CN110347710B

CN110347710B - Data extraction method, device, equipment and storage medium

Info

Publication number: CN110347710B
Application number: CN201910624852.0A
Authority: CN
Inventors: 周鑫
Original assignee: Suzhou Dajiaying Information Technology Co Ltd
Current assignee: Suzhou Dajiaying Information Technology Co Ltd
Priority date: 2019-07-11
Filing date: 2019-07-11
Publication date: 2023-02-28
Anticipated expiration: 2039-07-11
Also published as: CN110347710A

Abstract

The embodiment of the invention discloses a data extraction method, a data extraction device, data extraction equipment and a storage medium. The method comprises the following steps: acquiring the behavior process calculation data of a first type of target personnel and the behavior process data of a second type of target personnel; using a first data extraction rule to extract data of the behavior process calculation data to obtain first behavior starting and stopping data of the first class of target personnel; and performing data extraction on the behavior process data by using a second data extraction rule to obtain second behavior start-stop data of the second type of target personnel. The technical scheme of the embodiment of the invention overcomes the technical defect that the accuracy of the determined entry and departure date of the labor staff is lower according to the labor information of the job hunting staff provided by the labor company in the prior art, and the action start and stop data of the labor staff of different categories are determined by using the data of different categories, so that the entry and departure date of the labor staff can be accurately determined.

Description

Data extraction method, device, equipment and storage medium

Technical Field

Embodiments of the present invention relate to data processing technologies, and in particular, to a data extraction method, apparatus, device, and storage medium.

Background

The process that the job seeker applies to the factory through the labor market generally comprises the steps that the job seeker registers job seeker information in a job introduction place, the job seeker is brought to a labor company with labor dispatching qualification by the job introduction place, and finally the labor company brings the job seeker to the factory for interviewing. Based on the above process, there are associated costs between the job introduction and the labor company, and between the labor company and the factory due to the flow of job hunting personnel.

Generally, the factory will feed back the labor information (such as interview information, job information, and job leaving information) of the job seeker to the labor company in time, so that the labor information of the job seeker grasped by the labor company is more comprehensive and accurate than that of the job introduction. Therefore, the job referral typically uses the labor information (e.g., compensation data, dates of entry and dates of departure) of the job seeker provided by the labor company to determine the revenue that the job seeker would have for providing the labor to the plant.

In the process of implementing the invention, the inventor finds that the prior art has the following defects: the labor information of job hunting personnel provided by the labor company often has errors, for example, the entry dates provided twice before and after are inconsistent, the departure dates are missing, the entry dates are future dates, and the like, so that the number of the job hunting personnel who count up the number of the job hunting personnel and the number of the days of the job hunting are incorrect, the accuracy of the income receivable calculated according to the labor information of the job hunting personnel is lower, and great loss can be brought to professional introduction.

Disclosure of Invention

The embodiment of the invention provides a data extraction method, a data extraction device, data extraction equipment and a data extraction storage medium, which are used for accurately determining the entry and exit dates of labor staff.

In a first aspect, an embodiment of the present invention provides a data extraction method, including:

acquiring the behavior process calculation data of a first type of target personnel and the behavior process data of a second type of target personnel;

using a first data extraction rule to extract data of the behavior process calculation data to obtain first behavior starting and stopping data of the first class of target personnel;

and performing data extraction on the behavior process data by using a second data extraction rule to obtain second behavior starting and stopping data of the second type of target personnel.

In the above method, optionally, after the using the second data extraction rule to perform data extraction on the behavior process data to obtain second behavior start-stop data of the second type of target person, the method further includes:

and correcting the first behavior start-stop data and the second behavior start-stop data to obtain corrected first behavior start-stop data and corrected second behavior start-stop data.

In the above method, optionally, the performing data extraction on the behavioral process calculation data by using a first data extraction rule to obtain first behavior start-stop data of the first type of target person includes:

determining the accurate starting date of the behaviors of the first class of target personnel according to the behavior starting date in the behavior process calculation data;

if the behavior process calculation data comprises a behavior termination date, determining the accurate termination date of the behaviors of the first class of target people according to the behavior termination date;

if the behavior ending date is not included in the behavior process calculation data but the behavior calculation expiration date is included, determining the accurate ending date of the behavior of the first type of target personnel according to the behavior calculation expiration date;

if the behavior ending date is not included in the behavior process calculation data and the behavior calculation ending date is not included, determining the behavior accurate starting date as the behavior accurate ending date of the first class target person when the time interval between the behavior accurate starting date and the current date is larger than a calculation time interval threshold value.

In the above method, optionally, if a behavior termination date is included in the behavior process calculation data, determining an accurate termination date of the behavior of the first type target person according to the behavior termination date includes:

if the behavior process calculation data comprises the behavior termination date, judging whether the behavior termination date is abnormal or not;

if the behavior ending date is abnormal, determining that the behavior ending date is not included in the behavior process calculation data;

and if the behavior termination date is normal, determining the accurate termination date of the behavior of the first type of target personnel according to the behavior termination date.

In the above method, optionally, the determining an accurate start date of the behavior of the first type target person according to the start date of the behavior in the behavior process calculation data includes:

and taking the behavior starting date corresponding to the latest behavior calculation deadline in the behavior process calculation data as the accurate behavior starting date of the first class of target personnel.

In the above method, optionally, the calculating an expiration date according to the behavior, and determining an accurate expiration date of the behavior of the first type of target person includes:

if the time interval between the latest behavior calculation deadline in the behavior process calculation data and the current date is larger than the calculation time interval threshold, taking the latest behavior calculation deadline in the behavior process calculation data as the accurate ending date of the behavior of the first class of target people;

determining that the first class target person does not have the behavior accurate termination date if a time interval between the latest behavior calculation deadline in the behavior process calculation data and the current date is less than or equal to the calculation time interval threshold.

In the above method, optionally, the behavior process calculation data includes:

monthly behavior process calculation data and weekly behavior process calculation data;

correspondingly, the using the first data extraction rule to perform data extraction on the behavior process calculation data to obtain the first behavior start-stop data of the first class of target people includes:

determining the accurate starting date of the behaviors of the first class of target personnel according to the behavior starting date in the monthly behavior process calculation data;

if the monthly behavior process calculation data comprise a monthly behavior termination date, determining the accurate termination date of the behaviors of the first class of target personnel according to the monthly behavior termination date;

if the monthly behavior termination date is not included in the monthly behavior process calculation data, but the weekly behavior termination date is included in the weekly behavior process calculation data, determining the accurate termination date of the behaviors of the first class of target people according to the weekly behavior termination date;

and if the monthly behavior termination date is not included in the monthly behavior process calculation data and the weekly behavior termination date is not included in the weekly behavior process calculation data, calculating an expiration date according to the weekly behavior in the weekly behavior process calculation data, and determining the accurate termination date of the behaviors of the first class of target people.

In the above method, optionally, the determining the accurate ending date of the behavior of the first type target person according to the weekly behavior calculation deadline in the weekly behavior process calculation data includes:

if the weekly behavior calculation deadline in the weekly behavior process calculation data is not null, determining the accurate ending date of the behavior of the first class target person according to the weekly behavior calculation deadline;

and if the weekly behavior calculation deadline in the weekly behavior process calculation data is empty, determining the accurate ending date of the behaviors of the first class of target people according to the monthly behavior calculation deadline in the monthly behavior process calculation data.

In the above method, optionally, the modifying the first behavior start-stop data and the second behavior start-stop data to obtain modified first behavior start-stop data and modified second behavior start-stop data includes:

if the accurate ending date of the behavior is earlier than the accurate starting date of the behavior, correcting the accurate ending date of the behavior to be the same date as the accurate starting date of the behavior;

modifying the behavior accurate expiration date to be the same date as the latest behavior calculation expiration date if a time interval between the behavior accurate expiration date and the latest behavior calculation expiration date in the behavior procedure calculation data is greater than a first set time interval threshold.

In the above method, optionally, the performing data extraction on the behavior process data by using a second data extraction rule to obtain second behavior start-stop data of the second type of target person includes:

determining the accurate personnel identification of the second type of target personnel according to the personnel identification in the behavior process data;

and determining the accurate start date and the accurate expiration date of the second type of target personnel according to the corresponding date of the accurate personnel identification in the behavior process data.

