Intelligent bidding and tendering file generation system and method

Abstract

The invention provides an intelligent bidding and tendering file generation system and method, and belongs to the technical field of information processing, and the system comprises a demand obtaining module which obtains user input data and carries out the analysis, and further determines the demands of a user; the candidate determination module is used for determining an initial attribute value of the bidding project based on the demand of the user, and determining a bidding file candidate template in a preset bidding file template library based on the initial attribute value; the template screening module is used for analyzing the bidding and tendering file candidate templates based on a plurality of preset index types so as to determine a plurality of first templates; the combination determining module is used for determining an optimal template combination based on all the first templates and further generating a dynamic template file; and the file generation module is used for performing split analysis on the data input by the user and the dynamic template file, generating bidding and tendering file configuration information based on a split analysis result, and further generating an optimized and integrated bidding and tendering file in combination with the dynamic template file. And the efficiency of the bidding and tendering process and the accuracy of the file are improved.

Description

Technical Field

[0001] The present invention relates to the field of information processing technology, and in particular to an intelligent bidding document generation system and method. Background Art

[0002] With the development of information technology, the accuracy and efficiency of document generation in the bidding process are becoming increasingly demanding. The traditional bidding document generation process often relies on manual operations, which is not only time-consuming and labor-intensive, but also prone to human errors, resulting in document content that does not meet actual needs, affecting the fairness and efficiency of bidding.

[0003] In the prior art, some systems have attempted to automatically generate bidding documents through template libraries, but most of these systems have single functions and cannot flexibly adapt to the needs of different projects, and lack intelligent template screening and optimization functions. For example, some systems can only generate documents based on fixed templates and cannot dynamically adjust template combinations according to the specific needs of users, resulting in the lack of pertinence and optimization of the generated documents.

[0004] Therefore, the present invention provides an intelligent bidding document generation system and method. Summary of the invention

[0005] The present invention provides an intelligent bidding document generation system and method, which are used to intelligently analyze user input requirements, dynamically match candidate templates, and screen and score templates in combination with multiple preset indicators to achieve automatic generation of the optimal template combination. It can be flexibly adjusted according to project requirements to generate accurate bidding documents, improve document generation efficiency and quality, and solve the defects of fixed templates, low document generation efficiency and lack of intelligent adjustment in the prior art.

[0006] The present invention provides an intelligent bidding document generation system, comprising:

[0007] Demand acquisition module: acquires user input data and analyzes the user input data to obtain a first analysis result, and determines the user's demand based on the first analysis result;

[0008] Candidate determination module: determines the first attribute of the bidding project based on the user's needs, and determines a number of bidding document candidate templates in a preset bidding document template library based on the first attribute of the bidding project;

[0009] Template screening module: analyzing candidate templates of bidding documents based on a number of preset indicator types, obtaining a second analysis result, and determining a number of first templates based on the second analysis result;

[0010] Combination determination module: determines the optimal template combination based on all first templates, and then generates a dynamic template file;

[0011] File generation module: Perform split analysis on user input data and dynamic template files, generate bidding document configuration information based on the results of the split analysis, and then combine the dynamic template files to generate optimized and integrated bidding documents.

[0012] The present invention provides an intelligent bidding document generation system, a candidate determination module, comprising:

[0013] Text parsing unit: constructs and parses the demand text based on the user's needs to obtain demand keywords;

[0014] Attribute determination unit: maps the parsed demand keywords to an attribute space, and then obtains several demand attributes corresponding to the demand;

[0015] Demand determination unit: performs similarity analysis on the demand text and each demand attribute, and obtains several demand attributes whose similarity is greater than a preset similarity;

[0016] Scoring and screening unit: Scoring each requirement attribute whose similarity is greater than the preset similarity:

[0017] Among them, S i is the score of the i-th requirement attribute, r i is the similarity between the i-th requirement attribute and the requirement text, f i is the frequency of occurrence of the i-th requirement attribute in the requirement text, is the preset weight corresponding to the similarity score between the i-th requirement attribute and the requirement text, is the preset weight corresponding to the frequency of occurrence of the i-th requirement attribute in the requirement text, and β1 is the preset adjustment parameter;

[0018] An attribute determination unit: acquiring a first attribute whose score value is greater than a preset score value;

[0019] Template screening unit: screening in the bidding document template library based on the first attribute, and determining all bidding document templates matching the first attribute as candidate bidding document templates.

