Method, device, computer equipment and storage medium for detecting bid rigging

Abstract

The present invention provides a method, device, computer equipment and storage medium for detecting bid rigging and collusion. The method comprises: obtaining bidding transaction data in a historical period, the transaction data comprising bid section information, bidding enterprise information, bidding enterprise information and bid-winning enterprise information; determining a candidate core enterprise from the bidding enterprise information according to the transaction data; determining candidate accompanying bidding enterprises related to the candidate core enterprise from the bidding enterprise information; determining a target bid section in which the candidate core enterprise and the candidate accompanying bidding enterprises jointly participate; and determining whether there is bid rigging and collusion between the candidate accompanying bidding enterprises and the candidate core enterprise according to changes in a first bid-winning rate of the candidate core enterprise and changes in a second bid-winning rate of the candidate accompanying bidding enterprises.

Description

Technical Field

[0001] The present invention relates to the technical field of bidding and tendering, and in particular to a method, device, computer equipment and storage medium for detecting bid rigging and collusion. Background Art

[0002] The bidding system plays a very important role in my country's construction industry. Since its implementation, bid rigging and collusion have been rampant, seriously affecting the fair and orderly competition environment in the construction market. At present, most of the schemes for detecting bid rigging and collusion are based on complex network community detection models. The bidding companies are used to construct a graph network, with the bidding companies as nodes and the bidding relationships as edges. The strength of the community structure is quantitatively measured based on a certain evaluation function, and the suspected group behavior between companies is explained from the bidding frequency and the meeting frequency.

[0003] However, the above method ignores certain regional attributes and business characteristics of bidding behavior and has significant defects. For example, in some regions, bidders in certain industry sectors have concentrated bidding, such as the power industry in some provinces and cities, that is, bidders in this field will participate in the bidding every time the bidding is opened. In this way, the existing model will meet the judgment of the frequency of encounter, which may lead to misjudgment in the conclusion. Summary of the invention

[0004] The purpose of the present invention is to provide a technical solution that can quickly and accurately detect bid-rigging and collusion in bidding transactions, so as to solve the above-mentioned problems existing in the prior art.

[0005] To achieve the above object, the present invention provides a method for detecting bid-rigging behavior, comprising:

[0006] Obtaining bidding transaction data in a historical period, wherein the transaction data includes bidding section information, bidding enterprise information, bidding enterprise information, and winning enterprise information;

[0007] Determining candidate core enterprises from the bidding enterprise information according to the transaction data;

[0008] Determining candidate accompanying bidding enterprises related to the candidate core enterprise from the bidding enterprise information;

[0009] Determine the target bidding section in which the candidate core enterprise and the candidate accompanying bidding enterprises jointly participate;

[0010] Based on the change in the first winning bid rate of the candidate core enterprise and the change in the second winning bid rate of the candidate accompanying bidding enterprise, determine whether there is collusion in bidding between the candidate accompanying bidding enterprises and the candidate core enterprise; wherein, the first winning bid rate change is the change in the winning bid rate of the candidate core enterprise in all bidding sections and the winning bid rate of the candidate core enterprise in the target bidding section, and the second winning bid rate change is the change in the winning bid rate of the candidate accompanying bidding enterprise in all bidding sections and the winning bid rate of the candidate accompanying bidding enterprise in the target bidding section.

[0011] According to the method for detecting bid-rigging provided by the present invention, the step of obtaining bidding transaction data in a historical period includes:

[0012] Obtaining all bidding section information within the historical period to form a bidding section set;

[0013] Obtaining information of all bidding companies participating in the bidding section during the historical period to form a set of bidding companies;

[0014] The information of all successful bidders participating in the bidding section during the historical period is obtained to form a successful bidder set.

[0015] According to the method for detecting bid-rigging provided by the present invention, the step of determining candidate core enterprises from the bidding enterprise information based on the transaction data comprises:

[0016] Determine the basic bid winning rate of each bidding enterprise in the historical period according to the bidding section information, the bidding enterprise information and the successful bidder information;

[0017] The candidate core enterprises are selected in order from the bidding enterprise information in order of basic bid winning rate from high to low.

