A Quality Evaluation Method, Device, Equipment and Storage Medium for Bidding Documents

Abstract

The present invention discloses a method, device, equipment and storage medium for quality evaluation of tender documents. The method for quality evaluation of tender documents includes: parsing the document directory of the target tender document to generate a page index container, and parsing the document body of the target tender document to generate a content vector container; generating a target tender directory tree based on the initial tender directory tree, the page index container and the content vector container; based on the target tender directory tree, using a large language model to perform content feature analysis on the target tender document, and generating a tender index container according to the analysis result returned by the large language model; and performing quality evaluation on the target tender document based on the tender index container. Through the above technical solution, the accuracy of the target tender document and the quality detection efficiency are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and particularly to a method, device, equipment and storage medium for evaluating the quality of bidding documents. Background Art

[0002] When conducting project bidding, the quality of the bidding document largely determines whether the bidder wins the bid. Therefore, the quality of the bidding document is particularly important.

[0003] Currently, after the bidding document is completed, the quality of the bidding document is evaluated by manual review to determine the quality of the bidding document and the location of defects. However, the quality evaluation by manual review depends on the meticulousness and historical experience of the evaluator, and it is difficult to detect small defects and common defect problems in the bidding document. Often, a small oversight can lead to the rejection of the project bid. Summary of the Invention

[0004] The present invention provides a method, device, equipment and storage medium for evaluating the quality of bidding documents to improve the quality of the bidding document.

[0005] According to one aspect of the present invention, there is provided a method for evaluating the quality of a bidding document, the method comprising:

[0006] By parsing the document directory of the target bidding document, a page index container is generated, and by parsing the document body of the target bidding document, a content vector container is generated; wherein, the page index container is used to store the directory information of the target bidding document, and the content vector container is used to store the body information of the target bidding document;

[0007] Based on the initial bidding directory tree, the page index container and the content vector container, a target bidding directory tree is generated; wherein, the initial bidding directory tree includes the directory feature information of the bidding document; the target bidding directory tree includes the document body information of the target bidding document;

[0008] Based on the target bidding directory tree, a large language model is used to perform content feature analysis on the target bidding document, and a bidding index container is generated according to the analysis result returned by the large language model; wherein, the bidding index container is used to store the bidding index information indicated by the target bidding document;

[0009] Based on the bidding index container, the quality of the target bidding document is evaluated.

[0010] According to another aspect of the present invention, there is provided a device for evaluating the quality of a bidding document, the device comprising:

[0011] The tender invitation analysis module is used to generate a page index container by analyzing the file directory of the target tender invitation document, and generate a content vector container by analyzing the file body of the target tender invitation document; wherein, the page index container is used to store the directory information of the target tender invitation document, and the content vector container is used to store the body information of the target tender invitation document;

[0012] The tender invitation directory module is used to generate a target tender invitation directory tree based on the initial tender invitation directory tree, the page index container, and the content vector container; wherein, the initial tender invitation directory tree includes the directory feature information of the tender invitation document; the target tender invitation directory tree includes the file body information of the target tender invitation document;

[0013] The tender invitation index module is used to perform content feature analysis on the target tender invitation document based on the target tender invitation directory tree by using a large language model, and generate a tender invitation index container according to the analysis result returned by the large language model; wherein, the tender invitation index container is used to store the tender invitation index information indicated by the target tender invitation document;

[0014] The quality evaluation module is used to evaluate the quality of the target tender offer document based on the tender invitation index container.

[0015] According to another aspect of the present invention, there is provided an electronic device, which includes:

[0016] At least one processor;

[0017] And a memory communicatively connected to the at least one processor;

[0018] Wherein, the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the quality evaluation method of the tender offer document according to any embodiment of the present invention.

[0019] According to another aspect of the present invention, there is provided a computer-readable storage medium storing computer instructions for causing a processor to implement the quality evaluation method of the tender offer document according to any embodiment of the present invention when executed.

