CN115577691A - Bidding generation method, storage medium and electronic device - Google Patents
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Abstract
The application discloses a method for generating a bidding document, a storage medium and an electronic device, which relate to the technical field of information processing, and the method for generating the bidding document comprises the following steps: acquiring invitation mark demand information and first target portrait information; inputting the bidding demand information and the target portrait information into a pre-trained scheme generation model to obtain target product scheme information; inputting the product scheme information into a pre-trained bidding document generation model to obtain a target bidding document; the pre-trained scheme generation model is obtained by training an initial scheme generation model according to a training data set, and the pre-trained standard book generation model is obtained by training the initial standard book generation model according to a preset standard book making database and a preset standard book case library. The target product scheme information with better quality and higher bid rate is generated more intelligently and accurately, manpower resources are saved, and meanwhile, the bidding documents are generated accurately and efficiently.
Description
Technical Field
The present disclosure relates to the field of information processing technologies, and in particular, to a method for generating a bidding document, a storage medium, and an electronic device.
Background
With the high-speed development of economy in China and the gradual standardization of a market economy system, bidding plays an increasingly large role as a standardized market trading mode.
In the bidding process, the difficulty of manually analyzing the bidding demand information and the first party bidding characteristics is high, the quality of the manufactured product scheme is not high, and the subsequent bid rate is low; the process and format requirements for manually making the bidding document according to the product scheme are complex, the bidding document content is covered a lot, the cost of manpower resources for making the bidding document is high, and the making efficiency is low.
Therefore, it is an urgent need to provide a method for generating a bidding document with low manufacturing cost, high efficiency and high medium-standard rate.
Disclosure of Invention
The application provides a bid generation method, a storage medium and an electronic device, which are used for solving the defects that the bid rate is low in a product scheme manufactured through manual analysis, and the bid manufacturing cost and efficiency are high and low in manual manufacturing according to the product scheme in the prior art, and achieving the bid generation effects of low manufacturing cost, high efficiency and high bid rate.
The application provides a bid generation method, which comprises the following steps:
acquiring invitation mark demand information and first target portrait information;
inputting the bidding demand information and the first target portrait information into a pre-trained scheme generation model to obtain target product scheme information;
inputting the target product scheme information into a pre-trained bidding document generation model to obtain a target bidding document;
the pre-trained scheme generation model is obtained by training an initial scheme generation model according to a training data set, and the pre-trained standard book generation model is obtained by training the initial standard book generation model according to a preset standard book manufacturing database and a preset standard book case library.
According to the method for generating the bidding document, the training data set is obtained through the following steps:
acquiring a first target portrait information training sample, corresponding historical bidding demand information and a second target portrait information training sample;
desensitizing, screening and labeling the first target portrait information training sample, the historical bidding requirement information and the second target portrait information training sample to obtain the training data set.
According to the bidding document generation method, the first target portrait information training sample comprises purchasing habit information, payment period information and key person information;
the second target portrait information training sample comprises product information, industry preference information, bidding habit information and bid rate information.
According to the method for generating the standard book, the pre-trained scheme generation model is obtained through the following steps:
training a preset initial scheme generation model according to the training data set to obtain a first scheme generation model;
inputting a pre-acquired bidding requirement information verification sample and a first target portrait information verification sample into the first scheme generation model to obtain a first product scheme information sample;
and updating parameters of the first scheme generation model according to the first product scheme information sample and a first preset rule to obtain the scheme generation model.
According to the method for generating the bidding document, the bidding document making database and the bidding document case library are obtained through the following steps:
acquiring qualification certificate information, product data information and historical bidding document data of a target enterprise;
generating a bidding document making database according to the qualification certificate information and the product data information;
and generating a bidding case library according to the historical bidding data.
According to the method for generating the standard book, the pre-trained standard book generation model is obtained through the following steps:
training a preset initial standard generating model according to the standard making database and the standard case library to obtain a first standard generating model;
inputting a second product scheme information sample obtained in advance into the first bidding document generation model to obtain a bidding document sample;
and updating parameters of the first bidding document generation model according to the bidding document sample and a second preset rule to obtain the bidding document generation model.