[0018] According to the method for detecting bid-rigging provided by the present invention, the step of determining candidate secondary bidding enterprises related to the candidate core enterprise from the bidding enterprise information comprises:

[0019] Determine the first bidding section set in which the candidate core enterprise participates;

[0020] Acquire a first set of enterprises that have bid for a preset number of bid sections in the first set of bid sections;

[0021] Select any one bidding enterprise from the first set of enterprises as the candidate bidding enterprise.

[0022] According to the method for detecting bid-rigging provided by the present invention, the step of determining the target bidding section in which the candidate core enterprise and the candidate accompanying bidding enterprises jointly participate includes:

[0023] Determine the set of second bidding sections in which the candidate bidding enterprises participate;

[0024] The intersection of the first bid section set and the second bid section set is used as the target bid section.

[0025] According to the method for detecting bid rigging provided by the present invention, the first step of calculating the bid winning rate includes:

[0026] Calculate the core winning rate of the candidate core enterprise in the target bidding section; calculate the growth data of the core winning rate relative to the basic winning rate of the candidate core enterprise;

[0027] The step of calculating the second bid winning rate comprises:

[0028] Calculate the bid winning rate of the candidate bidders in the target bidding section; calculate the decline data of the bid winning rate relative to the basic bid winning rate of the candidate bidders.

[0029] According to the method for detecting bid rigging provided by the present invention, the step of determining whether there is bid rigging between the candidate accompanying bidding enterprises and the candidate core enterprise according to the change in the first winning bid rate of the candidate core enterprise and the change in the second winning bid rate of the candidate accompanying bidding enterprises provided by the present invention comprises:

[0030] When the growth data is greater than the first threshold and the decline data is greater than the second threshold, it is determined that there is bid rigging between the candidate accompanying bidding enterprises and the candidate core enterprise.

[0031] To achieve the above-mentioned purpose, the present invention further provides a device for detecting bid-rigging behavior, comprising:

[0032] A data acquisition module is used to acquire bidding transaction data in a historical period, wherein the transaction data includes bidding section information, bidding enterprise information, bidding enterprise information, and winning enterprise information;

[0033] A candidate core enterprise module, adapted to determine candidate core enterprises from the bidding enterprise information according to the transaction data;

[0034] A candidate bidding enterprise module, adapted to determine candidate bidding enterprises related to the candidate core enterprise from the bidding enterprise information;

[0035] A target bidding section module, adapted to determine the target bidding section in which the candidate core enterprise and the candidate accompanying bidding enterprise jointly participate;

[0036] The bid rigging and collusion determination module is suitable for determining whether there is bid rigging and collusion between the candidate accompanying bidding enterprises and the candidate core enterprise based on the change of the first winning bid rate of the candidate core enterprise and the change of the second winning bid rate of the candidate accompanying bidding enterprise; wherein the first winning bid rate change is the change of the winning bid rate of the candidate core enterprise in all bidding sections and the winning bid rate of the candidate core enterprise in the target bidding section, and the second winning bid rate change is the change of the winning bid rate of the candidate accompanying bidding enterprise in all bidding sections and the winning bid rate of the candidate accompanying bidding enterprise in the target bidding section.

[0037] To achieve the above objectives, the present invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above method when executing the computer program.

[0038] To achieve the above object, the present invention also provides a computer-readable storage medium on which a computer program is stored, and the computer program implements the steps of the above method when executed by a processor.

