Purchase risk management method and system based on AI technology

Abstract

The invention discloses a procurement risk management method and system based on an AI technology, and relates to the technical field of bidding, and the method comprises the steps: obtaining enterprise procurement related information collected by a bidding intelligent supervision system; analyzing the enterprise purchase related information to obtain key information related to the purchase risk, and comparing the key information with risk information set in preset risk types to determine a corresponding risk name and a risk level; when the risk level of one of the target risks is higher than a preset level threshold value, the supervision authority is started, a supervision pop-up window is sent after a supervision instruction is received, and the supervision pop-up window is used for receiving supervision suggestions for the risks and sending the supervision suggestions to the corresponding target unit. According to the invention, the problem of poor accuracy during purchase risk management in the prior art is solved.

Description

Technical Field

[0001] The present invention relates to the field of bidding technology, and in particular to a procurement risk management method and system based on AI technology. Background Art

[0002] With the rapid development of information technology, especially the popularization of electronic means, the traditional procurement bidding process has gradually turned to digitalization and automation, and the electronic bidding system has become an important tool for public procurement of many enterprises. Through electronic means, procurement units can more efficiently publish bidding information, receive bidding documents, etc., and monitor the procurement process in real time.

[0003] At present, when supervising procurement risks, the same response strategy is adopted regardless of the level of risk, resulting in poor accuracy in risk procurement governance. Summary of the invention

[0004] In view of this, the purpose of the present invention is to provide a procurement risk management method and system based on AI technology, aiming to solve the problem of poor accuracy in procurement risk management in the prior art.

[0005] On the one hand, the present invention proposes a procurement risk management method based on AI technology, which is used to manage enterprise procurement risks collected by a bidding intelligent supervision system. The method includes: Obtaining enterprise procurement related information collected by the bidding and tendering intelligent supervision system, including procurement documents, bidding documents, tender documents, supplier registration related behavior records and supplier basic information, bid evaluation expert basic information and bid evaluation report; Analyze the enterprise procurement related information to obtain key information related to procurement risks, and determine the corresponding risk name and risk level based on the key information and the risk information set in the preset risk type; When the risk level of one of the target risks is higher than the preset level threshold, the supervision authority is enabled and a supervision pop-up window is sent after receiving the supervision instruction. The supervision pop-up window is used to receive supervision suggestions for the risk and send the supervision suggestions to the corresponding target unit.

[0006] Furthermore, in the above-mentioned procurement risk management method based on AI technology, the steps of analyzing the enterprise procurement-related information to obtain key information related to procurement risks, and comparing the key information with the risk information set in the preset risk type to determine the corresponding risk name and risk level include: Obtain the risk types and corresponding procurement links of different risk names, and determine the target enterprise procurement-related information required based on the risk types and corresponding procurement links; Obtain the key elements described in the risk name, analyze the target company's procurement-related information, collect key information related to the key elements, and determine the risk name based on the comparison between the key information and the key elements.

[0007] Furthermore, in the above-mentioned procurement risk management method based on AI technology, the risk types include procedural risk, bidding risk, quotation risk, bid evaluation risk and associated risk; The procurement process includes registration, quotation, transaction and bid evaluation.

[0008] Furthermore, in the above-mentioned procurement risk governance method based on AI technology, when the risk level of one of the target risks is higher than the preset level threshold, the supervision authority is enabled and a supervision pop-up window is sent after receiving the supervision instruction, and the supervision pop-up window is used to receive supervision suggestions for the risk and send the supervision suggestions to the corresponding target unit. The step also includes: Obtain target enterprises with risks and use the target enterprises as entity nodes; Determine the attributes of the entity node according to the preset rules based on the number of risks of the target enterprise, and establish an enterprise risk relationship map based on the risk relationship between the entity node and the target enterprise; After receiving the supervision suggestions for the target risk, the enterprise risk relationship map is used to determine other target enterprises that are associated with the target unit in terms of the target risk, and the supervision suggestions are forwarded to the other target enterprises.

