CN111489055A - Passenger data processing method and device, storage medium and computer equipment - Google Patents
Passenger data processing method and device, storage medium and computer equipment Download PDFInfo
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Abstract
The embodiment of the invention provides a passenger data processing method and device, a storage medium and computer equipment, wherein the passenger data processing method comprises the following steps: establishing a passenger confidence loss risk model according to the historical behavior data of the passenger and the confidence loss risk indexes; evaluating the risk of the passenger losing confidence according to the passenger losing confidence risk model to obtain an evaluation result; screening out target passengers according to the evaluation result, wherein the probability of losing confidence of the target passengers is larger than the preset probability; and outputting prompt information, wherein the prompt information is used for prompting ticket checking of the target passenger. The technical scheme provided by the embodiment of the invention can prompt the ticket checking of the passengers with high risk of losing credit to be started.
Description
[ technical field ] A method for producing a semiconductor device
The present invention relates to the field of data processing, and in particular, to a passenger data processing method and apparatus, a storage medium, and a computer device.
[ background of the invention ]
The rapid construction of the China railway passenger transport high-speed transportation network facilitates the travel of passengers, and the railway travel gradually becomes the first choice for medium-short distance travel. While facilitating travel of passengers, railway departments also find some distrust behaviors in passenger transportation organizations, such as: some passengers frequently buy two tickets and half tickets with short sitting length, and the purpose of reducing travel cost is realized by shielding ticket surface information at the outbound ticket gate or passing through the outbound ticket gate at the end. The behavior infringes the income of railway transportation enterprises, reduces the income of passenger transportation, and also disturbs the normal transportation order, and particularly in the peak transportation period, the behavior can increase the standard operation time of ticket checking workers and the outbound time, so that passengers who normally buy tickets and passengers who lose confidence are in dispute due to seat attribution, and even in the peak passenger flow period, the actual passenger carrying capacity is inconsistent with the passenger carrying capacity, so that the overtaking transportation of trains is caused, and the driving safety is damaged.
[ summary of the invention ]
In view of this, embodiments of the present invention provide a method and an apparatus for processing passenger data, a storage medium, and a computer device, which are used to prompt a passenger with high risk of losing credit to start ticket checking.
The embodiment of the invention provides a passenger data processing method, which comprises the following steps: establishing a passenger confidence loss risk model according to the historical behavior data of the passenger and the confidence loss risk indexes; evaluating the risk of the passenger losing confidence according to the passenger losing confidence risk model to obtain an evaluation result; screening out target passengers according to the evaluation result, wherein the target passengers are passengers with the probability of losing confidence larger than the preset probability; and outputting prompt information, wherein the prompt information is used for prompting ticket checking of the target passenger.
Further, the historical behavior data of the passenger comprises: the passenger's data of checking tickets of entering the station, data of checking tickets of leaving the station, data of buying tickets.
Further, the confidence loss risk indicators include: at least one of a first index, a second index, a third index and a fourth index, wherein the first index is used for indicating the number of times that a passenger only enters a station for ticket checking; the second index is used for indicating the proportion of the passengers purchasing the short distance tickets; the third index is used for indicating the proportion of breakpoints of the journey of the passenger in the round-trip interval, and the fourth index is used for measuring the reasonability of the breakpoints of the passenger in the round-trip interval.
Further, the establishing of the passenger confidence loss risk model comprises the following steps: establishing the passenger confidence Risk model according to the formula Risk ═ f (x) + g (y) + h (z), wherein Risk represents the Risk probability of confidence loss,
x represents the number of ticket checks for a passenger merely entering the station,
y represents the proportion of the passenger buying a short-distance ticket ride,
z is the proportion of the round trip interval in which the break point occurs.
Further, before the outputting the prompt message, the method further includes: inquiring the riding information of the target passenger; and generating the prompt information according to the riding information of the target passenger.
