Green purchase list management system

Abstract

The embodiment of the invention relates to a green purchase list management system, and the system comprises a data collection and arrangement and database subsystem which is used for carrying out data source collection, and constructing a big data index database; an application enterprise module of the green purchase list management subsystem is used for receiving enterprise login information; the authentication mechanism module calls a big data index database for verification according to the authentication certificate and the PI N code; the application enterprise module receives enterprise information and declaration information after receiving the authentication passing message, the enterprise information comprises enterprise basic information and sales contact information, and the declaration information comprises product information and a commitment book; the management mechanism generates list publicity information according to the enterprise information and the declaration information, and displays the product list and the enterprise; the list publication information is sent to an application enterprise module; and the management mechanism module receives auditing information for adjusting the product information, and generates formal list information after the auditing is passed.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a green purchase list management system. Background Art

[0002] There is an urgent need to apply mainstream information management technology and big data technology to the information resource library for corporate environmental protection requirements, the information resource library for environmental label products, and the resource library for corporate environmental archives, so as to collect, analyze, process, and manage the interface docking methods with various existing information systems and various types of unstructured data, and initially form an effective corporate environmental information big data collection library.

[0003] In the prior art, data in the existing green procurement list management system requires a lot of manual processing by business personnel before a public list can be finally formed (only twice a year). If the frequency of list publication is adjusted to once a month, it is basically impossible to complete the list publication through manual processing.

[0004] The use process requires a lot of reliance on existing developers to participate in data processing, which has affected the long-term healthy operation and maintenance of the system. Automatic data docking cannot be achieved. With the increase in business volume and data volume of the new generation of product systems, the IT operation and maintenance pressure of the bilateral systems will inevitably increase.

[0005] Therefore, a new green procurement list management system is urgently needed. Summary of the invention

[0006] The purpose of the present invention is to provide a green purchasing list management system to solve the problems existing in the prior art.

[0007] To achieve the above objectives, the present invention provides a green purchasing list management system, comprising:

[0008] The data collection, collation and database subsystem is used to collect data sources, including a first type of data source and a second type of data source; process the first type of data source and the second type of data source to build a big data index library;

[0009] Green purchase list management subsystem, including management agency module, certification agency module, and application enterprise module;

[0010] The application enterprise module is used to receive enterprise login information, which includes an authentication certificate and a PIN code, and send the authentication certificate and PIN code to the authentication authority module;

[0011] The certification authority module calls the big data index library for verification based on the certification certificate and the PIN code, and after the verification is passed, sends a certification pass message to the applicant enterprise module;

[0012] After receiving the authentication pass message, the application enterprise module receives enterprise information and declaration information, wherein the enterprise information includes basic enterprise information and sales contact information, and the declaration information includes product information and a letter of commitment; and sends the product information and declaration information to the management agency module;

[0013] The management agency generates list disclosure information based on the enterprise information and declaration information, and displays the product list and enterprise; and sends the list disclosure information to the applicant enterprise module;

[0014] The application enterprise module receives the adjusted product information based on the list public information, and sends the adjusted product information to the management agency module;

[0015] The management agency module receives the review information for the adjusted product information, and generates formal list information after the review is passed.

[0016] In a possible implementation, the management agency module is also used to intelligently review the declared information through machine learning and natural language processing technology to determine risk points and non-compliant items. In a possible implementation, the certification agency module calls the big data index library for verification based on the certification certificate and the PIN code, and after the verification is passed, sends a certification pass message to the applicant enterprise module. Specifically used for:

[0017] The certification authority module calls the big data index library for verification based on the certification certificate and the PIN code, verifies the enterprise, and when the enterprise passes the verification, verifies the product. When the product passes the verification, an environmental label certificate is generated and sent to the data collection and database subsystem;

[0018] The data collection, collation and database subsystem stores the environmental label certificate.

[0019] In one possible implementation, the basic enterprise information includes the manufacturer name, manufacturer address, nature of the enterprise, legal representative, organization code certificate, contact name, contact landline number, contact email, and contact mobile phone; the shareholder detailed information includes shareholder name, investment amount, and investment ratio; the sales contact information includes the name and contact information of the sales contact and the supervisor.

[0020] In a possible implementation, the product information includes declaration guide, product editing, list draft form, list product query, review status query, and historical product functions.

[0021] In a possible implementation, before receiving the declaration information, the application enterprise module further includes:

[0022] When a product is selected to be added to the purchase list and the CA electronic signature is received, declaration information is generated.

[0023] In a possible implementation, the management agency module is also used to extract and save the letter of commitment in the declaration information.