In the above method, optionally, the determining, according to the person identifier in the behavior process data, an accurate person identifier of the second type of target person includes:

sequencing different personnel identifications appearing in each behavior process data corresponding to any one second-type target personnel according to the total times of the personnel identifications appearing in each behavior process data corresponding to any one second-type target personnel;

selecting a first personnel identifier in the sequencing result as a personnel identifier to be identified;

judging whether the total number of letters and numbers included in the identification of the person to be recognized is greater than a set number threshold value or not;

if the total number of letters and numbers included in the identification of the person to be recognized is larger than a set number threshold, taking the identification of the person to be recognized as the accurate person identification of any one of the second-class target persons;

and if the total number of the letters and the numbers included in the identification of the personnel to be recognized is less than or equal to a set number threshold, taking the identification of the personnel positioned behind the identification of the personnel to be recognized in the sequencing result as a new identification of the personnel to be recognized, and returning to execute the operation of judging whether the total number of the letters and the numbers included in the identification of the personnel to be recognized is greater than the set number threshold until the sequencing result is traversed.

In the above method, optionally, the determining, according to the date corresponding to the accurate person identifier in the behavior process data, a behavior accurate start date and a behavior accurate expiration date of the second type of target person includes:

taking the behavior starting date with the most repetition times in each piece of behavior process data comprising the accurate personnel identification as the accurate starting date of the behavior of the second type target personnel;

and if the behavior expiration dates in the behavior process data including the accurate personnel identification are not all null, taking the behavior expiration date with the maximum repetition times in the behavior process data including the accurate personnel identification as the behavior accurate expiration date of the second-class target personnel.

And if all the behavior expiration dates in the behavior process data including the accurate personnel identification are null, calculating the latest behavior calculation expiration date corresponding to the behavior process data including the accurate personnel identification as the behavior accurate expiration date of the second-class target personnel.

deleting second behavior start-stop data of the second type target personnel with the behavior accurate expiration date being earlier than the behavior accurate start date;

and deleting second behavior start-stop data of the second type target personnel, wherein the time interval between the behavior accurate ending date and the behavior accurate starting date is larger than a second set time interval.

In a second aspect, an embodiment of the present invention further provides a data extraction apparatus, including:

the data acquisition module is used for acquiring the behavior process calculation data of the first type of target personnel and the behavior process data of the second type of target personnel;

the first behavior starting and stopping data extraction module is used for extracting data from the behavior process calculation data by using a first data extraction rule to obtain first behavior starting and stopping data of the first type of target personnel;

and the second behavior starting and stopping data extraction module is used for extracting data from the behavior process data by using a second data extraction rule to obtain second behavior starting and stopping data of the second type of target personnel.

In a third aspect, an embodiment of the present invention further provides an apparatus, where the apparatus includes:

one or more processors;

a storage device for storing one or more programs,

when executed by the one or more processors, cause the one or more processors to implement a data extraction method as in any embodiment of the invention.

In a fourth aspect, embodiments of the present invention further provide a storage medium containing computer-executable instructions, which when executed by a computer processor, are configured to perform the data extraction method according to any of the embodiments of the present invention.

The embodiment of the invention provides a data extraction method, a data extraction device, equipment and a storage medium, wherein data extraction is carried out on behavior process calculation data by using a first data extraction rule to obtain first behavior start-stop data of a first class of target personnel, meanwhile, data extraction is carried out on behavior process data by using a second data extraction rule to obtain second behavior start-stop data of a second class of target personnel, the technical defect that the accuracy of determined entry and exit dates of the labor personnel is low according to labor information of job hunting personnel provided by a labor company in the prior art is overcome, the behavior start-stop data of different classes of labor personnel are determined by using different classes of data, and the entry and exit dates of the labor personnel are accurately determined.

Drawings

FIG. 1 is a flow chart of a data extraction method according to an embodiment of the present invention;

FIG. 2 is a flow chart of a data extraction method according to a second embodiment of the present invention;

FIG. 3 is a flowchart of a data extraction method according to a third embodiment of the present invention;

FIG. 4 is a flowchart of a data extraction method according to a fourth embodiment of the present invention;

fig. 5 is a structural diagram of a data extraction device according to a fifth embodiment of the present invention;

fig. 6 is a block diagram of an apparatus according to a sixth embodiment of the present invention.

Detailed Description

The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not to be construed as limiting the invention. It should be further noted that, for the convenience of description, only some structures related to the present invention are shown in the drawings, not all of them.

Example one

Fig. 1 is a flowchart of a data extraction method according to an embodiment of the present invention, where the embodiment is applicable to determining entry and exit dates of staff members, the method may be executed by a data extraction device, the device may be implemented by software and/or hardware, and the device may be integrated in a server or other devices. As shown in fig. 1, the method specifically includes the following steps:

s101, acquiring the behavior process calculation data of the first type of target personnel and the behavior process data of the second type of target personnel.

In this embodiment, the behavior start-stop data of the target person is obtained through steps 101 to 103. In this embodiment, the target persons are divided into two types, where the first type of target persons are persons having corresponding behavioral process calculation data, and the second type of target persons are persons not having corresponding behavioral process calculation data.

Specifically, the behavior process data may specifically be data used to record contents such as node time, implementation mode, and the like of the first type of target person for implementing a certain behavior or certain behaviors. The behavior process calculation data may specifically be data for recording behavior results obtained by the first type of target person after performing a certain behavior or certain behaviors. For example, the behavioral process data may be a start time, an end time, and the like of the staff working in the enterprise, and correspondingly, the behavioral process calculation data may be monthly salary data obtained by the staff working in the enterprise, such as a calculation start date and a calculation end date corresponding to the monthly salary, and the like.

Further, for a first class of target people, behavioral process calculation data may be used to obtain behavioral start-stop data; for the second type of target person, the behavioral process data may be used to obtain the behavioral start-stop data.

And S102, performing data extraction on the behavior process calculation data by using a first data extraction rule to obtain first behavior starting and stopping data of a first class of target personnel.

In this embodiment, after acquiring the behavior process calculation data of the first type of target person, the first data extraction rule corresponding to the behavior process calculation data is used to extract the first behavior start-stop data of the first type of target person from the behavior process calculation data. The first behavior start-stop data may specifically be start time and end time of a behavior corresponding to the first-class target person implementation behavior process calculation data.

Generally, the behavior process calculation data includes behavior result data of each time segment in a behavior process performed by a person. For example, if the behavioral process calculation data is compensation data of the first type of target person, the behavioral process calculation data includes monthly compensation data of the first type of target person.

Further, since the action result data of each time segment generally includes the start time of the first-class target person for implementing the action process, and the action result data of the last time segment may also include the end time of the first-class target person for implementing the action process, even if the end time of the first-class target person for implementing the action process is not included, the end time of the first-class target person for implementing the action process may be determined by calculating the deadline time using the result corresponding to the action result data of the last time segment, and therefore, the first action start-stop data of the first-class target person may be obtained according to the action process calculation data.

S103, performing data extraction on the behavior process data by using a second data extraction rule to obtain second behavior starting and stopping data of second-class target personnel.

In this embodiment, after acquiring the behavior process data of the second type of target person, the second data extraction rule corresponding to the behavior process data is used to extract the second behavior start-stop data of the second type of target person from the behavior process data. The second action starting and stopping data may specifically be the starting time and the ending time of the action corresponding to the second type target person implementation action process data.

Generally, the behavior process data includes time node data of a behavior process implemented by a person. For example, if the behavioral process data is the work data of the second type of target person in the enterprise, the start time, the end time, etc. of the work of the second type of target person in the enterprise are included in the behavioral process data. Therefore, the second behavior starting and stopping data of the second type target personnel can be obtained according to the behavior process data.

The embodiment of the invention provides a data extraction method, which is characterized in that data extraction is carried out on behavior process calculation data by using a first data extraction rule to obtain first behavior start-stop data of a first type of target personnel, meanwhile, data extraction is carried out on behavior process data by using a second data extraction rule to obtain second behavior start-stop data of a second type of target personnel, the technical defect that the accuracy of determined entry and departure dates of staff is low according to labor information of job hunting staff provided by a labor company in the prior art is overcome, the entry and departure dates of the staff of different types are determined by using different types of data, and the entry and departure dates of the staff are accurately determined.

