CN116244106A - Data detection method of civil aviation data, storage medium and electronic equipment - Google Patents
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Abstract
The invention relates to the field of data processing, in particular to a data detection method, a storage medium and electronic equipment of civil aviation data, wherein the method comprises the following steps: if the target field content is the same as the first field content group B 1 If any of the target field contents is the same, determining the target field contents as normal field contents; b (B) 1 Is determined by the following method: acquisition of a in history field content group A, A i Historical field content corresponding to the target field name in event data of the ith historical event corresponding to the target mark; acquiring B in preset field content group B j The j preset field content corresponding to the target field name; a, a i E B; acquisition of h j ＝p j /n，p j For A and b j The number of the same history field contents, n being the number of history field contents in A; if h j Not less than Q1, b j As the first field content to obtain B 1 . Thus, the accuracy of data detection of the target field content can be improved.
Description
Technical Field
The present invention relates to the field of data processing, and in particular, to a method for detecting civil aviation data, a storage medium, and an electronic device.
Background
With the continuous development of economy, more and more people can choose to take an airplane as a travel mode, and a large amount of civil aviation data can be generated almost every day.
In order to ensure the data reliability of civil aviation data as much as possible, the civil aviation data is generally subjected to data detection after being generated, and whether each piece of sub-data in the data to be detected exists in the historical data is generally determined in the process of carrying out data detection on any piece of data to be detected; the historical data are data generated before the data to be detected, and the historical data and the data to be detected are data of the same navigation; based on the above, if any sub-data in the data to be detected exists in the history data, the sub-data is the normal sub-data with high probability; otherwise, the sub-data is the abnormal sub-data with high probability.
However, if there is abnormal data in the history data, even if any sub-data of the data to be detected is abnormal sub-data, the sub-data still exists in the history data, and at this time, the sub-data is misjudged as normal sub-data, so that the accuracy of detecting the data to be detected is low.
Disclosure of Invention
Aiming at the technical problems, the invention adopts the following technical scheme:
according to an aspect of the present invention, there is provided a data detection method of civil aviation data, the data detection method comprising the steps of:
s100, in event data of a target event corresponding to a target identifier, taking field content corresponding to a target field name as target field content; the event data of the target event comprises a plurality of field names and field contents corresponding to each field name, wherein the target field name is any field name.
S200, determining whether the target field content is in accordance with the first field content group B 1 The content of any first field in the database is the same; if yes, the target field content is determined to be the normal field content.
First field content group B 1 Is determined by the following method:
s210, acquiring a history field content group A= (a) corresponding to the target field name 1 ,a 2 ,...,a i ,...,a n ) I=1, 2, n; wherein a is i The method comprises the steps that historical field content corresponding to a target field name in event data of an ith historical event corresponding to a target identifier is obtained, and n is the number of the historical events corresponding to the target identifier; the event end time of each historical event is before the event execution time of the target event; the event data of the historical event comprises each field name and historical field content corresponding to each field name; target field name has corresponding preset field content group b= (B) 1 ,b 2 ,...,b j ,...,b m ) J=1, 2, m; wherein b j The j preset field content corresponding to the target field name is obtained, and m is the number of the preset field contents corresponding to the target field name; a, a i ∈B。
S220, according to a and B, obtain the first priority group h= (H) 1 ,h 2 ,...,h j ,...,h m ) The method comprises the steps of carrying out a first treatment on the surface of the Wherein h is j For the j-th first priority in H, H j ＝p j /n，p j Is a as 1 、a 2 、...、a i 、...、a n Intermediate and b j Number of identical history field contents.
S230, if h j Greater than or equal to the first threshold Q1, then b j As the first field content to obtain a first field content group B 1 ＝(b 1 1 ,b 2 1 ,...,b k 1 ,...,b q 1 ) K=1, 2, q; wherein b k 1 Is B 1 The kth first field content of (B), q is B 1 The number of first field contents in (a); q is less than or equal to m.
According to another aspect of the present invention, there is also provided a non-transitory computer readable storage medium storing at least one instruction or at least one program, the at least one instruction or the at least one program being loaded and executed by a processor to implement the data detection method of civil aviation data.
According to another aspect of the present invention, there is also provided an electronic device comprising a processor and the above-described non-transitory computer-readable storage medium.