According to the bidding document generation method provided by the application, the target product scheme information is input into a pre-trained bidding document generation model to obtain a target bidding document, and then the method further comprises the following steps:
obtaining the bidding result information of the target bidding document;
and updating the parameters of the scheme generation model and the parameters of the bidding document generation model according to the bidding result information.
The present application further provides a device for generating a bidding document, including:
the system comprises an acquisition unit, a display unit and a display unit, wherein the acquisition unit is used for acquiring bidding demand information and first target portrait information;
the generating unit is used for inputting the bidding demand information and the first target portrait information into a pre-trained scheme generating model to obtain target product scheme information; inputting the product scheme information into a pre-trained bidding document generation model to obtain a target bidding document;
the pre-trained scheme generation model is obtained by training an initial scheme generation model according to a training data set, and the pre-trained standard book generation model is obtained by training the initial standard book generation model according to a preset standard book making database and a preset standard book case library.
The present application further provides an electronic device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor is configured to implement the method for generating a bidding document according to any of the above methods by executing the computer program.
The present application further provides a computer-readable storage medium, which includes a stored program, wherein when the program is run, the program performs the method for generating the bidding document according to any one of the above methods.
The present application also provides a computer program product comprising a computer program which, when executed by a processor, implements the method of generating a bidding document as described in any of the above.
The bidding document generation method, the storage medium and the electronic device provided by the application train the initial scheme generation model according to the training data set to obtain the scheme generation model, input the bidding requirement information and the first target portrait information into the scheme generation model to obtain the target product scheme information, and compared with the product scheme manufactured by manually analyzing the bidding requirement information and the first target portrait bidding characteristics in the prior art, the method and the device realize more intelligent and accurate generation of the target product scheme information with better quality and higher bid rate. The initial standard generation model is trained according to the standard making database and the standard case library to obtain a standard generation model, and the target product scheme information is input into the standard generation model to obtain the target standard.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and together with the description, serve to explain the principles of the application.
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly described below, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.
FIG. 1 is a schematic flow chart of a method for generating a bidding document provided herein;
FIG. 2 is a schematic diagram of a bid generation process provided herein;
FIG. 3 is a schematic structural diagram of a bidding document generating apparatus provided in the present application;
fig. 4 is a schematic structural diagram of an electronic device provided in the present application.
Detailed Description
In order to make the technical solutions of the present application better understood by those skilled in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only some embodiments of the present application, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that the terms "first," "second," and the like in the description and claims of this application and in the accompanying drawings are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the application described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
The application provides a method for generating a bidding document, which comprises S11-S13 as shown in FIG. 1.
S11, acquiring bidding demand information and first target portrait information.
And S12, inputting the bidding demand information and the first target portrait information into a pre-trained scheme generation model to obtain target product scheme information.
And S13, inputting the target product scheme information into a pre-trained standard book generation model to obtain a target standard book.
The pre-trained scheme generation model is obtained by training an initial scheme generation model according to a training data set, and the pre-trained standard book generation model is obtained by training the initial standard book generation model according to a preset standard book manufacturing database and a preset standard book case library.
Specifically, the first target representation information may be information of bidding characteristics of a party (i.e., the first party) who issues a bidding request in bidding, and may include, but is not limited to, information of special requirements, purchasing habits, and payment periods.
In the embodiment of the application, the initial scheme generating model is trained according to the training data set to obtain the scheme generating model, the bid inviting demand information and the first target portrait information are input into the scheme generating model to obtain the target product scheme information, and compared with a product scheme manufactured by manually analyzing the bid inviting demand information and the first party bid inviting characteristics in the prior art, the method and the device can be used for intelligently and accurately generating the target product scheme information with better quality and higher bid rate. The initial standard generation model is trained according to the standard making database and the standard case library to obtain a standard generation model, and the target product scheme information is input into the standard generation model to obtain the target standard.