[0020] The present invention provides an intelligent bidding document generation system, a template screening module, comprising:

[0021] Scoring determination unit: evaluates and analyzes each candidate template of the bidding document based on the preset indicator type, obtains specific data of each preset indicator of each candidate template of the bidding document, and then determines the template score of each candidate template of the bidding document:

[0022] Among them, T g Score the template of the g-th candidate template of the bidding document, Ig,j is the index data of the jth type of preset index of the gth bidding document candidate template, γ g,j is the preset processing parameter corresponding to the indicator data of the j-th type of preset indicator of the g-th candidate template of the bidding document, is the preset scoring weight corresponding to the indicator data of the jth type of preset indicator of the gth candidate template of the bidding document, n is the number of preset indicator types, μ g is the preset weight corresponding to the cross-impact value between all preset indicators of the g-th candidate template of the bidding document, R g is the cross-influence value between all preset indicators of the g-th candidate template of the bidding document, and lg is the logarithmic function:

[0023] in, is the preset weight of the preset indicator of the jth type of the gth bidding document candidate template, I g,j+1 is the index data of the j+1th type of preset index of the gth candidate template of the bidding document, and ∈ is the preset adjustment parameter;

[0024] Template determination unit: selects a preset number of bidding document candidate templates with the highest scores as the first template.

[0025] The present invention provides an intelligent bidding document generation system, which presets indicator types including: applicability indicator, flexibility indicator, performance indicator, user experience indicator and scalability indicator.

[0026] The present invention provides an intelligent bidding document generation system, a document generation module, comprising:

[0027] Split analysis unit: performs split analysis on user input data and dynamic template files, and generates bidding document configuration information based on the results of the split analysis;

[0028] Sub-file generation unit: generates several sub-files based on dynamic templates, bidding document configuration information and preset multi-threaded construction generation tasks;

[0029] File integration unit: integrates several generated sub-files based on a preset integration method to generate several bidding target files;

[0030] Feedback acquisition unit: acquires the user's feedback result on the bidding target document, and determines the second attribute value based on the user's feedback result;

[0031] Document optimization unit: optimizes the integrated bidding document based on the second attribute value, and thereby obtains the optimized integrated bidding document.

[0032] The present invention provides an intelligent bidding document generation system, a split analysis unit, comprising:

[0033] Data splitting subunit: preliminarily classifies the data input by the user based on the preset algorithm, and preliminarily organizes the data input by the user according to the preset dimensions;

[0034] File splitting subunit: The system performs the first splitting of the dynamic template file, and disassembles the dynamic template file into several template modules that can be processed independently;

[0035] Second splitting subunit: associates and matches the user input data after preliminary classification with the parsed template module, maps the user input data to the corresponding template module according to the preset rules, and at the same time, performs a second splitting on the user input data after preliminary classification and the parsed template module;

[0036] Information expression subunit: expresses the user input data after the second split and the template module information as bidding document configuration information based on a preset expression method.

[0037] The present invention provides an intelligent bidding document generation system, wherein the sub-files include: basic information files, technical and commercial files and additional documents.

[0038] The present invention provides an intelligent bidding document generation method, comprising:

[0039] Step 1: Obtain user input data and analyze the user input data to obtain a first analysis result, and determine the user's needs based on the first analysis result;

[0040] Step 2: determining the first attribute of the bidding project based on the user's needs, and determining a number of bidding document candidate templates in a preset bidding document template library based on the first attribute of the bidding project;

[0041] Step 3: Analyze the candidate templates of the bidding document based on a number of preset indicator types to obtain a second analysis result, and determine a number of first templates based on the second analysis result;

[0042] Step 4: Determine the optimal template combination based on all first templates, and then generate a dynamic template file;

[0043] Step 5: Perform split analysis on the user input data and the dynamic template file, generate bidding document configuration information based on the results of the split analysis, and then generate optimized and integrated bidding documents in combination with the dynamic template file.

[0044] The present invention provides an intelligent bidding document generation system and method, which intelligently analyzes user input requirements, dynamically matches candidate templates, and screens and scores templates in combination with multiple preset indicators to achieve automatic generation of the optimal template combination. It can be flexibly adjusted according to project requirements to generate accurate bidding documents, improve document generation efficiency and quality, and solve the defects of fixed templates, low file generation efficiency and lack of intelligent adjustment in the prior art. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0046] Figure 1 It is a structural schematic diagram of an intelligent bidding document generation system provided by an embodiment of the present invention;

[0047] Figure 2 It is a flow chart of an intelligent bidding document generation method provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0048] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0049] Example 1

[0050] like Figure 1 As shown, an intelligent bidding document generation system provided by an embodiment of the present invention includes:

[0051] Demand acquisition module: acquires user input data and analyzes the user input data to obtain a first analysis result, and determines the user's demand based on the first analysis result;

[0052] Candidate determination module: determines the first attribute of the bidding project based on the user's needs, and determines a number of bidding document candidate templates in a preset bidding document template library based on the first attribute of the bidding project;

[0053] Template screening module: analyzing candidate templates of bidding documents based on a number of preset indicator types, obtaining a second analysis result, and determining a number of first templates based on the second analysis result;

[0054] Combination determination module: determines the optimal template combination based on all first templates, and then generates a dynamic template file;

[0055] File generation module: Perform split analysis on user input data and dynamic template files, generate bidding document configuration information based on the results of the split analysis, and then combine the dynamic template files to generate optimized and integrated bidding documents.

[0056] In this embodiment, user input data refers to information or data provided by the user when using the system, including basic requirements of the project, bidding conditions, project description, budget range, time frame, etc. For example, the user inputs information such as the project name "a certain construction project", the budget "5 million yuan", and the construction period "6 months";

[0057] In this embodiment, analyzing the input data means that the system processes and interprets the data input by the user through algorithms or preset rules, so as to extract key information and further determine the needs of the user. For example, the system analyzes the "budget of 5 million yuan" input by the user and interprets it as "a medium-sized construction project budget", and identifies the time requirement of the project with a construction period of "6 months";

[0058] In this embodiment, the user's needs are the core needs of the user that the system preliminarily identifies after analyzing the user's input data. This is the basis of the entire document generation process. For example, through analysis, the system determines that the user's needs are "to generate bidding documents suitable for medium-sized construction projects with a construction period of 6 months."

[0059] In this embodiment, the first attribute value refers to a key feature or parameter defined by the system according to the user's needs to guide the selection of the template. For example, for the above needs, the first attribute value may be "construction project type: medium-sized", "budget range: 3 million to 7 million yuan", "construction period: 4 to 8 months";

[0060] In this embodiment, the preset template library is a collection of various bidding document templates built into the system that have been pre-designed and classified. These templates can adapt to the needs of different projects. For example, the template library may contain templates of different categories such as "construction engineering", "IT service", and "equipment procurement", and each type of template is divided into different budget ranges and construction period settings;

[0061] In this embodiment, the candidate template refers to a set of templates that match user needs and are screened out by the system in a preset template library based on the first attribute value. For example, based on the first attribute value of the construction project type and the budget range, the system screens out three qualified candidate templates.

[0062] In this embodiment, the first template refers to the best template selected from the candidate templates after further screening and scoring. For example, among the three candidate templates, the system selects the best matching one as the first template after evaluation, such as "Medium-sized Construction Project Bidding Template No. 1";

[0063] In this embodiment, the optimal template combination means that the system selects and combines a template group that best meets the user's needs from multiple first templates to generate the final file. For example, the system may combine "Medium-sized Construction Project Bidding Template No. 1" with another "6-month construction period template" into an optimal template combination.

[0064] In this embodiment, the dynamic template file refers to a template file automatically generated based on the optimal template combination, combined with the user's specific needs and input data. The file has a certain degree of flexibility and can be adjusted according to changes in needs, including specific project descriptions, budget details and construction schedules, and can flexibly adapt to the special requirements of the project in terms of content;

[0065] In this embodiment, split analysis refers to the system performing refinement and decomposition processing on the data input by the user and the dynamic template file, analyzing the specific content of each part, so as to optimize the file structure and configuration. For example, the system performs split analysis on the budget part, identifies the details such as material cost, labor cost, management fee, etc., so as to optimize the file configuration;

[0066] In this embodiment, the file configuration information refers to the setting information generated by the system for adjusting and optimizing the final file structure and content according to the result of the split analysis, including adjusting the order of file chapters, adding specific clauses, formatting, etc.;

[0067] In this embodiment, the optimized integrated file refers to the bidding document ultimately generated by the system based on the dynamic template file and file configuration information. The file is optimized to ensure that the content is accurate and meets user needs. For example, the final output bidding document includes a complete project description, budget breakdown, schedule, contract terms, etc., with a clear structure and detailed content.

[0068] The beneficial effects of the above technical solution are: through intelligent analysis of user input requirements, dynamic matching of candidate templates, and screening and scoring of templates in combination with multiple preset indicators, the automatic generation of the optimal template combination is achieved, which can be flexibly adjusted according to project requirements, generate accurate bidding documents, improve document generation efficiency and quality, and solve the defects of fixed templates, low file generation efficiency and lack of intelligent adjustment in the existing technology.