The invention has at least the following beneficial effects:
in the invention, in event data of each historical event, the historical field content corresponding to a target field name is determined to obtain A, then H is determined, namely, the first priority of each preset field content corresponding to the target field name is determined, thus obtaining the quantity proportion of each preset field content corresponding to the target field name in A, and then the preset field content corresponding to each first priority which is greater than or equal to Q1 in H is taken as the first field content to obtain B 1 At this time, B 1 The first priority of each first field content in (a) is larger, namely B 1 The number of the first field contents in A is larger than the number of the first field contents in A; based on this, if the target field content is equal to B 1 If any of the first field contents is the same, the target field content is determined to be the normal field content.
In contrast to the related art, in which the target field content is determined to be the normal field content when the target field content is included in A, the present invention is based on B 1 Detecting the contents of the target field, due to B 1 The number of the first field contents in A is larger than the number of the first field contents in A, so that each first field content is the same as more historical field contents, and the possibility of abnormal field contents in event data of which any first field content is a historical event can be reduced, thus the target field content and B are the same 1 When any one of the first field contents is the same, the target field content is determined to be the normal field content, so that the purpose of improving the accuracy of data detection on the target field content is achieved.
In addition, the target field content is determined to be the normal field content when the target field content is included in a than in the related art, but since the same history field content is more likely to exist in a, it is more likely to exist to combine the target field content with the same history fieldUnder the condition of content comparison, the computing resource is wasted, and the invention adopts the method based on B 1 Data detection method for detecting content of target field, due to B 1 The content of any two first fields is different, so that the situation that the target field content is compared with the same first field content basically does not occur, the computing resource can be saved, and the efficiency of data detection can be improved.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and 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 a data detection method of civil aviation data provided by an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to fall within the scope of the invention.
The embodiment of the invention provides a data detection method for civil aviation data, wherein the method can be completed by any one or any combination of the following: terminals, servers, and other devices with processing capabilities, which are not limited in this embodiment of the present invention.
In the embodiment of the present invention, a server is taken as an example, and a method for detecting civil aviation data will be described below with reference to a flowchart of the method for detecting civil aviation data shown in fig. 1.
The data detection method comprises the following steps:
s100, in event data of a target event corresponding to the target identifier, taking field content corresponding to the target field name as target field content.
The event data of the target event comprises a plurality of field names and field contents corresponding to each field name, wherein the target field name is any field name.
Specifically, the target identifier is an identifier of the target navigation. The target event is any executed and ended flight mission, any executed and not ended flight mission, or any not executed flight mission in plan, as embodiments of the invention are not limited in this regard.
The object field name is an identifier luggage corresponding to the luggage carousel, and in the event data of the object event, the field content in the field name luggage is a, which indicates that the luggage carousel corresponding to the object event is a luggage carousel with a number a; based on this, the target field content is a.
S200, determining whether the target field content is in accordance with the first field content group B 1 The content of any first field in the database is the same; if yes, the target field content is determined to be the normal field content.
Wherein the first field content group B 1 Is determined by the following method:
s210, acquiring a history field content group A= (a) corresponding to the target field name 1 ,a 2 ,...,a i ,...,a n )，i＝1,2,...,n。
Wherein a is i The method comprises the steps that historical field content corresponding to a target field name in event data of an ith historical event corresponding to a target identifier is obtained, and n is the number of the historical events corresponding to the target identifier; the event end time of each historical event is before the event execution time of the target event; the event data of the historical event comprises each field name and historical field content corresponding to each field name. Target field name has corresponding preset field content group b= (B) 1 ,b 2 ,...,b j ,...,b m ) J=1, 2, m; wherein b j The j preset field content corresponding to the target field name is obtained, and m is the number of the preset field contents corresponding to the target field name; a, a i ∈B。
Specifically, the event end time is the aircraft landing time, the event execution event is the aircraft takeoff time, and the historical event is the flight task that has been executed and ended before the target event.
For example, the destination field name is an identifier luggage corresponding to a luggage carousel, the airports corresponding to the destination event and the history event include 4 luggage carousels with numbers A, B, C and D, respectively, based on this, a preset field content group b= (a, B, C, D) corresponding to luggage, and A, B, C and D are preset field contents corresponding to luggage. Correspondingly, a i A, B, C, D.
S220, according to a and B, obtain the first priority group h= (H) 1 ,h 2 ,...,h j ,...,h m )。
Wherein h is j For the j-th first priority in H, H j ＝p j /n，p j Is a as 1 、a 2 、...、a i 、...、a n Intermediate and b j Number of identical history field contents.