[0024] In a possible implementation, the data collection, collation and database subsystem is specifically used for:

[0025] The second type of data source is unstructured data, including text files, image data, audio data and video data;

[0026] Cleaning and format conversion of the text files, image data, audio data and video data;

[0027] Extract keywords from text data;

[0028] Use computer vision technology to extract features from image data;

[0029] Extracting audio features from audio data using sound recognition technology; the audio features include pitch and frequency;

[0030] Based on computer vision technology and sound recognition technology, the video data is processed to obtain time series image data and audio features;

[0031] Annotate keywords, image data features, and audio features, and add classification labels;

[0032] The index structure is determined based on the data characteristics and query requirements; the index structure includes an inverted index, a hash table, and a tree structure;

[0033] An index is constructed based on the extracted features and the index structure.

[0034] In a possible implementation, the data collection, collation and database subsystem is also used to compress or partition the index to optimize the index.

[0035] By applying the green purchase list management system provided by the embodiment of the present invention, an index can be constructed based on big data, and the three-party connection between enterprises, certification and management agencies is realized, thereby improving the procurement processing efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 A schematic diagram of the structure of a green purchasing list management system provided by an embodiment of the present invention;

[0037] Figure 2 This is a flow chart of the data collection and database subsystem. DETAILED DESCRIPTION

[0038] In order to make the purpose, technical scheme and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0039] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments.

[0040] Figure 1 This is a schematic diagram of the structure of the green purchase list management system provided by the embodiment of the present invention. The green purchase list management system includes a data collection and sorting and database subsystem and a green purchase list management subsystem. Figure 1 , the technical solution of the present invention is described with specific embodiments.

[0041] The data collection, collation and database subsystem 1 is used to collect data sources, including a first type of data source and a second type of data source; process the first type of data source and the second type of data source to build a big data index library.

[0042] Specifically, the first type of data source is structured data, and the second type of data source is unstructured data.

[0043] For the first type of data source, you can directly build single-column indexes, composite indexes, unique indexes, full-text indexes, clustered indexes, and non-clustered indexes. When building indexes for structured data, you can analyze the requirements, determine which fields are most commonly used for queries, and consider the selectivity of these fields, that is, the ratio of the number of different values ​​to the total number of records, and then select the appropriate index type, that is, select the appropriate index type according to the data type of the field and the query requirements. Finally, create the index, that is, use SQL statements or other database management tools to create the index.

[0044] For unstructured data, it includes text files, image data, audio data and video data. First, the text files, image data, audio data and video data are cleaned and formatted; wherein, cleaning is to remove irrelevant or redundant information, such as HTML tags, special characters, etc., and formatting is to convert data of different formats into a unified format for subsequent processing. Then, keyword extraction is performed on the text data; wherein, natural language processing technology (such as word segmentation, stemming, and word vectorization) can be used to extract features such as keywords and themes. Then, feature extraction is performed on the image data using computer vision technology; for example, feature extraction is performed using convolutional neural networks. Then, audio features are extracted from the audio data using sound recognition technology; the audio features include pitch and frequency; then, the video data is processed according to computer vision technology and sound recognition technology to obtain image data and audio features of the time series; then, the keywords, features of the image data, and audio features are annotated and classification labels are added; for example, the data is manually or automatically annotated, and classification labels or other attribute information are added to each piece of data. Next, the data characteristics and query requirements determine the index structure; the index structure includes an inverted index, a hash table, and a tree structure; finally, an index is constructed based on the extracted features and the index structure. Thus, the index is constructed based on the extracted features, so that relevant data records can be quickly located.

[0045] Furthermore, the index can be compressed or partitioned to optimize the index.

[0046] This application is aimed at green procurement. Therefore, the index library constructed by the data collection and collation and database subsystem can be sorted for each enterprise and the big data document source of each enterprise, thereby establishing the big data index library to facilitate subsequent enterprise authentication, verification and other operations.

[0047] The green purchase list management subsystem 2 includes an application enterprise module 21, a certification body module 22 and a management agency module 23; wherein the management agency module may be a module logged into by a manager terminal, the certification body module may be a module for accessing a certification body and used for logging into by a certification body terminal, and the application enterprise module is a module logged into by an enterprise terminal.

[0048] The application enterprise module is used to receive enterprise login information, which includes an authentication certificate and a PIN code, and send the authentication certificate and PIN code to the authentication authority module;

[0049] The certification body module calls the big data index library for verification based on the certification certificate and the PIN code, and after the verification is passed, sends a certification pass message to the applicant enterprise module.

[0050] Among them, the big data index library stores the company's information, including the number of certified people and PIN codes of the company. It can be directly called to determine whether the certification certificate and PIN code exist.

