Project scoring method and device, electronic equipment and storage medium

Abstract

The invention relates to the technical field of project scoring, in particular to a project scoring method and device, electronic equipment and a storage medium. According to the scheme provided by the invention, the method comprises the steps: obtaining to-be-scored project information, wherein the to-be-scored project information comprises a plurality of bidding units and a plurality of scoring detailed rules of a project; based on the to-be-scored item information, a scoring precondition is set according to a preset template, and the scoring precondition is used for specifying a scoring requirement of the to-be-scored item; determining a plurality of score points corresponding to each score detailed rule through a preset semantic analysis model based on the plurality of score detailed rules; acquiring actual scores of the experts on the plurality of bidding units; determining a calibration score based on the actual score and a plurality of score points corresponding to each score detailed rule; and determining a final score of each bidding unit based on the calibration score and the scoring precondition. According to the method, errors can be effectively recognized and corrected according to the scoring conditions of experts, and the accuracy and transparency of the bid evaluation process are ensured to be improved.

Description

Technical Field

[0001] The present application relates to the technical field of project scoring, and in particular to a project scoring method, a scoring device, an electronic device and a storage medium. Background Art

[0002] In the traditional bidding and evaluation process, since it mainly relies on manual operation and judgment, it is inevitable that there will be problems such as scoring errors or calculation errors. These problems may be caused by various reasons such as negligence, fatigue, differences in comprehension ability or lack of professional skills of the evaluators. Problems such as scoring errors or calculation errors may affect the fairness of the evaluation results. If some bidders are underestimated or overestimated due to errors, the fairness of the entire bidding process will be questioned. Errors in the evaluation results may lead to unnecessary disputes between the bidding parties. These disputes may not only take a lot of time and energy to resolve, but may also cause economic losses and reputation damage to both parties.

[0003] To improve the accuracy of the bid evaluation process, there needs to be an effective way to identify problems such as scoring errors or calculation errors. Once errors are identified, there also needs to be a mechanism to correct them. This may involve steps such as re-scoring, adjusting calculations, or re-evaluating.

[0004] Therefore, in the bidding and evaluation process, how to effectively identify and correct these errors and improve the accuracy and transparency of the evaluation process has become a problem that needs to be solved urgently. Summary of the invention

[0005] The present application provides a project scoring method, scoring device, electronic device and storage medium to effectively identify and correct scoring errors in the bidding evaluation process and improve the accuracy and transparency of the evaluation process.

[0006] In a first aspect, an embodiment of the present application provides a project scoring method, the method comprising: obtaining information of projects to be scored, the information of projects to be scored comprising multiple scoring criteria for multiple bidding units and projects; based on the information of projects to be scored, setting scoring preconditions according to a preset template, the scoring preconditions being used to specify scoring requirements for the projects to be scored; based on the multiple scoring criteria, determining multiple score points corresponding to each scoring criterion through a preset semantic analysis model; obtaining actual scores of the multiple bidding units by experts; determining a calibration score based on the actual scores and the multiple score points corresponding to the each scoring criterion; and determining a final score for each bidding unit based on the calibration score and the scoring preconditions.

[0007] In a possible implementation, the preset template includes: project number, project name, supplier, business score calculation method, review comments, minimum score value, purchaser number and the number of suppliers displayed.

[0008] In a possible implementation, the determining of the multiple score points corresponding to each scoring criterion through a preset semantic analysis model based on the multiple scoring criterion includes: determining the standard of each scoring criterion and the preliminary value corresponding to the standard through a preset semantic analysis model based on the multiple scoring criterion; determining the multiple score points corresponding to each scoring criterion based on the standard of each scoring criterion, the preliminary value corresponding to the standard and the preset maximum value and preset minimum value corresponding to each scoring criterion.

