A dynamic fare detection method, system, device and storage medium

Abstract

Embodiments of the present application provide a dynamic fare detection method, system, device and storage medium, wherein the method comprises: obtaining a dynamic fare of a target route published by an airline to a fare system, the dynamic fare comprising an identifier of a source dynamic fare and a plurality of ticket price influencing factors; determining a preset discount range corresponding to the source dynamic fare according to the identifier of the source dynamic fare; if the ticket price influencing factors at least include a fare discount value and a fare increase / decrease value, then analyzing each ticket price influencing factor in the dynamic fare, and based on the analysis result and the preset discount range corresponding to the source dynamic fare, obtaining an error evaluation coefficient of the dynamic fare; if the ticket price influencing factors only include the fare discount value, then based on the fare discount value and the preset discount range corresponding to the source dynamic fare, obtaining the error evaluation coefficient of the dynamic fare; and based on the error evaluation coefficient of the dynamic fare, performing error detection on the dynamic fare. The present application realizes detection of an error dynamic fare.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of aviation data processing, in particular to a dynamic fare detection method, system, device and storage medium. BACKGROUND

[0002] The dynamic fare is a fare product proposed by an airline to meet the market demand for flexibility of the fare product. The dynamic fare can include a route identifier, a cabin identifier and a ticket price influencing factor, for example, on a member day, each cabin of an A-B route is discounted by 30% for members of each level, and a first-level member is reduced by 100 yuan based on the discount. Among them, "member day" is the effective date and expiration date in the ticket price influencing factor, "A-B route" is the above-mentioned route identifier, "each cabin" is the above-mentioned cabin identifier, "discounted by 30%" is the fare discount value in the above-mentioned ticket price influencing factor, and "reduced by 100 yuan" is the fare increase / decrease value in the above-mentioned ticket price influencing factor. It can be seen that the above-mentioned dynamic fare does not specify a specific ticket price. In the process of generating a ticket price, the airline publishes the generated dynamic fare to the fare system, so that the fare system generates a ticket price based on each ticket price influencing factor in the dynamic fare, and publishes the generated ticket price.

[0003] However, since the ticket price influencing factor in the dynamic fare exists in the form of a string, and the dynamic fare is manually edited and generated by the fare publishing personnel of the airline, it is easy to cause errors in the dynamic fare due to editing errors when there are many ticket price influencing factors, thereby causing errors in the finally generated ticket price. SUMMARY

[0004] The purpose of the embodiment of the present application is to provide a dynamic fare detection method, system, device and storage medium to detect error dynamic fares. The specific technical solutions are as follows:

[0005] A dynamic fare detection method, the method comprising:

[0006] Obtaining a dynamic fare of a target route published by an airline to a fare system, the dynamic fare comprising an identifier of a source dynamic fare and a plurality of ticket price influencing factors, the source dynamic fare being a dynamic fare corresponding to the target route in the fare system that has completed detection;

[0007] Determining a preset discount range corresponding to the source dynamic fare according to the identifier of the source dynamic fare, the preset discount range being a discount range constructed based on a statistical result of a published fare of the target route;

[0008] If the ticket price influencing factor at least includes the freight rate discount value and the freight rate increase / decrease value, each of the ticket price influencing factors in the dynamic freight rate is analyzed, and based on the analysis result and a preset discount range corresponding to the source dynamic freight rate, an error evaluation coefficient of the dynamic freight rate is obtained, the error evaluation coefficient representing a risk degree of the dynamic freight rate being a wrong dynamic freight rate;

[0009] If the ticket price influencing factor only includes the freight rate discount value, based on the freight rate discount value and a preset discount range corresponding to the source dynamic freight rate, an error evaluation coefficient of the dynamic freight rate is obtained.

[0010] Based on the error evaluation coefficient of the dynamic freight rate, the dynamic freight rate is detected for error.

[0011] Optionally, the determining of the preset discount range corresponding to the source dynamic freight rate according to the identification of the source dynamic freight rate comprises:

[0012] Based on the identification of the source dynamic freight rate, an error evaluation coefficient of the source dynamic freight rate is determined, and a preset discount range corresponding to the error evaluation coefficient of the source dynamic freight rate is determined as the preset discount range corresponding to the source dynamic freight rate, the error evaluation coefficient and the preset discount range having a corresponding relationship.

[0013] Optionally, the obtaining of the error evaluation coefficient of the dynamic freight rate based on the analysis result and the preset discount range corresponding to the source dynamic freight rate comprises:

[0014] An initial evaluation reference value corresponding to the route identification and the cabin identification in the dynamic freight rate is obtained, the initial evaluation reference value is corrected based on the analysis result to obtain an evaluation reference value;

[0015] A quotient value obtained by dividing the freight rate increase / decrease value by the evaluation reference value is determined as a freight rate discount increase / decrease value;

[0016] A product of an intermediate value of the preset discount range corresponding to the source dynamic freight rate and the freight rate discount value is obtained, and a sum of the product and the freight rate discount increase / decrease value is obtained;

[0017] A preset discount range corresponding to the sum is searched, and an error evaluation coefficient corresponding to the preset discount range corresponding to the sum is determined as the error evaluation coefficient of the dynamic freight rate.

[0018] Optionally, the obtaining of the initial evaluation reference value corresponding to the route identification and the cabin identification in the dynamic freight rate comprises:

[0019] In a case where there are a plurality of historical air ticket prices corresponding to the route identification and the cabin identification, a weighted average value of the plurality of historical air ticket prices is determined as the initial evaluation reference value.

[0020] In the absence of a plurality of historical ticket prices corresponding to the route identifier and the cabin identifier, inputting each of the ticket price influencing factors, the cabin identifier and the route identifier in the dynamic fare into a preset reference value generation model to obtain the initial evaluation reference value output by the preset reference value generation model.