[0009] Furthermore, in the above-mentioned procurement risk governance method based on AI technology, the step of determining the attributes of the entity node according to the preset rules based on the risk quantity of the target enterprise, and establishing the enterprise risk relationship map based on the risk relationship between the entity node and the target enterprise includes: Obtain the number of procurement links involved in the target enterprise, and plan a concentric circle area composed of preset circular areas in sequence according to the number of procurement links as the entity node of the target enterprise; Obtain the number of risks of the target enterprise in different procurement links, and determine the size of each circular area according to the number of risks; The concentric circle areas corresponding to the procurement links where risks occur for target enterprises with risk relationships are connected by line segments, and the corresponding risk descriptions are attached to obtain an enterprise risk relationship map.

[0010] Furthermore, in the above-mentioned procurement risk governance method based on AI technology, after the step of connecting the concentric circle areas corresponding to the procurement links where the risks occur of the target enterprises with risk relationships through line segments and attaching the corresponding risk descriptions to obtain the enterprise risk relationship map, the step further includes: According to the enterprise risk relationship graph, multiple candidate entity nodes with risk quantities higher than a threshold are obtained respectively; Calculate the betweenness centrality and degree centrality of each procurement link in the candidate entity nodes respectively, and determine the risk value of each procurement link according to the betweenness centrality and degree centrality; Identify the target procurement links with risk values ​​greater than the preset values, and increase the risk level within the target procurement links to the preset level to enable supervision authority.

[0011] Furthermore, the above-mentioned procurement risk management method based on AI technology includes: The calculation formula of degree centrality is: ; The calculation formula for betweenness centrality is: ; The formula for calculating the risk value is: ; in, deg ( v ) represents the node of the procurement link v The degree indicates how many edges are directly connected to other procurement links. σ ( s,t ) represents the node of the procurement link s To the point of procurement t The number of shortest paths, σ ( s,t ∣ v ): Node in the procurement process v From the node s in the procurement process to the node in the procurement process t The number of occurrences in the shortest path between w 1 and w 2 are the weight coefficients of degree centrality and betweenness centrality respectively.

[0012] Another object of the present invention is to provide a procurement risk management system based on AI technology, which is used to manage enterprise procurement risks collected by a bidding intelligent supervision system, and the system includes: An acquisition module is used to obtain enterprise procurement related information collected by the bidding and tendering intelligent supervision system, wherein the enterprise procurement related information includes procurement documents, bidding documents, tender documents, supplier registration related behavior records and supplier basic information, bid evaluation expert basic information and bid evaluation report; An analysis module is used to analyze the enterprise procurement-related information to obtain key information related to procurement risks, and determine the corresponding risk name and risk level according to the comparison between the key information and the risk information set in the preset risk type; The supervision module is used to enable supervision authority and send a supervision pop-up window after receiving the supervision instruction when the risk level of one of the target risks is higher than the preset level threshold. The supervision pop-up window is used to receive supervision suggestions for the risk and send the supervision suggestions to the corresponding target unit.

[0013] Another object of the present invention is to provide a readable storage medium having a computer program stored thereon, wherein the program implements the steps of the above method when executed by a processor.

[0014] Another object of the present invention is to provide an electronic device, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor implements the steps of the above method when executing the program.

[0015] The present invention obtains enterprise procurement related information collected by the bidding and tendering intelligent supervision system; analyzes enterprise procurement related information to obtain key information related to procurement risks, and determines the corresponding risk name and risk level by comparing the key information with the risk information set in the preset risk type; when the risk level of one of the target risks is higher than the preset level threshold, the supervision authority is enabled and a supervision pop-up window is sent after receiving the supervision instruction, and the supervision pop-up window is used to receive supervision suggestions for the risk and send the supervision suggestions to the corresponding target unit. Different risk levels are set, and the supervision mechanism is used to supervise high-risk risks, and low-risk risks do not need to be supervised, so as to achieve accurate risk management and avoid the waste of resources caused by a unified supervision strategy. The problem of poor accuracy in procurement risk management in the prior art is solved. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 This is a flowchart of a procurement risk management method based on AI technology in the first embodiment of the present invention; Figure 2 This is a structural block diagram of a procurement risk management system based on AI technology in the third embodiment of the present invention.