[0069] Example 2

[0070] An intelligent bidding document generation system provided by an embodiment of the present invention includes a candidate determination module, comprising:

[0071] Text parsing unit: constructs and parses the demand text based on the user's needs to obtain demand keywords;

[0072] Attribute determination unit: maps the parsed demand keywords to an attribute space, and then obtains several demand attributes corresponding to the demand;

[0073] Demand determination unit: performs similarity analysis on the demand text and each demand attribute, and obtains several demand attributes whose similarity is greater than a preset similarity;

[0074] Scoring and screening unit: Scoring each requirement attribute whose similarity is greater than the preset similarity:

[0075] Among them, S i is the score of the i-th requirement attribute, r i is the similarity between the i-th requirement attribute and the requirement text, f i is the frequency of occurrence of the i-th requirement attribute in the requirement text, is the preset weight corresponding to the similarity score between the i-th requirement attribute and the requirement text, is the preset weight corresponding to the frequency of occurrence of the i-th requirement attribute in the requirement text, and β1 is the preset adjustment parameter;

[0076] An attribute determination unit: acquiring a first attribute whose score value is greater than a preset score value;

[0077] Template screening unit: screening in the bidding document template library based on the first attribute, and determining all bidding document templates matching the first attribute as candidate bidding document templates.

[0078] In this embodiment, the demand keywords refer to the core words or phrases extracted from the demand text input by the user. These keywords represent the main content and characteristics of the user's demand. If the user enters "construction project, budget of 5 million yuan, construction period of 6 months", the system may extract "construction project", "budget of 5 million yuan" and "construction period of 6 months" as demand keywords;

[0079] In this embodiment, the attribute space is a multi-dimensional structure, which includes attributes related to various requirements and their possible value ranges. The specific characteristics of the requirements are defined by mapping the requirement keywords to this attribute space. For example, the attribute space may include dimensions such as "project type", "budget range", "construction period", and "project scale". Each dimension may contain different values, such as "budget range" can be "1 million to 3 million", "3 million to 7 million", etc.

[0080] In this embodiment, the demand attributes are specific features mapped from the attribute space based on the demand keywords. These features are used to describe the user's needs and guide subsequent template screening. If the keyword is "construction project", the demand attributes may include "project type: construction project", "budget range: about 5 million", and "construction period: 6 months".

[0081] In this embodiment, the preset adjustment parameter is a small positive number, which is used to avoid division by zero.

[0082] The beneficial effects of the above technical solution are: through intelligent analysis of user demand text, extraction of keywords and mapping to attribute space, determination of demand attributes, and accurate screening of candidate templates that meet the needs through similarity analysis and scoring screening mechanism, the accuracy and efficiency of bidding document generation are effectively improved, manual intervention is reduced, the document generation process is optimized, and the automated and intelligent generation of bidding documents is realized.

[0083] Example 3

[0084] An intelligent bidding document generation system provided by an embodiment of the present invention includes a template screening module, comprising:

[0085] Scoring determination unit: evaluates and analyzes each candidate template of the bidding document based on the preset indicator type, obtains specific data of each preset indicator of each candidate template of the bidding document, and then determines the template score of each candidate template of the bidding document:

[0086] Among them, T g Score the template of the g-th candidate template of the bidding document, I g,j is the index data of the jth type of preset index of the gth bidding document candidate template, γ g,j is the preset processing parameter corresponding to the indicator data of the j-th type of preset indicator of the g-th candidate template of the bidding document, is the preset scoring weight corresponding to the indicator data of the jth type of preset indicator of the gth candidate template of the bidding document, n is the number of preset indicator types, μ gis the preset weight corresponding to the cross-impact value between all preset indicators of the g-th candidate template of the bidding document, R g is the cross-influence value between all preset indicators of the g-th candidate template of the bidding document, and lg is the logarithmic function:

[0087] in, is the preset weight of the preset indicator of the jth type of the gth bidding document candidate template, I g,j+1 is the index data of the j+1th type of preset index of the gth candidate template of the bidding document, and ∈ is the preset adjustment parameter;

[0088] Template determination unit: selects a preset number of bidding document candidate templates with the highest scores as the first template.

[0089] In this embodiment, the preset processing parameters are used to adjust lg(1+I g,j ) part, which is often used to smooth larger indicator values.

[0090] The beneficial effects of the above technical solution are: by comprehensively evaluating the candidate templates, determining the score of each template based on the specific data of the preset indicator type, selecting the template with the highest score as the first template, ensuring that the selected template best meets user needs, and improving the accuracy and efficiency of the generation of bidding documents. This system optimizes the template screening process, reduces the workload of manual screening, and significantly improves the intelligence and automation of document generation.