On the basis of the above embodiments, the first data extraction rule is used to perform data extraction on the behavior process calculation data to obtain the first behavior start-stop data of the first type of target person, which is specifically: according to the behavior starting date in the behavior process calculation data, determining the accurate starting date of the behavior of the first class of target personnel; if the behavior process calculation data comprises a behavior termination date, determining the accurate termination date of the behavior of the first class of target personnel according to the behavior termination date; if the behavior process calculation data does not include the behavior termination date but includes the behavior calculation expiration date, determining the accurate behavior termination date of the first type of target personnel according to the behavior calculation expiration date; and if the behavior process calculation data does not comprise the behavior ending date and the behavior calculation ending date, determining the behavior accurate starting date as the behavior accurate ending date of the first class target person when the time interval between the behavior accurate starting date and the current date is greater than the calculation time interval threshold value.

In this embodiment, the behavior process calculation data includes a behavior start date, and may further include a behavior end date and a behavior calculation end date, and these dates may be used to determine the first behavior start-end data, that is, the behavior accurate start date and the behavior accurate end date, of the first type of target person.

Specifically, the accurate start date of the behavior of the first type target person is determined according to the start date of the behavior in the behavior process calculation data. The accurate ending date of the behavior of the first type target person is determined according to the ending date, the ending date or the accurate starting date of the behavior in the calculation data of the behavior process.

The benefits of this arrangement are: when the data content included in the behavior process calculation data is different, the accurate ending date of the behavior of the first type target person can be accurately determined.

On the basis of the above embodiments, the second data extraction rule is used to perform data extraction on the behavior process data to obtain second behavior start-stop data of the second type of target person, which is embodied as: determining the accurate personnel identification of the second type of target personnel according to the personnel identification in the behavior process data; and determining the accurate start date and the accurate expiration date of the second type of target personnel according to the corresponding date of the accurate personnel identification in the behavior process data.

In this embodiment, the behavior process data further includes a person identifier of a second type of target person, where the person identifier is used to uniquely identify one second type of target person, and specifically, each time node data in one behavior process implemented by one second type of target person included in the behavior process data may correspond to one person identifier. Because of human misoperation, the person identifiers corresponding to the time node data may not be completely consistent, and therefore, in this embodiment, the accurate person identifier of the second type of target person needs to be further determined according to the person identifier in the behavior process data. For example, the person identifier with the largest number of occurrences may be used as the accurate person identifier.

Further, after the accurate person identifier is determined, the accurate behavior start date and the accurate behavior expiration date of the second type of target person are determined according to the time node data corresponding to the accurate person identifier.

The benefits of this arrangement are: and the accuracy of the behavior accurate starting date and the behavior accurate ending date of the second type target personnel is improved.

Example two

Fig. 2 is a flowchart of a data extraction method according to a second embodiment of the present invention. In this embodiment, a specific implementation manner of a method for determining the accurate termination date of the behavior of the first-class target person is provided by adding a data correction step. The same or corresponding terms as those in the above embodiments are explained, and the description thereof is omitted.

Correspondingly, the method of the embodiment specifically includes:

s201, acquiring the behavior process calculation data of the first type of target personnel and the behavior process data of the second type of target personnel.

S202, determining the accurate starting date of the behaviors of the first class of target personnel according to the behavior starting date in the behavior process calculation data.

In the present embodiment, the behavior procedure calculation data includes a behavior start date. The action start date may specifically be a start date when the first type of target person performs a certain action. For example, when the behavioral process calculation data is monthly salary data obtained by the first type target person working in the enterprise, the behavioral start date may be the job entry date of the first type target person in the enterprise.

Further, in the calculation data of the behavioral process in this embodiment, a behavioral start date corresponds to the behavioral result data of each time slot in a behavioral process implemented by the first-class target person.

Due to human operator error, the same first-class target person may have a plurality of different behavior start dates in the behavior process calculation data, and then an accurate behavior start date needs to be determined from the plurality of different behavior start dates. Specifically, the action start date with the largest occurrence number may be selected as the action accurate start date, and the action start date with the date closest to the current date may also be selected as the accurate start date, which is not limited in this embodiment.

S203, judging whether the behavior process calculation data comprises a behavior ending date, if so, executing a step 204, and if not, executing a step 206.

In the present embodiment, the behavior expiration date of the first type target person is determined through steps 203 to 212. Specifically, in different cases, the accurate behavior termination date of the first type target person may be determined according to the behavior termination date, the latest behavior calculation expiration date, and one of the accurate behavior initiation dates. In this embodiment, the behavior process calculation data at least includes a behavior start date for determining an accurate start date of the behavior.

Specifically, the "behavior end date" has the highest priority among the three dates, and if the normal behavior end date is included in the behavior process data, the accurate behavior end date of the first-class target person is determined according to the normal behavior end date. Therefore, first, it is determined whether or not an action-ending date is included in the action-process calculation data by this step.

As shown in table 1, the behavior process data includes a behavior start date, a behavior end date, and a behavior calculation deadline, where the behavior start date is specifically an "entry date", the behavior end date is specifically an "departure date", the behavior calculation deadline is specifically an "monthly salary settlement date" or a "weekly salary settlement date", and table 1 exemplifies the "monthly salary settlement date".

TABLE 1

And S204, judging whether the behavior ending date is abnormal or not, if so, executing the step 205, and if not, determining that the behavior ending date is not included in the behavior process calculation data, and executing the step 206.

In this embodiment, when the behavior process calculation data includes the behavior termination date, it is further determined whether the behavior termination date is normal. For example, whether the behavior ending date is earlier than the behavior accurate starting date or not is determined. If the action expiration date is normal, determining the exact expiration date of the action of the first type of target person, via step 205; if the behavior-ending date is abnormal, it is determined that the behavior-ending date is not included in the behavior-process calculation data, and it is determined whether a behavior-calculation-expiration date is included in the behavior-process calculation data, via step 206.

S205, determining the accurate termination date of the first class of target people according to the termination date of the behaviors.

In this embodiment, when a normal behavior termination date is included in the behavior procedure calculation data, the behavior termination date may be determined as an accurate termination date of the behavior of the first type target person. As shown in Table 1, the accurate ending date of the behavior of Zhang III is the ending date of the behavior (i.e., the departure date) 2018/10/15.

S206, judging whether the behavior process calculation data comprises a behavior calculation deadline, if so, executing a step 207, and if not, executing a step 210.

In this embodiment, when the normal behavior expiration date is not included in the behavior process calculation data, it is determined whether the behavior calculation expiration date is included in the behavior process calculation data through the step 206, so as to determine the accurate behavior expiration date according to the behavior calculation expiration date. As shown in Table 1, there are four behavior calculation expiration dates Zhang III, namely 2018/7/31, 2018/8/31, 2018/9/30 and 2018/10/31.

S207, judging whether the time interval between the latest behavior calculation deadline in the behavior process calculation data and the current date is larger than a calculation time interval threshold, if so, executing a step 208, and if not, executing a step 209.

In this embodiment, after determining that the behavior calculation due date is included in the behavior calculation data through step 206, it is further determined whether the time interval between the latest behavior calculation due date and the current date in the behavior calculation data is greater than the calculation time interval threshold. The calculation time interval threshold may specifically be a maximum time interval between a determination date of an action calculation expiration date and a previous action calculation expiration date of the action calculation expiration date.

It is understood that in the process of performing a certain action, after completing the work for a period of time in the process, a person will determine the action result data corresponding to the period of time. However, the determination of the behavior result data may be delayed in time, and it is not necessarily immediately after the end of the period of time. Therefore, it is determined that the person actually terminates the "certain action" only when the time interval between the current date and the latest action calculation deadline is longer than the delay time.

Therefore, in this embodiment, it is determined whether the time interval between the latest behavior calculation expiration date and the current date in the behavior process calculation data is greater than the calculation time interval threshold, so as to determine whether the first-class target person has terminated the behavior corresponding to the behavior process calculation data.

Illustratively, if the behavioral process calculation data is monthly salary data obtained by the first type of target personnel at the business, then the calculation time interval threshold should be the time interval from the monthly salary settlement date of the previous month to the latest determined date of the monthly salary data, which may typically be 60 days.

