Acquired file processing method and device and collected file review system

Abstract

The invention relates to a collected document processing method and device and a collected document review system. The method comprises the following steps: analyzing and processing a target collection file by using a natural language processing technology and an optical character recognition technology to obtain key content information; calling a pre-trained artificial intelligence analysis model, and inputting the key content information into the artificial intelligence analysis model to obtain a collection file analysis result; wherein the artificial intelligence analysis model is constructed by utilizing an artificial intelligence algorithm and based on a preset review rule knowledge base; generating visual information according to the analysis result of the collection file, and displaying the visual information; according to the technical scheme, the accuracy and efficiency of the collection file processing can be improved, so that large-scale, complex and changeable data processing requirements can be met.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a method and device for processing bidding and procurement documents, and a bidding and procurement document review system. Background Art

[0002] With the development of computer Internet technology, most bidding and procurement can now be carried out through the bidding and procurement platform. Procurement data is the data generated by bidding, procurement and other activities through the network system. The processing of procurement data is usually completed by the procurement document review system using relevant data processing methods, thereby providing important technical support for enterprises to conduct various bidding and procurement.

[0003] Traditional methods of processing bidding documents mainly rely on manual operations and preset rule matching to review and screen bidding documents. These technical solutions are relatively stable and can handle the data processing requirements of most basic review tasks. However, with the increase in data processing and the increase in accuracy requirements, these technical solutions have significant shortcomings, such as low efficiency, inability to quickly respond to the data processing requirements of a large number of bidding document reviews, and insufficient accuracy, which can easily miss important information or misjudge, and is difficult to adapt to complex and changing application scenarios. Summary of the invention

[0004] Based on this, it is necessary to provide a method and device for processing bidding and procurement documents and a bidding and procurement document review system, which can improve the accuracy and operating efficiency of bidding and procurement document processing.

[0005] A method for processing a procurement document, comprising:

[0006] Use natural language processing technology and optical character recognition technology to analyze and process target procurement documents to obtain key content information;

[0007] Calling a pre-trained artificial intelligence analysis model, inputting the key content information into the artificial intelligence analysis model to obtain a procurement document analysis result; wherein the artificial intelligence analysis model is constructed using an artificial intelligence algorithm and based on a preset review rule knowledge base;

[0008] The analysis results of the bidding and procurement documents are generated into visual information for display.

[0009] In one embodiment, the method for processing bidding documents further includes:

[0010] Use knowledge graph technology to analyze the relationship between structured review rule information and review elements;

[0011] Building an examination rule knowledge base based on the structured examination rule information, the examination elements and the association relationship;

[0012] The artificial intelligence analysis model is constructed based on the review rule knowledge base and using artificial intelligence algorithms.

[0013] In one embodiment, the method for processing bidding documents further includes:

[0014] Use robotic process automation technology to analyze different types of procurement documents to obtain procurement content extraction process templates;

[0015] Based on the procurement content extraction process template and using optical character recognition technology, texts and tables of procurement documents in different file formats are structuredly parsed to extract review elements;

[0016] Perform error correction on the extracted review elements.

[0017] In one embodiment, the method for processing bidding documents further includes:

[0018] Using natural language processing technology and input experience information to perform semantic analysis on the review standard document to obtain the review key points, review specification content and standard requirements in the review standard document;

[0019] The structured review rule information is formed based on the review key points content, review specification content and standard requirements content.

[0020] In one embodiment, the artificial intelligence analysis model is constructed based on the review rule knowledge base and using an artificial intelligence algorithm, including:

[0021] Building AI analysis models based on AI neural network algorithms;

[0022] Based on the review rule knowledge base and using association rule learning algorithm and cluster analysis algorithm, the artificial intelligence analysis model is trained so that it has the function of analyzing the integrity, correctness, rationality and compliance of procurement documents.