[0021] Optionally, the training process of the preset reference value generation model comprises:

[0022] Obtaining a plurality of published ticket prices corresponding to historical dynamic fares of the fare system, wherein the historical dynamic fares comprise the ticket prices corresponding to the historical dynamic fares, route identifiers, cabin identifiers and a plurality of ticket price influencing factors.

[0023] Training an initial preset reference value generation model using each of the historical dynamic fares to obtain the preset reference value generation model, wherein the input of the preset reference value generation model is the cabin identifier, the route identifier and each ticket price influencing factor in the dynamic fare published by the airline to the fare system, and the output is the initial evaluation reference value corresponding to the route identifier and the cabin identifier in the dynamic fare.

[0024] Optionally, if the ticket price influencing factors only include a fare discount value, then based on the fare discount value and a preset discount range corresponding to the source dynamic fare, an error evaluation coefficient of the dynamic fare is obtained, comprising:

[0025] Obtaining the product of the intermediate value of the preset discount range corresponding to the source dynamic fare and the fare discount value, and searching for a preset discount range corresponding to the product;

[0026] Determining the error evaluation coefficient corresponding to the preset discount range corresponding to the product as the error evaluation coefficient of the dynamic fare.

[0027] Optionally, the error detection of the dynamic fare based on the error evaluation coefficient of the dynamic fare comprises:

[0028] Obtaining a preset evaluation interval corresponding to the route identifier;

[0029] In the case where the error evaluation coefficient is less than the lower limit value of the preset evaluation interval, the output content is a feedback result that the dynamic fare is incorrect, and the dynamic fare is blocked;

[0030] In the case where the error evaluation coefficient is within the preset evaluation interval, the output content is a feedback result that the dynamic fare has a risk of error;

[0031] In a case where the error evaluation coefficient is greater than an upper limit value of the preset evaluation interval, generating a ticket price based on the dynamic fare.

[0032] A detection system of a dynamic fare, the system comprising:

[0033] a fare obtaining module configured to obtain a dynamic fare of a target route published by an airline to a fare system, the dynamic fare comprising an identification of a source dynamic fare and a plurality of fare influencing factors, the source dynamic fare being a detected dynamic fare corresponding to the target route in the fare system;

[0034] a range determining module configured to determine a preset discount range corresponding to the source dynamic fare according to the identification of the source dynamic fare, the preset discount range being a discount range constructed based on a statistical result of a published fare of the target route;

[0035] a first coefficient obtaining module configured to, if the fare influencing factors at least comprise a fare discount value and a fare increase / decrease value, analyze each of the fare influencing factors in the dynamic fare, and obtain an error evaluation coefficient of the dynamic fare based on an analysis result and the preset discount range corresponding to the source dynamic fare, the error evaluation coefficient representing a risk degree of the dynamic fare being an error dynamic fare;

[0036] a second coefficient obtaining module configured to, if the fare influencing factors only comprise a fare discount value, obtain an error evaluation coefficient of the dynamic fare based on the fare discount value and the preset discount range corresponding to the source dynamic fare;

[0037] an error detection module configured to perform error detection on the dynamic fare based on the error evaluation coefficient of the dynamic fare.

[0038] Optionally, the range determining module is configured to:

[0039] determine an error evaluation coefficient of the source dynamic fare based on the identification of the source dynamic fare, and determine a preset discount range corresponding to the error evaluation coefficient of the source dynamic fare as the preset discount range corresponding to the source dynamic fare, the error evaluation coefficient and the preset discount range having a corresponding relationship.

[0040] Optionally, the first coefficient obtaining module is configured to, when obtaining the error evaluation coefficient of the dynamic fare based on the analysis result and the preset discount range corresponding to the source dynamic fare:

[0041] obtain an initial evaluation reference value corresponding to a route identification and a cabin identification in the dynamic fare, correct the initial evaluation reference value based on the analysis result to obtain an evaluation reference value;

[0042] determining a quotient of the fare increase / decrease value divided by the evaluation reference value as a fare discount increase / decrease value;

[0043] obtaining a product of a middle value of a preset discount range corresponding to the source dynamic fare and the fare discount value, and obtaining a sum of the product and the fare discount increase / decrease value;

[0044] finding a preset discount range corresponding to the sum, and determining an error evaluation coefficient corresponding to the preset discount range corresponding to the sum as the error evaluation coefficient of the dynamic fare.

[0045] Optionally, the first coefficient obtaining module is configured to:

[0046] when there are multiple historical ticket prices corresponding to the route identifier and the cabin identifier, determining a weighted average of the multiple historical ticket prices as the initial evaluation reference value;

[0047] when there are no multiple historical ticket prices corresponding to the route identifier and the cabin identifier, inputting each of the fare influencing factors, the cabin identifier and the route identifier in the dynamic fare into a preset reference value generation model to obtain the initial evaluation reference value output by the preset reference value generation model.

[0048] Optionally, the system further comprises a model training module, which is configured to:

[0049] obtain historical dynamic fares corresponding to multiple published ticket prices of the fare system, the historical dynamic fares comprising the ticket prices, route identifiers, cabin identifiers and multiple fare influencing factors corresponding to the historical dynamic fares;

[0050] train an initial preset reference value generation model by using each of the historical dynamic fares to obtain the preset reference value generation model, the input of the preset reference value generation model being the cabin identifier, the route identifier and each of the fare influencing factors in the dynamic fare published by the airline to the fare system, and the output of the preset reference value generation model being the initial evaluation reference value corresponding to the route identifier and the cabin identifier in the dynamic fare.