And S208, taking the latest behavior calculation deadline in the behavior process calculation data as the accurate behavior deadline of the first-class target personnel.

In this embodiment, when the time interval between the latest behavior calculation deadline in the behavior process calculation data and the current date is greater than the calculation time interval threshold, the latest behavior calculation deadline in the behavior process calculation data is used as the accurate ending date of the behavior of the first-class target person. As shown in Table 1, the accurate end of behavior date for the first category of target people may be 2018/10/31.

And S209, determining that the first-class target person has no behavior accurate ending date.

In this embodiment, when the time interval between the latest behavior calculation expiration date in the behavior process calculation data and the current date is less than or equal to the calculation time interval threshold, it is determined that the first type of target person does not have a behavior accurate expiration date, that is, the first type of target person may not have a behavior corresponding to the behavior process calculation data.

S210, judging whether the time interval between the accurate behavior starting date and the current date is larger than the calculated time interval threshold value, if so, executing a step 211, and if not, executing a step 212.

In this embodiment, when the behavior process calculation data does not include the behavior termination date nor the behavior calculation expiration date, it is further determined whether a time interval between the behavior accurate start date and the current date is greater than the calculation time interval threshold value, so as to determine whether the first-class target person really terminates the behavior corresponding to the behavior process calculation data.

And S211, determining the accurate behavior starting date as the accurate behavior ending date of the first-class target person.

In this embodiment, when the time interval between the accurate start date of behavior and the current date is greater than the calculation time interval threshold, it is determined that the first type of target person has ended the behavior corresponding to the calculated data of the behavior process, and the accurate start date of behavior is determined as the accurate end date of behavior of the first type of target person.

And S212, determining that the first-class target person has no behavior accurate ending date.

In this embodiment, when the time interval between the accurate start date of behavior and the current date is less than or equal to the calculated time interval threshold, it is determined that the first type of target person does not have an accurate end date of behavior, that is, the first type of target person may not have a behavior corresponding to the end behavior process calculation data.

And S213, performing data extraction on the behavior process data by using a second data extraction rule to obtain second behavior starting and stopping data of the second type of target personnel.

S214, correcting the accurate start date and the accurate end date of the behavior of the first type of target personnel and the second behavior start-stop data to obtain the corrected accurate start date and the corrected accurate end date of the behavior of the first type of target personnel and the corrected second behavior start-stop data.

In this embodiment, the accurate start date and the accurate end date of the behavior of the first type of target person and the second start-stop data of the behavior are corrected to ensure the logical correctness between the start-stop data of each behavior, between the start-stop data of the behavior and the calculation data of the behavior process, and between the start-stop data of the behavior and the calculation data of the behavior process.

The embodiment of the invention provides a data extraction method, which adds a data correction step, improves the accuracy of behavior starting and stopping data, also embodies a method for determining the accurate stopping date of the behavior of a first class of target personnel, and realizes that the behavior starting and stopping data of the first class of target personnel can be accurately, simply and effectively determined when the data contents in the behavior process calculation data are different.

On the basis of the above embodiments, the accurate start date of the behavior of the first type of target person is determined according to the start date of the behavior in the behavior process calculation data, which is embodied as: and taking the behavior starting date corresponding to the latest behavior calculation deadline in the behavior process calculation data as the accurate behavior starting date of the first class of target personnel.

In the present embodiment, the behavior calculation expiration date is included in the behavior procedure calculation data. The behavior calculation expiration date may specifically be a calculation expiration date used for calculating behavior result data of each time period in the process of implementing a certain behavior by the first-class target person. Illustratively, when the behavioral process calculation data is monthly salary data obtained by the first type of target personnel working at the business, then the behavioral calculation deadline is a settlement date of monthly salary, typically the last day of each month.

Further, in the embodiment, in the data for calculating the behavior process, the data for the behavior result of each time period in one behavior process implemented by the person includes a behavior start date and a behavior calculation deadline corresponding to the behavior start date. Illustratively, as shown in table 2, the "behavior start date" is specifically the "job entry date", and the "behavior calculation deadline" is specifically the "monthly salary settlement date". Each month of the monthly salary settlement date corresponds to the 'entry date', and due to the fact that human operation errors exist, the same first-class target person may have a plurality of entry dates, as shown in table 2, the entry dates of zhang san are three different dates.

Names of persons	Date of job entry	Monthly salary calculation date	Monthly salary settlement date
				Zhang San	2018/7/2	2018/7/1	2018/7/31
Zhang San	2018/7/3	2018/8/1	2018/8/31/
				Zhang San	2018/7/2	2018/9/1	2018/9/30
Zhang San	2018/7/1	2018/10/1	2018/10/31

TABLE 2

In this embodiment, the accurate start date of the behavior of the first-class target person is the behavior start date corresponding to the latest behavior calculation deadline in the behavior process calculation data. If Table 2 calculates data for all behavioral processes of Zhang three, then the exact start date of Zhang three's behavior is 2018/7/1 because 2019/10/31 calculates the expiration date for the latest behavior.

The benefits of this arrangement are: the accurate starting date of the first class target person's behavior is determined more accurately, conveniently and quickly.

EXAMPLE III

Fig. 3 is a flowchart of a data extraction method according to a third embodiment of the present invention. In this embodiment, a specific implementation manner is provided for embodying the data of the behavior process as the monthly behavior process calculation data and the weekly behavior process calculation data, and accordingly, further embodying the method for acquiring the first behavior start-stop data of the first type of target person. The same or corresponding terms as those of the above-described embodiments are explained, and the description of the present embodiment is omitted.

Correspondingly, the method of the embodiment specifically includes:

s301, acquiring monthly behavior process calculation data and weekly behavior process calculation data of the first type of target personnel and behavior process data of the second type of target personnel.

In this embodiment, the behavior process calculation data is specifically monthly behavior process calculation data and weekly behavior process calculation data, that is, the behavior process calculation data includes weekly behaviors and monthly behaviors of the first type of target users, which are respectively corresponding to behavior result data. The monthly behavior process calculation data may specifically be monthly salary data of the first type of target user working in the enterprise, and the weekly behavior process calculation data may specifically be weekly salary data of the first type of target user working in the enterprise.

S302, according to the behavior starting date in the monthly behavior process calculation data, the accurate behavior starting date of the first class target person is determined.

In this embodiment, the accurate start date of the behavior of the first type target person is specifically determined according to the start date of the behavior in the monthly behavior process calculation data. Specifically, the action start date with the largest occurrence number in the monthly action process calculation data may be determined as the action accurate start date, or the action start date in the latest monthly action process calculation data may be determined as the action accurate start date.

S303, judging whether the monthly behavior process calculation data comprises a monthly behavior termination date or not, if so, executing a step 304, and if not, executing a step 305.

In this embodiment, the accurate action ending date is also determined according to the monthly action process calculation data, and when the monthly action process calculation data does not include the monthly action ending date, the accurate action ending date is determined according to the weekly action process calculation data in the weekly action process calculation data.

Therefore, it is first determined by this step 303 whether or not the monthly behavior progress calculation data includes a monthly behavior expiration date.

S304, determining the accurate ending date of the first type of target person according to the monthly behavior ending date.

In this embodiment, when the monthly behavior process calculation data includes the monthly behavior termination date, the accurate termination date of the behavior of the first type target person is determined according to the monthly behavior termination date. Specifically, the date of the termination of the monthly behaviors in the monthly behavior procedure calculation data may be determined as the accurate date of the termination of the behaviors of the first type target person.

S305, judging whether the weekly behavior process calculation data comprises the weekly behavior ending date, if so, executing a step 306, and if not, executing a step 307.

In this embodiment, if the monthly behavior end date is not included in the monthly behavior procedure calculation data, it is continuously determined whether the weekly behavior end date is included in the weekly behavior procedure calculation data.

And S306, determining the accurate behavior termination date of the first-class target person according to the weekly behavior termination date.

In this embodiment, when the weekly behavior procedure calculation data includes the weekly behavior expiration date, the accurate expiration date of the behavior of the first type target person is determined according to the weekly behavior expiration date. Specifically, the weekly behavior ending date in the weekly behavior process calculation data may be determined as the accurate ending date of the behavior of the first type target person.