[0020] According to another aspect of the present invention, there is provided a computer program product including a computer program, and the computer program implements the quality evaluation method of the tender offer document according to any embodiment of the present invention when executed by a processor.

[0021] The technical solution of the embodiment of the present invention parses the table of contents and the main text of the target tender document, updates the initial tender directory tree according to the parsing results to generate a target tender directory tree, determines the directory features of the target tender document, and determines the index information of the file content corresponding to the directory features of the target tender document according to the target tender directory tree, and performs automated quality detection on the target tender document according to the index information, improving the accuracy and quality detection efficiency of the target tender document.

[0022] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present invention, nor is it used to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. Brief Description of the Drawings

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0024] Figure 1 is a flowchart of a method for evaluating the quality of a tender document according to Embodiment 1 of the present invention;

[0025] Figure 2 is a flowchart of a method for evaluating the quality of a tender document according to Embodiment 2 of the present invention;

[0026] Figure 3 is a flowchart of a method for evaluating the quality of a tender document according to Embodiment 3 of the present invention;

[0027] Figure 4 is a schematic structural diagram of a device for evaluating the quality of a tender document according to Embodiment 4 of the present invention;

[0028] Figure 5 is a schematic structural diagram of an electronic device for implementing the method for evaluating the quality of a tender document in the embodiment of the present invention. Detailed Embodiments

[0029] In order to enable those skilled in the art to better understand the solution of the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0030] It should be noted that the terms "first", "second", etc. in the description, claims and above-mentioned drawings of the present invention are used to distinguish similar objects, and do not necessarily describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device comprising a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0031] Embodiment 1

[0032] Figure 1 FIG. is a flowchart of a method for evaluating the quality of a tender document provided in Embodiment 1 of the present invention. This embodiment is applicable to the situation of evaluating the quality of a tender document to be tendered according to a published tender document. This method can be executed by a quality evaluation device for tender documents. The quality evaluation device for tender documents can be implemented in the form of hardware and / or software, and the quality evaluation device for tender documents can be configured in various general computing devices. As Figure 1 shown, the method includes:

[0033] S110. By parsing the file directory of the target tender document, a page index container is generated, and by parsing the file body of the target tender document, a content vector container is generated.

[0034] Among them, the target tender document may refer to the tender document published by the tenderer; the page index container can be used to store the directory information of the target tender document, and the content vector container can be used for the body information of the target tender document.

[0035] In the embodiment of the present invention, the content of the target tender document publicly disclosed by the tenderer can be parsed, and the parsed content can be stored using a dual metadata cache to improve the access efficiency of the target tender document.

[0036] S120. Based on the initial tender directory tree, the page index container, and the content vector container, a target tender directory tree is generated.

[0037] Among them, the initial tender directory tree may include the directory feature information of the tender document; the target tender directory tree may include the file body information of the target tender document. It should be noted that the target tender directory tree is generated based on the initial tender directory tree.

[0038] Optionally, in the embodiments of the present invention, the initial tender directory tree can be generated according to a preset large language model. Exemplarily, a request message of "generating the key element directory of the tender document" is input to the large language model, and according to the return result of the large language model, the initial tender directory tree of the tender document is constructed, and the initial tender directory tree is improved according to the document content of the target tender document to generate the target tender directory tree corresponding to the target tender document. It should be noted that the initial tender directory tree can be used to represent the document format of the tender document, that is, the characteristic directory essential for the tender document.

[0039] S130. Based on the target tender directory tree, use the large language model to perform content feature analysis on the target tender document, and generate a tender index container according to the analysis result returned by the large language model.

[0040] Among them, the tender index container can store the tender index information indicated by the target tender document, and is used to indicate the format information and / or content information of the tender documents required by the target tender document. Exemplarily, for example, the tender index information can refer to the tender qualification requirement information, evaluation method information, and document directory information, etc. indicated in the target tender document. It should be noted that the format information of the tender document can refer to the document directory information of the tender document.