[0023] In one embodiment, the method for processing bidding documents further includes:

[0024] Inputting the key content information of the target procurement document into a preset procurement document classification model and a credit evaluation model for analysis to obtain the classification type of the target procurement document and the credit rating of the supplier;

[0025] Analyze the target procurement documents using the time series analysis technology and the classification type and supplier credit rating to obtain corresponding trend reference information and risk assessment information;

[0026] The analysis results of the bidding and procurement documents, the trend reference information and the risk assessment information are generated into visual information for display.

[0027] In one embodiment, the method for processing bidding documents further includes:

[0028] Collecting procurement documents from multiple data sources, and pre-processing the documents by using robotic process automation technology to clean the data and unify the format;

[0029] Machine learning algorithms are used to perform big data analysis on the preprocessed procurement document data, and a procurement document classification model and a credit assessment model are constructed based on the procurement document data.

[0030] In one embodiment, a pre-trained artificial intelligence analysis model is called, and the key content information is input into the artificial intelligence analysis model to obtain a procurement document analysis result, including:

[0031] Calling a pre-trained artificial intelligence analysis model, and setting an analysis strategy of the artificial intelligence analysis model according to the trend reference information and risk assessment information;

[0032] The key content information is input into the artificial intelligence analysis model, so that the artificial intelligence analysis model analyzes the key content information according to the set analysis strategy and outputs corresponding procurement document analysis results.

[0033] In one embodiment, the method for processing bidding documents further includes:

[0034] The visualization information of the analysis results of the bidding and procurement documents is shared in real time on a pre-built collaborative review platform;

[0035] Receive review auxiliary information input by multiple users participating in the sharing, and form bidding and procurement document review decision information based on the review auxiliary information and the bidding and procurement document analysis results.

[0036] A procurement document processing device, comprising:

[0037] An information acquisition unit is used to analyze and process target procurement documents using natural language processing technology and optical character recognition technology to obtain key content information;

[0038] A model recognition unit, used to call a pre-trained artificial intelligence analysis model, input the key content information into the artificial intelligence analysis model to obtain a procurement document analysis result; wherein the artificial intelligence analysis model is constructed using an artificial intelligence algorithm and based on a preset review rule knowledge base;

[0039] The result display unit is used to generate visual information from the analysis results of the bidding and procurement documents for display.

[0040] A procurement document review system is used to execute the steps of the procurement document processing method.

[0041] In one embodiment, the procurement document review system includes:

[0042] Data collection and preprocessing module: used to collect procurement document data, clean the procurement document data, and unify the format; as well as analyze and process the target procurement documents to obtain key content information.

[0043] Big data analysis module: used to conduct big data analysis on bidding and procurement document data, build bidding document classification models and credit assessment models to identify key content information, trend reference information and risk assessment information.

[0044] Artificial intelligence analysis module: Use artificial intelligence analysis models to analyze the key content information of procurement documents and intelligently identify the key information of procurement documents.

[0045] Collaborative review and decision support module: used to build a collaborative work platform for real-time sharing and collaborative work among multiple users.

[0046] The technical solution of the present application utilizes natural language processing technology and optical character recognition technology to analyze and process target procurement documents to obtain key content information, constructs an artificial intelligence analysis model based on a preset review rule knowledge base, inputs the key content information into the artificial intelligence analysis model to obtain the procurement document analysis results, and generates visual information for display; this technical solution can improve the accuracy and efficiency of procurement document processing to meet large-scale, complex and changeable data processing needs. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 is a flow chart of a method for processing a procurement document according to an embodiment;

[0048] Figure 2 is a schematic diagram of a procurement document processing process based on a combination of big data analysis and artificial intelligence in one embodiment;

[0049] Figure 3 is a structural schematic diagram of a procurement document processing device according to an embodiment;

[0050] Figure 4 It is a schematic diagram of the structure of a procurement document review system according to an embodiment. DETAILED DESCRIPTION

[0051] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0052] In the embodiments of the present application, "at least one" means one or more, and "multiple" means two or more. For example, multiple objects refer to two or more objects. "Include" or "comprising" and other similar words mean that the information appearing before "include" or "comprising" covers the information listed after "include" or "comprising" and its equivalents, and does not exclude other information. The "and / or" mentioned in the embodiments of the present application indicates that there can be three kinds of relationships. The character " / " generally indicates that the objects associated before and after are in an "or" relationship.