The embodiment of the invention provides a passenger data processing device, which comprises: the establishing unit is used for establishing a passenger confidence losing risk model according to the historical behavior data of the passenger and the confidence losing risk indexes; the evaluation unit is used for evaluating the risk of the passenger losing credit according to the passenger losing credit risk model to obtain an evaluation result; the screening unit is used for screening out target passengers according to the evaluation result, wherein the probability of losing confidence of the target passengers is larger than the preset probability; and the output unit is used for outputting prompt information, and the prompt information is used for prompting ticket checking of the target passenger.
Further, the historical behavior data of the passenger comprises: the passenger's data of checking tickets of entering the station, data of checking tickets of leaving the station, data of buying tickets.
Further, the confidence loss risk indicators include: at least one of a first index, a second index, a third index and a fourth index, wherein the first index is used for indicating the number of times that a passenger only enters a station for ticket checking; the second index is used for indicating the proportion of the passengers purchasing the short distance tickets; the third index is used for indicating the proportion of breakpoints of the journey of the passenger in the round-trip interval, and the fourth index is used for measuring the reasonability of the breakpoints of the passenger in the round-trip interval.
Further, the establishing unit is configured to: establishing the passenger confidence Risk model according to the formula Risk ═ f (x) + g (y) + h (z), wherein Risk represents the Risk probability of confidence loss,
x represents the number of ticket checks for a passenger merely entering the station,
y represents the proportion of the passenger buying a short-distance ticket ride,
z is the proportion of the round trip interval in which the break point occurs.
Further, the apparatus further comprises: the inquiry unit is used for inquiring the riding information of the target passenger before the prompt information is output; and the generating unit is used for generating the prompt information according to the riding information of the target passenger.
The embodiment of the invention provides a storage medium, which comprises a stored program, wherein when the program runs, a device where the storage medium is located is controlled to execute the method.
An embodiment of the present invention provides a computer device, including a memory for storing information including program instructions and a processor for controlling execution of the program instructions, where the program instructions are loaded by the processor and executed to implement the steps of the above method.
In the embodiment of the invention, a passenger confidence loss risk model is established according to the historical behavior data of the passenger and the confidence loss risk indexes; evaluating the risk of the passenger losing confidence according to the passenger losing confidence risk model to obtain an evaluation result; screening out target passengers according to the evaluation result, wherein the target passengers are passengers with the probability of losing confidence larger than the preset probability; and outputting prompt information, wherein the prompt information is used for prompting ticket checking of the target passenger, and the effect of prompting the ticket checking starting of the passenger with high risk of losing credit is achieved.
[ description of the drawings ]
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive labor.
Fig. 1 is a schematic diagram of a train passing through a station according to an embodiment of the present invention;
fig. 2-1 is a schematic diagram of a time distribution of passenger entering and not making station tickets according to an embodiment of the present invention;
fig. 2-2 is a schematic diagram of a distribution of trip breakpoint times and station-only ticket checking times of passengers according to an embodiment of the present invention;
2-3 are schematic diagrams of the distribution of the number of passengers who buy the short distance ticket in proportion to the trip according to the embodiment of the invention;
FIG. 3 is a flowchart illustrating a method for measuring and verifying the risk of losing confidence of a traveler who purchases a short seat length according to an embodiment of the present invention;
FIG. 4 is a flowchart of a passenger data processing method according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of a passenger data processing apparatus according to an embodiment of the present invention;
fig. 6 is a schematic diagram of a computer device according to an embodiment of the present invention.
[ detailed description ] embodiments
For better understanding of the technical solutions of the present invention, the following detailed descriptions of the embodiments of the present invention are provided with reference to the accompanying drawings.