[0017] The following specific implementation manner will further illustrate the present invention in conjunction with the above-mentioned drawings. DETAILED DESCRIPTION

[0018] In order to facilitate the understanding of the present invention, the present invention will be described more fully below with reference to the relevant drawings. Several embodiments of the present invention are given in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive.

[0019] It should be noted that when an element is referred to as being "fixed to" another element, it may be directly on the other element or there may be a central element. When an element is considered to be "connected to" another element, it may be directly connected to the other element or there may be a central element at the same time. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are for illustrative purposes only.

[0020] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which the present invention belongs. The terms used herein in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more of the related listed items.

[0021] Embodiment 1 See also Figure 1 , shown is a procurement risk management method based on AI technology in the first embodiment of the present invention, which is used to manage enterprise procurement risks collected by a bidding intelligent supervision system, and the method includes steps S10 to S12.

[0022] Step S10, obtaining the enterprise procurement related information collected by the bidding and tendering intelligent supervision system, wherein the enterprise procurement related information includes procurement documents, bidding documents, tender documents, supplier registration related behavior records and supplier basic information, evaluation expert basic information and evaluation report.

[0023] Among them, the intelligent bidding and tendering supervision system is a platform for supervising behaviors, data and other information in the enterprise procurement process. It is a management system based on modern information technology, especially big data, cloud computing, artificial intelligence and other technologies. It can collect relevant information about enterprise procurement from all aspects of enterprise procurement. Based on these data, the enterprise's procurement process can be supervised and risks can be discovered in a timely manner. Specifically, enterprise procurement-related information includes procurement documents, bidding documents, tender documents, supplier registration-related behavior records and supplier basic information, evaluation expert basic information and evaluation reports, etc.

[0024] Step S11, analyzing the enterprise procurement related information to obtain key information related to procurement risks, and determining the corresponding risk name and risk level based on the key information and the risk information set in the preset risk type.

[0025] Among them, these data can be analyzed and mined to obtain key information related to risks. Relevant risk types are pre-established within the system, including procedural risks, bidding risks, quotation risks, evaluation risks and associated risks. Each risk type has different risk names, which represent different risks, such as "the bidding announcement period is too short" and "too many project failures". Each different risk name has corresponding judgment rules and detailed risk information, that is, when what conditions are met, there is a corresponding risk. The collected key information can be compared with the set risk information in the risk type to determine whether there is a risk at present. Specifically, NLP technology can be used to automatically parse text content, such as bidding announcements, bids, etc., to extract key information. Structured data can also be actively entered according to the established risks, that is, what data is needed for risk judgment, and the corresponding data is actively entered and input into the system for management and control.

[0026] In addition, in some optional embodiments of the present invention, the step of analyzing the enterprise procurement-related information to obtain key information related to procurement risks, and determining the corresponding risk name and risk level according to the key information compared with the risk information set in the preset risk type includes: Obtain the risk types and corresponding procurement links of different risk names, and determine the target enterprise procurement-related information required based on the risk types and corresponding procurement links; Obtain the key elements described in the risk name, analyze the target company's procurement-related information, collect key information related to the key elements, and determine the risk name based on the comparison between the key information and the key elements.

[0027] Among them, in order to obtain the key information of risk governance that may be involved in the enterprise procurement process in a targeted and efficient manner, different risk types are divided for different risks. Different procurement links are divided under each risk type according to the links where risks occur, such as the registration link, quotation link, transaction link and bid evaluation link. Specific risk names are divided under the procurement link. Therefore, according to the procurement link and risk type where the risk name is located, it is possible to quickly locate and determine which data of enterprise procurement these key information can be obtained from. For example, when one of the risk names is "the expert score difference is large", it is in the bid evaluation risk of the bid evaluation link. Therefore, it can be determined that the key information used to judge whether the expert score difference is large comes from the "bid evaluation report" file, and the bid evaluation report can be accurately analyzed to obtain the key information required for risk name determination, and finally the final risk result is determined, specifically, including the specific name of the risk and the risk level. Among them, the risk level is pre-determined by the system based on experience and actual conditions, that is, each risk name is assigned a different risk level, which can include low risk, medium risk and high risk.

