Purchase associated information display method and device based on AI large model, equipment and medium

Abstract

The invention discloses a procurement associated information display method and device based on an AI large model, equipment and a medium, and belongs to the technical field of Internet. The method comprises the following steps: collecting material information, and storing the material information in a database; receiving a target material input by a user; searching the historical price of the target material, the supplier quotation and the supplier basic information in the material information pre-stored in the database; determining the price trend of the target material according to the historical price and the supplier quotation, and determining the comprehensive supply capability of the supplier according to the supplier basic information; and displaying the price trend of the target material and the comprehensive supply capability of the supplier to the user. According to the technical scheme, the related information of the materials needing to be purchased by the user can be counted, sorted and displayed, so that the user can quickly know the price change trend of the materials and the related information of suppliers, the comprehensive supply capability of each supplier is determined, and the purchasing efficiency and the decision-making quality are remarkably improved.

Description

Technical Field

[0001] The present application belongs to the field of Internet technology, and specifically relates to an application request processing method, device, equipment and medium. Background Art

[0002] In the procurement management of modern enterprises, choosing suitable suppliers and reasonable procurement prices are the keys to achieving cost control and improving procurement efficiency.

[0003] At present, the traditional procurement method usually requires staff to manually collect and compare the historical transaction prices of the required materials, supplier quotations and supplier transaction quality, and select the best solution from them. This procurement method is highly dependent on manual experience, and collecting information consumes a lot of time and energy. It is prone to statistical entry errors, resulting in low material procurement efficiency.

[0004] Therefore, how to provide users with comprehensive material procurement information is a technical problem that needs to be solved urgently by technical personnel in this field. Summary of the invention

[0005] The embodiments of the present application provide a method, device, equipment and medium for displaying procurement-related information based on an AI big model, the purpose of which is to count, organize and display relevant information of materials that users need to purchase, so that users can quickly understand the price change trend of materials and relevant information of suppliers, thereby determining the comprehensive supply capacity of each supplier and significantly improving procurement efficiency and decision-making quality.

[0006] In a first aspect, this embodiment provides a method for displaying procurement-related information based on an AI big model, the method comprising:

[0007] Collect material information and store the material information in a database; wherein the material information includes material name, historical price, supplier quotation and supplier basic information;

[0008] Receive target materials input by users;

[0009] Retrieving historical prices, supplier quotations, and basic supplier information corresponding to the target material from the material information pre-stored in the database;

[0010] Determine the price trend of the target material according to the historical price and the supplier's quotation, and determine the supplier's comprehensive supply capacity according to the supplier's basic information;

[0011] The price trend of the target material and the comprehensive supply capacity of the supplier are displayed to the user to assist the user in completing the purchase of the target material.

[0012] Further, collecting material information and storing the material information in a database includes:

[0013] Obtain material information from the resource management system according to a preset cycle, or receive material information uploaded by users;

[0014] Identify missing values ​​and outliers in material information, delete material information with missing values ​​or outliers, and store the deleted material information in the database.

[0015] After further retrieving the historical price, supplier quotation and supplier basic information corresponding to the target material from the material information pre-stored in the database, the method further includes:

[0016] When historical prices, supplier quotations or basic supplier information are missing, the corresponding missing information is retrieved through big data and the material information is supplemented.

[0017] Further, determining the price trend of the target material according to the historical price and the supplier's quotation includes:

[0018] Inputting the historical prices and corresponding years into a pre-built price prediction model, and obtaining the predicted price of the predicted year through the price prediction model;

[0019] Mark the historical prices and the predicted prices in the price trend graph of the target material according to the corresponding years, and draw a material price curve;

[0020] The quotations of each supplier are marked in the price trend chart of the target material according to the corresponding year, and the supplier quotation curve is drawn.

[0021] Furthermore, before inputting the historical prices and corresponding years into the pre-built price prediction model, the method further includes:

[0022] The prices of preset years in historical prices are used as labels, and the remaining prices and their years are used as input variables for supervised training to build a price prediction model.