S230, if h j Greater than or equal to the first threshold Q1, then b j As the first field content to obtain a first field content group B 1 ＝(b 1 1 ,b 2 1 ,...,b k 1 ,...,b q 1 )，k＝1,2,...,q。
Wherein b k 1 Is B 1 The kth first field content of (B), q is B 1 The number of first field contents in (a); q is less than or equal to m.
From this, in the event data of each history event, the history field content corresponding to the target field name is determined to obtain a, then H is determined, that is, the first priority of each preset field content corresponding to the target field name is determined, so as to obtain the number ratio of each preset field content corresponding to the target field name in a, and then the preset field content corresponding to each first priority greater than or equal to Q1 in H is used as the first field content to obtain B 1 At this time, B 1 Each first word of (a)The first priority of the segment content is greater, i.e. B 1 The number of the first field contents in A is larger than the number of the first field contents in A; based on this, if the target field content is equal to B 1 If any of the first field contents is the same, the target field content is determined to be the normal field content.
In contrast to the related art, in which the target field content is determined to be the normal field content when the target field content is included in A, the present invention is based on B 1 Detecting the contents of the target field, due to B 1 The number of the first field contents in A is larger than the number of the first field contents in A, so that each first field content is the same as more historical field contents, and the possibility of abnormal field contents in event data of which any first field content is a historical event can be reduced, thus the target field content and B are the same 1 When any one of the first field contents is the same, the target field content is determined to be the normal field content, so that the purpose of improving the accuracy of data detection on the target field content is achieved.
In addition, compared with the related art, the target field content is determined to be the normal field content when the target field content is included in A, but because the same history field content is more likely to exist in A, the situation that the target field content is compared with the same history field content is more likely to exist, and the calculation resource is wasted is more likely to exist, and the invention adopts the method based on B 1 Data detection method for detecting content of target field, due to B 1 The content of any two first fields is different, so that the situation that the target field content is compared with the same first field content basically does not occur, the computing resource can be saved, and the efficiency of data detection can be improved.
Optionally, step S200 includes the steps of:
s201, determining whether the target field content is in accordance with the first field content group B 1 The content of any first field in the database is the same; if yes, determining the target field content as normal field content; otherwise, step S300 is entered.
Based on this, the data detection method further includes the steps of:
s300, determining whether the target field content is in the same group as the second field content 2 The content of any second field in the database is the same; if yes, the target field content is determined to be the normal field content.
Wherein, after step S220, the second field content group B 2 Is determined by the following method:
s310, if h j Less than the first threshold Q1, b will be j As the third field content to obtain a third field content group B 3 ＝(b 1 3 ,b 2 3 ,...,b c 3 ,...,b d 3 )，c＝1,2,...,d。
Wherein b c 3 Is B 3 The content of the c third field, d is B 3 The number of third field contents in (c); d is less than or equal to m.
S320, if b c 3 Satisfying the preset priori condition, b c 3 As the second field content to obtain a second field content group B 2 ＝(b 1 2 ,b 2 2 ,...,b e 2 ,...,b f 2 )，e＝1,2,...,f。
Wherein the prior condition is that the corresponding field content is trusted data, b e 2 Is B 2 The e second field content, f is B 2 The number of second field contents in the database; f is less than or equal to d.
Therefore, after determining H, the preset field content corresponding to each first priority level smaller than Q1 in H is used as the third field content to obtain B 3 At this time, B 3 The first priority of each third field content in (B) is smaller, i.e. B 3 The number of the third field contents in A is smaller than the prior condition in B 3 Screening to obtain B 2 The method comprises the steps of carrying out a first treatment on the surface of the Based on this, if the target field content is different from each of the second field contents, then the target field content is different from B 2 Any of the second fields having the same content, the target word can still be usedThe segment content is determined as normal field content. Compared with the fact that if the number of any preset field content in A is smaller, whether the target field content identical to the preset field content is normal field content is uncertain, if any preset field content meets the priori condition, namely the preset field content is trusted data, even if the number of the preset field content in A is smaller, the target field content identical to the preset field content can be determined to be normal field content, and the accuracy of data detection of the target field content can be improved.