[0051] Optionally, the second coefficient obtaining module is configured to:

[0052] obtain a product of a middle value of a preset discount range corresponding to the source dynamic fare and the fare discount value, and find a preset discount range corresponding to the product;

[0053] The error evaluation coefficient corresponding to the preset discount range corresponding to the product is determined as the error evaluation coefficient of the dynamic fare.

[0054] Optionally, the error detection module is configured to:

[0055] obtain a preset evaluation interval corresponding to the route identifier;

[0056] In a case where the error evaluation coefficient is less than a lower limit value of the preset evaluation interval, output a feedback result that the dynamic fare is erroneous, and perform a blocking operation on the dynamic fare;

[0057] In a case where the error evaluation coefficient is within the preset evaluation interval, output a feedback result that the dynamic fare has an error risk;

[0058] In a case where the error evaluation coefficient is greater than an upper limit value of the preset evaluation interval, generate a ticket price based on the dynamic fare.

[0059] A detection device of a dynamic fare, the device comprising:

[0060] a processor;

[0061] a memory for storing instructions executable by the processor;

[0062] The processor is configured to execute the instructions to implement the detection method of the dynamic fare as described in any one of the above.

[0063] A computer-readable storage medium, when instructions in the computer-readable storage medium are executed by a processor of a detection device of a dynamic fare, enable the detection device of the dynamic fare to perform the detection method of the dynamic fare as described in any one of the above.

[0064] The method, system, device and storage medium provided by the embodiment of the present application can obtain the dynamic fare of the target route published by the airline to the fare system through configuration, and detect the dynamic fare before the dynamic fare generates the ticket price, thereby avoiding the risk that the wrong dynamic fare enters the ticket price generation link and causes the generation of wrong ticket price. Meanwhile, since the preset discount range is constructed based on the statistical result of the published fare of the target route, and the published fare cannot be wrong, the error evaluation coefficient representing the risk degree of the dynamic fare being the wrong dynamic fare is obtained by configuring the ticket price influencing factor based on the dynamic fare and the preset discount range corresponding to the source dynamic fare, and the dynamic fare is detected based on the error evaluation coefficient, thereby realizing the accurate detection of whether the dynamic fare is wrong. Finally, since the preset discount range and the dynamic fare are used only when the evaluation and detection are performed, a large amount of flight information, segment information and passenger information do not need to be obtained, the calculation cost is reduced, and the detection efficiency is improved. It can be seen that the present application realizes the detection of the wrong dynamic fare.

[0065] Of course, implementing any product or method of the present application does not necessarily require achieving all the advantages described above at the same time. BRIEF DESCRIPTION OF DRAWINGS

[0066] The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent by describing in detail the embodiments thereof with reference to the attached drawings in which:

[0067] Figure 1 A flowchart of a dynamic fare detection method provided by the embodiment of the present application;

[0068] Figure 2 A block diagram of a dynamic fare detection system provided by the embodiment of the present application;

[0069] Figure 3 A block diagram of a dynamic fare detection device provided by the embodiment of the present application. DETAILED DESCRIPTION

[0070] Embodiments of the present disclosure will be described more fully hereinafter with reference to the accompanying drawings. Although some embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure can be implemented in various forms and should not be interpreted as being limited to the embodiments set forth herein, but rather these embodiments are provided so that the present disclosure can be more thoroughly and completely understood. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not intended to limit the scope of protection of the present disclosure.

[0071] As used herein, the term "includes" and its variants are to be read to be analogous to "comprises," or "comprising." The term "based on" is to be read as "based, at least in part, on." The term "one embodiment" means "at least one embodiment." The term "another embodiment" means "at least one additional embodiment." The term "some embodiments" means "at least some embodiments." Related definitions are given throughout the description below.

[0072] It should be noted that the terms "first", "second", and the like in the present disclosure are merely used to distinguish different devices, modules or units, and do not imply the order or interdependence of the functions performed by these devices, modules or units.

[0073] It should be noted that the terms "one", "multiple" in the present disclosure are illustrative and not restrictive, and those skilled in the art should understand that "one or more" should be understood unless otherwise explicitly indicated in the context.

[0074] The embodiment of the present application provides a dynamic fare detection method, as shown in the figure, the dynamic fare detection method comprises: Figure 1

[0075] S101, obtaining the dynamic fare of the target route published by the airline to the fare system, the dynamic fare comprising the identification of the source dynamic fare and a plurality of ticket price influencing factors, the source dynamic fare being the dynamic fare corresponding to the target route in the fare system which has completed detection.

[0076] Optionally, in an optional embodiment of the present application, the above-mentioned source dynamic fare can be a static fare published by the airline to the fare system in addition to the dynamic fare corresponding to the target route in the fare system which has completed detection. The static fare has a specific ticket price, and the static fare is not an incorrect fare.

[0077] It should be noted that in the actual application scenario, the above-mentioned dynamic fare can be based on the source dynamic fare of the same target route to adjust the fare. As shown in the following table:

[0078]

[0079] It should be noted that in the actual application scenario, the type of the above-mentioned ticket price influencing factor includes: fare change value and travel rule change, wherein the fare change value can be at least one of fare discount value and fare increase / decrease value. The above-mentioned travel rule change includes but is not limited to: baggage restriction, sales channel, change and cancellation rule, etc.

[0080] ​It should be noted that in the actual application scenario, in the process of generating ticket price based on dynamic fare, the airline's fare control personnel publishes the edited dynamic fare to the fare system, and the fare system calculates the ticket price based on the ticket price influencing factors in the dynamic fare, the identifier of the source dynamic fare and other parameters after receiving the dynamic fare. The present application obtains the dynamic fare of the target route published by the airline to the fare system through configuration, and detects it before the dynamic fare generates ticket price, avoiding the risk of generating incorrect ticket price caused by incorrect dynamic fare entering the ticket price generation link.