According to the method for generating the bidding document, the training data set is obtained through the following steps:
acquiring a first target portrait information training sample, corresponding historical bidding demand information and a second target portrait information training sample;
desensitizing, screening and labeling the first target portrait information training sample, the historical bidding requirement information and the second target portrait information training sample to obtain the training data set.
Specifically, in one example, the first target portrait information training sample may be information of relevant bidding characteristics of the first party in the historical bidding project. The historical bidding requirement information is the bidding requirement information of the historical bidding project. The second target portrait information training sample may be information related to a plurality of users or businesses involved in the bid. In order to ensure privacy security, desensitization is carried out on the first target portrait information training sample, the historical bidding requirement information and the second target portrait information training sample, and desensitization processing such as fuzzy processing or deletion is carried out on sensitive information in the first target portrait information training sample, the historical bidding requirement information and the second target portrait information training sample. And screening and labeling the information according to actual requirements to obtain a training data set.
Optionally, the first target portrait information training sample includes purchasing habit information, payment period information, and key person information; the second target portrait information training sample comprises product information, industry preference information, bidding habit information and bid rate information.
In the embodiment of the application, a training data set with high quality and safety and comprising a plurality of dimension information is obtained by obtaining a first target portrait information training sample, historical bidding demand information and a second target portrait information training sample and carrying out desensitization, screening and labeling on the training data set, so that a good data basis is provided for a subsequent training initial scheme generation model, and the subsequent training scheme generation model can be analyzed according to a plurality of dimensions to generate high-quality product scheme information.
According to the method for generating the standard book, the pre-trained scheme generation model is obtained through the following steps:
training a preset initial scheme generation model according to the training data set to obtain a first scheme generation model;
inputting a pre-acquired bidding requirement information verification sample and a first target portrait information verification sample into the first scheme generation model to obtain a first product scheme information sample;
and updating parameters of the first scheme generation model according to the first product scheme information sample and a first preset rule to obtain the scheme generation model.
Specifically, the initial scheme generation model is trained in a first stage according to a training data set, and parameters of the initial scheme generation model are optimized in the training process, so that the initial scheme generation model learns the capability of generating product scheme information, and the first scheme generation model is obtained.
Because the training data set is used for optimization during training, the training data and the data actually put into use have difference, and the accuracy of the product scheme information generated by the first scheme generation model under the actual use condition needs to be verified at the second stage.
Inputting a pre-acquired bidding demand information verification sample and a first target portrait information verification sample into a first scheme generation model to obtain a first product scheme information sample. The bidding requirement information verification sample and the first product scheme information verification sample are different from the training data set, and the training data set does not include the bidding requirement information verification sample and the first product scheme information verification sample.
And in the third stage, parameters of the first scheme generation model are further updated according to the first product scheme information sample and the first preset rule, so that the first scheme generation model can more accurately generate product scheme information to obtain a final scheme generation model.
In the embodiment of the application, the initial scheme generation model is trained through the training data set, so that the initial scheme generation model has the capability of generating product scheme information, and the first scheme generation model is obtained. And then verifying the first scheme generation model, inputting the first scheme generation model through the bidding requirement information verification sample and the first target portrait information verification sample to generate a first product scheme information sample, and then updating parameters of the first scheme generation model according to the first product scheme information sample and a first preset rule to complete verification and updating of the first scheme generation model, so that the robustness and accuracy of the first scheme generation model under the actual use condition are improved, and the final scheme generation model is obtained.
According to the method for generating the bidding document, the bidding document making database and the bidding document case database are obtained through the following steps:
acquiring qualification certificate information, product data information and historical bidding document data of a target enterprise;
generating a bidding document making database according to the qualification certificate information and the product data information;
and generating a bidding case library according to the historical bidding data.