Optionally, step S320 includes the steps of:
s321, if b c 3 For any one of a plurality of preset trusted field contents, b is then c 3 As the second field content to obtain a second field content group B 2 ＝(b 1 2 ,b 2 2 ,...,b e 2 ,...,b f 2 )，e＝1,2,...,f。
In a specific embodiment of the step S321, B may be obtained at the server 3 After that, the server can obtain the trusted field content corresponding to the target identifier and the target field name input by airport staff from the preset storage space, and then if b c 3 For any one of a plurality of preset trusted field contents, b is then c 3 As a second field content to obtain B 2 . The preset storage space may be a storage space in the server or a storage space in other devices except the server.
Optionally, step S300 includes the steps of:
s301, determining whether the target field content is in the same group as the second field content 2 The content of any second field in the database is the same; if yes, determining the target field content as normal field content; otherwise, step S400 is entered.
Based on this, the data detection method further includes the steps of:
s400, determining whether the target field content is in group B with the fourth field content 4 In (a) and (b)Any fourth field has the same content; if yes, the target field content is determined to be the normal field content.
Wherein, after step S320, the fourth field content group B 4 Is determined by the following method:
s410, if
Will b c 3 As the fifth field content to obtain a fifth field content group B 5 ＝(b 1 5 ,b 2 5 ,...,b var 5 ,...,b amo 5 )，var＝1,2,...,amo。
Wherein b e 5 Is B 5 In the fifth field content of var, amo is B 2 The number of fifth field contents in (a); amo is less than or equal to m.
S420, if a i The corresponding first object identifier is the same as the second object identifier, and then a i As target history field content to obtain target history field content group A 1 ＝(a 1 1 ,a 2 1 ,...,a cha 1 ,...,a cin 1 )，cha＝1,2,...,cin。
The first object is identified as the object for executing the corresponding historical event, and the second object is identified as the object for executing the target event; a, a cha 1 Is A 1 The content of the cha-th target history field in the table, and cin is A 1 The number of target history field contents in the database.
Specifically, in one possible implementation manner, the target object is an aircraft, the first target object identifier and the second target object identifier may be numbers of corresponding target objects, and the first target object identifier and the second target object identifier may also be flight numbers corresponding to the corresponding target objects, which is not limited in this embodiment of the present invention.
S430, according to A 1 And B, acquiring a second priority group H 1 ＝(h 1 1 ,h 2 1 ,...,h j 1 ,...,h m 1 )。
Wherein h is j 1 Is H 1 The j th second priority, h j 1 ＝p j 1 /cin，p j 1 Is a as 1 1 、a 2 1 、...、a cha 1 、...、a cin 1 Intermediate and b j Number of identical history field contents.
S230, if h j 1 Greater than or equal to the second threshold Q2, then b j As the fourth field content to obtain a fourth field content group B 4 ＝(b 1 4 ,b 2 4 ,...,b str 4 ,...,b con 4 )，str＝1,2,...,con。
Wherein b str 4 Is B 4 Str fourth field content in (2), con is B 6 The number of fourth field contents; con is less than or equal to m.
Specifically, 0.4.ltoreq.q2.ltoreq.0.7, preferably q2=0.5.
It can be seen that in the present invention, the target field content and the second field content group B 2 In the case that the contents of each second field are different, it can be determined whether the contents of the target field are different from B 4 The content of any fourth field in the list is the same; if yes, the target field content is determined to be the normal field content. Due to B 4 Each of the fourth field contents in A is smaller in number than in A, but in A 1 The number of (A) is relatively large due to A 1 The identification of the object corresponding to the event corresponding to the content of each object history field is the same, thus B can be explained 4 The possibility that each fourth field content is error data is small, so that the possibility that the target field content which is the same as any fourth field content is determined to be abnormal field content can be reduced, and the purpose of improving the accuracy of data detection on the target field content is achieved.
In one possible embodiment, the first threshold Q1 is determined by the following method:
s231, acquiring a preset field content list T= (T) 1 ,t 2 ,...,t sqr1 ,...,t tan1 ),t sqr1 ＝(t sqr1 1 ,t sqr1 2 ,...,t sqr1 por1 ,...,t sqr1 L1(sqr1) )，sqr1＝1,2,...,tan1，por1＝1,2,...,L1(sqr1)。
Wherein t is sqr1 For a preset field content group corresponding to the sqr1 th field name, tan1 is the number of field names, t sqr1 por1 For the preset field content of the por1 corresponding to the field name of the sqr1, L1 (sqr 1) is the number of the preset field content corresponding to the field name of the sqr 1; b is t 1 、t 2 、...、t sqr 、...、t tan Any one of the above.