[0081] S102, determine the preset discount range corresponding to the source dynamic fare according to the identifier of the source dynamic fare, and the preset discount range is a discount range constructed based on the statistical results of the published fare of the target route.

[0082] Optionally, in an optional embodiment of the present application, the above-mentioned published fare is a valid, error-free fare. Specifically, the above-mentioned published fare can be a standard fare published by an airline without error, or a dynamic fare after detection, the detection result of which represents that the dynamic fare has no error, and the ticket price is generated based on the error-free dynamic fare, and the dynamic fare is published after the ticket price is validated.

[0083] It should be noted that in the actual application scenario, there are many ways to obtain the above-mentioned preset discount range, and one of them is provided here as an example:

[0084] Obtain a plurality of published fares of the target route, wherein the type of the above-mentioned published fare includes: one standard fare F0, and a plurality of detected dynamic fares Fi, i∈(1, n) generated based on the standard fare. For example: the identifier of the source dynamic fare of F1 is F0, the identifier of the source dynamic fare of F2 is F1, the identifier of the source dynamic fare of F3 is F2, and the identifier of the source dynamic fare of F4 is F1.

[0085] Based on the specific ticket price of the above-mentioned standard fare and the ticket price influencing factors of each detected dynamic fare, the ticket price corresponding to each detected dynamic fare is obtained. And calculate the discount of the ticket price of each dynamic fare compared with the ticket price of the standard fare. Then based on the risk of each discount, the human evaluation is determined, and each initial preset discount range of the target route and the error evaluation coefficient corresponding to each initial preset discount range are determined.

[0086] Again, obtain a plurality of dynamic fares for correction of the target route, and the type of the above-mentioned dynamic fare for correction includes error-free dynamic fare and error dynamic fare. Based on the above-mentioned dynamic fare for correction, the method provided by the present application is used to Figure 1The detection method of the dynamic fare shown determines the initial preset discount range and the error evaluation coefficient corresponding to each dynamic fare for correction, and corrects the initial preset discount range and the error evaluation coefficient corresponding to each dynamic fare for correction based on the type of the dynamic fare for correction, to determine the preset discount range of the target route and the error evaluation coefficient corresponding to each preset discount range.

[0087]

[0088]

[0089] It should be noted that in an actual application scenario, since the preset discount range is constructed based on the statistical results of the published fares of the target route, and the published fares will not be incorrect, by configuring the preset discount range corresponding to the source dynamic fare based on the ticket price influencing factors and the source dynamic fare, the error evaluation coefficient representing the risk degree of the dynamic fare being an incorrect dynamic fare is obtained, and the dynamic fare is detected based on the error evaluation coefficient, thereby realizing accurate detection of whether the dynamic fare is incorrect.

[0090] S103, if the ticket price influencing factors at least include the fare discount value and the fare increase / decrease value, each ticket price influencing factor in the dynamic fare is analyzed, and based on the analysis result and the preset discount range corresponding to the source dynamic fare, the error evaluation coefficient of the dynamic fare is obtained, which represents the risk degree of the dynamic fare being an incorrect dynamic fare.

[0091] Optionally, in an optional embodiment of the present application, the implementation manner of identifying whether the ticket price influencing factors include the fare discount value and the fare increase / decrease value, and analyzing each ticket price influencing factor can be realized by a string recognition manner, specifically:

[0092] Suppose the dynamic fare is: 80% of the fare of F1, minus 100 yuan, and modify the sales channel to B channel.

[0093] Then the preset string recognition algorithm is used to recognize the string of the above dynamic fare. Suppose that "%" is the identifier of the fare discount value, "-… yuan" is the identifier of the fare increase / decrease value, "sales channel" is the identifier of the modification rule, and ".channel" is the identifier of the modification rule content. Then the recognition result after recognition includes: "80%", "-100 yuan", "sales channel" and "B channel".

[0094] Those skilled in the art can understand that in actual application scenarios, the types of the above preset string recognition algorithm are various, such as a brute force (BF) algorithm, a boyer-moore (BM) algorithm, a knuth morris pratt (KMP) algorithm, and the like. The present application does not make too many limitations and repetitions on the specific type and construction process of the above preset string recognition algorithm.

[0095] In S104, if the ticket price influencing factor only includes the fare discount value, the error evaluation coefficient of the dynamic fare is obtained based on the fare discount value and the preset discount range corresponding to the source dynamic fare.

[0096] It should be noted that in actual application scenarios, since the preset discount range and the dynamic fare are used in the evaluation and detection of the present application, a large amount of flight information, segment information and passenger information is not required, thereby reducing the calculation cost and improving the detection efficiency.

[0097] It should be noted that in actual application scenarios, the above steps S103 and S104 can be concurrent operation steps, that is, the above steps S103 and S104 are concurrently executed according to the difference of the ticket price influencing factors of the plurality of dynamic fares.

[0098] In S105, the error detection of the dynamic fare is performed based on the error evaluation coefficient of the dynamic fare.

[0099] The present application detects the dynamic fare of the target route published by the airline to the fare system through configuration before the dynamic fare generates the ticket price, thereby avoiding the risk that the error dynamic fare enters the ticket price generation link to cause the generation of error ticket price. Meanwhile, since the preset discount range is constructed based on the statistical result of the published fare of the target route, and the published fare will not be error, the error evaluation coefficient representing the risk degree of the dynamic fare as an error dynamic fare is obtained by configuring the ticket price influencing factor of the dynamic fare and the preset discount range corresponding to the source dynamic fare, and the error detection of the dynamic fare is performed based on the error evaluation coefficient, thereby realizing the accurate detection of whether the dynamic fare is error. Finally, since the preset discount range and the dynamic fare are used in the evaluation and detection of the present application, a large amount of flight information, segment information and passenger information is not required, thereby reducing the calculation cost and improving the detection efficiency. It can be seen that the present application realizes the detection of the error dynamic fare.