[0041] Specifically, the nodes in the target tender directory tree can be traversed, and according to the tender index information stored in the node, the document content corresponding to the tender index information in the target tender can be determined. Then, the large language model can be used to perform content feature analysis on the document content, return the tender index information corresponding to the document content and store it to generate a tender index container. It should be noted that the tender index container is a storage medium for storing tender index information.

[0042] Optionally, based on the target tender directory tree, use the large language model to perform content feature analysis on the target tender document, and generate a tender index container according to the analysis result returned by the large language model, including: traversing the nodes in the target tender directory tree, if the storage object in the node is directory feature information, obtain the tender sub-content corresponding to the directory feature information in the target tender document, and use the large language model to analyze the tender sub-content to determine the tender index corresponding to the tender sub-content; if the storage object in the node is the document information of the target tender document, use the large language model to analyze the document information to determine the tender index corresponding to the document information; store the tender index to generate a tender index container.

[0043] Optionally, the tender sub-content corresponding to the directory feature information can be determined by querying in the content vector container according to the directory feature information.

[0044] Among them, the tender sub - content can be the file content after segmenting the target tender document according to the title information of the target tender document. The file information of the target tender document can refer to the vector normalization value of the tender sub - content.

[0045] It should be noted that in the embodiment of the present invention, the tender index container can provide writing support for the target tender document writers, and the writers can view the tender index information stored in the tender index container.

[0046] By traversing the target tender directory tree, the tender indexes of the target tender document are further determined to parse the target tender document and generate a tender index container, avoiding accessing the target tender document and improving the acquisition efficiency of the file information of the target tender document.

[0047] S140. Based on the tender index container, perform a quality assessment on the target tender document.

[0048] Optionally, based on the tender index container, performing a quality assessment on the target tender document includes: segmenting the target tender document according to the title information of the target tender document to generate tender sub - content; taking the tender sub - content, the title information to which the tender sub - content belongs, and the page number information corresponding to the title information as a container node to generate a tender document content container; for each index node in the tender index container indicating tender index information, traversing the container nodes in the tender document content container to determine whether the index information exists in the tender document content container; if it exists, the quality inspection of the target tender document passes; if it does not exist, it indicates that there are defects in the target tender document and an alarm prompt is issued.

[0049] Among them, the tender sub - content can refer to the file content generated after segmenting the target tender document according to the title information of the target tender document.

[0050] In the embodiment of the present invention, by verifying whether the tender index information indicated by each index node in the tender index container exists in the tender document content container, the file format and / or file content of the target tender document can be detected to determine whether the target tender document meets the tender requirements indicated by the target tender document.

[0051] The technical solution of the embodiment of the present invention, by performing directory parsing and text parsing on the target tender document, and updating the initial tender directory tree according to the parsing results to generate a target tender directory tree, determines the directory features of the target tender document, and determines the index information of the file content corresponding to the directory features of the target tender document according to the target tender directory tree, and performs an automated quality inspection on the target tender document according to the index information, improving the accuracy and quality inspection efficiency of the target tender document.

[0052] Embodiment 2

[0053] Figure 2 The figure is a flowchart of a method for evaluating the quality of a tender document provided in Embodiment 2 of the present invention. This embodiment is further extended on the basis of the above embodiment, and provides specific steps for parsing the document directory of the target tender document to generate a page index container, and parsing the document body of the target tender document to generate a content vector container. It should be noted that for the parts not described in detail in the embodiments of the present invention, reference can be made to the relevant descriptions of other embodiments, which will not be elaborated here. As Figure 2 shown, the method includes:

[0054] S210. Identify the document directory of the target tender document, and determine the title information of the target tender document and the page number information corresponding to the title information.

[0055] S220. Store the title information of the target tender document and the page number information corresponding to the title information in the page index container in the form of key-value pairs.

[0056] S230. Determine the title hierarchy path of the title information of the target tender document according to the subordinate relationship between the title information in the target tender document.