Specifically, the qualification certificate information may include, but is not limited to, business licenses, quality management system certification, environment management system certification, occupational health safety management system, secure production licenses, high-tech enterprise certificates, patent certificates, honor award certificates, annual financial reports for audits, product detection capabilities, factory data, account opening licenses, credit certificates, trademark data, general taxpayer certificates, relationship certificates, and other information.
Product profile information may include, but is not limited to, product parameters, photographs, instructions for use, energy efficiency indicia, mandatory product certification certificates and test reports for the product.
And generating a bidding document making database according to the qualification certificate information and the product data information, and providing a data basis for the initial bidding document generation model generation bidding document generation model of the subsequent training through the bidding document making database. And generating a standard case library according to the historical standard data, and providing a data basis for writing rules of the initial standard learning historical standard for subsequent training through the standard case library.
In the embodiment of the application, the benchmarking database is generated according to the qualification certificate information and the product data information of the target enterprise, the benchmarking case library is generated according to the historical expression data, and the benchmarking database and the benchmarking case library enable a benchmarking generation model obtained through subsequent training to accurately and efficiently generate benchmarks.
According to the bidding document generation method provided by the application, the pre-trained bidding document generation model is obtained through the following steps:
training a preset initial standard generating model according to the standard making database and the standard case library to obtain a first standard generating model;
inputting a second product scheme information sample acquired in advance into the first bidding document generation model to obtain a bidding document sample;
and updating parameters of the first bidding document generation model according to the bidding document sample and a second preset rule to obtain the bidding document generation model.
Specifically, the initial standard generation model is trained in a first stage according to a standard making database and a standard case library, and parameters of the initial standard generation model are optimized in the training process, so that the initial standard generation model learns the writing rules of the historical standard, and the first standard generation model is obtained.
Due to the difference between the training situation and the actual use situation, the accuracy of the first bidding document generation model for generating the bidding document in the actual use situation needs to be verified in the second stage.
And inputting a second product scheme information sample obtained in advance into the first bidding document generation model to obtain a bidding document sample, wherein the second product scheme information sample can be consistent with or inconsistent with the first product scheme information sample.
And in the third stage, parameters of the first bidding document generation model are further updated according to the bidding document sample and a second preset rule, so that the first bidding document generation model can generate the bidding document more accurately to obtain a final bidding document generation model.
In the embodiment of the application, the initial bidding document generation model is trained through the bidding document making database and the bidding document case database so that the initial bidding document generation model learns the compiling rules of the historical bidding documents, and the first bidding document generation model is obtained. And then verifying the first bidding document generation model, inputting the second product scheme information sample into the first bidding document generation model to generate a bidding document sample, updating the parameters of the first bidding document generation model according to the bidding document sample and a second preset rule, completing verification and updating of the first bidding document generation model, improving the robustness and accuracy of the first bidding document generation model under the actual use condition, and obtaining the final bidding document generation model.
According to the bidding method provided by the application, after the step S13, the method further comprises:
and S14, obtaining the bidding result information of the target bidding document.
And S15, updating the parameters of the scheme generation model and the parameters of the bidding document generation model according to the bidding result information.
Specifically, in one example, after the target bidding document is delivered, the bidding result of the target bidding document can be continuously focused, and the bidding result information of the target bidding document can be obtained. And updating corresponding parameters according to the bidding result information analysis scheme generation model of the target bidding document and the aspect to be improved of the bidding document generation model.
In the embodiment of the application, the bidding result information of the target bidding document is obtained, the parameter of the scheme generation model and the parameter of the bidding document generation model are updated according to the bidding result information of the target bidding document, and the iterative upgrade of the scheme generation model and the bidding document generation model is realized, so that the generation of product scheme information with better quality and higher bid rate and the generation of more accurate bidding documents are realized through the scheme generation model and the bidding document generation model of the iterative upgrade.
According to one example of the above embodiments, as shown in fig. 2, the bidding document generation flow includes the following steps S201 to S211.
S201, bidding demand information and first target portrait information are obtained.
And S202, sending the bidding requirement information to an engineer.