It should be understood that the described embodiments are only some embodiments of the invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The terminology used in the embodiments of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the examples of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
The invention mainly analyzes the motivation and the mode of the passenger's action of losing credit, obtains the behavior motivation of the passenger who takes the initiative action of losing credit and the characteristic data of the historical transaction data discrimination based on the history, takes the motivation and the means of the passenger who takes the action of losing credit to evade tickets, compares and verifies the characteristic data with the transaction record of the general passenger, summarizes the behavior characteristics of the passenger with higher risk of losing credit, analyzes the relation between the behavior characteristics by adopting a mathematical analysis means, establishes a risk measurement model of the passenger who takes the action of losing credit, and introduces the model in detail as follows:
the statistical analysis of the passenger transaction data of the historical check and purchase of the two-head ticket and the half ticket generally has the following actions:
1. short distance ticket riding with different train number purchased by self-identity card
Assuming that a passenger purchases tickets of a train number A to go to a station number x4 from a station number x1, the train number A passes through a station number x2 and the train number B passes through a station number x3 and a station number x4 on a certain day, in order to reduce travel cost, the passenger only purchases tickets of the station numbers x1 to x2 and the tickets of the station numbers x3 to x4 at the similar time, the tickets of the station numbers x1 to x2 of the train number A are used for entering and ticket checking during entering, and the tickets of the station numbers x3 to x4 of the train number B are used for exiting and ticket checking during exiting, so that the ticket purchasing cost of the station numbers x2 to x3 is avoided. Such behavior is highly concealed when ticket checking is performed in the face of entering and exiting, but is relatively easy to check when ticket checking is performed in the front of the vehicle before leaving.
2. Short distance ticket riding with different ID card for same train number
Assuming that a passenger purchases tickets of the A bus number on a certain day, the passenger departs from a station x1 to a station x4, the A bus number passes through the station x2 and the station x3, in order to reduce the travel cost, the passenger purchases the tickets of the stations x1 to x2 by using the own ID card, purchases the tickets of the stations x3 to x4 by using the ID card of the passenger, checks tickets of the passenger by using the own ID card and the tickets of the stations x1 to x2 when entering the station, and checks tickets of the passenger by using the ID card of the passenger and the tickets of the stations x3 to x4 when leaving the station. When the ticket is checked out, if the consistency of the ticket is checked seriously, the behavior can be checked out.
3. Buying half ticket ride
Supposing that a passenger A purchases a ticket of a bus number A on a certain day and goes to a station x4 from a station x1, the bus number A passes through the station x2 and the station x3, in order to reduce travel cost, the passenger A only purchases tickets of the stations x1 to x2 by using an identity card of the passenger A, the ticket checking and the ticket checking are possible to be found in the in-train ticket checking and the out-station ticket checking, and the passenger A generally appears on a common speed train which is high in overtime and difficult to frequently check tickets in the train in the in-train ticket checking period.
Summarizing the above three classes of passengers, it can be inferred that there are 4 common points: 1. the passengers who actively take the action of losing credit all use the tickets purchased by the identity documents to check the tickets when entering the station, but the passengers who often take the action of losing credit can not use the tickets used when entering the station to check the tickets when leaving the station, so that most of the tickets purchased by the passengers are in a state that the tickets are only recorded when entering the station. 2. Passengers who actively take the action of losing credit all aim to reduce the travel cost, and when the travel cost is actually reduced in the process of trying, the passengers can frequently take the same way to escape. 3. Frequent breakpoints can occur on the travel track of the deceased passengers (such as passengers who frequently go to and from an x1 station and an x4 station but do not purchase whole-journey tickets) who frequently go back and forth in a specific section by taking trains (such as passengers who frequently purchase tickets from an x1 station to an x2 station to an x4 station and return tickets from an x4 station to an x3 station to an x1 station). 4. For the passenger who takes the action of losing credit to reduce the travel cost, the ticket mileage of the station from x1 to x2 purchased by the passenger is shorter and less than a certain proportion of the station mileage from x1 to x4, otherwise, no profit is available, and the three actions are considered to have risks of being checked in the ticket checking process in different degrees, the running mileage of the station from x1 to x4 selected by the passenger when taking the action of losing credit cannot be too long, so the mileage of the actual travel interval of the passenger who takes the action of losing credit to reduce the fare for escaping has upper and lower thresholds.