[0100] Optionally, the above determining the preset discount range corresponding to the source dynamic fare according to the identifier of the source dynamic fare includes:

[0101] The error evaluation coefficient of the source dynamic fare is determined based on the identification of the source dynamic fare, and a preset discount range corresponding to the error evaluation coefficient of the source dynamic fare is determined as a preset discount range corresponding to the source dynamic fare. The error evaluation coefficient and the preset discount range have a corresponding relationship.

[0102] It should be noted that in actual application scenarios, after each dynamic fare is detected, whether the dynamic fare is an error dynamic fare or not, the dynamic fare and its corresponding error evaluation coefficient need to be stored for subsequent calling of the dynamic fare. At the same time, by storing each dynamic fare and the error evaluation coefficient, the airline can avoid generating an error fare again on the basis of an error dynamic fare that has been released, but due to the error evaluation coefficient of the error source dynamic fare not being stored, the error evaluation coefficient of the source dynamic fare needs to be determined again, thereby causing the risk of reduced detection efficiency.

[0103] Optionally, the error evaluation coefficient of the dynamic fare is obtained based on the analysis result and the preset discount range corresponding to the source dynamic fare, and includes:

[0104] An initial evaluation reference value corresponding to the route identifier and the cabin identifier in the dynamic fare is obtained, the initial evaluation reference value is corrected based on the analysis result to obtain an evaluation reference value;

[0105] The quotient of the fare increase / decrease value divided by the evaluation reference value is determined as a fare discount increase / decrease value;

[0106] The product of the intermediate value of the preset discount range corresponding to the source dynamic fare and the fare discount value is obtained, and the sum of the product and the fare discount increase / decrease value is obtained;

[0107] The preset discount range corresponding to the sum is searched, and the error evaluation coefficient corresponding to the preset discount range corresponding to the sum is determined as the error evaluation coefficient of the dynamic fare.

[0108] It should be noted that in actual application scenarios, the inventors of the present application have found that for ticket price influencing factors involving travel rule modification, different types of travel rules have a large difference in the influence on the price of the ticket. For example: when the sales channel is modified, the rule has little effect on the price of the ticket. However, through data statistical analysis, when the pre-sale period is modified, the shortening of the pre-sale period will inevitably lead to an increase in the price of the ticket. At this time, if the initial evaluation reference value of a certain cabin of the route is used to determine the error evaluation coefficient, the discount change caused by the increase in the price of the ticket will be ignored. Therefore, the present application corrects the initial evaluation reference value based on the analysis result to obtain an evaluation reference value, and determines the error evaluation coefficient based on the evaluation reference value, thereby improving the final detection accuracy.

[0109] It should be noted that in the actual application scenario, the above implementation of obtaining the error evaluation coefficient of the dynamic transport price based on the preset discount range corresponding to the analysis result and the source dynamic transport price has multiple modes, and one of them is exemplarily provided herein:

[0110] For the target route, it is assumed that the dynamic transport price F3 is: the ticket price is adjusted to the price of F2 * 50% + 100 yuan, and the pre-sale period is shortened from 30 days to 10 days.

[0111] The source dynamic transport price F2 is: the ticket price is 60% of the published transport price F0. The error evaluation coefficient is 7.

[0112] The price of the published transport price F0 is 1000 yuan, and the pre-sale period is 30 days. Among them, 1000 yuan is the standard transport price of the target route. The subsequent dynamic transport price is adjusted on the basis of 1000 yuan.

[0113] After analyzing the dynamic transport price F3, the analysis result obtained is: the transport price discount value is “50%”, the transport price increase or decrease value is “+100 yuan”, the modification rule is “pre-sale period”, and the modification rule content is “shortened from 30 days to 10 days”. Since “preset period” is a ticket price influencing factor with high degree of influence on ticket price, it is necessary to modify the initial evaluation reference value F0.

[0114] Based on the modification rule and the modification rule content, the preset database table is queried, and it is known that the ticket price of the same route and the same cabin with a pre-sale period of 14 days is 200 yuan higher than that with a pre-sale period of 30 days. Therefore, when the dynamic transport price F2 is executed, the corresponding published price should be the price with a pre-sale period of 14 days, i.e. the corrected evaluation reference value is: 1000+200=1200.

[0115] Subsequently, since the present application uniformly converts ticket price influencing factors to the discount dimension for analysis, it is necessary to convert the influence degree of the transport price increase value on the ticket price to the discount dimension, i.e. the quotient value obtained by dividing the transport price increase or decrease value by the evaluation reference value is determined as the transport price discount increase or decrease value: 100÷1200=0.083.

[0116] It is assumed that the preset discount range corresponding to F2 is 5-6 times. Then take the middle number 5.5 times. Then the calculation process of obtaining the product of the middle value of the preset discount range corresponding to the source dynamic transport price and the transport price discount value, and the sum of the product and the transport price discount increase or decrease value is: 5.5*0.5+0.83=3.58 times. By comparing 3.58 times with each preset discount interval, it is found that 3.58 times is in the preset discount range of 3.5-4 times, and the error evaluation coefficient corresponding to the preset discount range is 4.

[0117] It should be noted that in actual application scenarios, the above travel rules and their influence on the ticket price can be determined based on historical data of the ticket price. The present application does not make too many limitations.

[0118] Optionally, the initial evaluation reference value corresponding to the route identifier and the seat identifier in the dynamic fare is obtained, comprising:

[0119] In the case where there are multiple historical ticket prices corresponding to the route identifier and the seat identifier, the weighted average of the multiple historical ticket prices is determined as the initial evaluation reference value;

[0120] In the case where there are no multiple historical ticket prices corresponding to the route identifier and the seat identifier, the ticket price influencing factors, the seat identifier and the route identifier in the dynamic fare are input into the preset reference value generation model to obtain the initial evaluation reference value output by the preset reference value generation model.