[0028] Step S12, when the risk level of one of the target risks is higher than the preset level threshold, the supervision authority is enabled and a supervision pop-up window is sent after receiving the supervision instruction. The supervision pop-up window is used to receive supervision suggestions for the risk and send the supervision suggestions to the corresponding target unit.

[0029] Among them, the preset level threshold is set to high risk. When there is a high risk, the supervision authority can be enabled in the display interface inside the system. After enabling the supervision authority, the corresponding supervision pop-up window can be sent by clicking on the supervision instruction. Through the supervision pop-up window, relevant personnel can supervise the risk, that is, send the supervision suggestions to the relevant responsible units.

[0030] In summary, the procurement risk management method based on AI technology in the above embodiment of the present invention obtains enterprise procurement related information collected by the bidding and tendering intelligent supervision system; analyzes enterprise procurement related information to obtain key information related to procurement risks, and determines the corresponding risk name and risk level based on the key information and the risk information set in the preset risk type; when the risk level of one of the target risks is higher than the preset level threshold, the supervision authority is enabled and a supervision pop-up window is sent after receiving the supervision instruction. The supervision pop-up window is used to receive supervision suggestions for the risk and send the supervision suggestions to the corresponding target unit. Different risk levels are set, and the supervision mechanism is used to supervise high-risk risks. Low-risk risks do not need to be supervised, so as to achieve accurate risk management and avoid the waste of resources caused by unified supervision strategies. The problem of poor accuracy in procurement risk management in the prior art is solved.

[0031] Embodiment 2 This embodiment also proposes a procurement risk management method based on AI technology. The difference between the procurement risk management method based on AI technology in this embodiment and the procurement risk management method based on AI technology in the first embodiment is that: When the risk level of one of the target risks is higher than the preset level threshold, the supervision authority is enabled and a supervision pop-up window is sent after receiving the supervision instruction, wherein the supervision pop-up window is used to receive supervision suggestions for the risk and send the supervision suggestions to the corresponding target unit, and the step further includes: Obtain target enterprises with risks and use the target enterprises as entity nodes; Determine the attributes of the entity node according to the preset rules based on the number of risks of the target enterprise, and establish an enterprise risk relationship map based on the risk relationship between the entity node and the target enterprise; After receiving the supervision suggestions for the target risk, the enterprise risk relationship map is used to determine other target enterprises that are associated with the target unit in terms of the target risk, and the supervision suggestions are forwarded to the other target enterprises.

[0032] Among them, in order to more intuitively display the risks faced by enterprises during procurement and analyze the potential risk relationships between enterprises, an enterprise risk relationship map is constructed. Specifically, after the target enterprises with risks have been monitored in advance, these enterprises are obtained and used as entity nodes, and an enterprise risk relationship map is established based on the risk relationships between enterprises. It should be noted that some of the risks of enterprise procurement are related to other enterprises. For example, "enterprises use the same equipment to bid" and "use the same IP to register". These risks that require at least two enterprises to form can be considered as risk relationships between enterprises, and then an enterprise risk relationship map is established based on this risk relationship and enterprise entity nodes.

[0033] In addition, since risks are displayed in the form of a list, after the enterprise risk relationship map is established, in order to efficiently execute supervision, after receiving supervision suggestions for high-risk target risks, the enterprise risk relationship map is used to determine other target enterprises that are associated with the target unit in terms of target risks. That is, when the target risk involves multiple enterprises, when one of the enterprises is found to send supervision suggestions, it will automatically be linked to other target enterprises and forward the supervision suggestions.