[0053] refer to Figure 1 As shown, Figure 1 The flowchart of the method for processing bidding documents of an embodiment includes the following steps:

[0054] Step S10, using natural language processing technology and optical character recognition technology to analyze and process the target procurement documents to obtain key content information.

[0055] In this step, the input target procurement documents are analyzed and processed by utilizing Natural Language Processing (NLP) technology, combined with applications in the field of artificial intelligence, integrating linguistics, computer science and machine learning; the character information on pictures and the like in the target procurement documents is recognized using Optical Character Recognition (OCR) technology; and the key content information of the target procurement documents is finally obtained through the above analysis.

[0056] Step S20, calling a pre-trained artificial intelligence analysis model, inputting the key content information into the artificial intelligence analysis model to obtain the analysis results of the procurement document; wherein, the artificial intelligence analysis model utilizes an artificial intelligence algorithm and is constructed based on a preset review rule knowledge base.

[0057] In this step, a large number of bidding and procurement documents are used, and artificial intelligence algorithms are used to pre-train the artificial intelligence analysis model based on a preset review rule knowledge base, so that it can automatically analyze whether the information in the bidding and procurement documents meets the set requirements. The review rule knowledge base can be a knowledge base based on various review rules and review requirements and their relationships.

[0058] For example, the artificial intelligence analysis model can be used to analyze key terms, qualification requirements, compliance checks, and quotation rationality assessments in procurement documents.

[0059] Step S30, generating visual information based on the analysis results of the bidding and procurement documents for display.

[0060] In this step, the analysis results of the procurement documents are converted into visual graphic content and displayed on the system interface to provide data support for review and decision-making.

[0061] As in the solution of the above-mentioned embodiment, when reviewing and screening the bidding and procurement documents, the artificial intelligence analysis model is pre-trained, and automated analysis is performed through intelligent technical means, which improves the review efficiency and accuracy of the bidding and procurement document information, realizes the intelligent upgrade of bidding and procurement document processing, greatly shortens the review and screening cycle, and improves work efficiency.

[0062] In order to make the technical solution of the present application more clear, more embodiments are described below.

[0063] In one embodiment, in order to improve the accuracy and efficiency of the processing of the bidding and procurement documents; this embodiment also provides a method for training an artificial intelligence analysis model; accordingly, the bidding and procurement document processing method of the present application also includes:

[0064] Step S201, using knowledge graph technology to analyze the relationship between structured review rule information and review elements.

[0065] Specifically, the knowledge graph technology can be used to display the relationship between structured review rule information and review elements in a visual graph.

[0066] Step S202: constructing an examination rule knowledge base based on the structured examination rule information, the examination elements and the association relationship.

[0067] Specifically, by structuring review rule information and combining review elements and the relationships between them, a review rule knowledge base can be constructed, which can greatly enrich the recognition capabilities of artificial intelligence analysis models.

[0068] Step S203, constructing the artificial intelligence analysis model based on the review rule knowledge base and using artificial intelligence algorithms.

[0069] Specifically, artificial intelligence algorithms are used to build and train accurate artificial intelligence analysis models based on the knowledge data provided by the review rule knowledge base.

[0070] As in the solution of the above-mentioned embodiment, knowledge graph technology is used to analyze structured review rule information and review elements to form a review rule knowledge base, so that artificial intelligence algorithms can be used to build an artificial intelligence analysis model with high accuracy and efficiency.

[0071] In one embodiment, in order to build a more accurate artificial intelligence analysis model, this embodiment also provides a method for extracting the review elements required for step S201; accordingly, the procurement document processing method of this application also includes:

[0072] (a) Use robotic process automation technology to analyze different types of procurement documents to obtain a procurement content extraction process template.