According to the method, the motivation and means of passengers who possibly adopt the credit loss users are analyzed to respectively obtain the wind control parameters, and a credit loss risk scoring model is established according to the wind control parameters and is combined with pre-sale transaction data to form an early warning system. The invention establishes the passenger in-road credit loss risk control index through transaction data and carries out early warning on the passenger ticket evasion and credit loss behavior.
The invention mainly comprises two steps: modeling the user confidence losing behavior and evaluating the confidence losing risk.
Modeling of user loss of confidence behavior
1. Firstly, calculating all-road transaction data and ticket checking data, and extracting the frequency distribution of only ticket checking for entering a station and not checking for the station in the passenger riding process, so that the number of passengers exceeding 12 times in one year accounts for one thousandth of the total number of passengers, and the number of passengers exceeding 24 times in one year accounts for 0.02% of the total number of passengers, which is obviously different from the ticket buying behavior of general passengers, as shown in fig. 2-1.
2. Defining the tickets with the mileage of the ticket buying and taking interval less than half of the whole journey of the train as short-distance tickets, classifying the passengers buying the tickets for traveling in one year according to the number of the purchased tickets with the ticket checking record only when entering the station, and analyzing the proportion of the number of the purchased short-distance tickets to the total travel times, so as to know that the more the tickets with the ticket checking record only when entering the station are, the higher the proportion of the purchased short-distance tickets to the travel times is. And for the passengers who purchase all short distance tickets on the trip, the correlation between the number of the tickets purchased by the passengers and the number of the tickets purchased by the passengers, which are only recorded with the check tickets when the passengers enter the station, is obvious, as shown in tables 1 and 2.
Analysis of variance: monthly occupancy rate analysis of passengers with 100% short-distance ticket purchasing proportion in 2018
Table 1: SUMMARY
| Group of | Number of observations | Summing | Average | Variance (variance) |
| All road | 21 | 489.9 | 23.3 | 15.4 |
| Checking tickets more than 12 times only when entering station | 21 | 597.4 | 28.4 | 7.0 |
| Checking tickets more than 24 times only when entering station | 21 | 658.2 | 31.3 | 3.7 |
| Checking tickets more than 48 times when only entering station | 21 | 715.8 | 34.1 | 3.4 |
Table 2: analysis of variance
3. The travel track of passengers traveling by a train is depicted, and frequent breakpoints (such as frequently purchasing tickets from x1 to x2 to go to the x4 station and then purchasing return tickets from x4 to x3 to return to the x1 station) appear on the travel track of the deceased passengers who frequently travel in a specific section (such as passengers who travel to and from the x1 station and the x4 station for a long time but do not purchase full-distance tickets). The method includes the steps that tickets for getting on the train from a station x1 to a station x4 to get off from a station x1 to a station x2 are purchased within half a year, more than 10 tickets for getting on the train from a station x4 to a station x4 to a station x1 to get off from a station x4 to get off from the station x3 are purchased within 3 days, the travelers with frequent breakpoints on the journey tracks are defined as travelers, 6596 travelers are shared in the last half of 2019, and the travelers are analyzed for the journey of the travelers, so that the number of times of the passenger journey breakpoints is positively correlated with the number of times of ticket checking for only entering the station and the number of times of travelers purchasing short distance tickets, and the travelers are respectively shown in fig. 2-2 and fig. 2-3.
User loss of trust behavior assessment
Through analysis of the transaction data, the frequent 'ticket checking only by entering', proportion of buying short distance ticket and taking and 'break point of trip in round trip interval' of the passenger are mutually positively correlated and are different from the general passenger behaviors, so that the passenger behavior is an index for measuring the risk of losing confidence of the passenger who purchases short sitting and long sitting, the frequency of the four behaviors is used as an independent variable, the risk of losing confidence of the passenger is used as a dependent variable, and a passenger risk model of losing confidence is established.
Specifically, a passenger distrust Risk model is established according to the formula Risk ═ f (x) + g (y) + h (z),
wherein Risk represents the Risk probability of losing credit,
After the model is established, the risk of losing confidence of the passengers who buy the short sitting length is measured and proved, and the flow is shown in fig. 3:
step S301: and acquiring passenger trip behavior data.