[0039] The detection method, device, computer equipment and storage medium for bid rigging provided by the present invention provide a technical solution for accurately detecting bid rigging based on the bid winning rate. The present invention is based on the analysis of bidding transaction data in the historical period, and for any two enterprises that meet the minimum number of encounters, the changes in the bid winning rate before and after the encounter are calculated. If the bid winning rate of one enterprise increases before and after the encounter and the bid winning rate of the other enterprise decreases before and after the encounter, then it can be determined that there is bid rigging between the two enterprises. The present invention makes full use of the key factor of the bid winning rate for data analysis, without the need to train a community detection model for complex networks, and improves the detection efficiency and accuracy of bid rigging while effectively reducing the detection cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 Schematic flow chart of Embodiment 1 of the method for detecting bid-rigging behavior of the present invention;

[0041] Figure 2 This is a schematic flow chart of determining candidate bidding companies according to the first embodiment of the present invention;

[0042] Figure 3 It is a schematic diagram of a program module of a first embodiment of a detection device for fraudulent bidding of the present invention;

[0043] Figure 4 This is a schematic diagram of the hardware structure of the first embodiment of the detection device for detecting collusion in bidding of the present invention. DETAILED DESCRIPTION

[0044] In order to make the purpose, technical scheme and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0045] Embodiment 1

[0046] See also Figure 1 This embodiment proposes a method for detecting bid-rigging behavior, comprising the following steps:

[0047] S100: Acquire bidding transaction data in a historical period, wherein the transaction data includes bidding section information, bidding enterprise information, bidding enterprise information, and winning enterprise information.

[0048] This embodiment obtains bidding transaction data based on historical bidding transaction events that have occurred, such as transaction data within the past three months, transaction data within the past six months, transaction data within the past year, etc. Among them, the bidding section information in the transaction data refers to the bidding object in the bidding project, such as the construction of a section of highway, the exterior wall decoration of a building and other specific projects. The bidding section information can be represented by different bidding section identification numbers, such as the first bidding section S1, the second bidding section S2, the third bidding section S3... The bidding enterprise information refers to the specific enterprise participating in the bidding of a certain bidding section, and the bidding enterprise information can be represented by different enterprise identification numbers or enterprise names, such as the first bidding enterprise Z1, the second bidding enterprise Z2, the third bidding enterprise Z3... The bidding enterprise information refers to the specific enterprise participating in the bidding of a certain bidding section, and the bidding enterprise information can be represented by different enterprise identification numbers or enterprise names, such as the first bidding enterprise T1, the second bidding enterprise T2, the third bidding enterprise T3... The winning enterprise information refers to the specific enterprise selected to be responsible for the construction of a certain bidding section during the bidding process. The winning enterprise information can be represented by different enterprise identification numbers or enterprise names, such as the first winning enterprise G1, the second winning enterprise G2, the third winning enterprise G3... Therefore, all bidding section information can form a bidding section set S{S1, S2, S3...}, all bidding enterprise information can form a bidding enterprise set T{T1, T2, T3...}, and all winning enterprise information can form a winning enterprise set G{G1, G2, G3...}.

[0049] S200: Determine candidate core enterprises from the bidding enterprise information according to the transaction data.

[0050] According to the rules of bid rigging, to determine whether there is bid rigging or bid collusion among bidders, it is only necessary to determine whether the bidders meet the following characteristics:

[0051] (1) Core members and accompanying bidders may appear in the same bidding section multiple times;

[0052] (2) In the bidding sections where there is bid-rigging and collusion, the core members’ winning rate will increase significantly due to the presence of bid-rigging and collusion groups;

[0053] (3) The winning rate of the bidding members themselves will decrease.

[0054] In the above text, core members refer to the winning bidders that benefit from bid-rigging in bidding transactions, and accompanying bidders refer to the unsuccessful bidders that facilitated the winning of the core members due to bid-rigging in bidding transactions.