[0073] Specifically, we obtain various types of procurement documents, and use Robot Process Automation (RPA) technology to simulate manual analysis of procurement documents to obtain procurement content extraction process templates, which greatly improves work efficiency and accuracy.

[0074] (b) Based on the procurement content extraction process template and using optical character recognition technology, structural analysis is performed on the text and tables of procurement documents in different file formats to extract review elements.

[0075] Specifically, the procurement content extraction process template is used in combination with OCR technology to perform structured analysis on procurement documents in various file formats (such as Word, PDF) to extract the review elements of the procurement documents.

[0076] (c) Performing error correction on the extracted examination factors.

[0077] Specifically, after the review elements are extracted, the review elements are further subjected to intelligent error correction processing to ensure subsequent recognition accuracy.

[0078] As in the solution of the above-mentioned embodiment, the review factors are extracted through the procurement content extraction process template, and intelligent error correction processing is performed, so that more accurate review factors can be obtained, which helps to build a more accurate artificial intelligence analysis model.

[0079] In one embodiment, in order to build a more accurate artificial intelligence analysis model, this embodiment also provides a method for extracting the structured review rule information required for step S201; accordingly, the procurement document processing method of this application also includes:

[0080] (d) Using natural language processing technology and input experience information to perform semantic analysis on the review standard document to obtain the review key points, review specifications and standard requirements in the review standard document.

[0081] Specifically, NLP technology and input human experience are used to perform semantic analysis on the review standard document to obtain the review points, review specifications and standard requirements.

[0082] (e) forming the structured examination rule information based on the examination key points, examination specification and standard requirements.

[0083] Specifically, structured review rule information is formed by organizing the review points, review specifications and standard requirements.

[0084] As in the above-mentioned embodiment, NLP technology is used in combination with human experience to analyze the review documents, organize the review points, review specifications, standard requirements and other contents to form structured review rule information; thereby, more accurate review rule information can be obtained, which helps to build a more accurate artificial intelligence analysis model.

[0085] In one embodiment, in order to obtain an artificial intelligence analysis model with higher accuracy, intelligence and recognition efficiency, for the artificial intelligence analysis model constructed in step S203, this embodiment provides a method for constructing an artificial intelligence analysis model, including the following:

[0086] (f) Construct an artificial intelligence analysis model based on artificial intelligence neural network algorithm.

[0087] Specifically, an artificial intelligence analysis model for analyzing and processing procurement document information is built based on artificial neural network (ANN) technology.

[0088] (g) Based on the review rule knowledge base and using association rule learning algorithm and cluster analysis algorithm, the artificial intelligence analysis model is trained so that it has the function of analyzing the integrity, correctness, rationality and compliance of the procurement documents.

[0089] Specifically, by using the constructed review rule knowledge base, artificial intelligence analysis models can be trained using algorithms such as association rule learning algorithms and cluster analysis algorithms. For example, the artificial intelligence analysis models can be trained to identify various aspects of the integrity, correctness, rationality and compliance of procurement document information.

[0090] As in the above-mentioned embodiment, the procurement document samples can be combined with the review rule knowledge base, and various artificial intelligence algorithms can be used to train the artificial intelligence analysis model so that it can have multiple analysis and recognition functions, thereby accurately and intelligently identifying and analyzing the procurement document information.

[0091] In one embodiment, in order to provide more accurate and efficient data support for review decisions, this embodiment also provides a procurement document processing solution based on the combination of big data analysis and artificial intelligence. Figure 2 As shown, Figure 2 The following is a schematic diagram of a procurement document processing process based on a combination of big data analysis and artificial intelligence in one embodiment; accordingly, the procurement document processing method of the present application also includes:

[0092] Step S210, collect procurement documents from multiple data sources, use robotic process automation technology to perform data cleaning and format unification preprocessing on the procurement documents; use machine learning algorithms to perform big data analysis on the preprocessed procurement document data, and build a procurement document classification model and a credit assessment model based on the procurement document data.