Step S302: and modeling the user behavior according to the passenger travel behavior data. Specifically, a passenger distrust Risk model is established according to the formula Risk ═ f (x) + g (y) + h (z),
wherein Risk represents the Risk probability of losing credit,
Step S303: and analyzing abnormal isolated points of user behaviors.
Step S304: and modeling normal behaviors.
Step S305: and acquiring the trip data of the user.
Step S306: and carrying out risk assessment on the user.
Step S307: and determining the highly suspicious users who lose confidence.
Step S308: and early warning is carried out, and the station and the train are prompted to start ticket checking service aiming at the highly suspicious users losing credit.
Referring to fig. 4, a flowchart of a passenger data processing method according to an embodiment of the present invention is shown.
The method comprises the following steps:
step S401: and establishing a passenger confidence loss risk model according to the historical behavior data of the passenger and the confidence loss risk indexes. The historical behavioral data of passengers includes: the passenger's data of checking tickets of entering the station, data of checking tickets of leaving the station, data of buying tickets. The confidence loss risk indicators include: at least one of a first index, a second index, a third index and a fourth index, wherein the first index is used for indicating the number of times that a passenger only enters a station for ticket checking; the second index is used for indicating the proportion of the passengers purchasing the short distance tickets; the third index is used for indicating the proportion of breakpoints of the journey of the passenger in the round-trip interval, and the fourth index is used for measuring the reasonability of the breakpoints of the passenger in the round-trip interval.
Establishing a passenger confidence Risk model according to the formula Risk ═ f (x) + g (y) + h (z),
wherein Risk represents the Risk probability of losing credit,
Step S402: and evaluating the risk of the passenger losing confidence according to the passenger losing confidence risk model to obtain an evaluation result.
Step S403: and screening out the target passenger according to the evaluation result, wherein the probability of losing confidence of the target passenger is larger than the preset probability. Inquiring riding information of a target passenger; and generating prompt information according to the riding information of the target passenger.
Step S404: and outputting prompt information, wherein the prompt information is used for prompting ticket checking of the target passenger.
According to the method, the motivation and means of passengers who possibly adopt the credit loss users are analyzed to respectively obtain the wind control parameters, and a credit loss risk scoring model is established according to the wind control parameters and is combined with pre-sale transaction data to form an early warning system. The invention establishes the passenger in-road credit loss risk control index through transaction data for the first time, and carries out early warning on the passenger ticket evasion credit loss behavior, thereby being an important measure for the passenger credit qualification management on the whole road, having milestone significance and having important significance for improving the service quality of customers, cultivating credit high-quality customers, protecting the passenger transport benefit of railways and driving safety.
The embodiment of the invention provides a passenger data processing device. Referring to fig. 5, a schematic diagram of an apparatus according to an embodiment of the present invention is shown, the apparatus including: the device comprises a establishing unit 10, an evaluating unit 20, a screening unit 30 and an output unit 40.
The establishing unit 10 is used for establishing a passenger confidence risk model according to the historical behavior data of the passenger and the confidence risk indexes.
And the evaluation unit 20 is used for evaluating the risk of the passenger losing credit according to the passenger losing credit risk model to obtain an evaluation result.
And the screening unit 30 is used for screening out the target passenger according to the evaluation result, wherein the target passenger is the passenger with the probability of losing confidence larger than the preset probability.
And the output unit 40 is used for outputting prompt information, and the prompt information is used for prompting ticket checking of the target passenger.
Optionally, the historical behavior data of the passenger comprises: the passenger's data of checking tickets of entering the station, data of checking tickets of leaving the station, data of buying tickets.
Optionally, the confidence loss risk indicator comprises: at least one of a first index, a second index, a third index and a fourth index, wherein the first index is used for indicating the number of times that a passenger only enters a station for ticket checking; the second index is used for indicating the proportion of the passengers purchasing the short distance tickets; the third index is used for indicating the proportion of breakpoints of the journey of the passenger in the round-trip interval, and the fourth index is used for measuring the reasonability of the breakpoints of the passenger in the round-trip interval.