[0009] In a possible implementation, the determining of the multiple score points corresponding to each scoring criterion based on the criteria of each scoring criterion, the preliminary values ​​corresponding to the criteria, and the preset maximum and minimum values ​​corresponding to each scoring criterion includes: judging whether the preliminary values ​​corresponding to the criteria are repeated based on the criteria of each scoring criterion and the preliminary values ​​corresponding to the criteria; if repeated, marking the repeated preliminary values ​​to prompt manual modification, and determining the modified preliminary values; and determining the multiple score points corresponding to each scoring criterion based on the modified preliminary values ​​and the preset maximum and minimum values.

[0010] In one possible implementation, determining the calibration score based on the actual score and multiple score points corresponding to the various scoring criteria includes: determining whether the actual score has a corresponding score point; if the actual score does not have a corresponding score point, prompting the corresponding scorer to make modifications to determine the calibration score.

[0011] In one possible implementation, determining the final score of each bidding unit based on the calibration score and the scoring precondition includes: based on the calibration score, determining the abnormal score in the calibration score by a preset algorithm; based on the abnormal score, prompting the scorer corresponding to the abnormal score to determine the final score; based on the final score and the scoring precondition, determining the final score of each bidding unit.

[0012] In a possible implementation, the preset algorithm is a Z-Score algorithm, and determining the abnormal scores in the calibration scores through the preset algorithm includes: obtaining the calibration scores of all experts for any scoring criterion of the same bidding unit; based on the calibration scores of all experts for any scoring criterion of the same bidding unit, determining the abnormal scores in the calibration scores through the Z-Score algorithm.

[0013] In a second aspect, an embodiment of the present application provides a project scoring device, which includes: an acquisition module for acquiring project information to be scored, wherein the project information to be scored includes multiple scoring criteria for multiple bidding units and projects; a processing module for setting scoring preconditions according to a preset template based on the project information to be scored, wherein the scoring preconditions are used to specify scoring requirements for the project to be scored; a determination module for determining, based on the multiple scoring criteria and through a preset semantic analysis model, a plurality of score points corresponding to each scoring criterion; the acquisition module is also used to acquire actual scores of the multiple bidding units by experts; the determination module is also used to determine a calibration score based on the actual score and the multiple score points corresponding to the each scoring criterion; the determination module is also used to determine the final score of each bidding unit based on the calibration score and the scoring precondition.

[0014] In a third aspect, an embodiment of the present application provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method described in the first aspect or any one of the implementation methods thereof is implemented.

[0015] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method described in the first aspect or any one of the implementation methods thereof is implemented.

[0016] The solution provided by the embodiment of the present application is as follows: obtaining information of the project to be scored, which includes multiple scoring rules for multiple bidding units and projects; setting scoring preconditions based on the information of the project to be scored according to a preset template, and the scoring preconditions are used to specify the scoring requirements of the project to be scored; determining multiple score points corresponding to each scoring rule through a preset semantic analysis model based on multiple scoring rules; obtaining the actual scores of the experts for multiple bidding units; determining the calibration scores based on the actual scores and multiple score points corresponding to each scoring rule; determining the final scores of each bidding unit based on the calibration scores and the scoring preconditions. Compared with the scoring errors or calculation errors that occur in the bid evaluation process in the prior art, the present application can effectively identify and correct these errors in the expert's scoring, ensuring the improvement of the accuracy and transparency of the bid evaluation process. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0018] Figure 1 A schematic diagram of a process flow of a project scoring method provided in one embodiment of the present application;

[0019] Figure 2 A schematic diagram of a preset template provided in an embodiment of the present application;

[0020] Figure 3 A structural block diagram of a project scoring device provided in one embodiment of the present application;

[0021] Figure 4 A schematic diagram of the structure of an electronic device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0022] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.

[0023] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, wholes, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or combinations thereof.

[0024] It should also be understood that the term “and / or” used in the specification and appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0025] As used in the specification and appended claims of this application, the term "if" can be interpreted as "when" or "uponce" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" can be interpreted as meaning "uponce it is determined" or "in response to determining" or "uponce [described condition or event] is detected" or "in response to detecting [described condition or event]", depending on the context.