[0093] Specifically, by automatically collecting procurement document data from multiple data sources (such as procurement document libraries, supplier databases, etc.) and performing pre-processing work such as data cleaning and format unification, a high-quality data foundation is provided for subsequent analysis. Machine learning algorithms are used to conduct in-depth mining of the pre-processed procurement document data, and procurement document classification models and credit assessment models are constructed, which can be used to classify and conduct risk assessment of procurement documents.

[0094] Step S220, inputting the key content information of the target procurement document into a preset procurement document classification model and a credit evaluation model for analysis to obtain the classification type of the target procurement document and the credit rating of the supplier.

[0095] Specifically, the preset procurement document classification model and credit evaluation model are used to classify and evaluate the key content information of the target procurement document, so as to accurately determine the classification type of the target procurement document and the credit rating of the supplier.

[0096] Step S230, using the time series analysis technology and the classification type and supplier credit rating to analyze the target procurement document to obtain corresponding trend reference information and risk assessment information.

[0097] Specifically, through time series analysis and other techniques, combined with classification type and supplier credit rating, the target procurement documents are analyzed to obtain corresponding trend reference information and risk assessment information, so as to discover potential trends and risks and provide accurate data support for review decisions.

[0098] When generating visualization information from the analysis results of the bidding and procurement documents for display in step S30, the analysis results of the bidding and procurement documents and the trend reference information and risk assessment information are generated into visualization information for display.

[0099] As in the above-mentioned embodiment, the bidding and procurement document processing solution based on the combination of big data analysis and artificial intelligence can realize the automated review of bidding and procurement document information and provide intelligent decision support, which can assist in realizing the rapid and accurate review of bidding and procurement documents.

[0100] In one embodiment, in order to provide more accurate data support for review decisions, the present application also provides a technical solution for automatically adjusting the analysis strategy of the artificial intelligence analysis model based on big data analysis; accordingly, the method of calling the pre-trained artificial intelligence analysis model in step S20 and inputting the key content information into the artificial intelligence analysis model to obtain the analysis results of the procurement document may include the following:

[0101] Call a pre-trained artificial intelligence analysis model, and set the analysis strategy of the artificial intelligence analysis model according to the trend reference information and risk assessment information; input the key content information into the artificial intelligence analysis model, so that the artificial intelligence analysis model analyzes the key content information according to the set analysis strategy, and outputs corresponding procurement document analysis results.

[0102] Specifically, based on the pre-trained artificial intelligence analysis model and the trend reference information and risk assessment information obtained in step S230, the analysis strategy of the artificial intelligence analysis model is determined. The adjustment of the analysis strategy includes adjusting the level of the recognition function of the artificial intelligence analysis model. The key content information is then input into the artificial intelligence analysis model to analyze the key content information under the determined analysis strategy to obtain the procurement document analysis results.

[0103] For example, the levels of the artificial intelligence analysis model in identifying the completeness, correctness, rationality or compliance of the information in the procurement documents can be adjusted according to the analysis strategy. For example, when the trend is good and the risk is low, the levels of completeness and rationality can be lowered; when the trend is poor and the risk is high, the levels of correctness and compliance can be increased, thereby improving the recognition accuracy and providing accurate data reference for the final review decision of the procurement documents.

[0104] In one embodiment, in order to promote collaborative work among multiple users, the present application also provides a technical solution for building a collaborative review platform to achieve real-time sharing of information and collaborative work among multiple parties; accordingly, the procurement document processing method of the present application may also include the following:

[0105] The visualization information of the analysis results of the bidding and procurement documents is shared in real time on a pre-built collaborative review platform; review auxiliary information input by multiple users participating in the sharing is received, and bidding and procurement document review decision information is formed based on the review auxiliary information and the analysis results of the bidding and procurement documents.