And S307, determining the accurate ending date of the behaviors of the first class of target personnel according to the weekly behavior calculation ending date in the weekly behavior process calculation data.

In this embodiment, when the monthly behavior termination date is not included in the monthly behavior procedure calculation data and the weekly behavior termination date is not included in the weekly behavior procedure calculation data, the expiration date is calculated according to the weekly behavior in the weekly behavior procedure calculation data, and the accurate termination date of the behavior of the first-class target person is determined.

It can be understood that the week behavior calculation expiration date in the week behavior process calculation data may be earlier than the month behavior calculation expiration date in the month behavior process calculation data of the "month" in which the "week" is located, and therefore, the week behavior calculation expiration date may more accurately represent the date of the behavior corresponding to the first-class target person termination behavior process calculation data.

And S308, performing data extraction on the behavior process data by using a second data extraction rule to obtain second behavior starting and stopping data of the second type of target personnel.

S309, correcting the accurate start date and the accurate end date of the behavior of the first type of target personnel and the second behavior start-stop data to obtain the corrected accurate start date and the corrected accurate end date of the behavior of the first type of target personnel and the corrected second behavior start-stop data.

The embodiment of the invention provides a data extraction method, which embodies the data of behavior process as the calculation data of monthly behavior process and the calculation data of weekly behavior process, correspondingly further embodies the acquisition method of the first behavior start-stop data of the first class of target personnel, and improves the accuracy of the accurate start date and the accurate stop date of the behavior of the first class of target personnel by reasonably using the calculation data of monthly behavior process and the calculation data of weekly behavior process.

On the basis of the above embodiments, the accurate termination date of the behavior of the first type of target person is determined according to the weekly behavior calculation deadline in the weekly behavior process calculation data, which is embodied as: if the weekly behavior calculation deadline in the weekly behavior process calculation data is not null, determining the accurate ending date of the behaviors of the first class of target personnel according to the weekly behavior calculation deadline; and if the weekly behavior calculation deadline in the weekly behavior process calculation data is empty, determining the accurate ending date of the behaviors of the first class of target people according to the monthly behavior calculation deadline in the monthly behavior process calculation data.

The benefits of this arrangement are: the accurate expiration date of the first type of target person's behavior can be effectively determined.

On the basis of the foregoing embodiments, the modifying the first behavior start-stop data and the second behavior start-stop data to obtain modified first behavior start-stop data and modified second behavior start-stop data is embodied as: if the accurate ending date of the behavior is earlier than the accurate starting date of the behavior, correcting the accurate ending date of the behavior to be the same as the accurate starting date of the behavior; and if the time interval between the behavior accurate expiration date and the latest behavior calculation expiration date in the behavior process calculation data is greater than the first set time interval threshold, modifying the behavior accurate expiration date to be the same date as the latest behavior calculation expiration date.

In this embodiment, after determining the accurate behavior termination date and the accurate behavior start date of the first-class target person, it is determined whether the accurate behavior termination date and the accurate behavior start date are reasonable. Firstly, the accurate ending date of the behavior is later than the accurate starting date of the behavior; second, the time interval between the behavior accurate expiration date and the latest behavior calculation expiration date in the behavior process calculation data should not be too large, and if so, the determined behavior accurate expiration date may not be accurate.

The benefits of this arrangement are: the accuracy of the behavior start-stop data is improved.

Example four

Fig. 4 is a flowchart of a data extraction method according to a fourth embodiment of the present invention. In this embodiment, a specific implementation manner of a method for determining an accurate person identifier that specifies the second type of target person and a method for determining an accurate start date and an accurate expiration date of a behavior that specifies the second type of target person is provided. The same or corresponding terms as those in the above embodiments are explained, and the description thereof is omitted.

Correspondingly, the method of the embodiment specifically includes:

s401, acquiring monthly behavior process calculation data and weekly behavior process calculation data of a first type of target personnel and behavior process data of a second type of target personnel.

S402, determining the accurate starting date of the behaviors of the first class of target personnel according to the behavior starting date in the monthly behavior process calculation data.

S403, judging whether the monthly behavior process calculation data includes a monthly behavior termination date, if so, executing step 404, and if not, executing step 405.

S404, determining the accurate ending date of the first-class target person according to the ending date of the monthly behaviors.

S405, judging whether the weekly behavior process calculation data comprises the weekly behavior ending date, if so, executing step 406, and if not, executing step 407.

And S406, determining the accurate behavior termination date of the first-class target person according to the weekly behavior termination date.

S407, calculating an expiration date according to the weekly behaviors in the weekly behavior process calculation data, and determining the accurate expiration date of the behaviors of the first class of target people.

S408, sorting different personnel identifications appearing in each behavior process data corresponding to any second-type target personnel according to the total times of the personnel identifications appearing in each behavior process data corresponding to any second-type target personnel.

In the present embodiment, the accurate start date and the accurate expiration date of the behavior of the second type target person are determined through steps 408 to 416.

In this embodiment, each piece of behavior process data corresponding to the second type of target person may include a person identifier, and the person identifier is used to uniquely identify one second type of target person. It is understood that, since there may be human errors, the person identifications in the behavior process data corresponding to a second type of target person may be different, and in this embodiment, the accurate person identification of the second type of target person is determined through the steps 408 to 412 first. As shown in table 3, a plurality of pieces of behavior process data of a second type target person are exemplarily shown, and the behavior process data further includes a behavior start time and a behavior expiration date.

Personnel identification	Date of onset of action	Action deadline
			700125	2019/5/1
700124	2019/5/1
			700125	2019/5/1
700125	2019/5/1
			700123	2019/5/1
700125	2019/5/2	2019/5/31
			700123	2019/5/2

TABLE 3

In this embodiment, in the process of determining an accurate person identifier, the person identifiers are first sorted according to the total times of occurrence of the person identifiers in each piece of behavior process data corresponding to any one of the second-type target persons.

Exemplarily, as shown in table 3, "700123" appears 2 times in table 3, "700124" appears 1 time in table 3, "700125" appears 4 times in table 3, and thus the results of the sorting are 700125, 700123, 700124.

And S409, selecting the first personnel identifier in the sequencing result as the personnel identifier to be identified.

In this embodiment, after the sorting result is determined, one person identifier is sequentially selected from the sorting result from front to back to serve as the person identifier to be recognized. Illustratively, as can be seen from the sorting result in table 3, the first person identifier as the person identifier to be recognized is "700125".

S410, judging whether the total number of letters and numbers included in the identification of the person to be recognized is larger than a set number threshold, if so, executing a step 411, and if not, executing a step 412.

In this embodiment, whether the identification of the person to be recognized is correct is determined by judging whether the total number of letters and numbers included in the identification of the person to be recognized is greater than a set number threshold. The set threshold value may typically be 4 or the like. Illustratively, the person identification "700125" in table 3 includes 6 numbers, and if the set number threshold is less than 6, it is determined that the person identification "700125" is correct.

S411, taking the identification of the person to be identified as the accurate person identification of any second-class target person.

In this embodiment, when the total number of the letters and the numbers included in the to-be-recognized person identifier is greater than the set number threshold, the to-be-recognized person identifier is used as the accurate person identifier of any second-type target person, and the person identifier in the sorting result is not determined again.

S412, taking the personnel identifier behind the to-be-identified personnel identifier in the sequencing result as a new to-be-identified personnel identifier, and returning to execute the step 410 until the sequencing result is traversed.

In this embodiment, if the total number of letters and numbers included in the to-be-recognized person identifier is less than or equal to the set number threshold, the person identifier located behind the to-be-recognized person identifier in the sorting result is used as a new to-be-recognized person identifier. Illustratively, if the total number of digits of the person identifier "700125" in table 3 is less than or equal to the set number threshold, the person identifier "700123" is taken as the person identifier to be recognized.

Further, after the identification of the person to be recognized is updated, the step 410 is executed again until the sorting result is traversed. It should be noted here that, as long as the set number threshold is set reasonably, when the whole sorting result is traversed, it must be determined that one person identifier can be used as an accurate person identifier of the second type of target person.

And S413, taking the behavior starting date with the most repetition times in each piece of behavior process data including accurate personnel identification as the behavior accurate starting date of the second type target personnel.