[0026] In addition, in the description of the present application specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0027] References to "one embodiment" or "some embodiments" etc. described in the specification of this application mean that one or more embodiments of the present application include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the statements "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0028] For ease of understanding, the technical solution of the present application will be described in detail below with reference to the accompanying drawings.

[0029] Figure 1 This is a flowchart of a project scoring method provided in an embodiment of the present application. For the sake of convenience, only the part related to this embodiment is shown. The method provided in this embodiment includes the following steps:

[0030] S110, obtaining information of the project to be scored, where the information of the project to be scored includes multiple bidding units and multiple scoring rules of the project.

[0031] For example, a project may be bid by three or more bidding units; the scoring details may include: project service plan, supply capacity, service commitment, similar performance, etc.

[0032] S120, based on the information of the items to be rated, setting the rating preconditions according to a preset template, where the rating preconditions are used to specify the rating requirements of the items to be rated.

[0033] In a possible implementation, the preset template is as follows: Figure 2 As shown, the preset template includes: project number, project name, supplier, business score calculation method, review opinion, minimum score value, purchaser number, and number of suppliers displayed.

[0034] Furthermore, the preset template also includes: whether to implement price discounts, whether there are objective scores, whether non-group leaders are allowed to score objective scores, whether to allow viewing of total scores and rankings, and whether there are review comments.

[0035] For example, before scoring the bidders, it is first necessary to set the scoring preconditions for this bid evaluation through a preset template. The scoring preconditions are used to specify the scoring requirements for the items to be scored, and the final evaluation results are determined based on the scoring preconditions and the expert scores.

[0036] S130, based on the multiple scoring criteria, determine multiple score points corresponding to each scoring criterion through a preset semantic analysis model.

[0037] In a possible implementation, based on multiple scoring criteria, a preset semantic analysis model is used to determine multiple score points corresponding to each scoring criterion, including: based on multiple scoring criteria, a preset semantic analysis model is used to determine the standard of each scoring criterion and the preliminary value corresponding to the standard; based on the standard of each scoring criterion, the preliminary value corresponding to the standard and the preset maximum value and preset minimum value corresponding to each scoring criterion, multiple score points corresponding to each scoring criterion are determined.

[0038] In a possible implementation, based on the standards of each scoring criterion, the preliminary values ​​corresponding to the standards, and the preset maximum and minimum values ​​corresponding to each scoring criterion, determining multiple score points corresponding to each scoring criterion includes: based on the standards of each scoring criterion and the preliminary values ​​corresponding to the standards, judging whether the preliminary values ​​corresponding to the standards are repeated; if repeated, marking the repeated preliminary values, prompting manual modification, and determining the modified preliminary values; based on the modified preliminary values ​​and the preset maximum and minimum values, determining multiple score points corresponding to each scoring criterion.

[0039] For example, taking the "service commitment" in the scoring rules as an example, the content of the service commitment is: "Comprehensive evaluation is conducted based on the service commitments (service response, quality assurance measures and emergency plans, etc.) provided by each bidding unit: 1. 20 points will be awarded for complete commitments to all indicators proposed in the bidding requirements and a self-penalty commitment; 2. 17 points will be awarded for complete commitments to all indicators proposed in the bidding requirements without self-penalty measures; 3. 12 points will be awarded for omissions in the commitments to all indicators proposed in the bidding requirements; 4. 5 points will be awarded for vague or major omissions in the commitments to all indicators proposed in the bidding requirements."

[0040] Furthermore, based on the service commitment content in the scoring criteria, the preset semantic analysis model extracts preliminary values ​​"20, 17, 12, 5".

[0041] Furthermore, when the preset semantic analysis model extracts errors, for example: the extracted preliminary values ​​are "20, 20, 12, 5", that is, there are repeated scores in the preliminary values ​​of the extraction layer, the repeated preliminary values ​​will be marked and prompted for manual modification. The user will make modifications based on the prompts and determine the modified preliminary values.