S203, acquiring a first target portrait information training sample, corresponding historical bidding requirement information and a second target portrait information training sample to obtain a training data set.
And S204, training a preset initial scheme generation model according to the training data set to obtain a first scheme generation model.
S205, verifying the first scheme generation model, and updating parameters of the first scheme generation model according to the verification result and a preset rule to obtain the scheme generation model.
S206, inputting the bidding demand information and the first target portrait information into a scheme generation model to obtain target product scheme information.
S207, generating a standard making database and a standard case database.
S208, training a preset initial standard generation model according to the standard making database and the standard case library to obtain a first standard generation model.
S209, verifying the first bidding document generation model, and updating parameters of the first bidding document generation model according to the verification result and a preset rule to obtain the bidding document generation model.
And S210, inputting the target product scheme information into the standard book generation model to obtain the target standard book.
S211, obtaining the bidding result of the target bidding document, and updating the parameters of the scheme generation model and the parameters of the bidding document generation model according to the bidding result.
Specifically, the steps are already described in the foregoing embodiments, and are not described herein again. Step S201 may refer to step S11. Step S203 may refer to the aforementioned embodiment of obtaining the training data set. Steps S204-S205 may refer to embodiments of the previously described pre-trained solution generation model. Step S206 may refer to step S12. Step S207 may refer to the aforementioned embodiments for obtaining the bidding document production library and the bidding document case library. S208-S209 may refer to embodiments of the pre-trained benchmarking model previously described. Step S13 may be referred to as S210. Step S211 may refer to steps S14-S15.
The following describes the bidding document generating device provided in the present application, and the bidding document generating device described below and the bidding document generating method described above may be referred to correspondingly.
The present application also provides a bidding document generating apparatus, as shown in fig. 3, including:
an acquisition unit 31 for acquiring bidding demand information and first target portrait information;
the generating unit 32 is configured to input the bidding requirement information and the first target portrait information into a pre-trained scheme generation model to obtain target product scheme information; inputting the product scheme information into a pre-trained bidding document generation model to obtain a target bidding document;
the pre-trained scheme generation model is obtained by training an initial scheme generation model according to a training data set, and the pre-trained standard book generation model is obtained by training the initial standard book generation model according to a preset standard book making database and a preset standard book case library.
In the embodiment of the application, the initial scheme generating model is trained according to the training data set to obtain the scheme generating model, the bid inviting demand information and the first target portrait information are input into the scheme generating model to obtain the target product scheme information, and compared with a product scheme manufactured by manually analyzing the bid inviting demand information and the first party bid inviting characteristics in the prior art, the method and the device can be used for intelligently and accurately generating the target product scheme information with better quality and higher bid rate. The initial standard generation model is trained according to the standard making database and the standard case library to obtain a standard generation model, and the target product scheme information is input into the standard generation model to obtain the target standard.
According to the apparatus for generating a bidding document provided by the present application, the training data set is obtained by the following steps:
acquiring a first target portrait information training sample, corresponding historical bidding demand information and a second target portrait information training sample;
desensitizing, screening and labeling the first target portrait information training sample, the historical bidding requirement information and the second target portrait information training sample to obtain the training data set.
According to the bidding document generation device provided by the application, the first target portrait information training sample comprises purchasing habit information, payment period information and key person information;
the second target portrait information training sample comprises product information, industry preference information, bidding habit information and bid rate information.
According to the apparatus for generating a bidding document provided by the application, the pre-trained scheme generation model is obtained through the following steps:
training a preset initial scheme generation model according to the training data set to obtain a first scheme generation model;
inputting a pre-acquired bidding requirement information verification sample and a first target portrait information verification sample into the first scheme generation model to obtain a first product scheme information sample;
and updating parameters of the first scheme generation model according to the first product scheme information sample and a first preset rule to obtain the scheme generation model.
According to the bidding document generation device provided by the application, the bidding document making database and the bidding document case library are obtained through the following steps:
acquiring qualification certificate information, product data information and historical bidding document data of a target enterprise;
generating a bidding document making database according to the qualification certificate information and the product data information;
and generating a bidding case library according to the historical bidding data.