[0051] After receiving the authentication pass message, the application enterprise module receives enterprise information and declaration information, wherein the enterprise information includes basic enterprise information, shareholder details and sales contact information, and the declaration information includes product information and a letter of commitment; and sends the product information and declaration information to the management agency module.

[0052] Among them, the basic information of the enterprise includes the manufacturer name, manufacturer address, enterprise nature, legal representative, organization code certificate, contact name, contact landline, contact email, contact mobile phone; the shareholder detailed information includes shareholder name, investment amount, investment ratio; the sales contact information includes the name and contact information of the sales contact and the supervisor. Product information is the basic information of the product to be declared. The commitment letter is the commitment information submitted after receiving the confirmation selection message in the whether to commit option when submitting the declaration information. The commitment letter includes the enterprise commitment letter and the historical commitment letter. Enterprise commitment letter The enterprise makes a commitment to the products added to the list, and the CA electronic signature is affixed to the commitment letter, which has legal effect. Once the commitment letter is signed, the product editing function and the deletion function of the publicized product will no longer be able to operate. When signing the commitment letter, you must first click "Sign" and then click "Submit" after the "Sign Success" prompt appears. The historical commitment letter is to archive the commitment letters submitted by the enterprise, and the historical commitment letters can be queried.

[0053] During the public announcement period and when the company's commitment has not been signed, the detailed information of the product can be filled in and maintained; including product query and export. The query includes: querying the company's products by item, brand, product model, certificate number, certificate expiration date, whether it is included in the list, and product status. Export includes generating an EXCEL file. Edit as: The company can only edit the product during the reporting period and when the commitment has not been signed. If "Is it added to the purchase list" is selected as yes, the required items can be saved after they are filled in. When "Is it added to the purchase list" is selected as no, the required items can be saved without filling in. Product details and product images are not required, and the rest are required.

[0054] The management agency generates list disclosure information based on the enterprise information and declaration information, and displays the product list and the enterprise; and sends the list disclosure information to the applicant enterprise module.

[0055] Among them, the list disclosure information includes the product list, which includes the enterprise product list, the list disclosure draft, the list approval draft, and the current data archive backup. The list approval draft can query the product data of the reviewed enterprise.

[0056] The application enterprise module receives the adjusted product information based on the list public information, and sends the adjusted product information to the management agency module;

[0057] The adjusted product information refers to the information after the product information is adjusted.

[0058] The management agency module receives the review information for the adjusted product information, and generates formal list information after the review is passed.

[0059] The management agency module is also used to conduct intelligent review of declared information through machine learning and natural language processing technology to identify risk points and non-compliance items.

[0060] Specifically, first, collect a large amount of historical declaration information, including approved and unapproved cases. Collect the corresponding review results, including approval, rejection, and need for additional materials. Mark the risk points and non-compliant items of each declaration information. Then, perform data preprocessing, including text cleaning, removing irrelevant characters, punctuation, stop words, etc., and retaining the core content. Standardization, standardize the text content, such as unifying the date format, amount unit, etc. Feature extraction, extract useful features from the text, such as keywords, entities, syntactic structures, etc. Next, perform feature engineering processing, including text feature extraction, including calculating the importance of words to distinguish keywords from ordinary words. Use pre-trained word embedding models (such as Word2Vec, G loVe) to convert words into vector representations. Named entity recognition, identify and extract entity information such as names of people, places, and organizations. Feature extraction includes field value extraction, extracting key field values ​​in the declaration form, such as applicant name, contact information, declaration type, etc. Time feature extraction, extracting time-related features, such as declaration date, deadline, etc. Numerical feature extraction, extracting numerical features such as quantity. Next, the model is selected and trained. At this time, the machine learning models include but are not limited to logistic regression, random forest, support vector machine, and gradient boosting tree. Then the model is trained. Including: Data partitioning: Divide the data set into training set, validation set, and test set. Training process: Use the training set to train the model, use the validation set to tune the hyperparameters, and use the test set to evaluate the model performance. Loss function: Select a suitable loss function, such as cross entropy loss, mean square error loss, etc. Optimization algorithm: Use gradient descent, Adam and other optimization algorithms for model training. Finally, identify risk points and non-compliant items. Including: Rule matching: Define a series of rules, such as keyword matching, pattern matching, etc., for preliminary screening of potential risk points. Model prediction: Use the trained model to predict the declared information and output risk scores and non-compliant items. Comprehensive judgment: Combine the rule matching and model prediction results to comprehensively judge the risk points and non-compliant items of the declared information.