[0057] S240. Segment the target tender document according to the title information of the target tender document, generate the tender sub-content corresponding to each title information, and perform vector normalization on the tender sub-content.

[0058] S250. Establish a storage node for each title information in the target tender document to generate a content vector container. Among them, the storage node is used to store the title hierarchy path, the vector normalization value of the tender sub-content, and the page number information corresponding to the title information, and the node identifier of the storage node is determined according to the title hierarchy path.

[0059] In the embodiment of the present invention, in order to parse the target tender document, the appendix (i.e., the directory information) of the target tender document can be identified, the title information of the target tender document and the page number information corresponding to the title information can be determined, and key-value pair data is generated with the title information as the key position and the page number information corresponding to the title information as the value position, and the page index container is generated by storing the key-value pair data.

[0060] Further, by identifying the appendix format of the target tender document, the subordinate relationship between the title information in the target tender document can be determined. For example, there may be multiple sub-chapter titles under a chapter title, and based on this, the title hierarchy path of each title in the target tender document can be determined. For example, if there are sub-chapters a1, a2, and a3 under a chapter A, the title hierarchy path corresponding to a1 is A->a1. Exemplarily, the node identifier of the storage node corresponding to a1 in the content vector container is A->a1->the page number where a1 is located.

[0061] The technical solution of the embodiment of the present invention generates a page index container by performing directory recognition on the target tender document, generates tender sub-content by segmenting the target tender document, and generates a content vector container by aligning and normalizing vectors. The target tender document is stored through a dual-source cache data, which improves the access rate of the target tender document and improves the data fault tolerance ability.

[0062] Embodiment III

[0063] Figure 3 It is a flowchart of a method for evaluating the quality of a tender document provided in Embodiment III of the present invention. This embodiment is further extended on the basis of the above embodiments and provides specific steps for generating a target tender directory tree based on an initial tender directory tree, a page index container, and a content vector container. It should be noted that for the parts not detailed in the embodiments of the present invention, reference can be made to the relevant descriptions of other embodiments, which will not be elaborated here. As Figure 3 shown, the method includes:

[0064] S310. Generate a page index container by parsing the file directory of the target tender document, and generate a content vector container by parsing the file body of the target tender document.

[0065] S320. Use a large language model to generate an initial tender directory tree of the tender document, and traverse the title information in the page index container to determine whether the title information exists in the initial tender directory tree.

[0066] In the embodiment of the present invention, a query request for the file format of the tender document can be sent to the large language model. The query request can be used to request the necessary directory sections of the tender document, and an initial tender directory tree can be generated according to the request result returned by the large language model. Furthermore, the title information in the page index container can be traversed, and a query can be made in the initial tender directory tree according to the title information to determine whether the title information is stored in the initial tender directory tree.

[0067] S330. If it does not exist in the initial tender directory tree, use a large language model to obtain the document content features corresponding to the title information in the tender document, determine the storage node corresponding to the document content features in the content vector container, and update the initial tender directory tree according to the document information of the target tender document stored in the storage node to generate a target tender directory tree.

[0068] Optionally, if the document content features do not exist in the content vector container, the document content features can be vector-normalized, and the vector values after normalization of the document feature vectors are stored in the initial tender directory tree to update the initial tender directory tree; if the document content features exist in the content vector container, the initial tender directory tree is updated according to the vector normalization values of the tender sub-content stored corresponding to the document content features in the content vector container.

[0069] S340. Based on the target tender directory tree, use a large language model to analyze the content features of the target tender document and generate a tender index container according to the analysis results returned by the large language model.

[0070] S350. Evaluate the quality of the target tender document based on the tender index container.

[0071] Optionally, evaluating the quality of the target tender document based on the tender index container further includes: traversing the index nodes in the tender index container to determine the tender qualification criteria for the tenderer indicated in the target tender document; determining the tender sub-content corresponding to the tender qualification criteria in the tender document content container; verifying whether the tender sub-content meets the tender qualification criteria, and if it meets, determining that the target tender document meets the tender qualifications indicated by the target tender document.