According to the bidding document generation device provided by the application, the pre-trained bidding document generation model is obtained through the following steps:
training a preset initial bidding document generation model according to the bidding document making database and the bidding document case library to obtain a first bidding document generation model;
inputting a second product scheme information sample obtained in advance into the first bidding document generation model to obtain a bidding document sample;
and updating parameters of the first bidding document generation model according to the bidding document sample and a second preset rule to obtain the bidding document generation model.
According to the bidding document generating apparatus provided by the present application, the generating unit 32 is further configured to:
obtaining the bidding result information of the target bidding document;
and updating the parameters of the scheme generation model and the parameters of the bidding document generation model according to the bidding result information.
Fig. 4 illustrates a physical structure diagram of an electronic device, which may include, as shown in fig. 4: a processor (processor) 410, a communication Interface 420, a memory (memory) 430 and a communication bus 440, wherein the processor 410, the communication Interface 420 and the memory 430 are communicated with each other via the communication bus 440. Processor 410 may invoke logic instructions in memory 430 to perform a method of benchmarking, the method comprising: acquiring bidding demand information and first target portrait information; inputting the bidding demand information and the first target portrait information into a pre-trained scheme generation model to obtain target product scheme information; inputting the target product scheme information into a pre-trained bidding document generation model to obtain a target bidding document; the pre-trained scheme generation model is obtained by training an initial scheme generation model according to a training data set, and the pre-trained standard book generation model is obtained by training the initial standard book generation model according to a preset standard book making database and a preset standard book case library.
In addition, the logic instructions in the memory 430 may be implemented in the form of software functional units and stored in a computer readable storage medium when the software functional units are sold or used as independent products. Based on such understanding, the technical solutions of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the methods described in the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
In another aspect, the present application further provides a computer program product, the computer program product includes a computer program, the computer program can be stored on a storage medium readable by a computer, when the computer program is executed by a processor, the computer can execute the execution bidding document generating method provided by the above methods, the method includes: acquiring invitation mark demand information and first target portrait information; inputting the bidding demand information and the first target portrait information into a pre-trained scheme generation model to obtain target product scheme information; inputting the target product scheme information into a pre-trained bidding document generation model to obtain a target bidding document; the pre-trained scheme generation model is obtained by training an initial scheme generation model according to a training data set, and the pre-trained standard book generation model is obtained by training the initial standard book generation model according to a preset standard book manufacturing database and a preset standard book case library.
In another aspect, the present application further provides a computer-readable storage medium, which includes a stored program, where the program executes the execution bidding document generating method provided by the foregoing methods, and the method includes: acquiring bidding demand information and first target portrait information; inputting the bidding demand information and the first target portrait information into a pre-trained scheme generation model to obtain target product scheme information; inputting the target product scheme information into a pre-trained bidding document generation model to obtain a target bidding document; the pre-trained scheme generation model is obtained by training an initial scheme generation model according to a training data set, and the pre-trained standard book generation model is obtained by training the initial standard book generation model according to a preset standard book manufacturing database and a preset standard book case library.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions in the embodiments of the present application.
Claims (10)
1. A method for generating a bidding document is characterized by comprising the following steps:
acquiring invitation mark demand information and first target portrait information;
inputting the bidding demand information and the first target portrait information into a pre-trained scheme generation model to obtain target product scheme information;
inputting the target product scheme information into a pre-trained bidding document generation model to obtain a target bidding document;
the pre-trained scheme generation model is obtained by training an initial scheme generation model according to a training data set, and the pre-trained standard book generation model is obtained by training the initial standard book generation model according to a preset standard book manufacturing database and a preset standard book case library.
2. The method of claim 1, wherein the training data set is obtained by:
acquiring a first target portrait information training sample, corresponding historical bidding demand information and a second target portrait information training sample;
desensitizing, screening and labeling the first target portrait information training sample, the historical bidding requirement information and the second target portrait information training sample to obtain the training data set.