[0042] Furthermore, based on the modified preliminary value, determine whether the modified preliminary value is within the range of the preset maximum value and the preset minimum value. For example, the preset maximum value of the service commitment is 20, and the preset minimum value is 5. Then determine whether the modified preliminary values ​​are all within the range of 5 and 20. If they are within the range of 5 and 20, determine the multiple score points corresponding to each scoring criterion; if they are not within the range of 5 and 20, prompt manual modification, and the user makes modifications according to the prompt to determine the multiple score points corresponding to each scoring criterion.

[0043] S140, obtaining the actual scores given by experts to the multiple bidding units.

[0044] Exemplarily, the experts score each bidder according to the scoring criteria.

[0045] S150, determining a calibration score based on the actual score and multiple score points corresponding to each scoring criterion.

[0046] In one possible implementation, determining the calibration score based on the actual score and multiple score points corresponding to each scoring criterion includes: determining whether the actual score has a corresponding score point; if the actual score does not have a corresponding score point, prompting the corresponding scorer to make modifications to determine the calibration score.

[0047] Exemplarily, the experts score each bidding unit according to the scoring criteria. If the expert's score is not the score point corresponding to the scoring criteria, for example: the score points for the service commitment are "20, 17, 12, 5", but the expert scores "15", then the expert's score is not the score point corresponding to the service commitment. Therefore, the corresponding scoring personnel (experts) are prompted to make modifications to determine the calibration score.

[0048] S160, determining the final score of each bidding unit based on the calibration score and scoring preconditions.

[0049] In one possible implementation, the final score of each bidding unit is determined based on the calibration score and the scoring preconditions, including: based on the calibration score, determining the abnormal score in the calibration score through a preset algorithm; based on the abnormal score, prompting the scorers corresponding to the abnormal score to determine the final score; based on the final score and the scoring preconditions, determining the final score of each bidding unit.

[0050] In one possible implementation, the preset algorithm is a Z-Score algorithm, and determining abnormal scores in the calibration scores through the preset algorithm includes: obtaining the calibration scores of all experts for any scoring criterion of the same bidding unit; based on the calibration scores of all experts for any scoring criterion of the same bidding unit, determining abnormal scores in the calibration scores through the Z-Score algorithm.

[0051] Exemplarily, after the experts have finished scoring each scoring criterion of each bidding unit, the system summarizes the calibration scores of all experts, performs score calibration on the scores of the same scoring criterion of the same bidding unit, and determines abnormal scores in the calibration scores.

[0052] Specifically, if the four experts score "20, 20, 20, 5" for the scoring criterion of Bidder 1's service commitment respectively, the Z-Score algorithm will determine that the score "5" is an abnormal score in the calibration score. The system will then prompt the expert who scored the calibration score "5" to confirm whether the final score is correct, and determine the final score based on the expert's confirmation or modification.

[0053] Furthermore, the final score of each bidding unit is determined based on the final score and scoring preconditions.

[0054] The solution provided by the embodiment of the present application is as follows: obtaining information of the project to be scored, which includes multiple scoring rules for multiple bidding units and projects; setting scoring preconditions based on the information of the project to be scored according to a preset template, and the scoring preconditions are used to specify the scoring requirements of the project to be scored; determining multiple score points corresponding to each scoring rule through a preset semantic analysis model based on multiple scoring rules; obtaining the actual scores of the experts for multiple bidding units; determining the calibration scores based on the actual scores and multiple score points corresponding to each scoring rule; determining the final scores of each bidding unit based on the calibration scores and the scoring preconditions. Compared with the scoring errors or calculation errors that occur in the bid evaluation process in the prior art, the present application can effectively identify and correct these errors in the expert's scoring, ensuring the improvement of the accuracy and transparency of the bid evaluation process.

[0055] Figure 3 This is a structural block diagram of a project scoring device provided in an embodiment of the present application. For the sake of convenience, only the part related to the embodiment of the present application is shown. Figure 3 The project scoring device 300 may include: an acquisition module 301 , a processing module 302 , and a determination module 303 .

