, and whether a plurality of patients in the same village, the same cell, the same county, and/or the same region exist in each patient corresponding to the abnormal event is determined. And a plurality of patients in the same village, same cell, same county, and/or same region are drawn into the first target area. If the number of patients in the first target area exceeds a set threshold, an aggregate event may be identified, an emergency treatment protocol initiated, isolation or other precautionary measure directed to the first target area. The target area is determined based on the identity address, information is relatively convenient to obtain, and the area positioning process can be simplified.
In an embodiment, if the first target area does not exist, the resident area of each target object is obtained according to the identity information of the target object, and one or more common target objects corresponding to the resident area are obtained, wherein the resident area is determined by a mobile phone of the target object. Specifically, when the first target area is difficult to determine based on the identity information, the mobile network operator interface can be connected through the target object telephone, the access authority is obtained through identity verification, and then the access record of the target object logging in the mobile network operator base station is inquired based on the mobile telephone number. From the access record, the dwell region of the target object over time may be determined. Due to different urban and suburban communication demands, signal coverage ranges of different base stations are different. The size of the resident area can be adjusted according to the actual base station setting. The positioning based on the target object residence area is beneficial to contact history investigation, infection source tracking and the like aiming at infectious collective events, so that an emergency treatment scheme can be specified in a targeted manner and accurate early warning information can be given.
In an embodiment, the information screening can be performed twice by combining the identity address and the mobile phone, so that misjudgment information is eliminated, and the accuracy of positioning the resident area and tracking the target object is improved.
Referring to fig. 2, the present embodiment provides an event tracing system for executing the event tracing method in the foregoing method embodiments. Since the technical principle of the system embodiment is similar to that of the method embodiment, repeated description of the same technical details is omitted.
In one embodiment, an event trace processing system includes:
the event to be monitored creating module 10 is configured to construct an event set to be monitored, where each event factor in the event set to be monitored includes one or more corresponding key features;
the block data creating module 11 is configured to create block data including a plurality of data nodes based on data records of a plurality of data acquisition points in a defined area, where each data node corresponds to a data acquisition point in a different geographic location;
the abnormal acquisition module 12 is configured to search a real-time event record in a set time interval from the block data according to the key features of the event set to be monitored, and compare the real-time event record with a historical event record in the same period to acquire an abnormal event;
and the target tracking early warning module 13 is configured to locate a resident geographic position of the target object according to the abnormal event, and start event early warning if a common target object included in the resident geographic position exceeds a set threshold.
The event to be monitored creation module 10 is configured to assist in executing step S01 described in the foregoing method embodiment; the tile data creating module 11 is configured to execute step S02 described in the foregoing method embodiment; the anomaly obtaining module 12 is configured to perform step S03 described in the foregoing method embodiment; the target tracking early warning module 13 is configured to execute step S04 described in the foregoing method embodiment.
An embodiment of the present application further provides an event tracking processing device, where the event tracking processing device may include: one or more processors; and one or more machine readable media having instructions stored thereon that, when executed by the one or more processors, cause the apparatus to perform the method of fig. 1. In practical applications, the device may be used as a terminal device, and may also be used as a server, where examples of the terminal device may include: the mobile terminal includes a smart phone, a tablet computer, an electronic book reader, an MP3 (Moving Picture Experts Group Audio Layer III) player, an MP4 (Moving Picture Experts Group Audio Layer IV) player, a laptop, a vehicle-mounted computer, a desktop computer, a set-top box, an intelligent television, a wearable device, and the like.
The present application also provides a machine-readable medium, in which one or more modules (programs) are stored, and when the one or more modules are applied to a device, the device may execute instructions (instructions) included in the event tracking processing method in fig. 1 according to the present application. The machine-readable medium can be any available medium that a computer can store or a data storage device including one or more available media integrated servers, data centers, and the like. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.
Referring to fig. 3, the present embodiment provides a device 80, and the device 80 may be a desktop device, a laptop computer, a smart phone, or the like. In detail, the device 80 comprises at least, connected by a bus 81: a memory 82 and a processor 83, wherein the memory 82 is used for storing computer programs, and the processor 83 is used for executing the computer programs stored in the memory 82 to execute all or part of the steps of the foregoing method embodiments.
The above-mentioned system bus may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The system bus may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one thick line is shown, but this does not mean that there is only one bus or one type of bus. The communication interface is used for realizing communication between the database access device and other equipment (such as a client, a read-write library and a read-only library). The Memory may include a Random Access Memory (RAM), and may further include a non-volatile Memory (non-volatile Memory), such as at least one disk Memory.
The Processor may be a general-purpose Processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like; the Integrated Circuit may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, a discrete Gate or transistor logic device, or a discrete hardware component.