[0106] Specifically, a collaborative review platform is built in advance, and the visual information generated by the analysis results of the procurement documents (such as various graphic information, etc.) is displayed on the collaborative review platform, and various application functions are developed. Different users (such as reviewers, purchasing personnel, legal personnel, etc.) can share the information to achieve real-time sharing and collaborative work of multiple parties. At the same time, the collaborative review platform can also receive review auxiliary information input by multiple users participating in the sharing, and ultimately serve as a data reference for reviewers to quickly make review decisions, and form procurement document review decision information based on the review auxiliary information and the analysis results of the procurement documents.

[0107] As in the above-mentioned embodiment, a collaborative review platform is constructed to realize real-time sharing of multi-party information and data reference for intelligent review suggestions, which facilitates collaborative review and decision support, improves the coordination and transparency of the review work, greatly shortens the review accuracy of procurement documents, and improves work efficiency.

[0108] An embodiment of the procurement document processing device is described below.

[0109] refer to Figure 3 As shown, Figure 3 The structure diagram of a procurement document processing device according to an embodiment includes:

[0110] The information acquisition unit 10 is used to analyze and process the target procurement document using natural language processing technology and optical character recognition technology to obtain key content information;

[0111] The model recognition unit 20 is used to call a pre-trained artificial intelligence analysis model, input the key content information into the artificial intelligence analysis model to obtain the analysis result of the bidding and procurement documents; wherein the artificial intelligence analysis model is constructed using an artificial intelligence algorithm and based on a preset review rule knowledge base;

[0112] The result display unit 30 is used to generate visual information from the analysis results of the bidding and procurement documents for display.

[0113] The procurement document processing device of this embodiment can execute a procurement document processing method provided by the embodiment of the present application, and its implementation principle is similar. The actions performed by each module in the procurement document processing device in each embodiment of the present application correspond to the steps in the procurement document processing method in each embodiment of the present application. For the detailed functional description of each module of the procurement document processing device, please refer to the description in the corresponding procurement document processing method shown in the previous text, which will not be repeated here.

[0114] An implementation example of the procurement document review system is described below.

[0115] The present application provides a procurement document review system for executing the steps of the procurement document processing method of any of the aforementioned embodiments.

[0116] In one embodiment, based on the technical solution of the bidding document processing method of the present application, a bidding document review system can be constructed, referring to Figure 4 As shown, Figure 4 This is a schematic diagram of the structure of a procurement document review system of an embodiment, which mainly includes the following:

[0117] Data collection and preprocessing module: used to automatically collect procurement document data from multiple data sources before recognition, and perform preprocessing such as cleaning and formatting of the procurement document data to provide a high-quality data foundation for subsequent analysis; during recognition, natural language processing technology and optical character recognition technology are used to analyze and process the target procurement document to obtain key content information.

[0118] Big data analysis module: used to apply machine learning algorithms to conduct in-depth mining of pre-processed data, using the constructed bidding document classification model and credit assessment model; at the same time, through time series analysis and other technologies, the key content information of the target procurement documents is analyzed and risk assessed to discover potential trends and risks, providing data support for review decisions.

[0119] Artificial intelligence analysis module: Use artificial intelligence analysis models to automatically analyze key content information of procurement documents, intelligently identify key terms of procurement documents, and identify their completeness, correctness, rationality and compliance; and automatically adjust the review strategy based on the classification and evaluation results of the big data analysis module to improve the review accuracy and efficiency of procurement documents.

[0120] Collaborative review and decision support module: It is used to realize real-time sharing and collaborative work of review auxiliary information provided by multiple users such as reviewers, procurement personnel, and legal personnel based on the constructed cross-departmental collaborative work platform, and provide accurate data support for reviewers to make final review decisions.

[0121] As shown in the scheme of the above-mentioned embodiment, the provided bidding document review system provides a more accurate and efficient bidding document review system solution compared to the defects of traditional technology that relies on manual operation and simple rule matching to review and screen bidding documents. It has high stability, reduces the time consumption of the review process, and can quickly respond to the processing needs of a large amount of bidding document information; it can cover all possible review points to avoid missing important information or misjudgment; it can automatically adjust the analysis strategy of the artificial intelligence analysis model according to historical data and real-time information, and can adapt to the complex and changing market environment.