[0034] In addition, in some optional embodiments of the present invention, the step of determining the attributes of the entity node according to the preset rules based on the risk quantity of the target enterprise, and establishing the enterprise risk relationship map according to the risk relationship between the entity node and the target enterprise includes: Obtain the number of procurement links involved in the target enterprise, and plan a concentric circle area composed of preset circular areas in sequence according to the number of procurement links as the entity node of the target enterprise; Obtain the number of risks of the target enterprise in different procurement links, and determine the size of each circular area according to the number of risks; The concentric circle areas corresponding to the procurement links where risks occur for target enterprises with risk relationships are connected by line segments, and the corresponding risk descriptions are attached to obtain an enterprise risk relationship map.

[0035] Among them, the enterprise risk relationship map is further improved. Specifically, the factors of the number of risks of enterprises in different procurement links are taken into consideration. In the specific implementation, the same number of circular areas are determined according to the number of procurement links, that is, the types of procurement links. For example, if an enterprise has risks in the "registration link, quotation link, and transaction link", three circular areas are set. The three circular areas form a concentric circle area composed of circles of different sizes according to the order of the bidding process. According to the time sequence of the bidding process, it can be determined which circle is on the inside and which is on the outside. The size of each circular area is determined by the number of risks under the procurement link. The circular radius corresponding to the number can be found in the preset mapping table based on experience or big data analysis, so as to determine the radius of the circle according to the number. First, a circular area close to the center of the circle is determined, and then a second circular area is determined. In order to make each circular area distinguishable, the radius of the second circular area is determined. After mapping the radius, the radius of the previous center of the circle is added as the final radius. The circular area of ​​each procurement link in the entity node can be used as a procurement link sub-node under the entity node. Finally, the target enterprises with risk relationships are connected to obtain the enterprise risk relationship map.

[0036] Specifically, when making a connection, the location of the connection is determined based on the procurement link where the risk occurs. For example, if a certain risk relationship is generated in the "registration link" of two companies, the circular areas corresponding to the "registration links" of the two companies are connected by line segments.

[0037] In addition, in some optional embodiments of the present invention, in order to further improve the security of risk management, the enterprise's risks are deeply analyzed, and the risk level is adjusted by analyzing the properties of the enterprise risk relationship map. Specifically, multiple candidate entity nodes with risk quantities higher than the threshold are first determined, and the betweenness centrality and degree centrality of the nodes of the procurement link among the entity nodes are respectively determined. The risk value of each procurement link is determined according to the betweenness centrality and degree centrality. If the degree centrality of a procurement link is very high, it means that it has a direct risk relationship with multiple other links. It can be inferred that the link may be a core of risk transmission, or it itself bears greater risks. At this time, the risk level of the link should be increased. If the betweenness centrality of a procurement link is high, it means that it plays an important role in the shortest path between multiple procurement links. If a risk occurs in this link, it may spread rapidly to multiple other links, resulting in systemic risks. Therefore, it is necessary to focus on these nodes, combine degree centrality and betweenness centrality, and more comprehensively evaluate the risk coefficient. For example, a certain weight can be assigned to the degree centrality and betweenness centrality of each link, and a comprehensive risk index can be calculated.

[0038] Specifically, the calculation formula of degree centrality is: ; The calculation formula for betweenness centrality is: ; The formula for calculating the risk value is: ; in, deg ( v ) represents the node of the procurement link v The degree indicates how many edges are directly connected to other procurement links. σ ( s,t ) represents the node of the procurement link s To the point of procurement t The number of shortest paths, σ ( s,t ∣ v ) represents the node of the procurement link v From the node s in the procurement process to the node in the procurement process t The number of occurrences in the shortest path between w 1 and w 2 are the weight coefficients of degree centrality and betweenness centrality respectively.