In summary, according to the event tracking processing method, system, device and medium of the present invention, the event set to be monitored is set through the key features, so that more accurate event records can be obtained, and the accuracy of the abnormal event early warning is improved; evaluating the current event risk based on the historical event record, fully utilizing historical data to complete automatic data evaluation, reducing manual participation and improving processing efficiency and reliability; the method has the advantages that target area preliminary screening is carried out based on the identity address, concentrated abnormal events possibly existing are quickly positioned, accurate abnormal target object tracking is carried out by combining mobile phone positioning, contact history tracking and abnormal source tracing are facilitated, and abnormal early warning and tracking processing efficiency is improved. Therefore, the invention effectively overcomes various defects in the prior art and has high industrial utilization value.
The foregoing embodiments are merely illustrative of the principles and utilities of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or change the above-mentioned embodiments without departing from the spirit and scope of the present invention. Accordingly, it is intended that all equivalent modifications or changes which can be made by those skilled in the art without departing from the spirit and technical spirit of the present invention be covered by the claims of the present invention.
Claims (10)
1. An event tracing processing method, comprising:
constructing an event set to be monitored, wherein each event factor in the event set to be monitored comprises one or more corresponding key features;
creating block data comprising a plurality of data nodes based on data records of a plurality of data acquisition points in a defined area, wherein each data node corresponds to a data acquisition point at a different geographic position;
searching real-time event records in a set time interval from the block data according to the key features of the event set to be monitored, and comparing the real-time event records with historical synchronous event records to obtain abnormal events;
and positioning a resident geographical position of the target object according to the abnormal event, and starting event early warning if a common target object contained in the resident geographical position exceeds a set threshold value.
2. The event tracing processing method according to claim 1, wherein constructing a set of events to be monitored comprises:
acquiring event description information and extracting key features from the event description information;
and associating the key features with time nodes corresponding to events to serve as event factors in the event set to be monitored.
3. The event tracking processing method according to claim 1, wherein the step of searching real-time event records in a set time interval from the block data according to the key features in the event set to be monitored, and comparing the real-time event records with historical synchronous event records to obtain abnormal events comprises the steps of:
sequentially connecting key features of single event factors in the event set to be monitored to obtain a key feature sequence;
taking the case records in the block data, the similarity of which with the key feature sequence reaches a set threshold value, as the real-time event records, and acquiring the number of the real-time event records and the distribution of each data node in the block data;
and determining abnormal data nodes according to the distribution, and/or comparing the number of the real-time event records with the average value of historical synchronous number, and judging whether the real-time event records are abnormal or not to obtain abnormal events.
4. The event tracing processing method according to claim 3, wherein determining an abnormal data node from the distribution comprises:
if the proportion of the number of the real-time event records of one or more data nodes to the number of all the real-time event records in the block data exceeds a set number threshold, judging that the corresponding data node is abnormal, and acquiring the geographical position information of the abnormal data node;
and when the number of the abnormal data nodes is multiple, classifying the abnormal data nodes adjacent to the geographic position into one class to obtain one or more abnormal areas.
5. The event tracing processing method according to claim 1, wherein locating a target object resident geographic location according to the abnormal event comprises:
acquiring the identity information of the target object corresponding to the abnormal event, wherein the identity information comprises: name, identity address and mobile phone;
acquiring a first target area according to identity information of each target object, wherein the first target area is determined by a plurality of target objects with same-level identity addresses, and the same-level identity addresses comprise: the same village, the same cell and/or the same county city;
and if the first target area does not exist, acquiring the resident area of each target object according to the identity information of the target object, and acquiring one or more common target objects corresponding to the resident area, wherein the resident area is determined by a mobile phone of the target object.
6. The event tracking processing method according to claim 5, wherein the dwell region is determined by a mobile phone of the target object, comprising:
and according to the coverage range of one or more base stations, acquiring the resident area of the target object.
7. The event tracing processing method according to claim 1, wherein acquiring an exception event further comprises:
and carrying out consensus comparison on the real-time event record in the current block data and historical synchronous event records contained in the plurality of block data, and if the number of the feedback abnormal block data exceeds two thirds of the number of all the block data participating in the comparison, judging that the current real-time event record is abnormal.
8. An event trace processing system, comprising:
the event creating module to be monitored is used for constructing an event set to be monitored, and each event factor in the event set to be monitored comprises one or more corresponding key features;
the block data creating module is used for creating block data comprising a plurality of data nodes based on data records of a plurality of data acquisition points in a defined area, wherein each data node corresponds to a data acquisition point at a different geographic position;
the abnormal acquisition module is used for searching real-time event records in a set time interval from the block data according to the key features of the event set to be monitored, and comparing the real-time event records with historical synchronous event records to acquire abnormal events;
and the target tracking early warning module is used for positioning a resident geographical position of a target object according to the abnormal event, and starting event early warning if a common target object contained in the resident geographical position exceeds a set threshold value.
9. An event trace processing device, comprising:
one or more processors; and
one or more machine-readable media having instructions stored thereon that, when executed by the one or more processors, cause the apparatus to perform the method of any of claims 1-7.
10. A machine-readable medium having stored thereon instructions, which when executed by one or more processors, cause an apparatus to perform the method of any of claims 1-7.
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