[0121] It should be noted that in actual application scenarios, the above case where there are multiple historical ticket prices corresponding to the route identifier and the seat identifier represents that the above historical ticket prices have been sold and there is no error. At this time, the initial evaluation reference value can be determined based on the historical ticket price. For the case where there are no multiple historical ticket prices corresponding to the route identifier and the seat identifier, it represents that the route and the seat have not been sold, and there is no correct ticket price to refer to. Therefore, by introducing the preset reference value generation model to generate the initial evaluation reference value based on the ticket price influencing factors, the seat identifier and the route identifier, the accuracy of the initial evaluation reference value is improved.

[0122] Optionally, the training process of the above preset reference value generation model comprises:

[0123] Obtain the historical dynamic fares corresponding to the multiple published ticket prices of the fare system, the historical dynamic fares comprising: the historical dynamic corresponding ticket price, route identifier, seat identifier and multiple ticket price influencing factors;

[0124] Train the initial preset reference value generation model using each historical dynamic fare to obtain the preset reference value generation model, the input of the preset reference value generation model being the seat identifier, the route identifier and the ticket price influencing factors in the dynamic fare published by the airline to the fare system, and the output being the initial evaluation reference value corresponding to the route identifier and the seat identifier in the dynamic fare.

[0125] Optionally, if the ticket price influencing factors only include the fare discount value, the error evaluation coefficient of the dynamic fare is obtained based on the fare discount value and the preset discount range corresponding to the source dynamic fare, comprising:

[0126] a product of an intermediate value of a preset discount range corresponding to the source dynamic fare and the fare discount value is obtained, and a preset discount range corresponding to the product is searched;

[0127] An error evaluation coefficient corresponding to the preset discount range corresponding to the product is determined as the error evaluation coefficient of the dynamic fare.

[0128] It should be noted that in actual application scenarios, if the ticket price influencing factor only includes the fare discount value, there are various implementation manners for obtaining the error evaluation coefficient of the dynamic fare based on the fare discount value and the preset discount range corresponding to the source dynamic fare, and one of them is exemplarily provided as follows:

[0129] Suppose the dynamic fare F3 is that the ticket price is adjusted to F2*70%, and other rules remain unchanged, and the consumption channel is adjusted. Since the modification rule of the "consumption channel" belongs to a low degree of influence on the ticket price. Therefore, even if the ticket price influencing factor in the dynamic fare F3 includes "70%" and "consumption channel", the ticket price influencing factor of "consumption channel" is discarded.

[0130] Suppose the preset discount range of F2 is 3.5-4, then the intermediate value 3.75 is taken, and the product of the intermediate value and the fare discount value is 3.75*0.7=2.63. Since 2.63 is within the preset discount range 2-3, the error evaluation coefficient of the dynamic fare F3 is 2.

[0131] Optionally, the error detection of the dynamic fare based on the error evaluation coefficient of the dynamic fare includes:

[0132] A preset evaluation interval corresponding to the route identifier is obtained;

[0133] In a case where the error evaluation coefficient is less than a lower limit value of the preset evaluation interval, the output content is a feedback result that the dynamic fare is incorrect, and a blocking operation is performed on the dynamic fare;

[0134] In a case where the error evaluation coefficient is within the preset evaluation interval, the output content is a feedback result that the dynamic fare has an error risk;

[0135] In a case where the error evaluation coefficient is greater than an upper limit value of the preset evaluation interval, a ticket price is generated based on the dynamic fare.

[0136] It should be noted that in the actual application scenario, the above-mentioned preset evaluation interval can be formulated based on the ticket prices and costs of different cabins of different routes. For example, when the error evaluation coefficient is less than the lower limit value of the preset evaluation interval, if the dynamic yield corresponding to the error evaluation coefficient is used for sales, the generated ticket price will be much less than the operating cost. If the error evaluation coefficient is within the preset evaluation interval, if the dynamic yield corresponding to the error evaluation coefficient is used for sales, the generated ticket price can be equal to or slightly less than the operating cost, and the ticket price and the operating cost are within the acceptable range of the airline.

[0137] It should be noted that in the actual application scenario, the present application outputs a feedback result that the dynamic yield is incorrect when the error evaluation coefficient is less than the lower limit value of the preset evaluation interval, and performs a blocking operation on the dynamic yield, thereby avoiding the risk of generating a ticket price based on a dynamic yield with high error risk.

[0138] The names of the messages or information exchanged between the plurality of devices in the embodiments of the present disclosure are only for illustrative purposes, and are not intended to limit the scope of the messages or information.

[0139] Although the operations are depicted in a particular order, this should not be understood as requiring the operations to be performed in the particular order shown or in a sequential order. Under certain circumstances, multitasking and parallel processing can be advantageous.

[0140] It should be understood that each of the steps described in the method embodiments of the present disclosure can be performed in different orders and / or in parallel. In addition, the method embodiments can include additional steps and / or omit the execution of the steps shown. The scope of the present disclosure is not limited in this respect.

[0141] Computer program code for carrying out operations of the present disclosure can be written in one or more programming languages or combinations of languages including object oriented programming languages such as Java, Smalltalk, C++ or conventional procedural programming languages such as the "C" programming language or similar programming languages. The program code can 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 can 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 can be made to an external computer (for example, through the Internet using an Internet Service Provider).