[0055] Based on the above characteristics, this step can first determine the basic bid winning rate of each bidding enterprise in the historical period according to the bidding section information, bidding enterprise information and winning bidder information. The basic bid winning rate = number of winning bids / number of bids, and the bid winning rate is sorted from high to low. The bidding enterprises with the highest bid winning rate are selected as candidate core enterprises in turn. For example, the top three bidding enterprises with the highest bid winning rate are calculated as follows: the first bidding enterprise T1 has a bid winning rate of Z 01 The winning rate of the second bidding enterprise T2 is Z 02 The winning rate of the third bidding enterprise T3 is Z 03 , where Z 01 >Z 02 >Z 03 , then first select the first bidding enterprise T1 as the candidate core enterprise C.

[0056] S300: Determine candidate accompanying bidding enterprises related to the candidate core enterprise from the bidding enterprise information.

[0057] According to the characteristics of bid-rigging behavior described above, it can be known that the prerequisite for being a supporting bidder is that the supporting bidder and the core enterprise participate in the bidding process for the same bidding section. Therefore, the steps for determining candidate supporting bidders in this embodiment are as follows: Figure 2 As shown, including:

[0058] S310: Determine the first bidding section set in which the candidate core enterprise participates.

[0059] Assume that candidate core enterprise C has a corresponding basic bid winning rate of Z C According to the bidding section information and bidding enterprise information in the bidding transaction data, the first bidding section set S1 = {S11, S12, ..., S1 n}.

[0060] S320: Obtain a first set of enterprises that have bid for a preset number of bid sections in the first set of bid sections.

[0061] As mentioned above, core members and co-tender members may appear in the same bidding section multiple times. On the basis of determining the candidate core enterprise C, in order to determine the corresponding candidate co-tender enterprise M, it is necessary to first obtain the first enterprise that has participated in the same bidding section multiple times with the candidate core enterprise C. It is known that the first bidding section set S1 in which the candidate core enterprise C participates is S2 = {S11, S12, ..., S1 n}, then the enterprise that has participated in bidding more than the preset number of times in S1 is the first enterprise in this step. The preset number of times here can be set according to the minimum encounter threshold, such as two, three or more times. Assuming the preset number is 2, the bidding enterprise M1 has participated in the bidding process of sections S11 and S13 in the set S1, then M1 can be the first enterprise. When there are multiple enterprises that have participated in bidding more than the preset number of times in S1, the first enterprise set M = {M1, M2, ..., M n}.

[0062] S330: Select any one bidding enterprise from the first enterprise set as the candidate bidding enterprise, for example, select M1.

[0063] S400: Determine the target bidding section in which the candidate core enterprise and the candidate accompanying bidding enterprises jointly participate.

[0064] It is known that the bidding sections in which the candidate core enterprises participate are the first bidding section set S1 = {S11, S12, ..., S1 n}, the bidding section in which the candidate bidding enterprise M1 participates is determined from the set S1 as the target bidding section set. Assume that S C Indicates that Sc={Sc1,Sc2,..,Scn}.

[0065] S500: Determine whether there is bid rigging between the candidate accompanying bidding enterprises and the candidate core enterprise based on the first change in the bid winning rate of the candidate core enterprise and the second change in the bid winning rate of the candidate accompanying bidding enterprises; wherein the first change in the bid winning rate is the change in the bid winning rate of the candidate core enterprise in all bidding sections and the bid winning rate of the candidate core enterprise in the target bidding section, and the second change in the bid winning rate is the change in the bid winning rate of the candidate accompanying bidding enterprises in all bidding sections and the bid winning rate of the candidate accompanying bidding enterprises in the target bidding section.

[0066] The winning rate of candidate core enterprise C in all bidding sections is the basic winning rate of candidate core enterprise C calculated in step S200, which is recorded as Zc; the winning rate of candidate core enterprise C in the target bidding section is recorded as ZSc, ZSc=the number of times C wins the bid in the target bidding section set Sc / the number of bidding sections in Sc. Therefore, the first winning rate change=ZSc-Zc.

[0067] The winning rate of candidate bidder M1 in all bid sections is the basic winning rate of candidate bidder M1 calculated in step S200, recorded as Zm1; the winning rate of candidate bidder M1 in the target bid section is recorded as ZSm1, ZSm1=the number of times M1 wins the bid in the target bid section set Sc / the number of bid sections in Sc. Therefore, the second winning rate change=Zm1-ZSm1.