[0072] Specifically, the index nodes in the tender index container can be traversed to determine the index nodes in the index tender container for storing the tender qualification criteria of the tenderer; and the tender document content container can be traversed to determine the tender sub-content corresponding to the tenderer's own qualifications, and verify the tenderer's own qualification information indicated by the tender sub-content and the tender qualification criteria described by the index nodes in the index tender container to determine whether the tenderer has tender qualifications.

[0073] Optionally, the index nodes in the tender index container can also be traversed to determine the index nodes in the index tender container for storing evaluation criteria, self-check the target tender document according to at least one evaluation criterion described by the index nodes, determine the self-check score, and visualize and feedback the self-check results.

[0074] Optionally, if there are pictures in the tender sub - content, picture recognition can be further performed on the pictures in the tender sub - content to obtain the text information recorded in the pictures, so as to obtain more comprehensive tender information in the tender sub - content and improve the accuracy of the quality evaluation result of the target tender document.

[0075] In the technical solution of the embodiment of the present invention, an initial tender document catalog tree is pre - generated by a large - language model, and then the tender catalog tree is updated according to the page index container and the content vector container to generate a target tender catalog tree carrying all the catalog feature information of the target tender document, which improves the generation rate of the target index catalog tree and ensures the integrity of the document information in the target tender document.

[0076] Embodiment Four

[0077] Figure 4 It is a schematic structural diagram of a quality evaluation device for a tender document provided in Embodiment Four of the present invention. As Figure 4 shown, the device includes:

[0078] A tender parsing module 410, configured to generate a page index container by parsing the file catalog of the target tender document, and generate a content vector container by parsing the file text of the target tender document; wherein, the page index container is used to store the catalog information of the target tender document, and the content vector container is used to store the text information of the target tender document;

[0079] A tender catalog module 420, configured to generate a target tender catalog tree based on the initial tender catalog tree, the page index container, and the content vector container; wherein, the initial tender catalog tree includes the catalog feature information of the tender document; the target tender catalog tree includes the file text information of the target tender document;

[0080] A tender index module 430, configured to perform content feature analysis on the target tender document based on the target tender catalog tree by using a large - language model, and generate a tender index container according to the analysis result returned by the large - language model; wherein, the tender index container is used to store the tender index information indicated by the target tender document;

[0081] A quality evaluation module 440, configured to perform quality evaluation on the target tender document based on the tender index container.

[0082] The technical solution of the embodiment of the present invention parses the table of contents and the main text of the target tender document, updates the initial tender directory tree according to the parsing results to generate a target tender directory tree, determines the directory features of the target tender document, and determines the index information of the file content corresponding to the directory features of the target tender document according to the target tender directory tree, and automatically performs quality inspection on the target tender document according to the index information, improving the accuracy and quality inspection efficiency of the target tender document.

[0083] Optionally, the tender parsing module 410 includes:

[0084] The tender directory recognition unit is used to recognize the file directory of the target tender document and determine the title information of the target tender document and the page number information corresponding to the title information;

[0085] The page index container unit is used to store the title information of the target tender document and the page number information corresponding to the title information in the page index container in the form of key-value pairs;

[0086] The title path generation unit is used to determine the title level path of the title information of the target tender document according to the subordinate relationship between the title information in the target tender document;

[0087] The tender segmentation unit is used to segment the target tender document according to the title information of the target tender document, generate the tender sub-content corresponding to each title information, and perform vector normalization on the tender sub-content;

[0088] The content vector container unit is used to create a storage node for each title information in the target tender document to generate a content vector container; wherein, the storage node is used to store the title level path, the vector normalization value of the tender sub-content, and the page number information corresponding to the title information, and the node identifier of the storage node is determined according to the title level path.