[0061] Further, the certification authority module calls the big data index library for verification according to the certification certificate and the PIN code, and after the verification is passed, sends a certification pass message to the applicant enterprise module for:

[0062] The certification authority module calls the big data index library for verification based on the certification certificate and the PIN code, verifies the enterprise, and when the enterprise passes the verification, verifies the product. When the product passes the verification, an environmental label certificate is generated and sent to the data collection and database subsystem;

[0063] The data collection and database subsystem stores the environmental label certificate for subsequent use.

[0064] Specifically, the product certification module is the main channel for enterprises to apply for environmental label certificates. It can obtain detailed information related to enterprises at the first time. The relevant information uploaded by the enterprise can also be used as an important part of the enterprise archive. The system needs to realize the import of formatted data of required enterprise information and the collection of enterprise data of information systems that store relevant enterprise information. It needs to complete the interface call of enterprise archives and contact archives in the certification business system and reflect it in this project. Implement the file management module for electronic attachments.

[0065] By applying the green purchase list management system provided by the embodiment of the present invention, an index can be constructed based on big data, and the three-party connection between enterprises, certification and management agencies is realized, thereby improving the procurement processing efficiency.

[0066] The professionals should further realize that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in the above description according to the function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0067] The steps of the method or algorithm described in conjunction with the embodiments disclosed herein may be implemented using hardware, a software module executed by a processor, or a combination of the two. The software module may be placed in a random access memory (RAM), a memory, a read-only memory (ROM), an electrically programmable ROM, an electrically erasable programmable ROM, a register, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

[0068] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A green purchase list management system, characterized in that: The system comprises: The data collection, collation and database subsystem is used to collect data sources, including a first type of data source and a second type of data source; process the first type of data source and the second type of data source to build a big data index library; Green purchase list management subsystem, including management agency module, certification agency module, and application enterprise module; The application enterprise module is used to receive enterprise login information, which includes an authentication certificate and a PIN code, and send the authentication certificate and the PIN code to the authentication authority module; The certification authority module calls the big data index library for verification based on the certification certificate and the PIN code, and after the verification is passed, sends a certification pass message to the applicant enterprise module; After receiving the authentication pass message, the application enterprise module receives enterprise information and declaration information, wherein the enterprise information includes basic enterprise information and sales contact information, and the declaration information includes product information and a letter of commitment; and sends the product information and declaration information to the management agency module; The management agency generates list disclosure information based on the enterprise information and declaration information, and displays the product list and enterprise; and sends the list disclosure information to the applicant enterprise module; The application enterprise module receives the adjusted product information based on the list public information, and sends the adjusted product information to the management agency module; The management agency module receives the review information for the adjusted product information, and generates formal list information after the review is passed.

2. The system according to claim 1, characterized in that The management agency module is also used to conduct intelligent review of declared information through machine learning and natural language processing technology to identify risk points and non-compliance items.

3. The system according to claim 1, characterized in that The certification authority module calls the big data index library for verification according to the certification certificate and the PIN code, and after the verification is passed, sends a certification pass message to the applicant enterprise module specifically for: The certification authority module calls the big data index library for verification based on the certification certificate and the PIN code, verifies the enterprise, and when the enterprise passes the verification, verifies the product. When the product passes the verification, an environmental label certificate is generated and sent to the data collection and database subsystem; The data collection, collation and database subsystem stores the environmental label certificate.

4. The system according to claim 1, characterized in that The basic information of the enterprise includes the manufacturer's name, manufacturer's address, nature of the enterprise, legal representative, organization code certificate, contact name, contact landline number, contact email address, and contact mobile phone number; the sales contact information includes the name and contact information of the sales contact and supervisor.

5. The system according to claim 1, characterized in that The product information includes declaration guide, product editing, list draft form, list product query, review status query, and historical product functions.

6. The system according to claim 1, characterized in that Before receiving the declaration information, the application enterprise module also includes: When a product is selected to be added to the purchase list, declaration information is generated.

7. The system according to claim 6, characterized in that The management agency module is also used to extract and save the letter of commitment in the declaration information.

8. The system according to claim 1, characterized in that The data collection, collation and database subsystem is specifically used for: The second type of data source is unstructured data, including text files, image data, audio data and video data; Cleaning and format conversion of the text files, image data, audio data and video data; Extract keywords from text data; Use computer vision technology to extract features from image data; Extracting audio features from audio data using sound recognition technology; the audio features include pitch and frequency; Based on computer vision technology and sound recognition technology, the video data is processed to obtain time series image data and audio features; Annotate keywords, image data features, and audio features, and add classification labels; Determine the index structure according to data characteristics and query requirements; the index structure includes an inverted index, a hash table, and a tree structure; An index is constructed based on the extracted features and the index structure.

9. The system according to claim 8, characterized in that The data collection, collation and database subsystem is also used to compress or partition the index to optimize the index.

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