In this embodiment, after the accurate person identifier of the second type of target person is determined, the behavior process data of which the person identifier is the accurate person identifier is selected from the behavior process data of the second type of target person. Then, the behavior starting date with the most repetition times is searched from the selected behavior process data, and the behavior starting date with the most repetition times is used as the accurate behavior starting date of the second class of people.

Illustratively, as shown in table 3, if the person identification "700125" is determined as the accurate person identification of the second type target person, then since the "700125" appears 4 times in total, wherein the behavior start dates corresponding to three "700125" are 2019/5/1, and the behavior start date corresponding to one "700125" is 2019/5/2, 2019/5/1 should be taken as the accurate start date of the behavior of the second type target person.

And S414, judging whether all behavior expiration dates in each behavior process data including accurate personnel identification are empty, if not, executing step 415, and if so, executing step 416.

In this embodiment, after determining the accurate person identifier, the accurate expiration date of the second category of target persons is determined through the steps 414 to 416. First, it is determined whether the action expiration dates are all empty in each piece of action process data including accurate person identification in this step 414. It can be seen that in the behavior process data, there may be a case where the behavior due date of the second type target person is all empty.

And S415, taking the behavior due date with the most repetition times in each piece of behavior process data including the accurate personnel identification as the behavior accurate due date of the second type target personnel.

In this embodiment, after the accurate person identifier of the second type of target person is determined, the behavior process data of which the person identifier is the accurate person identifier is further selected from the behavior process data of the second type of target person. Then, searching the action expiration date with the maximum repetition times from the selected action process data, and taking the action expiration date with the maximum repetition times as the action accurate expiration date of the second class personnel.

Illustratively, as shown in table 3, if the person identification "700125" confirms to be the accurate person identification of the second type target person, then since the "700125" appears 4 times in total, wherein the behavior expiration dates corresponding to one "700125" are all 2019/5/31, and the behavior expiration dates corresponding to three "700125" are not, 2019/5/31 should be taken as the behavior accurate expiration date of the second type target person.

And S416, calculating an expiration date of the latest behavior corresponding to each behavior process data including the accurate personnel identification, and taking the latest behavior as the accurate expiration date of the behavior of the second type target personnel.

In this embodiment, the latest behavior calculation expiration date corresponding to the behavior process data may specifically be a behavior calculation expiration date corresponding to the latest generation time of the behavior process data. It is to be understood that the pieces of behavior process data of the second type target person are generally generated continuously at certain time intervals, for example, one piece of behavior process data is generated every week or every month, and then the latest behavior calculation expiration date may be specifically the behavior calculation expiration date corresponding to the generation time of the last generated behavior process data.

As shown in table 4, a plurality of pieces of behavior process data of a second type target person are exemplarily shown, and the behavior process data further includes the generation time of the behavior process data.

Personnel identification	Date of onset of action	Action deadline	Date of data generation
				700125	2019/5/1	2019/5/10
700125	2019/5/1		2019/6/10
				700125	2019/5/1	2019/7/10
700125	2019/5/1		2019/8/10

TABLE 4

As shown in table 4, each piece of behavioral process data is generated at a fixed time per month (No. 10 per month), for example. The generation time of the last piece of behavior process data in table 4 is 2019/8/10, and therefore, the latest behavior calculation expiration date should be the behavior calculation expiration date corresponding to "2019/8/10". Generally, when the calculation time interval of data is calculated by using "month" as the action process, the last day of each month is used as the calculation expiration date of the action result data. Therefore, the behavior calculation deadline corresponding to the '2019/8/10' can be '2019/8/31', and accordingly '2019/8/31' is the behavior accurate deadline of the second type target person.

It is further noted that the behavioral process data may also include both weekly behavioral process data and monthly behavioral process data. In this case, in steps 408 to 413, specifically, data processing may be performed on the weekly behavior process data and the monthly behavior process data at the same time, and finally, the accurate behavior starting date of the second type target person is obtained according to the weekly behavior process data and the monthly behavior process data at the same time. However, when the accurate expiration date of the behavior of the second type target person is determined through the steps 414 to 416, the accurate expiration date of the behavior of the second type target person may be preferentially determined according to the behavior expiration date in the weekly behavior process data. And when the weekly behavior process data does not comprise the behavior expiration date, determining the accurate behavior expiration date of the second type target personnel by using the behavior expiration date in the monthly behavior process data.

And S417, correcting the accurate start date and the accurate end date of the behavior of the first type of target personnel, and the accurate start date and the accurate end date of the behavior of the second type of target personnel to obtain the corrected accurate start date and the corrected accurate end date of the behavior of the first type of target personnel, and the corrected accurate start date and the corrected accurate end date of the behavior of the second type of target personnel.

The embodiment of the invention provides a data extraction method, which embodies a method for determining the accurate personnel identification of a second type of target personnel, can accurately, simply and conveniently determine the accurate personnel identification of the second type of target personnel, also embodies a method for determining the accurate start date and the accurate stop date of the behavior of the second type of target personnel, and improves the accuracy of the behavior start and stop data of the second type of target personnel.

On the basis of the foregoing embodiments, the method for correcting the first behavior start-stop data and the second behavior start-stop data to obtain the corrected first behavior start-stop data and the corrected second behavior start-stop data includes: deleting second behavior start-stop data of the second type of target personnel with the behavior accuracy deadline being earlier than the behavior accuracy start date; and deleting second behavior start-stop data of the second type target personnel, wherein the time interval between the behavior accurate ending date and the behavior accurate starting date is larger than a second set time interval.

In this embodiment, after determining the accurate behavior start date and the accurate behavior expiration date of the second type target person, it is continuously determined whether the accurate behavior start date and the accurate behavior expiration date are reasonable. Firstly, the accurate action deadline is later than the accurate action start date; secondly, the time interval between the accurate start date and the accurate end date of the behavior should not be too large, because if it is too large, it indicates that the second type of target person has a longer time to implement the behavior corresponding to the behavior process data, and then the second type of target person may have the corresponding behavior process calculation data.

The benefits of this arrangement are: and improving the accuracy of the behavior start-stop data of the second type target personnel.

EXAMPLE five

Fig. 5 is a structural diagram of a data extraction device according to a fifth embodiment of the present invention, and this embodiment provides an implementation manner of a "data extraction method" on the basis of the foregoing embodiments. The same or corresponding terms as those of the above-described embodiments are explained, and the description of the present embodiment is omitted.

As shown in fig. 5, the apparatus includes: a data acquisition module 501, a first behavior start-stop data extraction module 502, and a second behavior start-stop data extraction module 503, wherein:

the data acquisition module 501 is configured to acquire behavioral process calculation data of a first type of target person and behavioral process data of a second type of target person;

a first behavior start-stop data extraction module 502, configured to perform data extraction on the behavior process calculation data by using a first data extraction rule, to obtain first behavior start-stop data of a first type of target person;

the second behavior start-stop data extraction module 503 is configured to perform data extraction on the behavior process data by using a second data extraction rule, so as to obtain second behavior start-stop data of the second type of target person.

The embodiment of the invention provides a data extraction device, which firstly obtains the behavior process calculation data of a first type of target personnel and the behavior process data of a second type of target personnel through a data acquisition module 501, then performs data extraction on the behavior process calculation data by using a first data extraction rule through a first behavior start and stop data extraction module 502 to obtain first behavior start and stop data of the first type of target personnel, and finally performs data extraction on the behavior process data by using a second data extraction rule through a second behavior start and stop data extraction module 503 to obtain second behavior start and stop data of the second type of target personnel.

The device has solved among the prior art according to the labour information of the job hunting personnel that the labour company provided, the lower technical defect of the degree of accuracy of the date of leaving and entering of the labour personnel who confirms, through using different types of data, confirms different types of labour personnel's action start and stop data, has realized the date of leaving and entering of accurate definite labour personnel.

On the basis of the above embodiments, the method may further include:

and the data correction module is used for correcting the first behavior start-stop data and the second behavior start-stop data after the second data extraction rule is used for extracting the behavior process data to obtain second behavior start-stop data of the second type of target personnel, and obtaining the corrected first behavior start-stop data and the corrected second behavior start-stop data.