S232, if L1 (sqr 1) =m, then t will be sqr1 As a target preset field content group, and t is set as sqr1 Each preset field content in the list is used as target preset field content to obtain a target preset field content list T1= (T1) 1 ,t1 2 ,...,t1 sqr2 ,...,t1 tan2 ),t1 sqr2 ＝(t1 sqr2 1 ,t1 sqr2 2 ,...,t1 sqr2 por2 ,...,t1 sqr2 L2(sqr2) )，sqr2＝1,2,...,tan2，por2＝1,2,...,L2(sqr2)。
Wherein t1 sqr2 For the sqr2 th target preset field content group in T1, tan2 is the number of target preset field content groups in T1, T1 sqr2 por2 Is t1 sqr2 The content of the target preset field of the (por 2) th target preset field, L2 (sqr 2) is t1 sqr2 The target preset field content amount.
S233, obtaining a history field content list KE= (KE) 1 ,ke 2 ,...,ke sqr2 ,...,ke tan2 )，
ke sqr2 ＝(ke sqr2 1 ,ke sqr2 2 ,...,ke sqr2 i ,...,ke sqr2 n )。
Wherein ke is sqr2 For the sqr2 th history field content group in KE，ke sqr2 i In event data of the ith historical event corresponding to the target identification, t1 sqr2 History field content corresponding to the corresponding field name; a is ke 1 、ke 2 、...、ke sqr2 、...、ke tan2 Any one of the above.
S234, according to T1 and KE, a priority list LEV= (LEV) to be processed is obtained 1 ,lev 2 ,...,lev sqr2 ,...,lev tan2 )，
lev sqr2 ＝(lev sqr2 1 ,lev sqr2 2 ,...,lev sqr2 por2 ,...,lev sqr2 L2(sqr2) )。
Wherein lev is sqr2 For the sqr2 th pending priority group in LEV, LEV sqr2 por2 Is lev sqr2 The first to-be-processed priority of (a) is set; lev (Lev) sqr2 por2 ＝gar1 sqr2 por2 /n，gar1 sqr2 por2 For ke sqr2 1 、ke sqr2 2 、...、ke sqr2 i 、...、ke sqr2 n Intermediate and t1 sqr2 por2 Number of identical history field contents.
S235, according to LEV, average priority group AVE= (AVE) is obtained 1 ,ave 2 ,...,ave sqr2 ,...,ave tan2 )。
Wherein ave sqr2 Is lev sqr2 Corresponding average priority, ave sqr2 ＝[∑ por2＝1 L2(sqr2) (lev sqr2 por2 )]/[L2(sqr2)]。
S236, if the data association characteristic value M corresponding to the AVE is smaller than or equal to the preset threshold value, Q1 is equal to the target average priority AVE 0 。
Wherein M= [ Σ sqr2＝1 tan2 (ave sqr2 -ave 0 ) 2 ]/tan2，ave 0 ＝[∑ sqr2＝1 tan2 (ave sqr2 )]/tan2。
From this, Q1 can be based on the preset field corresponding to the target field nameAnd determining the number of the contents, and determining a plurality of target preset field content groups in T to obtain T1, and obtaining Q1 based on T1. The number of target preset field contents included in each target preset field content group in T1 is the same, compared with the preset field content groups with different dimensions, Q1 determined based on the target preset field content groups with the same dimensions is more reasonable, and therefore B is smaller than B1 1 Is less likely to be abnormal data, and is further matched with B 1 The accuracy of the detection result of detecting the target field content with the same content of any first field is higher, and the aim of improving the accuracy of detecting the data of the target field content is fulfilled.
Optionally, after step S235, the first threshold Q1 is further determined by:
s237, if the data association characteristic value M corresponding to the AVE is greater than the preset threshold, Q1 is equal to the preset target threshold corresponding to the target identifier. Wherein the preset threshold is greater than or equal to 0.01 and less than or equal to 0.15, preferably the preset threshold is equal to 0.01
In another possible embodiment, Q1 is a preset value pres, optionally 0.005. Ltoreq.pres.ltoreq.0.1, preferably pres=0.01.
Therefore, compared with the steps S231 to S237, the Q1 in the present invention can directly use the preset value pres without calculation to save the calculation resources.
Optionally, step S400 includes the steps of:
s401, determining whether the target field content is in group B with the fourth field content 4 The content of any fourth field in the list is the same; if yes, determining the target field content as normal field content; otherwise, the target field content is determined to be the abnormal field content.