[0068] As mentioned above, when there is bid rigging, the winning rate of the core members will increase significantly while the winning rate of the accompanying bidders will decrease. Based on the above rules, this step judges the first winning rate change and the second winning rate change. When the first winning rate change is greater than the first threshold Fm and the second winning rate change is greater than Fn, it is determined that there may be bid rigging between the candidate core enterprise C and the candidate accompanying bidder M1. Fm and Fn are thresholds set based on experience.

[0069] Continue to loop and judge other bidders M2, M3...Mn, and finally the qualified bidders form a suspected group {C:M1,M2...Mn}. Furthermore, the suspected group {C:M1,M2...Mn} can be further screened, and the members who meet the minimum combined bid winning rate threshold Pn will eventually form a bid-rigging group K.

[0070] In summary, the method for detecting bid-rigging and collusion proposed in this embodiment closely follows the characteristics of bidding and tendering business, and judges bid-rigging and collusion groups based on the fact of changes in the winning bid rate, which is more practical and feasible. Through the parameterized configuration of the threshold, the formation conditions of the group can be determined according to the dynamic threshold, which is flexible and reliable. Furthermore, for suspected groups, this embodiment can also add auxiliary judgment indicators, which are gradually progressive in steps and layers, so as to improve the accuracy of bid-rigging and collusion detection and avoid misjudgment.

[0071] Please continue reading Figure 3, shows a device for detecting bid rigging. In this embodiment, the device 30 for detecting bid rigging may include or be divided into one or more program modules. One or more program modules are stored in a storage medium and executed by one or more processors to complete the present invention and implement the above-mentioned method for detecting bid rigging. The program module referred to in the present invention refers to a series of computer program instruction segments that can perform specific functions, which is more suitable for describing the execution process of the device 30 for detecting bid rigging in a storage medium than the program itself. The following description will specifically introduce the functions of each program module in this embodiment:

[0072] The data acquisition module 31 acquires the bidding transaction data in the historical period, wherein the transaction data includes bidding section information, bidding enterprise information, bidding enterprise information, and winning enterprise information;

[0073] A candidate core enterprise module 32 is adapted to determine a candidate core enterprise from the bidding enterprise information according to the transaction data;

[0074] A candidate bidding enterprise module 33, adapted to determine candidate bidding enterprises related to the candidate core enterprise from the bidding enterprise information;

[0075] The target bidding section module 34 is adapted to determine the target bidding section in which the candidate core enterprise and the candidate accompanying bidding enterprise jointly participate;

[0076] The bid rigging determination module 35 is adapted to determine whether there is bid rigging between the candidate accompanying bidding enterprises and the candidate core enterprise based on the change in the first bid winning rate of the candidate core enterprise and the change in the second bid winning rate of the candidate accompanying bidding enterprises; wherein the first bid winning rate change is the change in the bid winning rate of the candidate core enterprise in all bidding sections and the bid winning rate of the candidate core enterprise in the target bidding section, and the second bid winning rate change is the change in the bid winning rate of the candidate accompanying bidding enterprise in all bidding sections and the bid winning rate of the candidate accompanying bidding enterprise in the target bidding section.

[0077] The present embodiment also provides a computer device, such as a smart phone, tablet computer, laptop computer, desktop computer, rack server, blade server, tower server or cabinet server (including an independent server or a server cluster composed of multiple servers) that can execute programs. The computer device 40 of the present embodiment includes at least but is not limited to: a memory 41 and a processor 42 that can communicate with each other through a system bus, such as Figure 4 It should be pointed out that Figure 4 Only a computer device 40 having components 41 - 42 is shown, but it should be understood that implementing all of the components shown is not a requirement, and more or fewer components may alternatively be implemented.