3. The bidding document generating method according to claim 2, wherein the first target portrait information training sample includes purchasing habit information, payment period information, and key person information;
the second target portrait information training sample comprises product information, industry preference information, bidding habit information and bid rate information.
4. The method of claim 1, wherein the pre-trained solution generation model is obtained by:
training a preset initial scheme generation model according to the training data set to obtain a first scheme generation model;
inputting a pre-acquired bidding requirement information verification sample and a first target portrait information verification sample into the first scheme generation model to obtain a first product scheme information sample;
and updating parameters of the first scheme generation model according to the first product scheme information sample and a first preset rule to obtain the scheme generation model.
5. The method as claimed in claim 1, wherein the bidding document generation database and the bidding document case library are obtained by the following steps:
acquiring qualification certificate information, product data information and historical bidding document data of a target enterprise;
generating a bidding document making database according to the qualification certificate information and the product data information;
and generating a bidding case library according to the historical bidding data.
6. The method of claim 1, wherein the pre-trained bidding document generation model is obtained by:
training a preset initial standard generating model according to the standard making database and the standard case library to obtain a first standard generating model;
inputting a second product scheme information sample obtained in advance into the first bidding document generation model to obtain a bidding document sample;
and updating parameters of the first bidding document generation model according to the bidding document sample and a second preset rule to obtain the bidding document generation model.
7. The method of claim 1, wherein the target product solution information is input into a pre-trained bidding document generation model to obtain a target bidding document, and then further comprising:
obtaining the bidding result information of the target bidding document;
and updating the parameters of the scheme generation model and the parameters of the bidding document generation model according to the bidding result information.
8. An apparatus for generating a bidding document, comprising:
the system comprises an acquisition unit, a display unit and a display unit, wherein the acquisition unit is used for acquiring bidding demand information and first target portrait information;
the generating unit is used for inputting the bidding demand information and the first target portrait information into a pre-trained scheme generating model to obtain target product scheme information; inputting the product scheme information into a pre-trained bidding document generation model to obtain a target bidding document;
the pre-trained scheme generation model is obtained by training an initial scheme generation model according to a training data set, and the pre-trained standard book generation model is obtained by training the initial standard book generation model according to a preset standard book making database and a preset standard book case library.
9. A computer-readable storage medium comprising a stored program, wherein the program when executed performs the bidding document generation method according to any one of claims 1 to 7.
10. An electronic device comprising a memory and a processor, wherein the memory has a computer program stored therein, and the processor is configured to execute the method of generating a bidding document according to any one of claims 1 to 7 by the computer program.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116187956A (en) * | 2023-04-25 | 2023-05-30 | 上海百通项目管理咨询有限公司 | Method and system for generating bidding documents |
| CN117150000A (en) * | 2023-10-27 | 2023-12-01 | 北京大学 | Method, device, equipment and storage medium for generating bid |
| CN117687972A (en) * | 2023-11-24 | 2024-03-12 | 电能易购(北京)科技有限公司 | Bill-of-interest file generation method based on blockchain |
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- 2022-09-27 CN CN202211185168.5A patent/CN115577691A/en active Pending
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116187956A (en) * | 2023-04-25 | 2023-05-30 | 上海百通项目管理咨询有限公司 | Method and system for generating bidding documents |
| CN116187956B (en) * | 2023-04-25 | 2023-07-18 | 上海百通项目管理咨询有限公司 | Method and system for generating bidding documents |
| CN117150000A (en) * | 2023-10-27 | 2023-12-01 | 北京大学 | Method, device, equipment and storage medium for generating bid |
| CN117150000B (en) * | 2023-10-27 | 2024-02-02 | 北京大学 | Method, device, equipment and storage medium for generating bid |
| CN117687972A (en) * | 2023-11-24 | 2024-03-12 | 电能易购(北京)科技有限公司 | Bill-of-interest file generation method based on blockchain |
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