[0142] Corresponding to the method embodiments, the application further provides a dynamic fare detection system, as shown in the figure, which comprises: Figure 2

[0143] a fare obtaining module 201, configured to obtain a dynamic fare of a target route published by an airline to a fare system, the dynamic fare comprising an identification of a source dynamic fare and a plurality of ticket price influencing factors, the source dynamic fare being a dynamic fare corresponding to the target route in the fare system and having completed detection;

[0144] a range determining module 202, configured to determine a preset discount range corresponding to the source dynamic fare according to the identification of the source dynamic fare, the preset discount range being a discount range constructed based on a statistical result of a published fare of the target route;

[0145] a first coefficient obtaining module 203, if the ticket price influencing factors at least comprise a fare discount value and a fare increase / decrease value, configured to analyze each ticket price influencing factor in the dynamic fare, and based on an analysis result and the preset discount range corresponding to the source dynamic fare, obtain an error evaluation coefficient of the dynamic fare, the error evaluation coefficient representing a risk degree of the dynamic fare being an error dynamic fare;

[0146] a second coefficient obtaining module 204, if the ticket price influencing factors only comprise the fare discount value, configured to obtain the error evaluation coefficient of the dynamic fare based on the fare discount value and the preset discount range corresponding to the source dynamic fare;

[0147] an error detection module 205, configured to perform error detection on the dynamic fare based on the error evaluation coefficient of the dynamic fare.

[0148] Optionally, the range determining module 202 is configured to:

[0149] determine an error evaluation coefficient of the source dynamic fare based on the identification of the source dynamic fare, and determine a preset discount range corresponding to the error evaluation coefficient of the source dynamic fare as the preset discount range corresponding to the source dynamic fare, the error evaluation coefficient and the preset discount range having a corresponding relationship.

[0150] Optionally, the first coefficient obtaining module 203 is configured to, when obtaining the error evaluation coefficient of the dynamic fare based on the analysis result and the preset discount range corresponding to the source dynamic fare:

[0151] obtain an initial evaluation reference value corresponding to a route identification and a cabin identification in the dynamic fare, correct the initial evaluation reference value based on the analysis result, and obtain an evaluation reference value;

[0152] determine a quotient value of the fare increase / decrease value divided by the evaluation reference value as a fare discount increase / decrease value;

[0153] ​obtaining the product of the middle value of the preset discount range corresponding to the source dynamic fare and the fare discount value, and obtaining the sum of the product and the fare discount increase / decrease value;

[0154] finding the preset discount range corresponding to the sum, and determining the error evaluation coefficient corresponding to the preset discount range corresponding to the sum as the error evaluation coefficient of the dynamic fare.

[0155] Optionally, the first coefficient obtaining module 203 is configured to, when obtaining the initial evaluation reference value corresponding to the route identifier and the cabin identifier in the dynamic fare:

[0156] in the case where there are multiple historical ticket prices corresponding to the route identifier and the cabin identifier, determining the weighted average of the multiple historical ticket prices as the initial evaluation reference value;

[0157] in the case where there are no multiple historical ticket prices corresponding to the route identifier and the cabin identifier, inputting each ticket price influencing factor, the cabin identifier and the route identifier in the dynamic fare into a preset reference value generation model to obtain an initial evaluation reference value output by the preset reference value generation model.

[0158] Optionally, the dynamic fare detection system as shown in Figure 2 Optionally, the dynamic fare detection system as shown in

[0159] obtaining historical dynamic fares corresponding to multiple published ticket prices of the fare system, the historical dynamic fares including: historical dynamic corresponding ticket prices, route identifiers, cabin identifiers and multiple ticket price influencing factors;

[0160] training the initial preset reference value generation model using each historical dynamic fare to obtain the preset reference value generation model, the input of the preset reference value generation model being the cabin identifier, the route identifier and each ticket price influencing factor in the dynamic fare published by the airline to the fare system, and the output being an initial evaluation reference value corresponding to the route identifier and the cabin identifier in the dynamic fare.

[0161] Optionally, the second coefficient obtaining module 204 is configured to:

[0162] obtaining the product of the middle value of the preset discount range corresponding to the source dynamic fare and the fare discount value, and finding the preset discount range corresponding to the product;

[0163] determining the error evaluation coefficient corresponding to the preset discount range corresponding to the product as the error evaluation coefficient of the dynamic fare.

[0164] Optionally, the error detection module 205 is configured to:

[0165] obtaining a preset evaluation interval corresponding to the route identifier;

[0166] In a case where the error evaluation coefficient is less than a lower limit value of the preset evaluation interval, a feedback result of a dynamic transport price error is output, and the dynamic transport price is blocked;

[0167] In a case where the error evaluation coefficient is in the preset evaluation interval, a feedback result of a dynamic transport price error risk is output;

[0168] In a case where the error evaluation coefficient is greater than an upper limit value of the preset evaluation interval, a ticket price is generated based on the dynamic transport price.

[0169] The modules described in the embodiments of the present disclosure can be implemented in a software manner or in a hardware manner. In some cases, the name of a module does not limit the module itself, for example, the first obtaining module can also be described as a module for obtaining at least two Internet protocol addresses.

[0170] The functions described above can be performed at least partially by one or more hardware logic components. For example, non-limiting example types of hardware logic components that can be used include: field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), system-on-a-chip (SOCs), complex programmable logic devices (CPLDs), and the like.

[0171] The embodiments of the present disclosure also provide a dynamic transport price detection device, as shown in Figure 3 The dynamic transport price detection device comprises:

[0172] a processor 301;

[0173] a memory 302 for storing instructions executable by the processor 301;

[0174] The processor 301 is configured to execute the instructions to implement any one of the dynamic transport price detection methods described above.

[0175] The embodiments of the present disclosure also provide a computer-readable storage medium, when the instructions in the computer-readable storage medium are executed by the processor of the dynamic transport price detection device, the dynamic transport price detection device can execute any one of the dynamic transport price detection methods described above.