[0039] In summary, the procurement risk management method based on AI technology in the above embodiment of the present invention obtains enterprise procurement related information collected by the bidding and tendering intelligent supervision system; analyzes enterprise procurement related information to obtain key information related to procurement risks, and determines the corresponding risk name and risk level based on the key information and the risk information set in the preset risk type; when the risk level of one of the target risks is higher than the preset level threshold, the supervision authority is enabled and a supervision pop-up window is sent after receiving the supervision instruction. The supervision pop-up window is used to receive supervision suggestions for the risk and send the supervision suggestions to the corresponding target unit. Different risk levels are set, and the supervision mechanism is used to supervise high-risk risks. Low-risk risks do not need to be supervised, so as to achieve accurate risk management and avoid the waste of resources caused by unified supervision strategies. The problem of poor accuracy in procurement risk management in the prior art is solved.

[0040] Embodiment 3 See also Figure 2 , shown is a procurement risk management system based on AI technology proposed in the third embodiment of the present invention, which is used to manage enterprise procurement risks collected by a bidding intelligent supervision system. The system includes: The acquisition module 100 is used to obtain the enterprise procurement related information collected by the bidding and tendering intelligent supervision system, and the enterprise procurement related information includes procurement documents, bidding documents, tender documents, supplier registration related behavior records and supplier basic information, bid evaluation expert basic information and bid evaluation report; Analysis module 200, used to analyze enterprise procurement-related information to obtain key information related to procurement risks, and determine corresponding risk names and risk levels based on the key information compared with risk information set in preset risk types; The supervision module 300 is used to enable supervision authority and send a supervision pop-up window after receiving the supervision instruction when the risk level of one of the target risks is higher than the preset level threshold. The supervision pop-up window is used to receive supervision suggestions for the risk and send the supervision suggestions to the corresponding target unit.

[0041] Furthermore, in the above-mentioned procurement risk management system based on AI technology, the steps of analyzing the enterprise procurement-related information to obtain key information related to procurement risks, and comparing the key information with the risk information set in the preset risk type to determine the corresponding risk name and risk level include: Obtain the risk types and corresponding procurement links of different risk names, and determine the target enterprise procurement-related information required based on the risk types and corresponding procurement links; Obtain the key elements described in the risk name, analyze the target company's procurement-related information, collect key information related to the key elements, and determine the risk name based on the comparison between the key information and the key elements.

[0042] Furthermore, in the above-mentioned procurement risk governance system based on AI technology, the risk types include procedural risk, bidding risk, quotation risk, bid evaluation risk and associated risk; The procurement process includes registration, quotation, transaction and bid evaluation.

[0043] Furthermore, in the procurement risk governance system based on AI technology, when the risk level of one of the target risks is higher than the preset level threshold, the supervision authority is enabled and a supervision pop-up window is sent after receiving the supervision instruction, and the supervision pop-up window is used to receive supervision suggestions for the risk and send the supervision suggestions to the corresponding target unit. The step also includes: Obtain target enterprises with risks and use the target enterprises as entity nodes; Determine the attributes of the entity node according to the preset rules based on the number of risks of the target enterprise, and establish an enterprise risk relationship map based on the risk relationship between the entity node and the target enterprise; After receiving the supervision suggestions for the target risk, the enterprise risk relationship map is used to determine other target enterprises that are associated with the target unit in terms of the target risk, and the supervision suggestions are forwarded to the other target enterprises.

[0044] Furthermore, in the above-mentioned procurement risk governance system based on AI technology, the step of determining the attributes of the entity node according to the preset rules based on the risk quantity of the target enterprise, and establishing the enterprise risk relationship map based on the risk relationship between the entity node and the target enterprise includes: Obtain the number of procurement links involved in the target enterprise, and plan a concentric circle area composed of preset circular areas in sequence according to the number of procurement links as the entity node of the target enterprise; Obtain the number of risks of the target enterprise in different procurement links, and determine the size of each circular area according to the number of risks; The concentric circle areas corresponding to the procurement links where risks occur for target enterprises with risk relationships are connected by line segments, and the corresponding risk descriptions are attached to obtain an enterprise risk relationship map.