[0091] Example 4

[0092] An intelligent bidding document generation system provided by an embodiment of the present invention has preset indicator types, including: applicability indicator, flexibility indicator, performance indicator, user experience indicator and scalability indicator.

[0093] In this embodiment, the applicability index measures the degree of match between the bidding documents generated by the system and the requirements of a specific project, ensuring that the generated documents have good applicability according to the industry, scale and technical requirements of the project. For example, in a construction project bidding, the applicability index may include whether specific construction plans and safety requirements are included;

[0094] In this embodiment, the flexibility index is to evaluate the adaptability of the document generated by the system in response to different changes in requirements, ensuring that the system can flexibly adjust the content of the document template according to the different requirements input by the user. For example, when the user modifies the bidding conditions or adds new requirements, the system can automatically update the relevant content without rewriting the entire document;

[0095] In this embodiment, the performance index is a measure of the speed, accuracy and stability of the system to generate documents. The performance index ensures that the system can respond quickly and output accurately when processing large amounts of data. For example, in a large-scale project bidding, the system needs to generate complex and accurate bidding documents in a short period of time while ensuring that the output process is correct;

[0096] In this embodiment, the user experience index focuses on the convenience and satisfaction of users when using the system to generate documents. The user experience index involves the friendliness of the system interface, the simplicity of operation, and the readability of the final generated documents. For example, the system provides an intuitive interface and clear navigation, so that users can quickly complete document generation and obtain bidding documents with neat layout and clear logic;

[0097] In this embodiment, the scalability index is a measure of the system's scalability when adding new functions or handling new types of requirements in the future. The scalability index ensures that the system can support more industries or types of requirements by adding new modules or templates. For example, as market demand changes, the system can support the generation of bidding documents for environmental protection projects by adding new extension modules.

[0098] The beneficial effects of the above technical solution are: through preset applicability, flexibility, performance, user experience and scalability indicators, it ensures that the generated bidding documents highly match the project requirements, flexibly responds to different changes, quickly generates high-quality documents, and provides a friendly user experience and good system expansion capabilities, thereby improving overall efficiency and user satisfaction.

[0099] Example 5

[0100] An intelligent bidding document generation system provided by an embodiment of the present invention includes a document generation module, comprising:

[0101] Split analysis unit: performs split analysis on user input data and dynamic template files, and generates bidding document configuration information based on the results of the split analysis;

[0102] Sub-file generation unit: generates several sub-files based on dynamic templates, bidding document configuration information and preset multi-threaded construction generation tasks;

[0103] File integration unit: integrates several generated sub-files based on a preset integration method to generate several bidding target files;

[0104] Feedback acquisition unit: acquires the user's feedback result on the bidding target document, and determines the second attribute value based on the user's feedback result;

[0105] Document optimization unit: optimizes the integrated bidding document based on the second attribute value, and thereby obtains the optimized integrated bidding document.

[0106] In this embodiment, the preset multithreading refers to a multithreading processing mechanism pre-set in the system, which is used to execute multiple generation tasks at the same time. Through multithreading processing, the system can process different file generation tasks in parallel to improve generation efficiency. For example, when generating multiple sub-files, the system can process the generation of different parts of the files at the same time by enabling multithreading, thereby speeding up the generation of the entire file.

[0107] In this embodiment, a generation task refers to a specific task that the system needs to perform during the file generation process according to the file configuration and dynamic template. Each generation task usually corresponds to the generation of a sub-file. Assuming that a bidding document containing technical specifications, a budget table and a project schedule needs to be generated, the system will decompose these contents into different generation tasks, and each task is responsible for generating a sub-file.

[0108] In this embodiment, the preset integration method refers to a method preset by the system for integrating multiple sub-files into a target file, including integration by chapter, by content type, or by a custom order. For example, the system may place the technical specifications in the first half of the target file, and integrate the budget table and project schedule into the second half of the file, and integrate them in a preset order;

[0109] In this embodiment, the target file refers to the file finally generated by the system after integrating several sub-files. The target file is the final document required by the user, usually a bidding or tendering document. For example, the user wants to generate a complete bidding document including all necessary document parts. The system generates a target file containing all the contents by integrating the generated sub-files.