Optionally, the establishing unit 10 is configured to:
establishing a passenger confidence Risk model according to the formula Risk ═ f (x) + g (y) + h (z),
wherein Risk represents the Risk probability of losing credit,
Optionally, the apparatus further comprises: the device comprises an inquiry unit and a generation unit.
And an inquiring unit for inquiring the riding information of the target passenger before the output unit 40 outputs the prompt information.
And the generating unit is used for generating prompt information according to the riding information of the target passenger.
The embodiment of the invention provides a storage medium, which comprises a stored program, wherein when the program runs, equipment where the storage medium is located is controlled to execute the following steps: establishing a passenger confidence loss risk model according to the historical behavior data of the passenger and the confidence loss risk indexes; evaluating the risk of the passenger losing confidence according to the passenger losing confidence risk model to obtain an evaluation result; screening out target passengers according to the evaluation result, wherein the probability of losing confidence of the target passengers is larger than the preset probability; and outputting prompt information, wherein the prompt information is used for prompting ticket checking of the target passenger.
Optionally, the apparatus for controlling the storage medium when the program runs further performs the following steps: establishing a passenger confidence loss Risk model according to the formula Risk ═ f (x) + g (y) + h (z), wherein Risk represents the Risk probability of confidence loss,
x represents the number of ticket checks for a passenger merely entering the station,
y represents the proportion of the passenger buying a short-distance ticket ride,
z is the proportion of the round trip interval in which the break point occurs.
Optionally, the apparatus for controlling the storage medium when the program runs further performs the following steps: inquiring the riding information of the target passenger before outputting the prompt information; and generating prompt information according to the riding information of the target passenger.
An embodiment of the present invention provides a computer device, including a memory and a processor, where the memory is used to store information including program instructions, and the processor is used to control execution of the program instructions, and the program instructions are loaded and executed by the processor to implement the following steps: establishing a passenger confidence loss risk model according to the historical behavior data of the passenger and the confidence loss risk indexes; evaluating the risk of the passenger losing confidence according to the passenger losing confidence risk model to obtain an evaluation result; screening out target passengers according to the evaluation result, wherein the probability of losing confidence of the target passengers is larger than the preset probability; and outputting prompt information, wherein the prompt information is used for prompting ticket checking of the target passenger.
Optionally, the program instructions when loaded and executed by the processor further implement the steps of: establishing a passenger confidence loss Risk model according to the formula Risk ═ f (x) + g (y) + h (z), wherein Risk represents the Risk probability of confidence loss,
x represents the number of ticket checks for a passenger merely entering the station,
y represents the proportion of the passenger buying a short-distance ticket ride,
z is the proportion of the round trip interval in which the break point occurs.
Optionally, the program instructions when loaded and executed by the processor further implement the steps of: inquiring the riding information of the target passenger before outputting the prompt information; and generating prompt information according to the riding information of the target passenger.
Fig. 6 is a schematic diagram of a computer device according to an embodiment of the present invention. As shown in fig. 6, the computer apparatus 50 of this embodiment includes: a processor 51, a memory 52, and a computer program 53 stored in the memory 52 and capable of running on the processor 51, wherein the computer program 53 implements the method in the embodiment when executed by the processor 51, and therefore, for avoiding repetition, the detailed description is omitted here. Alternatively, the computer program is executed by the processor 51 to implement the functions of each model/unit in the apparatus in the embodiment, which are not described herein for avoiding redundancy.
The computing device 50 may be a desktop computer, a notebook, a palm top computer, a cloud server, or other computing device. The computer device may include, but is not limited to, a processor 51, a memory 52. Those skilled in the art will appreciate that fig. 6 is merely an example of a computer device 50 and is not intended to limit the computer device 50 and that it may include more or fewer components than shown, or some components may be combined, or different components, e.g., the computer device may also include input output devices, network access devices, buses, etc.