[0056] An acquisition module 301 is used to acquire information of projects to be scored, wherein the information of projects to be scored includes multiple scoring rules of multiple bidding units and projects;

[0057] A processing module 302 is used to set scoring preconditions according to a preset template based on the information of the project to be scored, wherein the scoring preconditions are used to specify scoring requirements for the project to be scored;

[0058] A determination module 303 is used to determine a plurality of score points corresponding to each scoring criterion based on the plurality of scoring criterions by using a preset semantic analysis model;

[0059] The acquisition module 301 is further used to obtain the actual scores given by the experts to the multiple bidding units;

[0060] The determination module 303 is further used to determine a calibration score based on the actual score and a plurality of score points corresponding to each scoring rule;

[0061] The determination module 303 is further used to determine the final score of each bidding unit based on the calibration score and the scoring precondition.

[0062] The scheme provided by the project scoring device of the present application is as follows: an acquisition module 301 is used to acquire information of the project to be scored, and the information of the project to be scored includes multiple scoring rules for multiple bidding units and projects; a processing module 302 is used to set scoring preconditions according to a preset template based on the information of the project to be scored, and the scoring preconditions are used to specify the scoring requirements of the project to be scored; a determination module 303 is used to determine multiple score points corresponding to each scoring rule through a preset semantic analysis model based on multiple scoring rules; the acquisition module 301 is also used to acquire the actual scores of multiple bidding units by experts; the determination module 303 is also used to determine the calibration score based on the actual score and multiple score points corresponding to each scoring rule; the determination module 303 is also used to determine the final score of each bidding unit based on the calibration score and the scoring precondition. The present application can effectively identify and correct these errors in the expert's scoring, ensuring the improvement of the accuracy and transparency of the bid evaluation process.

[0063] It should be noted that the information interaction, execution process, etc. between the above-mentioned devices / units are based on the same concept as the method embodiment of the present application. Their specific functions and technical effects can be found in the method embodiment part and will not be repeated here.

[0064] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0065] Figure 4 This is a schematic diagram of the structure of an electronic device provided by an embodiment of the present application. Figure 4 As shown, the electronic device 4 of this embodiment includes: at least one processor 40 ( Figure 4 Only one is shown in the figure), a memory 41, and a computer program 42 stored in the memory 41 and executable on at least one processor 40, the processor 40 executes the computer program 42 to implement the above Figure 1 The steps in the method embodiment, or the implementation of the above Figure 3 Functions of each module / unit in the device embodiment.

[0066] The electronic device 4 may be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The electronic device 4 may include but is not limited to a processor 40 and a memory 41. Those skilled in the art will appreciate that Figure 4 It is only an example of the electronic device 4 and does not constitute a limitation on the electronic device 4. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, it may also include input and output devices, network access devices, etc.

[0067] The processor 40 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0068] In some embodiments, the memory 41 may be an internal storage unit of the electronic device 4, such as a hard disk or memory of the electronic device 4. In other embodiments, the memory 41 may also be an external storage device of the electronic device 4, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the electronic device 4. Further, the memory 41 may also include both an internal storage unit and an external storage device of the electronic device 4. The memory 41 is used to store an operating system, an application program, a boot loader (BootLoader), data, and other programs, such as program codes of a computer program. The memory 41 may also be used to temporarily store data that has been output or is to be output.

[0069] The embodiment of the present application further provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments can be implemented.

[0070] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, which can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include at least: any entity or device capable of carrying the computer program code to an electronic device, a recording medium, a computer memory, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), an electric carrier signal, a telecommunication signal, and a software distribution medium. For example, a USB flash drive, a mobile hard disk, a disk or an optical disk.

[0071] A computer-readable storage medium provided in an embodiment of the present application has the same beneficial effects as the above-mentioned project scoring method.

[0072] An embodiment of the present application provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments can be implemented.

[0073] A computer program product provided in an embodiment of the present application has the same beneficial effects as the above-mentioned project scoring method.