[0110] In this embodiment, the feedback result refers to the evaluation or opinion of the user on the content, format, structure, etc. of the generated target file after viewing or using the generated target file, which is used to guide the system to further optimize the generated file. For example, the user may feedback that a certain part of the content is unclear or the format is inappropriate, and the system will adjust the file according to the feedback to meet the user's needs;

[0111] In this embodiment, the second attribute value is an attribute determined based on user feedback results, and is used to optimize specific aspects of the file, such as the accuracy of the content, the aesthetics of the format, or the readability of the file. If the user feedback indicates that certain paragraphs in the target file are too long, the system may use "paragraph simplification" as the second attribute value to guide the next round of file optimization.

[0112] The beneficial effects of the above technical solution are: by realizing automatic generation, integration and optimization of bidding documents, using split analysis, dynamic templates and multi-threaded processing to improve generation efficiency, and continuously optimizing file content and format based on user feedback, it ensures that the generated files better meet user needs, significantly improving file generation quality and user satisfaction.

[0113] Example 6

[0114] An intelligent bidding document generation system provided by an embodiment of the present invention includes a split analysis unit, comprising:

[0115] Data splitting subunit: preliminarily classifies the data input by the user based on the preset algorithm, and preliminarily organizes the data input by the user according to the preset dimensions;

[0116] File splitting subunit: The system performs the first splitting of the dynamic template file, and disassembles the dynamic template file into several template modules that can be processed independently;

[0117] Second splitting subunit: associates and matches the user input data after preliminary classification with the parsed template module, maps the user input data to the corresponding template module according to the preset rules, and at the same time, performs a second splitting on the user input data after preliminary classification and the parsed template module;

[0118] Information expression subunit: expresses the user input data after the second split and the template module information as bidding document configuration information based on a preset expression method.

[0119] In this embodiment, the preset algorithm refers to a series of calculation rules or logics predefined and set in the system for processing, classifying or analyzing input data. Through these algorithms, the system can automatically operate on the data without human intervention. For example, the preset algorithm can be a rule for classifying input text data according to keywords or content types, such as classifying price-related information as "cost data" and classifying project progress-related information as "timetable data";

[0120] In this embodiment, the preset dimension refers to a classification standard or analysis angle predefined in the system, which is usually used to classify or organize data in multiple dimensions. Each dimension represents a different attribute or characteristic. The system organizes and analyzes data through these dimensions. For example, when generating bidding documents, the preset dimensions may include "time", "budget", "resource allocation", etc. The input data can be preliminarily organized according to these dimensions, such as dividing the data into "short-term", "medium-term" and "long-term" projects according to the time dimension.

[0121] In this embodiment, the first split refers to the initial disassembly process of the system on the dynamic template file, which decomposes the template file into several modules that can be processed independently. Each module can exist independently and can be used in combination with other modules. It contains multiple parts, such as "project overview", "technical solution", and "budget analysis". The first split splits these parts into independent modules for subsequent processing or customization;

[0122] In this embodiment, the independently processable module refers to the file part that is separated from the dynamic template file and can be independently executed or generated during the system split analysis process. It can be used alone or in combination with other modules in different occasions. For example, the "technical solution" module can be processed independently, combined with the "project overview" module to generate a complete file, or used alone as a proposal file for the technical part.

[0123] In this embodiment, association matching refers to the process by which the system matches and connects data or modules from different sources through specific rules or algorithms to ensure the association between data and template modules, for example, matching the project budget data input by the user with the "budget analysis" module in the template to ensure that the input data is correctly mapped to the corresponding template part;

[0124] In this embodiment, the preset rules are pre-set criteria or standards in the system, which are used to guide association matching or other automated processing steps. These rules are usually formulated based on specific business logic or user needs. For example, the preset rules may include "map all data containing the word 'budget' to the budget module", "format the date as YYYY-MM-DD", etc.;

[0125] In this embodiment, the second splitting refers to a further refinement processing step after the association matching, in which the data that has been preliminarily matched is further decomposed or optimized with the template module to ensure accurate matching and processing of the data and the module. For example, in the generation of bidding documents, the second splitting may further decompose each specific value in the budget data into sub-parts such as "cost", "tax", and "profit", and match them to the corresponding positions in the template module.

[0126] In this embodiment, the preset expression method is a format or method pre-set in the system for displaying, arranging or organizing data and information. Through this expression method, the generated document can be presented in a form that meets the requirements. In the generated bidding documents, the preset expression method may include using a "table" to display budget data, or using a "paragraph format" to describe the technical solution, so as to ensure the clarity, logic and readability of the document content.

[0127] The beneficial effects of the above technical solution are: through the refined processing of user input data and dynamic templates, preliminary classification and two split analysis are performed using preset algorithms and rules to ensure the accurate matching of data and templates, and file configuration information is generated through preset expressions, thereby improving the degree of automation, accuracy and customization of file generation to meet the diverse needs of users.