On the basis of the above embodiments, the first behavior start-stop data extraction module 502 may include:

the behavior accurate starting date determining unit is used for determining the behavior accurate starting date of the first class of target personnel according to the behavior starting date in the behavior process calculation data;

the first line is a precise ending date determining unit, and the precise ending date determining unit is used for determining the precise ending date of the behaviors of the first class of target personnel according to the behavior ending date if the behavior ending date is included in the behavior process calculation data;

a second behavior accurate termination date determination unit, configured to determine a behavior accurate termination date of the first type of target person according to the behavior calculation termination date if the behavior process calculation data does not include the behavior termination date but includes the behavior calculation termination date;

the third row is an accurate ending date determination unit, configured to determine, if the behavior ending date is not included in the behavior process calculation data and the behavior calculation ending date is not included, the behavior accurate starting date as the behavior accurate ending date of the first type of target person when a time interval between the behavior accurate starting date and the current date is greater than the calculation time interval threshold.

On the basis of the above embodiments, the first line accurate end date determination unit may include:

an abnormality judgment subunit, configured to judge whether the behavior end date is abnormal if the behavior process calculation data includes the behavior end date;

an abnormality determining subunit, configured to determine that the behavior process calculation data does not include the behavior end date if the behavior end date is abnormal;

and the normal determining subunit is used for determining the accurate behavior termination date of the first class target person according to the behavior termination date if the behavior termination date is normal.

On the basis of the foregoing embodiments, the behavior accurate start date determination unit may be specifically configured to:

On the basis of the above embodiments, the second behavior accurate expiration date determination unit may include:

the terminal date determining subunit is used for determining the latest behavior calculation deadline in the behavior process calculation data as the accurate terminal date of the behavior of the first-class target person if the time interval between the latest behavior calculation deadline in the behavior process calculation data and the current date is greater than the calculation time interval threshold;

and the non-ending date determining subunit is used for determining that the first class target person has no accurate ending date of the behavior if the time interval between the latest behavior calculation ending date in the behavior process calculation data and the current date is less than or equal to the calculation time interval threshold value.

On the basis of the above embodiments, the behavior process calculation data may include:

accordingly, the first action start-stop data extraction module 502 may include:

the starting date determining unit is used for determining the accurate starting date of the behaviors of the first class of target personnel according to the behavior starting date in the monthly behavior process calculation data;

a first termination date determination unit configured to determine an accurate termination date of the behavior of the first type of target person according to the monthly behavior termination date if the monthly behavior process calculation data includes the monthly behavior termination date;

a second termination date determination unit, configured to determine an accurate termination date of the behavior of the first type of target person according to the weekly behavior termination date if the monthly behavior termination date is not included in the monthly behavior process calculation data but the weekly behavior termination date is included in the weekly behavior process calculation data;

and the third termination date determining unit is used for determining the accurate termination date of the behaviors of the first class of target persons according to the weekly behavior calculation deadline in the weekly behavior process calculation data if the monthly behavior termination date is not included in the monthly behavior process calculation data and the weekly behavior termination date is not included in the weekly behavior process calculation data.

On the basis of the above embodiments, the third expiration date determination unit may include:

the first row is an accurate termination date determining subunit, which is used for determining the accurate termination date of the behavior of the first class of target personnel according to the week behavior calculation expiration date if the week behavior calculation expiration date in the week behavior process calculation data is not null;

and the second behavior accurate termination date determining subunit is used for determining the behavior accurate termination date of the first-class target person according to the month behavior calculation expiration date in the month behavior process calculation data if the week behavior calculation expiration date in the week behavior process calculation data is empty.

On the basis of the foregoing embodiments, the data modification module may include:

a first correcting unit for correcting the behavior accurate ending date to the same date as the behavior accurate starting date if the behavior accurate ending date is earlier than the behavior accurate starting date;

a second correcting unit configured to correct the behavior accuracy end date to the same date as the latest behavior calculation expiration date if a time interval between the behavior accuracy end date and the latest behavior calculation expiration date in the behavior procedure calculation data is larger than a first set time interval threshold.

On the basis of the foregoing embodiments, the second behavior start-stop data extraction module 503 may include:

the identification determining unit is used for determining the accurate personnel identification of the second type of target personnel according to the personnel identification in the behavior process data;

and the date determining unit is used for determining the accurate behavior starting date and the accurate behavior ending date of the second type target personnel according to the date corresponding to the accurate personnel identification in the behavior process data.

On the basis of the foregoing embodiments, the identification determination unit may include:

the sequencing subunit is used for sequencing different personnel identifications appearing in each behavior process data corresponding to any second-type target personnel according to the total times of the personnel identifications appearing in each behavior process data corresponding to any second-type target personnel;

the identifier selection unit is used for selecting a first personnel identifier in the sequencing result as a personnel identifier to be identified;

the judging unit is used for judging whether the total number of letters and numbers included in the identification of the person to be recognized is larger than a set number threshold value or not;

the accurate personnel identification determining unit is used for taking the personnel identification to be identified as the accurate personnel identification of any second-class target personnel if the total number of letters and numbers included in the personnel identification to be identified is greater than a set number threshold;

and the identifier updating unit is used for taking the personnel identifier positioned behind the identifier of the personnel to be recognized in the sequencing result as a new identifier of the personnel to be recognized if the total number of the letters and the numbers included in the identifier of the personnel to be recognized is less than or equal to the set number threshold, and returning to execute the operation of judging whether the total number of the letters and the numbers included in the identifier of the personnel to be recognized is greater than the set number threshold until the sequencing result is traversed.

On the basis of the above embodiments, the date determination unit may include:

the starting date determining subunit is used for taking the behavior starting date with the maximum repetition times in each piece of behavior process data including accurate personnel identification as the behavior accurate starting date of the second type of target personnel;

and the first deadline determining subunit is used for taking the behavior deadline with the maximum repetition times in each piece of behavior process data including the accurate personnel identification as the behavior accuracy deadline of the second type target personnel if the behavior deadline is not completely empty in each piece of behavior process data including the accurate personnel identification.

And the second cut-off date determining subunit is used for calculating the cut-off date of the latest behavior corresponding to each piece of behavior process data including the accurate personnel identification as the behavior accurate cut-off date of the second type target personnel if the behavior cut-off dates are all null in each piece of behavior process data including the accurate personnel identification.

On the basis of the above embodiments, the modification module may include:

the third correcting unit is used for deleting the second behavior starting and ending data of the second type of target personnel of which the behavior accuracy deadline is earlier than the behavior accuracy starting date;

and the fourth correction unit is used for deleting the second behavior starting and stopping data of the second type target personnel, wherein the time interval between the behavior accuracy ending date and the behavior accuracy starting date is larger than the second set time interval.

The data extraction device provided by the embodiment of the invention can execute the data extraction method provided by any embodiment of the invention, and has corresponding functional modules and beneficial effects of the execution method. For technical details that are not described in detail in this embodiment, reference may be made to the data extraction method provided in any embodiment of the present invention.

EXAMPLE six

Fig. 6 is a schematic structural diagram of an apparatus provided in embodiment 6 of the present invention. Fig. 6 illustrates a block diagram of an exemplary device 12 suitable for use in implementing embodiments of the present invention. The device 12 shown in fig. 6 is only an example and should not impose any limitation on the functionality and scope of use of embodiments of the present invention.

As shown in FIG. 6, device 12 is in the form of a general purpose computing device. The components of device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 that couples various system components including the system memory 28 and the processing unit 16.

Bus 18 represents one or more of any of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, and a processor or local bus using any of a variety of bus architectures. By way of example, such architectures include, but are not limited to, industry Standard Architecture (ISA) bus, micro-channel architecture (MAC) bus, enhanced ISA bus, video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus.

Device 12 typically includes a variety of computer system readable media. Such media may be any available media that is accessible by device 12 and includes both volatile and nonvolatile media, removable and non-removable media.

The system memory 28 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM) 30 and/or cache memory 32. The device 12 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 34 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 6, and commonly referred to as a "hard drive"). Although not shown in FIG. 6, a magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 18 by one or more data media interfaces. System memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the invention.

A program/utility 40 having a set (at least one) of program modules 42 may be stored, for example, in system memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which examples or some combination thereof may comprise an implementation of a network environment. Program modules 42 generally carry out the functions and/or methodologies of the described embodiments of the invention.