[0045] Furthermore, in the above-mentioned procurement risk governance system based on AI technology, after the step of connecting the concentric circle areas corresponding to the procurement links where the risks occur of the target enterprises with risk relationships through line segments and attaching the corresponding risk descriptions to obtain the enterprise risk relationship map, the step further includes: According to the enterprise risk relationship graph, multiple candidate entity nodes with risk quantities higher than a threshold are obtained respectively; Calculate the betweenness centrality and degree centrality of each procurement link in the candidate entity nodes respectively, and determine the risk value of each procurement link according to the betweenness centrality and degree centrality; Identify the target procurement links with risk values ​​greater than the preset values, and increase the risk level within the target procurement links to the preset level to enable supervision authority.

[0046] Furthermore, the above-mentioned procurement risk management system based on AI technology, wherein: The calculation formula of degree centrality is: ; The calculation formula for betweenness centrality is: ; The formula for calculating the risk value is: ; in, deg ( v ) represents the node of the procurement link v The degree indicates how many edges are directly connected to other procurement links. σ ( s,t ) represents the node of the procurement link s To the point of procurement t The number of shortest paths, σ ( s,t ∣ v ) represents the node of the procurement link v From the node s in the procurement process to the node in the procurement process t The number of occurrences in the shortest path between w 1 and w 2 are the weight coefficients of degree centrality and betweenness centrality respectively.

[0047] The functions or operation steps implemented when the above modules are executed are substantially the same as those in the above method embodiments, and will not be repeated here.

[0048] Embodiment 4 Another aspect of the present invention further provides a readable storage medium having a computer program stored thereon, and when the program is executed by a processor, the steps of the method described in any one of the above-mentioned embodiments 1 to 2 are implemented.

[0049] Embodiment 5 Another aspect of the present invention provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and running on the processor, and when the processor executes the program, the steps of the method described in any one of the above-mentioned embodiments 1 to 2 are implemented.

[0050] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0051] Those skilled in the art will appreciate that the logic and / or steps represented in the flowchart or otherwise described herein, for example, may be considered as an ordered list of executable instructions for implementing logical functions, and may be specifically implemented in any computer-readable storage medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For purposes of this specification, a "computer-readable storage medium" may be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0052] More specific examples (a non-exhaustive list) of computer-readable storage media include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable storage medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0053] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or a combination thereof: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0054] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" 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 representation of the above terms does 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.

[0055] The above-mentioned embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

Claims

1. A procurement risk management method based on AI technology, characterized in that: Used to manage enterprise procurement risks collected by a bidding intelligent supervision system, the method includes: Obtaining enterprise procurement related information collected by the bidding and tendering intelligent supervision system, including procurement documents, bidding documents, tender documents, supplier registration related behavior records and supplier basic information, bid evaluation expert basic information and bid evaluation report; Analyze the enterprise procurement related information to obtain key information related to procurement risks, and determine the corresponding risk name and risk level based on the key information and the risk information set in the preset risk type; When the risk level of one of the target risks is higher than the preset level threshold, the supervision authority is enabled and a supervision pop-up window is sent after receiving the supervision instruction. The supervision pop-up window is used to receive supervision suggestions for the risk and send the supervision suggestions to the corresponding target unit.

2. The procurement risk management method based on AI technology according to claim 1 is characterized in that: The step of analyzing the enterprise procurement related information to obtain key information related to procurement risks, and comparing the key information with the risk information set in the preset risk type to determine the corresponding risk name and risk level includes: Obtain the risk types and corresponding procurement links of different risk names, and determine the target enterprise procurement-related information required based on the risk types and corresponding procurement links; Obtain the key elements described in the risk name, analyze the target company's procurement-related information, collect key information related to the key elements, and determine the risk name based on the comparison between the key information and the key elements.

3. The procurement risk management method based on AI technology according to claim 2 is characterized in that: The risk types include procedural risk, bidding risk, quotation risk, bid evaluation risk and associated risk; The procurement process includes registration, quotation, transaction and bid evaluation.