[0078] In this embodiment, the memory 41 (i.e., readable storage medium) includes flash memory, hard disk, multimedia card, card-type memory (e.g., SD or DX memory, etc.), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, disk, optical disk, etc. In some embodiments, the memory 41 can be an internal storage unit of the computer device 40, such as a hard disk or memory of the computer device 40. In other embodiments, the memory 41 can also be an external storage device of the computer device 40, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card, etc. equipped on the computer device 40. Of course, the memory 41 can also include both the internal storage unit of the computer device 40 and its external storage device. In this embodiment, the memory 41 is generally used to store the operating system and various application software installed on the computer device 20, such as the program code of the detection device 30 for the collusion in bidding in the first embodiment, etc. In addition, the memory 41 can also be used to temporarily store various types of data that have been output or are to be output.

[0079] In some embodiments, the processor 42 may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chip. The processor 42 is generally used to control the overall operation of the computer device 40. In this embodiment, the processor 42 is used to run the program code stored in the memory 41 or process data, such as running the detection device 30 for bid rigging to implement the detection method for bid rigging of the first embodiment.

[0080] This embodiment also provides a computer-readable storage medium, such as a flash memory, a hard disk, a multimedia card, a card-type memory (for example, an SD or DX memory, etc.), a random access memory (RAM), a static random access memory (SRAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a programmable read-only memory (PROM), a magnetic memory, a disk, an optical disk, a server, an App application store, etc., on which a computer program is stored, and the program realizes corresponding functions when executed by a processor. The computer-readable storage medium of this embodiment is used to store a detection device 30 for bid-rigging behavior, and when executed by a processor, the detection method for bid-rigging behavior of embodiment 1 is realized.

[0081] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0082] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code that includes one or more executable instructions for implementing the steps of a specific logical function or process, and the scope of the preferred embodiments of the present invention includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present invention belong.

[0083] A person of ordinary skill in the art can understand that all or part of the steps carried out in the above-mentioned embodiment method can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable medium. When the program is executed, it includes one of the steps of the method embodiment or a combination thereof.

[0084] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example" or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0085] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method.

[0086] The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for detecting bid rigging, characterized in that: include: Obtaining bidding transaction data in a historical period, wherein the transaction data includes bidding section information, bidding enterprise information, bidding enterprise information, and winning enterprise information; According to the transaction data, determine the candidate core enterprises from the bidding enterprise information, wherein the core enterprise refers to the winning enterprise that benefits from the bid-rigging behavior in the bidding transaction, wherein the determining the candidate core enterprises from the bidding enterprise information according to the transaction data is specifically: according to the transaction data, calculate the basic bid-winning rate of each bidding enterprise in the historical period, wherein the basic bid-winning rate = the number of bid-winning times / the number of bids, and sort from high to low according to the bid-winning rate, and select the bidding enterprises with the highest bid-winning rate as the candidate core enterprises in turn; Determine candidate accompanying bidding enterprises related to the candidate core enterprise from the bidding enterprise information, wherein an accompanying bidding enterprise refers to an enterprise that bid but failed to win the bid due to bid-rigging behavior in a bidding transaction; Determine the target bidding section in which the candidate core enterprise and the candidate accompanying bidding enterprises jointly participate; Based on the change in the first winning bid rate of the candidate core enterprise and the change in the second winning bid rate of the candidate accompanying bidding enterprise, determine whether there is collusion in bidding between the candidate accompanying bidding enterprises and the candidate core enterprise; wherein, the first winning bid rate change is the change in the winning bid rate of the candidate core enterprise in all bidding sections and the winning bid rate of the candidate core enterprise in the target bidding section, and the second winning bid rate change is the change in the winning bid rate of the candidate accompanying bidding enterprise in all bidding sections and the winning bid rate of the candidate accompanying bidding enterprise in the target bidding section.