[0176] In the context of this disclosure, a machine-readable medium can be a tangible medium that can contain or store program code for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of the machine-readable storage medium would include one or more lines of electrical wire, portable computer diskette, hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or Flash memory), optical fiber, portable compact disc read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination of the foregoing.

[0177] It is noted that the computer-readable medium described above in the present disclosure can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. The computer-readable storage medium, for example, can be, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of the computer-readable storage medium can include, but are not limited to, one or more lines of electrical wire, portable computer diskette, hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or Flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination of the foregoing. In the present disclosure, the computer-readable storage medium can be any tangible medium that contains or stores a program for use by or in connection with an instruction execution system, apparatus, or device. In the present disclosure, the computer-readable signal medium can include a data signal that propagates in a baseband or as part of a carrier wave by any suitable means, in which the computer-readable program code is embodied. Such a propagated signal can take any suitable form, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination of the foregoing. The computer-readable signal medium can also be any computer-readable medium that is not a computer-readable storage medium, which can communicate, propagate, or transport program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained in the computer-readable medium can be transmitted by any suitable medium, including but not limited to a wire, cable, RF (radio frequency), or the like, or any suitable combination of the foregoing.

[0178] The computer-readable medium described above can be contained in the electronic device described above; or can exist separately without being assembled into the electronic device.

[0179] Those skilled in the art will appreciate that embodiments of the present application can be devised for a method, a system or a computer program product. Accordingly, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application can take the form of a computer program product on one or more computer readable storage media (including, but not limited to, disk storage, CD-ROMs, optical storage devices, etc.) embodying computer readable program code.

[0180] Although the subject matter has been described in language specific to structural features and / or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims.

[0181] Although specific implementation details have been included in the above discussion, these should not be construed as limiting the scope of the disclosure. Certain features described in the context of separate embodiments can also be implemented in combination in a single embodiment. Conversely, various features described in the context of a single embodiment can also be implemented separately or in any suitable subcombination. It will be appreciated that various features described herein can form the basis of independent patents / patent applications.

[0182] The above description is merely illustrative of the exemplary embodiments of this disclosure and the principles thereof. It is not intended to limit the scope of the disclosure to the specific forms described. Rather, the scope of the disclosure is to be determined by the claims, and equivalents thereof, as the disclosure is deemed amenable to modification to encompass any and all techniques consistent with the principles thereof. For example, the features described above with respect to the disclosed embodiments can be combined in any suitable manner in other embodiments.

Claims

1. A method for detecting dynamic fare, characterized by, The method comprises: obtaining a dynamic fare of a target route published by an airline to a fare system, the dynamic fare comprising an identification of a source dynamic fare and a plurality of ticket influencing factors, the source dynamic fare being a detected dynamic fare corresponding to the target route in the fare system; determining a preset discount range corresponding to the source dynamic fare according to the identification of the source dynamic fare, the preset discount range being a discount range constructed based on a statistical result of a published fare of the target route; if the ticket influencing factors at least comprise a fare discount value and a fare increase / decrease value, analyzing each of the ticket influencing factors in the dynamic fare, and obtaining an error evaluation coefficient of the dynamic fare based on an analysis result and the preset discount range corresponding to the source dynamic fare, the error evaluation coefficient representing a risk degree of the dynamic fare being an error dynamic fare; if the ticket influencing factors only comprise a fare discount value, obtaining an error evaluation coefficient of the dynamic fare based on the fare discount value and the preset discount range corresponding to the source dynamic fare; performing error detection on the dynamic fare based on the error evaluation coefficient of the dynamic fare.

2. The method of claim 1, wherein, The method comprises: determining an error evaluation coefficient of the source dynamic fare based on the identification of the source dynamic fare, and determining a preset discount range corresponding to the error evaluation coefficient of the source dynamic fare as the preset discount range corresponding to the source dynamic fare, the error evaluation coefficient and the preset discount range having a corresponding relationship.

3. The method of claim 2, wherein, The method comprises: obtaining an initial evaluation reference value corresponding to a route identification and a cabin identification in the dynamic fare, correcting the initial evaluation reference value based on the analysis result to obtain an evaluation reference value; dividing the fare increase / decrease value by the evaluation reference value to obtain a quotient value as a fare discount increase / decrease value; obtaining a product of a middle value of the preset discount range corresponding to the source dynamic fare and the fare discount value, and obtaining a sum of the product and the fare discount increase / decrease value; finding a preset discount range corresponding to the sum, and determining an error evaluation coefficient corresponding to the preset discount range corresponding to the sum as the error evaluation coefficient of the dynamic fare.

4. The method of claim 3, wherein, The method comprises: in a case where a plurality of historical air ticket prices corresponding to the route identification and the cabin identification exist, determining a weighted average value of the plurality of historical air ticket prices as the initial evaluation reference value; in a case where a plurality of historical air ticket prices corresponding to the route identification and the cabin identification do not exist, inputting each of the ticket influencing factors in the dynamic fare, the cabin identification and the route identification into a preset reference value generation model to obtain the initial evaluation reference value output by the preset reference value generation model.

5. The method of claim 4, wherein, The training process of the preset reference value generation model comprises: The system comprises: The system comprises:

6. The method of claim 2, wherein, The system comprises: The system comprises: The system comprises:

7. The method of claim 1, wherein, The system comprises: The system comprises: The system comprises: The system comprises: The system comprises:

8. A dynamic fare detection system, characterized by, The system comprises: The system comprises: The system comprises: The system comprises: The system comprises: The system comprises:

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processor-executable instructions; wherein the processor is configured to execute the instructions to implement the method for detecting dynamic freight rates as claimed in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium, when the instructions in the computer readable storage medium are executed by a processor of a dynamic freight rate detecting device, enables the dynamic freight rate detecting device to perform the method for detecting dynamic freight rates as claimed in any one of claims 1 to 7.

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