[0023] Furthermore, the comprehensive supply capacity of the supplier is determined based on the basic information of the supplier, including:

[0024] Obtaining basic information of historical suppliers, and predicting the comprehensive supply capacity of suppliers based on the basic information of historical suppliers to obtain training samples;

[0025] Performing supervised training on the training samples to build a comprehensive supply capacity analysis model;

[0026] The basic information of the supplier is input into a pre-built comprehensive supply capacity analysis model, and the comprehensive supply capacity of the supplier is predicted by the comprehensive supply capacity analysis model.

[0027] Furthermore, before displaying the price trend of the target material and the comprehensive supply capacity of the supplier to the user, the method includes:

[0028] Determining recommended suppliers based on the supplier's comprehensive supply capacity forecast results, and generating price negotiation suggestions based on the price trend chart;

[0029] Accordingly, the price trend of the target material and the comprehensive supply capacity of the supplier are displayed to the user, including:

[0030] The price trend chart, supplier comprehensive supply capacity forecast results, recommended suppliers and price negotiation suggestions are displayed to users.

[0031] In a second aspect, this embodiment provides a procurement-related information display device based on an AI big model, the device comprising:

[0032] A material information collection module is used to collect material information and store the material information in a database; wherein the material information includes material name, historical price, supplier quotation and supplier basic information;

[0033] A target material determination module is used to receive the target material input by the user;

[0034] A target material retrieval module is used to retrieve the historical price, supplier quotation and supplier basic information corresponding to the target material from the material information pre-stored in the database;

[0035] A retrieval information analysis module, used to determine the price trend of the target material according to the historical price and the supplier's quotation, and to determine the supplier's comprehensive supply capacity according to the supplier's basic information;

[0036] The analysis result display module is used to display the price trend of the target material and the comprehensive supply capacity of the supplier to the user, so as to assist the user in completing the purchase of the target material.

[0037] In a third aspect, an embodiment of the present application provides an electronic device, which includes a processor, a memory, and a program or instruction stored in the memory and executable on the processor, wherein the program or instruction, when executed by the processor, implements the steps of the method described in the first aspect.

[0038] In a fourth aspect, an embodiment of the present application provides a readable storage medium, on which a program or instruction is stored, and when the program or instruction is executed by a processor, the steps of the method described in the first aspect are implemented.

[0039] In a fifth aspect, an embodiment of the present application provides a chip, comprising a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is used to run a program or instruction to implement the method described in the first aspect.

[0040] In an embodiment of the present application, material information is collected and stored in a database; wherein the material information includes material name, historical price, supplier quotation and supplier basic information; a target material input by a user is received; the historical price, supplier quotation and supplier basic information corresponding to the target material are retrieved from the material information pre-stored in the database; the price trend of the target material is determined based on the historical price and the supplier quotation, and the comprehensive supply capacity of the supplier is determined based on the supplier basic information; the price trend of the target material and the comprehensive supply capacity of the supplier are displayed to the user to assist the user in completing the purchase of the target material. Through the above-mentioned method of displaying procurement-related information based on an AI large model, relevant information of the materials that the user needs to purchase can be counted, sorted and displayed, so that the user can quickly understand the price trend of the material and the relevant information of the supplier, thereby determining the comprehensive supply capacity of each supplier, and significantly improving procurement efficiency and decision-making quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 It is a flowchart of a method for displaying procurement-related information based on an AI big model provided in Embodiment 1 of the present application;

[0042] Figure 2 This is a schematic diagram of a display screen for receiving a target material input by a user provided in the first embodiment of the present application;

[0043] Figure 3 This is a schematic diagram of a display screen of the comprehensive supply capability of a supplier provided in the first embodiment of the present application;

[0044] Figure 4 It is a flowchart of a method for displaying procurement-related information based on an AI big model provided in Embodiment 2 of the present application;

[0045] Figure 5 It is a flowchart of a method for displaying procurement-related information based on an AI big model provided in Embodiment 3 of the present application;

[0046] Figure 6 This is a schematic diagram of a material price curve display screen provided in Example 3 of the present application;

[0047] Figure 7 It is a flowchart of a method for displaying procurement-related information based on an AI big model provided in Embodiment 4 of the present application;

[0048] Figure 8 It is a flowchart of the AI ​​model provided in the fourth embodiment of the present application providing a procurement auxiliary analysis report;