2. The method for detecting bid-rigging behavior according to claim 1, characterized in that: The step of obtaining the bidding transaction data in the historical period includes: Obtaining all bidding section information within the historical period to form a bidding section set; Obtaining information of all bidding companies participating in the bidding section during the historical period to form a set of bidding companies; The information of all successful bidders participating in the bidding section during the historical period is obtained to form a successful bidder set.

3. The method for detecting bid-rigging behavior according to claim 2, characterized in that: The step of determining candidate accompanying bidding enterprises related to the candidate core enterprise from the bidding enterprise information comprises: Determine the first bidding section set in which the candidate core enterprise participates; Acquire a first set of enterprises that have bid for a preset number of bid sections in the first set of bid sections; Select any one bidding enterprise from the first set of enterprises as the candidate bidding enterprise.

4. The method for detecting bid-rigging behavior according to claim 3, characterized in that: The step of determining the target bidding section in which the candidate core enterprise and the candidate accompanying bidding enterprise jointly participate comprises: Determine the set of second bidding sections in which the candidate bidding enterprises participate; The intersection of the first bid section set and the second bid section set is used as the target bid section.

5. The method for detecting bid-rigging behavior according to claim 4, characterized in that: The step of calculating the first bid winning rate comprises: Calculate the core winning rate of the candidate core enterprise in the target bidding section; calculate the growth data of the core winning rate relative to the basic winning rate of the candidate core enterprise; The step of calculating the second bid winning rate comprises: Calculate the bid winning rate of the candidate bidders in the target bidding section; calculate the decline data of the bid winning rate relative to the basic bid winning rate of the candidate bidders.

6. The method for detecting bid-rigging behavior according to claim 5, characterized in that: The step of determining whether there is bid rigging between the candidate accompanying bidding enterprises and the candidate core enterprise according to the change in the first bid winning rate of the candidate core enterprise and the change in the second bid winning rate of the candidate accompanying bidding enterprises comprises: When the growth data is greater than the first threshold and the decline data is greater than the second threshold, it is determined that there is bid rigging between the candidate accompanying bidding enterprises and the candidate core enterprise.

7. A device for detecting bid-rigging behavior, characterized in that: include: A data acquisition module is used to acquire bidding transaction data in a historical period, wherein the transaction data includes bidding section information, bidding enterprise information, bidding enterprise information, and winning enterprise information; The candidate core enterprise module is adapted to determine the candidate core enterprises from the bidding enterprise information according to the transaction data, wherein the core enterprise refers to the winning enterprise that benefits from the bid-rigging behavior in the bidding transaction, wherein the determining the candidate core enterprises from the bidding enterprise information according to the transaction data is specifically: calculating the basic bid-winning rate of each bidding enterprise in the historical period according to the transaction data, wherein the basic bid-winning rate = the number of bid-winning times / the number of bids, and sorting from high to low according to the bid-winning rate, and selecting the bidding enterprises with the highest bid-winning rate in turn as the candidate core enterprises; A candidate accompanying bidding enterprise module is used to determine candidate accompanying bidding enterprises related to the candidate core enterprise from the bidding enterprise information, wherein an accompanying bidding enterprise refers to an enterprise that bids but fails to win the bid due to bid-rigging behavior in a bidding transaction to facilitate the core member to win the bid; A target bidding section module, adapted to determine the target bidding section in which the candidate core enterprise and the candidate accompanying bidding enterprise jointly participate; The bid rigging and collusion determination module is suitable for determining whether there is bid rigging and collusion between the candidate accompanying bidding enterprises and the candidate core enterprise based on the change of the first winning bid rate of the candidate core enterprise and the change of the second winning bid rate of the candidate accompanying bidding enterprise; wherein the first winning bid rate change is the change of the winning bid rate of the candidate core enterprise in all bidding sections and the winning bid rate of the candidate core enterprise in the target bidding section, and the second winning bid rate change is the change of the winning bid rate of the candidate accompanying bidding enterprise in all bidding sections and the winning bid rate of the candidate accompanying bidding enterprise in the target bidding section.

8. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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