[0128] Example 7

[0129] An embodiment of the present invention provides an intelligent bidding document generation system, wherein sub-files include: basic information files, technical and business files, and additional documents.

[0130] In this embodiment, the basic information file is the part of the bidding document that contains basic data such as project information, company background, and bidder qualifications. It is used to provide a basic introduction to the project and the bidder to ensure that all participants have a clear understanding of the project and the bidder, including company profile, organizational structure, past project experience, contact information, etc. For example, the "Company Profile" module will provide a detailed introduction to the company's history, mission, and main business;

[0131] In this embodiment, technical and commercial documents are detailed documents in the bidding documents that are directly related to the project execution, such as technical solutions, construction plans, equipment configurations, cost budgets, quotations, etc. This part of the documents demonstrates the technical capabilities, implementation plans, and business conditions of the bidder. It includes detailed technical solutions for the project, such as engineering design drawings, technical indicator specifications, equipment lists, as well as project quotations, funding plans, and payment terms. For example, the "Technical Solution" module may describe the technical requirements and implementation steps of the project in detail, while the "Quotation" module lists the cost estimates for each job;

[0132] In this embodiment, additional documents refer to other supplementary materials that may be included in the bidding documents in addition to basic information and technical and commercial content, which are used to provide additional information to support the qualifications of the bidder or enhance the persuasiveness of the bidding plan, including contract templates, legal statements, confidentiality agreements, performance bond certificates, customer recommendation letters, environmental impact assessment reports, etc. For example, the "customer recommendation letter" module may include recommendation letters from past customers to prove the outstanding performance of the bidder in similar projects.

[0133] The beneficial effect of the above technical solution is: by dividing the bidding documents into basic information documents, technical and commercial documents and additional documents, the document structure is clearer and the content classification is clearer, which facilitates bidders to efficiently generate complete and compliant bidding documents, thereby improving the accuracy and professionalism of document preparation.

[0134] Example 8

[0135] like Figure 2As shown, an embodiment of the present invention provides an intelligent bidding document generation method, comprising:

[0136] Step 1: Obtain user input data and analyze the user input data to obtain a first analysis result, and determine the user's needs based on the first analysis result;

[0137] Step 2: determining the first attribute of the bidding project based on the user's needs, and determining a number of bidding document candidate templates in a preset bidding document template library based on the first attribute of the bidding project;

[0138] Step 3: Analyze the candidate templates of the bidding document based on a number of preset indicator types to obtain a second analysis result, and determine a number of first templates based on the second analysis result;

[0139] Step 4: Determine the optimal template combination based on all first templates, and then generate a dynamic template file;

[0140] Step 5: Perform split analysis on the user input data and the dynamic template file, generate bidding document configuration information based on the results of the split analysis, and then generate optimized and integrated bidding documents in combination with the dynamic template file.

[0141] The beneficial effects of the above technical solution are: through intelligent analysis of user input requirements, dynamic matching of candidate templates, and screening and scoring of templates in combination with multiple preset indicators, the automatic generation of the optimal template combination is achieved, which can be flexibly adjusted according to project requirements, generate accurate bidding documents, improve document generation efficiency and quality, and solve the defects of fixed templates, low file generation efficiency and lack of intelligent adjustment in the existing technology.

[0142] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention 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. However, 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 invention.

Claims

1. An intelligent bidding document generation system, characterized in that: include: Demand acquisition module: acquires user input data and analyzes the user input data to obtain a first analysis result, and determines the user's demand based on the first analysis result; Candidate determination module: determines the first attribute of the bidding project based on the user's needs, and determines a number of bidding document candidate templates in a preset bidding document template library based on the first attribute of the bidding project; Template screening module: analyzing candidate templates of bidding documents based on a number of preset indicator types, obtaining a second analysis result, and determining a number of first templates based on the second analysis result; Combination determination module: determines the optimal template combination based on all first templates, and then generates a dynamic template file; File generation module: Perform split analysis on user input data and dynamic template files, generate bidding document configuration information based on the results of the split analysis, and then combine the dynamic template files to generate optimized and integrated bidding documents.