[0089] Optionally, the tender directory module 420 includes:

[0090] The initial directory unit is used to generate the initial tender directory tree of the tender document by using a large language model, and traverse the title information in the page index container to determine whether the title information exists in the initial tender directory tree;

[0091] The target directory generation unit is used to, if it does not exist in the initial tender directory tree, use a large language model to obtain the file content features corresponding to the title information in the tender document, determine the storage node corresponding to the file content features in the content vector container, and update the initial tender directory tree according to the file information of the target tender document stored in the storage node to generate a target tender directory tree.

[0092] Optionally, the quality assessment module 440 includes:

[0093] A tender segmentation unit for segmenting the target tender document according to the title information of the target tender document to generate tender sub - contents;

[0094] A tender content container generation unit for using the tender sub - contents, the title information to which the tender sub - contents belong, and the page number information corresponding to the title information as a container node to generate a tender document content container;

[0095] A quality assessment unit for traversing the container nodes in the tender document content container for each tender index information indicated by the index nodes in the tender index container to determine whether the index information exists in the tender document content container; if it exists, the quality inspection of the target tender document passes.

[0096] Optionally, the quality assessment module 440 further includes:

[0097] A tender qualification unit for traversing the index nodes in the tender index container to determine the tender qualification criteria for the tenderer indicated in the target tender document;

[0098] A tender qualification verification unit for determining the tender sub - contents corresponding to the tender qualification criteria in the tender document content container; verifying whether the tender sub - contents meet the tender qualification criteria, and if they meet, determining that the target tender document meets the tender qualifications indicated by the target tender document.

[0099] Optionally, the tender index module 430 includes:

[0100] A target directory traversal unit for traversing the nodes in the target tender directory tree. If the storage object in the node is directory feature information, obtaining the tender sub - contents corresponding to the directory feature information in the target tender document and analyzing the tender sub - contents using a large - language model to determine the tender index corresponding to the tender sub - contents;

[0101] An index container generation unit for, if the storage object in the node is the file information of the target tender document, analyzing the file information using a large - language model to determine the tender index corresponding to the file information; storing the tender index to generate a tender index container.

[0102] The quality assessment device for tender documents provided by the embodiments of the present invention can execute the quality assessment method for tender documents provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects for executing the method.

[0103] Embodiment Five

[0104] Figure 5 FIG. 510 shows a schematic structural diagram of an electronic device 510 that can be used to implement an embodiment of the present invention. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0105] As Figure 5 shown, the electronic device 510 includes at least one processor 511, and a memory communicatively connected to the at least one processor 511, such as a read-only memory (ROM) 512, a random access memory (RAM) 513, etc. The memory stores a computer program executable by the at least one processor. The processor 511 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 512 or the computer program loaded from the storage unit 518 into the random access memory (RAM) 513. In the RAM 513, various programs and data required for the operation of the electronic device 510 can also be stored. The processor 511, the ROM 512, and the RAM 513 are connected to each other via a bus 514. An input / output (I / O) interface 515 is also connected to the bus 514.

[0106] A plurality of components in the electronic device 510 are connected to the I / O interface 515, including: an input unit 516, such as a keyboard, a mouse, etc.; an output unit 517, such as various types of displays, speakers, etc.; a storage unit 518, such as a magnetic disk, an optical disk, etc.; and a communication unit 519, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 519 allows the electronic device 510 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0107] The processor 511 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the processor 511 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The processor 511 executes the various methods and processes described above, such as the method for evaluating the quality of tender documents.

[0108] In some embodiments, the method for evaluating the quality of tender documents can be implemented as a computer program tangibly embodied in a computer-readable storage medium, such as storage unit 518. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 510 via ROM 512 and / or communication unit 519. When the computer program is loaded into RAM 513 and executed by the processor 511, one or more steps of the method for evaluating the quality of tender documents described above can be performed. Alternatively, in other embodiments, the processor 511 can be configured to execute the method for evaluating the quality of tender documents by any other suitable means (e.g., by means of firmware).