[0122] The above embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A method for processing bidding documents, characterized in that: include: Use natural language processing technology and optical character recognition technology to analyze and process target procurement documents to obtain key content information; Calling a pre-trained artificial intelligence analysis model, inputting the key content information into the artificial intelligence analysis model to obtain a procurement document analysis result; wherein the artificial intelligence analysis model is constructed using an artificial intelligence algorithm and based on a preset review rule knowledge base; The analysis results of the bidding and procurement documents are generated into visual information for display.

2. The method for processing bidding documents according to claim 1, characterized in that: Also includes: Use knowledge graph technology to analyze the relationship between structured review rule information and review elements; Building an examination rule knowledge base based on the structured examination rule information, the examination elements and the association relationship; The artificial intelligence analysis model is constructed based on the review rule knowledge base and using artificial intelligence algorithms.

3. The method for processing bidding documents according to claim 2, characterized in that: Also includes: Use robotic process automation technology to analyze different types of procurement documents to obtain procurement content extraction process templates; Based on the procurement content extraction process template and using optical character recognition technology, texts and tables of procurement documents in different file formats are structuredly parsed to extract review elements; Perform error correction on the extracted review elements.

4. The method for processing recruitment documents according to claim 2, characterized in that: Also includes: Using natural language processing technology and input experience information to perform semantic analysis on the review standard document to obtain the review key points, review specification content and standard requirements in the review standard document; The structured review rule information is formed based on the review key points content, review specification content and standard requirements content.

5. The method for processing bidding documents according to claim 2, characterized in that: The artificial intelligence analysis model is constructed based on the review rule knowledge base and using artificial intelligence algorithms, including: Building AI analysis models based on AI neural network algorithms; Based on the review rule knowledge base and using association rule learning algorithm and cluster analysis algorithm, the artificial intelligence analysis model is trained so that it has the function of analyzing the integrity, correctness, rationality and compliance of procurement documents.

6. The method for processing bidding documents according to any one of claims 1 to 5, characterized in that: Also includes: Inputting the key content information of the target procurement document into a preset procurement document classification model and a credit evaluation model for analysis to obtain the classification type of the target procurement document and the credit rating of the supplier; Analyze the target procurement documents using the time series analysis technology and the classification type and supplier credit rating to obtain corresponding trend reference information and risk assessment information; The analysis results of the bidding and procurement documents, the trend reference information and the risk assessment information are generated into visual information for display.

7. The method for processing bidding documents according to claim 6, characterized in that: Also includes: Collecting procurement documents from multiple data sources, and pre-processing the documents by using robotic process automation technology to clean the data and unify the format; Machine learning algorithms are used to perform big data analysis on the preprocessed procurement document data, and a procurement document classification model and a credit assessment model are constructed based on the procurement document data.

8. The method for processing recruitment documents according to claim 7, characterized in that: Calling a pre-trained artificial intelligence analysis model, inputting the key content information into the artificial intelligence analysis model to obtain the analysis results of the procurement document, including: Calling a pre-trained artificial intelligence analysis model, and setting an analysis strategy of the artificial intelligence analysis model according to the trend reference information and risk assessment information; The key content information is input into the artificial intelligence analysis model, so that the artificial intelligence analysis model analyzes the key content information according to the set analysis strategy and outputs corresponding procurement document analysis results.

9. The method for processing bidding documents according to claim 1, characterized in that: Also includes: The visualization information of the analysis results of the bidding and procurement documents is shared in real time on a pre-built collaborative review platform; Receive review auxiliary information input by multiple users participating in the sharing, and form bidding and procurement document review decision information based on the review auxiliary information and the bidding and procurement document analysis results.

10. A procurement document review system, characterized in that: Used to execute the steps of the method for processing recruitment and procurement documents as described in any one of claims 1-9.

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