[0074] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0075] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0076] In the embodiments provided in the present application, it should be understood that the disclosed devices / electronic devices and methods can be implemented in other ways. For example, the device / electronic device embodiments described above are merely schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0077] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0078] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A project scoring method, characterized in that: The method comprises: Acquire information of the project to be scored, wherein the information of the project to be scored includes multiple scoring rules for multiple bidding units and projects; Based on the information of the project to be rated, setting a rating precondition according to a preset template, wherein the rating precondition is used to specify the rating requirements of the project to be rated; Based on the multiple scoring criteria, a plurality of score points corresponding to each scoring criterion are determined by a preset semantic analysis model; Obtaining the actual scores given by the experts to the multiple bidding units; Determine a calibration score based on the actual score and multiple score points corresponding to each scoring rule; Based on the calibration score and the scoring preconditions, the final score of each bidding unit is determined.

2. The method according to claim 1, characterized in that The step of determining the multiple score points corresponding to each scoring criterion based on the multiple scoring criterions by using a preset semantic analysis model includes: Based on the multiple scoring criteria, determining the criteria of each scoring criterion and the preliminary values ​​corresponding to the criteria through a preset semantic analysis model; Based on the standards of the various scoring criteria, the preliminary values ​​corresponding to the standards, and the preset maximum values ​​and preset minimum values ​​corresponding to the various scoring criteria, a plurality of score points corresponding to the various scoring criteria are determined.

3. The method according to claim 2, characterized in that Determining the multiple score points corresponding to each scoring rule based on the standard of each scoring rule, the preliminary value corresponding to the standard, and the preset maximum value and the preset minimum value corresponding to each scoring rule includes: Based on the standards of the scoring rules and the preliminary values ​​corresponding to the standards, determining whether the preliminary values ​​corresponding to the standards are repeated; If there are duplications, the repeated preliminary values ​​will be marked, prompting manual modification and confirming the modified preliminary values; Based on the modified preliminary value and the preset maximum value and the preset minimum value, a plurality of score points corresponding to each scoring criterion are determined.

4. The method according to claim 1, characterized in that: Determining the final score of each bidding unit based on the calibration score and the scoring preconditions includes: Based on the calibration scores, determining abnormal scores in the calibration scores by a preset algorithm; Based on the abnormal score, prompt the scorer corresponding to the abnormal score to determine the final score; Based on the final score and the scoring preconditions, the final score of each bidding unit is determined.

5. The method according to claim 4, characterized in that The preset algorithm is a Z-Score algorithm, and determining the abnormal score in the calibration score by using the preset algorithm includes: Obtain the calibration scores of all experts for any scoring criteria of the same bidding unit; Based on the calibrated scores of all the experts for any scoring criterion of the same bidding unit, the abnormal scores in the calibrated scores are determined through the Z-Score algorithm.

6. The method according to claim 1, characterized in that The preset template includes: project number, project name, supplier, business score calculation method, review opinion, minimum score value, purchaser number and the number of suppliers displayed.

7. The method according to claim 1, characterized in that Determining the calibration score based on the actual score and the multiple score points corresponding to the scoring criteria includes: Determine whether the actual score has a corresponding score point; If the actual score does not have a corresponding score point, the corresponding scorer is prompted to make modifications to determine the calibration score.

8. A project scoring device, characterized in that: The device comprises: An acquisition module is used to acquire information of projects to be scored, wherein the information of projects to be scored includes multiple scoring rules for multiple bidding units and projects; A processing module, configured to set scoring preconditions according to a preset template based on the information of the items to be scored, wherein the scoring preconditions are used to specify scoring requirements for the items to be scored; A determination module, configured to determine, based on the plurality of scoring criteria, a plurality of score points corresponding to each scoring criterion through a preset semantic analysis model; The acquisition module is further used to obtain the actual scores given by the experts to the multiple bidding units; The determination module is further configured to determine a calibration score based on the actual score and a plurality of score points corresponding to each of the scoring criteria; The determination module is also used to determine the final score of each bidding unit based on the calibration score and the scoring preconditions.

9. An electronic 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 method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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