[0109] The various embodiments of the systems and techniques described above in this document can be implemented in digital electronic circuitry, integrated circuit systems, field-programmable gate arrays (FPGA), application-specific integrated circuits (ASIC), application-specific standard products (ASSP), systems-on-a-chip (SOC), complex programmable logic devices (CPLD), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special or general programmable processor that receives data and instructions from a storage system, at least one input device, and at least one output device, and transmits the data and instructions to the storage system, the at least one input device, and the at least one output device.

[0110] The computer programs for implementing the methods of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to the processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the computer programs are executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The computer programs can be executed entirely on the machine, partially on the machine, as a stand-alone software package partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0111] In the context of the present invention, a computer-readable storage medium can be a tangible medium that can contain or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer-readable storage medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, the computer-readable storage medium can be a machine-readable signal medium. More specific examples of the machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0112] To provide for interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the electronic device. Other kinds of devices can also be used to provide for interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0113] The systems and techniques described herein can be implemented in a computing system that includes backend components (such as, for example, a data server), or a computing system that includes middleware components (such as, for example, an application server), or a computing system that includes frontend components (such as, for example, a user computer having a graphical user interface or a web browser through which the user can interact with an implementation of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected by any form or medium of digital data communication (such as, for example, a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0114] A computing system may include a client and a server. The client and the server are generally far from each other and usually interact via a communication network. The client-server relationship is created by computer programs running on respective computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or a cloud host, which is a host product in the cloud computing service system, and solves the defects of difficult management and weak business scalability existing in traditional physical hosts and VPS services.

[0115] It should be understood that various forms of the processes shown above can be used, steps can be reordered, added or deleted. For example, the steps described in the present invention can be executed in parallel, sequentially or in a different order, as long as the desired results of the technical solution of the present invention can be achieved, and no limitation is made herein.

[0116] The above specific embodiments do not constitute a limitation on the protection scope of the present invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A quality assessment method for tender documents, characterized in that, Including: Parsing the file directory of the target tender document to generate a page index container, and parsing the file body of the target tender document to generate a content vector container; wherein, the page index container is used to store the directory information of the target tender document, and the content vector container is used to store the body information of the target tender document; Using a large language model to generate an initial tender directory tree for the tender document, and traversing the title information in the page index container to determine whether the title information exists in the initial tender directory tree; If it does not exist in the initial tender directory tree, use the large language model to obtain the file content features corresponding to the title information in the tender document, determine the storage node corresponding to the file content features in the content vector container, and update the initial tender directory tree according to the file information of the target tender document stored in the storage node to generate a target tender directory tree; wherein, the initial tender directory tree includes the directory feature information of the tender document, which is used to represent the necessary feature directory of the tender document; the target tender directory tree includes the file body information of the target tender document; Based on the target tender directory tree, use a large language model to analyze the content features of the target tender document, and generate a tender index container according to the analysis results returned by the large language model; wherein, the tender index container is used to store the tender index information indicated by the target tender document; Based on the tender index container, conduct a quality assessment of the target tender document; Among them, the conducting a quality assessment of the target tender document based on the tender index container includes: Segmenting the target tender document according to the title information of the target tender document to generate tender sub - contents; Taking the tender sub - content, the title information to which the tender sub - content belongs, and the page number information corresponding to the title information as a container node to generate a tender document content container; For each tender index information indicated by the index node in the tender index container, traverse the container nodes in the tender document content container to determine whether the index information exists in the tender document content container; If it exists, the quality inspection of the target tender document passes.