The Processor 51 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 52 may be an internal storage unit of the computer device 50, such as a hard disk or a memory of the computer device 50. The memory 52 may also be an external storage device of the computer device 50, such as a plug-in hard disk provided on the computer device 50, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like. Further, the memory 52 may also include both internal and external storage devices for the computer device 50. The memory 52 is used to store computer programs and other programs and data required by the computer device. The memory 52 may also be used to temporarily store data that has been output or is to be output.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the embodiments provided in the present invention, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and there may be other divisions in actual implementation, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.
The integrated unit implemented in the form of a software functional unit may be stored in a computer readable storage medium. The software functional unit is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) or a Processor (Processor) to execute some steps of the methods according to the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (10)
1. A passenger data processing method, characterized in that the method comprises:
establishing a passenger confidence loss risk model according to the historical behavior data of the passenger and the confidence loss risk indexes;
evaluating the risk of the passenger losing confidence according to the passenger losing confidence risk model to obtain an evaluation result;
screening out target passengers according to the evaluation result, wherein the target passengers are passengers with the probability of losing confidence larger than the preset probability;
and outputting prompt information, wherein the prompt information is used for prompting ticket checking of the target passenger.
2. The method of claim 1, wherein the historical behavior data of the passenger comprises: the passenger's data of checking tickets of entering the station, data of checking tickets of leaving the station, data of buying tickets.
3. The method of claim 2, wherein the confidence risk indicators comprise: at least one of a first index, a second index, a third index and a fourth index, wherein the first index is used for indicating the number of times that a passenger only enters a station for ticket checking; the second index is used for indicating the proportion of the passengers purchasing the short distance tickets; the third index is used for indicating the proportion of breakpoints of the journey of the passenger in the round-trip interval, and the fourth index is used for measuring the reasonability of the breakpoints of the passenger in the round-trip interval.
4. The method of claim 3, wherein establishing the passenger confidence risk model comprises:
establishing the passenger confidence Risk model according to the formula Risk ═ f (x) + g (y) + h (z),
wherein Risk represents the Risk probability of losing credit,
5. The method of any of claims 1 to 4, wherein prior to said outputting a prompt, the method further comprises:
inquiring the riding information of the target passenger;
and generating the prompt information according to the riding information of the target passenger.
6. A passenger data processing apparatus, characterized in that the apparatus comprises:
the establishing unit is used for establishing a passenger confidence losing risk model according to the historical behavior data of the passenger and the confidence losing risk indexes;
the evaluation unit is used for evaluating the risk of the passenger losing credit according to the passenger losing credit risk model to obtain an evaluation result;
the screening unit is used for screening out target passengers according to the evaluation result, wherein the probability of losing confidence of the target passengers is larger than the preset probability;
and the output unit is used for outputting prompt information, and the prompt information is used for prompting ticket checking of the target passenger.
7. The apparatus of claim 6, wherein the historical behavior data of the passenger comprises: the passenger's data of checking tickets of entering the station, data of checking tickets of leaving the station, data of buying tickets.
8. The apparatus of claim 7, wherein the confidence loss risk indicators comprise: at least one of a first index, a second index, a third index and a fourth index, wherein the first index is used for indicating the number of times that a passenger only enters a station for ticket checking; the second index is used for indicating the proportion of the passengers purchasing the short distance tickets; the third index is used for indicating the proportion of breakpoints of the journey of the passenger in the round-trip interval, and the fourth index is used for measuring the reasonability of the breakpoints of the passenger in the round-trip interval.
9. A storage medium, characterized in that the storage medium comprises a stored program, wherein the program, when executed, controls an apparatus in which the storage medium is located to perform the method of any one of claims 1 to 5.
10. A computer device comprising a memory for storing information including program instructions and a processor for controlling execution of the program instructions, characterized in that: the program instructions when loaded and executed by a processor implement the steps of the method of any one of claims 1 to 5.
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