4. The procurement risk management method based on AI technology according to claim 3 is characterized in that: When the risk level of one of the target risks is higher than the preset level threshold, the supervision authority is enabled and a supervision pop-up window is sent after receiving the supervision instruction, wherein the supervision pop-up window is used to receive supervision suggestions for the risk and send the supervision suggestions to the corresponding target unit, and the step further includes: Obtain target enterprises with risks and use the target enterprises as entity nodes; Determine the attributes of the entity node according to the preset rules based on the number of risks of the target enterprise, and establish an enterprise risk relationship map based on the risk relationship between the entity node and the target enterprise; After receiving the supervision suggestions for the target risk, the enterprise risk relationship map is used to determine other target enterprises that are associated with the target unit in terms of the target risk, and the supervision suggestions are forwarded to the other target enterprises.

5. The procurement risk management method based on AI technology according to claim 4 is characterized in that: The step of determining the attributes of the entity node according to the preset rules based on the risk quantity of the target enterprise, and establishing the enterprise risk relationship map based on the risk relationship between the entity node and the target enterprise includes: Obtain the number of procurement links involved in the target enterprise, and plan a concentric circle area composed of preset circular areas in sequence according to the number of procurement links as the entity node of the target enterprise; Obtain the number of risks of the target enterprise in different procurement links, and determine the size of each circular area according to the number of risks; The concentric circle areas corresponding to the procurement links where risks occur for target enterprises with risk relationships are connected by line segments, and the corresponding risk descriptions are attached to obtain an enterprise risk relationship map.

6. The procurement risk management method based on AI technology according to claim 5 is characterized in that: After the step of connecting the concentric circle areas corresponding to the procurement link where the risk occurs for the target enterprise with risk relationship through line segments and attaching the corresponding risk description to obtain the enterprise risk relationship map, the step further includes: According to the enterprise risk relationship graph, multiple candidate entity nodes with risk quantities higher than a threshold are obtained respectively; Calculate the betweenness centrality and degree centrality of each procurement link in the candidate entity nodes respectively, and determine the risk value of each procurement link according to the betweenness centrality and degree centrality; Identify the target procurement links with risk values ​​greater than the preset values, and increase the risk level within the target procurement links to the preset level to enable supervision authority.

7. The procurement risk management method based on AI technology according to claim 6 is characterized in that: The calculation formula of degree centrality is: ； The calculation formula for betweenness centrality is: ； The formula for calculating the risk value is: ； in, deg ( v ) represents the node of the procurement link v The degree indicates how many edges are directly connected to other procurement links. σ ( s,t ) represents the node of the procurement link s To the point of procurement t The number of shortest paths, σ ( s,t ∣ v ) represents the node of the procurement link v From the node s in the procurement process to the node in the procurement process t The number of occurrences in the shortest path between w 1 and w 2 are the weight coefficients of degree centrality and betweenness centrality respectively.

8. A procurement risk management system based on AI technology, characterized in that: Used to manage corporate procurement risks collected by a bidding and tendering intelligent supervision system, the system includes: An acquisition module is used to obtain enterprise procurement related information collected by the bidding and tendering intelligent supervision system, wherein the enterprise procurement related information includes procurement documents, bidding documents, tender documents, supplier registration related behavior records and supplier basic information, bid evaluation expert basic information and bid evaluation report; An analysis module is used to analyze the enterprise procurement-related information to obtain key information related to procurement risks, and determine the corresponding risk name and risk level according to the comparison between the key information and the risk information set in the preset risk type; The supervision module is used to enable supervision authority and send a supervision pop-up window after receiving the supervision instruction when the risk level of one of the target risks is higher than the preset level threshold. The supervision pop-up window is used to receive supervision suggestions for the risk and send the supervision suggestions to the corresponding target unit.

9. A readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

10. An electronic device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and running on the processor, wherein the processor implements the steps of the method according to any one of claims 1 to 7 when executing the program.

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