2. The method according to claim 1, characterized in that, The parsing the file directory of the target tender document to generate a page index container, and parsing the file body of the target tender document to generate a content vector container includes: Identifying the file directory of the target tender document to determine the title information of the target tender document and the page number information corresponding to the title information; Storing the title information of the target tender document and the page number information corresponding to the title information in the page index container in the form of key - value pairs; Determining the title level path of the title information of the target tender document according to the subordinate relationship between the title information in the target tender document; Segmenting the target tender document according to the title information of the target tender document to generate tender sub - contents corresponding to each title information, and normalizing the vectors of the tender sub - contents; Create a storage node for each title information in the target tender document to generate a content vector container; wherein, the storage node is used to store the title hierarchical path, the vector normalization value of the tender sub-content, and the page number information corresponding to the title information, and the node identifier of the storage node is determined according to the title hierarchical path.

3. The method according to claim 1, wherein The quality assessment of the target tender document based on the tender index container further includes: Traverse the index nodes in the tender index container to determine the tender qualification criteria for bidders indicated in the target tender document; Determine the tender sub-content corresponding to the tender qualification criteria in the tender document content container; verify whether the tender sub-content meets the tender qualification criteria, and if it meets, determine that the target tender document meets the tender qualification indicated by the target tender document.

4. The method according to claim 1, wherein The content feature analysis of the target tender document using a large language model based on the target tender directory tree and generating a tender index container according to the analysis result returned by the large language model includes: Traverse the nodes in the target tender directory tree. If the storage object in the node is directory feature information, obtain the tender sub-content corresponding to the directory feature information in the target tender document, and use the large language model to analyze the tender sub-content to determine the tender index corresponding to the tender sub-content; If the storage object in the node is the file information of the target tender document, use the large language model to analyze the file information to determine the tender index corresponding to the file information; store the tender index to generate a tender index container.

5. A quality evaluation device for tender documents, characterized in that, It includes: A tender parsing module for parsing the file directory of the target tender document to generate a page index container and parsing the file body of the target tender document to generate a content vector container; wherein, the page index container is used to store the directory information of the target tender document, and the content vector container is used to store the body information of the target tender document; A tender directory module for generating a target tender directory tree based on the initial tender directory tree, the page index container, and the content vector container; wherein, the initial tender directory tree includes the directory feature information of the tender document, which is used to represent the necessary feature directories of the tender document; the target tender directory tree includes the file body information of the target tender document; A tender index module for performing content feature analysis on the target tender document using a large language model based on the target tender directory tree and generating a tender index container according to the analysis result returned by the large language model; wherein, the tender index container is used to store the tender index information indicated by the target tender document; A quality assessment module for performing quality assessment on the target tender document based on the tender index container; Among them, the tender directory module includes: An initial directory unit for using a large language model to generate an initial tender directory tree of the tender document and traversing the title information in the page index container to determine whether the title information exists in the initial tender directory tree; A target directory generation unit, which, if it does not exist in the initial tender directory tree, uses a large language model to obtain the file content features corresponding to the title information in the tender document, determines the storage node corresponding to the file content features in the content vector container, and updates the initial tender directory tree according to the file information of the target tender document stored in the storage node to generate a target tender directory tree; Among them, the quality assessment module includes: A tender segmentation unit, which is used to segment the target tender document according to the title information of the target tender document to generate tender sub - contents; A tender container generation unit, which is used to use the tender sub - content, the title information to which the tender sub - content belongs, and the page number information corresponding to the title information as a container node to generate a tender document content container; A quality assessment unit, which is used to traverse the container nodes in the tender document content container for each tender index information indicated by the index nodes in the tender index container to determine whether the index information exists in the tender document content container; if it exists, the quality inspection of the target tender document passes.

6. An electronic device, characterized in that, The electronic device includes: At least one processor; And a memory communicatively connected to the at least one processor; Among them, the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the quality assessment method of the tender document according to any one of claims 1 - 4.

7. A computer-readable storage medium, characterized in that, The computer - readable storage medium stores computer instructions, and the computer instructions are used to implement the quality assessment method of the tender document according to any one of claims 1 - 4 when executed by a processor.

8. A computer program product, characterized in that, It includes a computer program, and the computer program implements the quality assessment method of the tender document according to any one of claims 1 - 4 when executed by a processor.

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