Optionally, the target field name is an identification corresponding to the event execution time, the event end time, the associated event execution position or the target object model.
Specifically, the event execution time is the aircraft take-off time, and the event end time is the aircraft landing time; based on this, for example, the identifier corresponding to the event execution time may be a fly-start, and the identifier corresponding to the event end time may be a fly-stop.
When the target field name is the identifier corresponding to the event execution time or the event end time, the preset field content corresponding to the target field name may be determined according to the time period where the time is located, for example, when the target field name is the identifier corresponding to the event execution time, the preset field content corresponding to the target field name is 01, 02 or 03, the preset field content corresponding to the target field name is 01 for indicating that the corresponding event execution time is between 0 and 8 points or 8 points on the same day, the preset field content corresponding to the target field name is 02 for indicating that the corresponding event execution time is between 8 and 16 points or 16 points on the same day, and the preset field content corresponding to the target field name is 03 for indicating that the corresponding event execution time is between 16 and 24 points or 24 points on the same day.
The related events are events such as baggage taking, check-in or shutdown after boarding and disembarking; based on this, for example, the identifier corresponding to the execution position of the associated event may be board, luggage, check or cea, where the preset field content corresponding to the target field name board is a specific gate number, the preset field content corresponding to the target field name luggage is a specific luggage carousel number, the preset field content corresponding to the target field name check is a specific value rack number, and the preset field content corresponding to the target field name cea is a specific stand number.
The target object model is an aircraft model, the identifier corresponding to the target object model may be an identifier representing the aircraft model, for example, the identifier corresponding to the target object model may be a number, where the preset field content corresponding to the target field name number is a specific aircraft model.
Embodiments of the present invention also provide a non-transitory computer readable storage medium that may be disposed in an electronic device to store at least one instruction or at least one program for implementing one of the methods embodiments, the at least one instruction or the at least one program being loaded and executed by the processor to implement the methods provided by the embodiments described above.
Embodiments of the present invention also provide an electronic device comprising a processor and the aforementioned non-transitory computer-readable storage medium.
Embodiments of the present invention also provide a computer program product comprising program code for causing an electronic device to carry out the steps of the method according to the various exemplary embodiments of the invention described in the present specification when the program product is run on the electronic device.
While certain specific embodiments of the invention have been described in detail by way of example, it will be appreciated by those skilled in the art that the above examples are for illustration only and are not intended to limit the scope of the invention. Those skilled in the art will also appreciate that many modifications may be made to the embodiments without departing from the scope and spirit of the invention. The scope of the present disclosure is defined by the appended claims.
Claims (10)
1. The data detection method of civil aviation data is characterized by comprising the following steps of:
s100, in event data of a target event corresponding to a target identifier, taking field content corresponding to a target field name as target field content; the event data of the target event comprises a plurality of field names and field contents corresponding to each field name, wherein the target field name is any field name;
s200, determining whether the target field content is in group B with the first field content 1 The content of any first field in the database is the same; if yes, determining the target field content as normal field content;
the first field content group B 1 Is determined by the following method:
s210, acquiring a history field content group A= (a) corresponding to the target field name 1 ,a 2 ,...,a i ,...,a n ) I=1, 2, n; wherein a is i The historical field content corresponding to the target field name in the event data of the ith historical event corresponding to the target mark is obtained, and n is the number of the historical events corresponding to the target mark; each houseThe event end time of the historical event is before the event execution time of the target event; the event data of the historical event comprises each field name and historical field content corresponding to each field name; the target field name has a corresponding preset field content group b= (B) 1 ,b 2 ,...,b j ,...,b m ) J=1, 2, m; wherein b j The j-th preset field content corresponding to the target field name is obtained, and m is the number of preset field contents corresponding to the target field name; a, a i ∈B；
S220, according to a and B, obtain the first priority group h= (H) 1 ,h 2 ,...,h j ,...,h m ) The method comprises the steps of carrying out a first treatment on the surface of the Wherein h is j For the j-th first priority in H, H j ＝p j /n，p j Is a as 1 、a 2 、...、a i 、...、a n Intermediate and b j The number of identical history field contents;
s230, if h j Greater than or equal to the first threshold Q1, then b j As the first field content to obtain a first field content group B 1 ＝(b 1 1 ,b 2 1 ,...,b k 1 ,...,b q 1 ) K=1, 2, q; wherein b k 1 Is B 1 The kth first field content of (B), q is B 1 The number of first field contents in (a); q is less than or equal to m.