Device 12 may also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 24, etc.), with one or more devices that enable a user to interact with device 12, and/or with any devices (e.g., network card, modem, etc.) that enable device 12 to communicate with one or more other computing devices. Such communication may be through an input/output (I/O) interface 22. Also, the device 12 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network such as the Internet) via the network adapter 20. As shown, the network adapter 20 communicates with the other modules of the device 12 via the bus 18. It should be understood that although not shown in the figures, other hardware and/or software modules may be used in conjunction with device 12, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, to name a few.

The processing unit 16 executes various functional applications and data processing, such as implementing a data extraction method provided by an embodiment of the present invention, by running a program stored in the system memory 28. Namely: acquiring the behavior process calculation data of a first type of target personnel and the behavior process data of a second type of target personnel; using a first data extraction rule to extract data of the behavior process calculation data to obtain first behavior starting and stopping data of the first class of target personnel; and performing data extraction on the behavior process data by using a second data extraction rule to obtain second behavior starting and stopping data of the second type of target personnel.

EXAMPLE seven

Seventh, an embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program is executed by a processor to implement the data extraction method according to any embodiment of the present invention. Namely: acquiring the behavior process calculation data of a first type of target personnel and the behavior process data of a second type of target personnel; using a first data extraction rule to extract data of the behavior process calculation data to obtain first behavior start-stop data of the first type of target personnel; and performing data extraction on the behavior process data by using a second data extraction rule to obtain second behavior start-stop data of the second type of target personnel.

Computer storage media for embodiments of the invention may employ any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having 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. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.

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

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

Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).

It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in some detail by the above embodiments, the invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the invention, and the scope of the invention is determined by the scope of the appended claims.

Claims

1. A method of data extraction, comprising:

acquiring the behavior process calculation data of a first type of target personnel and the behavior process data of a second type of target personnel; dividing target persons into a first type of target persons and a second type of target persons, wherein the second type of target persons are persons without corresponding behavior process calculation data, the behavior process calculation data is behavior result data obtained after the first type of target persons implement a first preset behavior, the behavior process data comprises time node data in a behavior process implemented by the second type of target persons, and the behavior process calculation data is different from the behavior process data;

using a first data extraction rule to extract data of the behavior process calculation data to obtain first behavior start-stop data of the first type of target personnel;

using a second data extraction rule to extract the data of the behavior process to obtain second behavior start-stop data of the second type of target personnel;

the using of the first data extraction rule to perform data extraction on the behavior process calculation data to obtain the first behavior start-stop data of the first type of target person specifically includes:

and determining the accurate starting date of the behaviors of the first class of target personnel according to the starting date of the behaviors in the behavior process calculation data, and determining the accurate ending date of the behaviors of the first class of target personnel according to the ending date, the ending date and the accurate starting date of the behaviors in the behavior process calculation data.

2. The method of claim 1, wherein after the performing data extraction on the behavior process data using the second data extraction rule to obtain second behavior start-stop data of the second type of target person, further comprises:

3. The method of claim 2, wherein determining the accurate behavior termination date of the first type of target person according to the behavior termination date, the behavior calculation expiration date and the accurate behavior start date in the behavior process calculation data comprises:

if the behavior process calculation data comprises a behavior termination date, determining the accurate termination date of the behavior of the first class of target personnel according to the behavior termination date;

if the behavior process calculation data does not include the behavior termination date but includes a behavior calculation expiration date, determining the accurate termination date of the behavior of the first class target person according to the behavior calculation expiration date;

and if the behavior process calculation data does not comprise the behavior ending date and a behavior calculation ending date, determining the behavior accurate starting date as the behavior accurate ending date of the first class target person when the time interval between the behavior accurate starting date and the current date is greater than a calculation time interval threshold value.

4. The method of claim 3, wherein if a behavior termination date is included in the behavior process calculation data, determining an accurate termination date of the behavior of the first class of target people according to the behavior termination date comprises:

if the behavior process calculation data comprises the behavior termination date, judging whether the behavior termination date is abnormal;

5. The method of claim 3, wherein determining the accurate start date of the behavior of the first type of target person according to the start date of the behavior in the behavior process calculation data comprises:

6. The method of claim 3, wherein said calculating an expiration date based on said behavior, determining an accurate expiration date for said first class of target person's behavior, comprises:

7. The method of claim 2, wherein the behavioral process calculation data comprises:

if the monthly behavior process calculation data comprises a monthly behavior termination date, determining the accurate behavior termination date of the first class target person according to the monthly behavior termination date;

8. The method of claim 7, wherein determining the exact expiration date of the first type of target person's behavior based on the weekly behavior calculated expiration date in the weekly behavior procedure calculation data comprises:

9. The method according to any one of claims 3 to 8, wherein the modifying the first behavior start-stop data and the second behavior start-stop data to obtain modified first behavior start-stop data and modified second behavior start-stop data comprises:

if the accurate ending date of the behavior is earlier than the accurate starting date of the behavior, correcting the accurate ending date of the behavior to be the same as the accurate starting date of the behavior;

10. The method of claim 2, wherein the performing data extraction on the behavior process data using a second data extraction rule to obtain second behavior start-stop data of the second type of target person comprises:

determining accurate personnel identification of the second type of target personnel according to the personnel identification in the behavior process data;

11. The method of claim 10, wherein determining the accurate person identifier of the second type of target person from the person identifiers in the behavioral process data comprises:

and if the total number of the letters and the numbers included in the personnel identification to be recognized is less than or equal to a set number threshold, taking the personnel identification positioned behind the personnel identification to be recognized in the sequencing result as a new personnel identification to be recognized, and returning to execute the operation of judging whether the total number of the letters and the numbers included in the personnel identification to be recognized is greater than the set number threshold until the sequencing result is traversed.

12. The method of claim 10, wherein the determining the accurate start date and the accurate deadline date for the behavior of the second type of target person according to the date corresponding to the accurate person identifier in the behavior process data comprises:

taking the behavior starting date with the most repetition times in each behavior process data including the accurate personnel identification as the behavior accurate starting date of the second type target personnel;

if the behavior expiration dates in the behavior process data including the accurate personnel identification are not completely empty, taking the behavior expiration date with the largest repetition times in the behavior process data including the accurate personnel identification as the behavior accurate expiration date of the second type target personnel;

and if all the behavior expiration dates in the behavior process data comprising the accurate personnel identification are empty, calculating the expiration date of the latest behavior corresponding to the behavior process data comprising the accurate personnel identification as the behavior accurate expiration date of the second type target personnel.

13. The method according to any of claims 10-12, wherein said modifying the first behavior start-stop data and the second behavior start-stop data to obtain modified first behavior start-stop data and modified second behavior start-stop data comprises:

and deleting second behavior start-stop data of the second type of target personnel, wherein the time interval between the behavior accuracy expiration date and the behavior accuracy start date is larger than a second set time interval.

14. A data extraction apparatus, comprising:

the data acquisition module is used for acquiring the behavioral process calculation data of the first type of target personnel and the behavioral process data of the second type of target personnel; dividing target persons into a first type of target persons and a second type of target persons, wherein the second type of target persons are persons without corresponding behavior process calculation data, the behavior process calculation data is behavior result data obtained after the first type of target persons implement a first preset behavior, the behavior process data comprises time node data in a behavior process implemented by the second type of target persons, and the behavior process calculation data is different from the behavior process calculation data;

the second behavior starting and stopping data extraction module is used for extracting data from the behavior process data by using a second data extraction rule to obtain second behavior starting and stopping data of the second type of target personnel;

the first behavior start-stop data extraction module is specifically configured to: and determining the accurate starting date of the behaviors of the first class of target personnel according to the starting date of the behaviors in the behavior process calculation data, and determining the accurate ending date of the behaviors of the first class of target personnel according to the ending date, the ending date and the accurate starting date of the behaviors in the behavior process calculation data.

15. A computer device, the device comprising:

one or more processors;

a storage device for storing one or more programs,

the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the data extraction method of any of claims 1-13.

16. A storage medium containing computer-executable instructions for performing the data extraction method of any one of claims 1-13 when executed by a computer processor.