2. According to claim 1, the intelligent bidding document generation system is characterized in that: Candidate determination module, including: Text parsing unit: constructs and parses the demand text based on the user's needs to obtain demand keywords; Attribute determination unit: maps the parsed demand keywords to an attribute space, and then obtains several demand attributes corresponding to the demand; Demand determination unit: performs similarity analysis on the demand text and each demand attribute, and obtains several demand attributes whose similarity is greater than a preset similarity; Scoring and screening unit: Scoring each requirement attribute whose similarity is greater than the preset similarity: Among them, S i is the score of the i-th requirement attribute, r i is the similarity between the i-th requirement attribute and the requirement text, f i is the frequency of occurrence of the i-th requirement attribute in the requirement text, is the preset weight corresponding to the similarity score between the i-th requirement attribute and the requirement text, is the preset weight corresponding to the frequency of occurrence of the i-th requirement attribute in the requirement text, and β1 is the preset adjustment parameter; An attribute determination unit: acquiring a first attribute whose score value is greater than a preset score value; Template screening unit: screening in the bidding document template library based on the first attribute, and determining all bidding document templates matching the first attribute as candidate bidding document templates.

3. The intelligent bidding document generation system according to claim 1 is characterized in that: Template filtering module, including: Scoring determination unit: evaluates and analyzes each candidate template of the bidding document based on the preset indicator type, obtains specific data of each preset indicator of each candidate template of the bidding document, and then determines the template score of each candidate template of the bidding document: Score the template of the g-th candidate template of the bidding document, I g,g is the index data of the jth type of preset index of the gth bidding document candidate template, γ j,g is the preset processing parameter corresponding to the indicator data of the j-th type of preset indicator of the g-th candidate template of the bidding document, is the preset scoring weight corresponding to the indicator data of the jth type of preset indicator of the gth candidate template of the bidding document, n is the number of preset indicator types, μ g is the preset weight corresponding to the cross-impact value between all preset indicators of the g-th candidate template of the bidding document, R g is the cross-influence value between all preset indicators of the g-th candidate template of the bidding document, and lg is the logarithmic function: in, is the preset weight of the preset indicator of the jth type of the gth bidding document candidate template, I g,j+1 is the index data of the j+1th type of preset index of the gth candidate template of the bidding document, and ∈ is the preset adjustment parameter; Template determination unit: selects a preset number of bidding document candidate templates with the highest scores as the first template.

4. The intelligent bidding document generation system according to claim 1 is characterized in that: Preset indicator types include: applicability indicator, flexibility indicator, performance indicator, user experience indicator, and scalability indicator.

5. The intelligent bidding document generation system according to claim 1 is characterized in that: File generation module, including: Split analysis unit: performs split analysis on user input data and dynamic template files, and generates bidding document configuration information based on the results of the split analysis; Sub-file generation unit: generates several sub-files based on dynamic templates, bidding document configuration information and preset multi-threaded construction generation tasks; File integration unit: integrates several generated sub-files based on a preset integration method to generate several bidding target files; Feedback acquisition unit: acquires the user's feedback result on the bidding target document, and determines the second attribute value based on the user's feedback result; Document optimization unit: optimizes the integrated bidding document based on the second attribute value, and thereby obtains the optimized integrated bidding document.

6. The intelligent bidding document generation system according to claim 5 is characterized in that: Split analysis unit, including: Data splitting subunit: preliminarily classifies the data input by the user based on the preset algorithm, and preliminarily organizes the data input by the user according to the preset dimensions; File splitting subunit: The system performs the first splitting of the dynamic template file, and disassembles the dynamic template file into several template modules that can be processed independently; Second splitting subunit: associates and matches the user input data after preliminary classification with the parsed template module, maps the user input data to the corresponding template module according to the preset rules, and at the same time, performs a second splitting on the user input data after preliminary classification and the parsed template module; Information expression subunit: expresses the user input data after the second split and the template module information as bidding document configuration information based on a preset expression method.

7. The intelligent bidding document generation system according to claim 3 is characterized in that: The sub-files include: Basic information files, technical and commercial files and additional documents.

8. An intelligent bidding document generation method, characterized in that: include: Step 1: Obtain user input data and analyze the user input data to obtain a first analysis result, and determine the user's needs based on the first analysis result; Step 2: determining the first attribute of the bidding project based on the user's needs, and determining a number of bidding document candidate templates in a preset bidding document template library based on the first attribute of the bidding project; Step 3: Analyze the candidate templates of the bidding document based on a number of preset indicator types to obtain a second analysis result, and determine a number of first templates based on the second analysis result; Step 4: Determine the optimal template combination based on all first templates, and then generate a dynamic template file; Step 5: Perform split analysis on the user input data and the dynamic template file, generate bidding document configuration information based on the results of the split analysis, and then generate optimized and integrated bidding documents in combination with the dynamic template file.

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