2. The data detection method according to claim 1, wherein the step S200 includes the steps of:
s201, determining whether the target field content is in group B with the first field content 1 The content of any first field in the database is the same; if yes, determining the target field content as normal field content; otherwise, go to step S300;
the data detection method further comprises the following steps:
s300, determining whether the target field content is in the second field content group B 2 The content of any second field in the database is the same; if so, the first and second data are not identical,determining the target field content as normal field content;
after the step S220, the second field content group B 2 Is determined by the following method:
s310, if h j Less than the first threshold Q1, b will be j As the third field content to obtain a third field content group B 3 ＝(b 1 3 ,b 2 3 ,...,b c 3 ,...,b d 3 ) C=1, 2,. -%, d; wherein b c 3 Is B 3 The content of the c third field, d is B 3 The number of third field contents in (c); d is less than or equal to m;
s320, if b c 3 Satisfying the preset priori condition, b c 3 As the second field content to obtain a second field content group B 2 ＝(b 1 2 ,b 2 2 ,...,b e 2 ,...,b f 2 ) E=1, 2,. -%, f; wherein the prior condition is that the corresponding field content is trusted data, b e 2 Is B 2 The e second field content, f is B 2 The number of second field contents in the database; f is less than or equal to d.
3. The data detection method according to claim 2, wherein the step S320 includes the steps of:
s321, if b c 3 For any one of a plurality of preset trusted field contents, b is then c 3 As the second field content to obtain a second field content group B 2 ＝(b 1 2 ,b 2 2 ,...,b e 2 ,...,b f 2 )，e＝1,2,...,f。
4. The data detection method according to claim 2, wherein the step S300 includes the steps of:
s301, determining whether the target field content is in a group B with a second field content 2 Any one of the secondThe field content is the same; if yes, determining the target field content as normal field content; otherwise, go to step S400;
the data detection method further comprises the following steps:
s400, determining whether the target field content is in group B with the fourth field content 4 The content of any fourth field in the list is the same; if yes, determining the target field content as normal field content;
after the step S320, the fourth field content group B 4 Is determined by the following method:
s410, if
Will b c 3 As the fifth field content to obtain a fifth field content group B 5 ＝(b 1 5 ,b 2 5 ,...,b var 5 ,...,b amo 5 ) Var=1, 2, amo; wherein b e 5 Is B 5 In the fifth field content of var, amo is B 2 The number of fifth field contents in (a); amo is less than or equal to m;
s420, if a i The corresponding first object identifier is the same as the second object identifier, and then a i As target history field content to obtain target history field content group A 1 ＝(a 1 1 ,a 2 1 ,...,a cha 1 ,...,a cin 1 ) Cha=1, 2,., cin; the first object is identified as the object for executing the corresponding historical event, and the second object is identified as the object for executing the target event; a, a cha 1 Is A 1 The content of the cha-th target history field in the table, and cin is A 1 The number of target history field contents in (a);
s430, according to A 1 And B, acquiring a second priority group H 1 ＝(h 1 1 ,h 2 1 ,...,h j 1 ,...,h m 1 ) The method comprises the steps of carrying out a first treatment on the surface of the Wherein,,h j 1 is H 1 The j th second priority, h j 1 ＝p j 1 /cin，p j 1 Is a as 1 1 、a 2 1 、...、a cha 1 、...、a cin 1 Intermediate and b j The number of identical history field contents;
s230, if h j 1 Greater than or equal to the second threshold Q2, then b j As the fourth field content to obtain a fourth field content group B 4 ＝(b 1 4 ,b 2 4 ,...,b str 4 ,...,b con 4 ) Str=1, 2,., con; wherein b str 4 Is B 4 Str fourth field content in (2), con is B 6 The number of fourth field contents; con is less than or equal to m.
5. The data detection method according to any one of claims 1 to 4, characterized in that the first threshold Q1 is determined by:
s231, acquiring a preset field content list T= (T) 1 ,t 2 ,...,t sqr1 ,...,t tan1 ),t sqr1 ＝(t sqr1 1 ,t sqr1 2 ,...,t sqr1 por1 ,...,t sqr1 L1(sqr1) ) Sqr1=1, 2, tan1, por1=1, 2, L1 (sqr 1); wherein t is sqr1 For a preset field content group corresponding to the sqr1 th field name, tan1 is the number of the field names, t sqr1 por1 For the preset field content of the por1 corresponding to the field name of the sqr1, L1 (sqr 1) is the number of the preset field content corresponding to the field name of the sqr 1; b is t 1 、t 2 、...、t sqr 、...、t tan Any one of the following;
s232, if L1 (sqr 1) =m, then t will be sqr1 As a target preset field content group, and t is set as sqr1 Each preset field content in the list is used as target preset field content to obtain a target preset field content list T1= (T1) 1 ,t1 2 ,...,t1 sqr2 ,...,t1 tan2 ),t1 sqr2 ＝(t1 sqr2 1 ,t1 sqr2 2 ,...,t1 sqr2 por2 ,...,t1 sqr2 L2(sqr2) ) Sqr2=1, 2, tan2, por2=1, 2, L2 (sqr 2); wherein t1 sqr2 For the sqr2 th target preset field content group in T1, tan2 is the number of target preset field content groups in T1, T1 sqr2 por2 Is t1 sqr2 The content of the target preset field of the (por 2) th target preset field, L2 (sqr 2) is t1 sqr2 The number of target preset field contents in the database;
s233, obtaining a history field content list KE= (KE) 1 ,ke 2 ,...,ke sqr2 ,...,ke tan2 )，ke sqr2 ＝(ke sqr2 1 ,ke sqr2 2 ,...,ke sqr2 i ,...,ke sqr2 n ) The method comprises the steps of carrying out a first treatment on the surface of the Wherein ke is sqr2 For the sqr2 th history field content group in KE, KE sqr2 i T1 in event data of the ith historical event corresponding to the target identification sqr2 History field content corresponding to the corresponding field name; a is ke 1 、ke 2 、...、ke sqr2 、...、ke tan2 Any one of the following;
s234, according to T1 and KE, a priority list LEV= (LEV) to be processed is obtained 1 ,lev 2 ,...,lev sqr2 ,...,lev tan2 )，lev sqr2 ＝(lev sqr2 1 ,lev sqr2 2 ,...,lev sqr2 por2 ,...,lev sqr2 L2(sqr2) ) The method comprises the steps of carrying out a first treatment on the surface of the Wherein lev is sqr2 For the sqr2 th pending priority group in LEV, LEV sqr2 por2 Is lev sqr2 The first to-be-processed priority of (a) is set; lev (Lev) sqr2 por2 ＝gar1 sqr2 por2 /n，gar1 sqr2 por2 For ke sqr2 1 、ke sqr2 2 、...、ke sqr2 i 、...、ke sqr2 n Intermediate and t1 sqr2 por2 The number of identical history field contents;
s235, according to LEV, average priority group AVE= (AVE) is obtained 1 ,ave 2 ,...,ave sqr2 ,...,ave tan2 ) The method comprises the steps of carrying out a first treatment on the surface of the Wherein ave sqr2 Is lev sqr2 Corresponding average priority, ave sqr2 ＝[∑ por2＝1 L2(sqr2) (lev sqr2 por2 )]/[L2(sqr2)]；
S236, if the data association characteristic value M corresponding to the AVE is smaller than or equal to the preset threshold value, Q1 is equal to the target average priority AVE 0 The method comprises the steps of carrying out a first treatment on the surface of the Wherein M= [ Σ sqr2＝1 tan2 (ave sqr2 -ave 0 ) 2 ]/tan2，ave 0 ＝[∑ sqr2＝1 tan2 (ave sqr2 )]/tan2。
6. The data detection method according to claim 5, wherein after step S235, the first threshold Q1 is further determined by:
s237, if the data association characteristic value M corresponding to the AVE is greater than the preset threshold, Q1 is equal to the preset target threshold corresponding to the target identifier.
7. The method according to claim 4, wherein the step S400 comprises the steps of:
s401, determining whether the target field content is in group B with the fourth field content 4 The content of any fourth field in the list is the same; if yes, determining the target field content as normal field content; otherwise, the target field content is determined to be abnormal field content.
8. The method of claim 1, wherein the target field name is an event execution time, an event end time, an associated event execution location, or an identification corresponding to a target model number.
9. A non-transitory computer readable storage medium having stored therein at least one instruction or at least one program, wherein the at least one instruction or the at least one program is loaded and executed by a processor to implement the method of any one of claims 1-8.
10. An electronic device comprising a processor and the non-transitory computer-readable storage medium of claim 9.
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