[0049] Fig. 9 This is a structural diagram of a procurement-related information display device based on an AI large model provided in Embodiment 5 of the present application;

[0050] Fig.10 It is a structural diagram of an electronic device provided in Example 6 of the present application. DETAILED DESCRIPTION

[0051] In order to make the purpose, technical scheme and advantages of the present application clearer, the specific embodiments of the present application are further described in detail below in conjunction with the accompanying drawings. It is understood that the specific embodiments described herein are only used to explain the present application, rather than to limit the present application. It should also be noted that, for the convenience of description, only the part related to the present application but not all the contents are shown in the accompanying drawings. Before discussing the exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flow charts. Although the flow chart describes each operation (or step) as a sequential process, many of the operations therein can be implemented in parallel, concurrently or simultaneously. In addition, the order of each operation can be rearranged. The process can be terminated when its operation is completed, but it can also have additional steps not included in the accompanying drawings. The process can correspond to a method, a function, a procedure, a subroutine, a subprogram, etc.

[0052] The following will be combined with the drawings in the embodiments of the present application to clearly describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments in the present application belong to the scope of protection of this application.

[0053] The terms "first", "second", etc. in the specification and claims of the present application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable under appropriate circumstances, so that the embodiments of the present application can be implemented in an order other than those illustrated or described here, and the objects distinguished by "first", "second", etc. are generally of one type, and the number of objects is not limited. For example, the first object can be one or more. In addition, "and / or" in the specification and claims represents at least one of the connected objects, and the character " / " generally indicates that the objects associated with each other are in an "or" relationship.

[0054] In combination with the accompanying drawings, a procurement-related information display method, device, equipment and medium based on an AI big model provided by an embodiment of the present application are described in detail through specific embodiments and their application scenarios.

[0055] Embodiment 1

[0056] Figure 1 It is a flow chart of a method for displaying procurement-related information based on an AI big model provided in Example 1 of the present application.

[0057] like Figure 1 As shown, the specific steps include:

[0058] S101, collecting material information and storing the material information in a database; wherein the material information includes material name, historical price, supplier quotation and supplier basic information;

[0059] The application scenario of this solution can be to retrieve and display relevant information of the target material to assist the user in determining the supplier and the purchase price of the target material.

[0060] Based on the above scenario, it can be understood that the executor of this scenario can be an intelligent terminal used to retrieve and display material information, such as a computer or software component that provides services in a network environment, etc., and no excessive limitations are made here.

[0061] Material name, which can be the name of the item or raw material to be purchased, for example, aluminum, steel, or diode, etc.

[0062] The historical price can be the transaction price when purchasing materials in previous years, or the average transaction price of the material in the market in previous years.

[0063] The supplier quotation can be the selling price of the material by each supplier of the material.

[0064] The basic information of suppliers can be the production scale, product quality, industry reputation and other related information of the supplier selling the materials. A comprehensive analysis of the supplier's quotation and basic information can help you choose a supplier with low price and high quality to purchase materials.

[0065] The material information can be collected by staff by compiling and organizing the material information of the materials needed by the enterprise or the material purchase records of previous years, and entering them into a designated database for storage.

[0066] S102, receiving a target material input by a user;

[0067] The target material can be the material that the user wants to purchase or query related information.

[0068] The method of receiving the target material input by the user can be that the user enters the name of the target material in a designated input box through the terminal device, and the terminal device obtains the specific content entered by the user and sends it to the smart terminal for reception. For example, Figure 2 is a schematic diagram of a display screen for receiving a target material input by a user provided in the first embodiment of the present application, such as Figure 2 As shown, the user can enter the name of the target material in the input box after the material name, and the display will record the user's input and send it to the server for processing.

[0069] S103, searching the material information pre-stored in the database for the historical price, supplier quotation and supplier basic information corresponding to the target material;

[0070] The method of retrieving the historical price, supplier quotation and basic supplier information corresponding to the target material may be to search the target material in the database and extract the historical price, supplier quotation and basic supplier information associated with the material name consistent with the target material. For example, if the name of the target material "steel" is searched in the database, the search result is the record related to steel in the database, that is, the historical price of steel, the quotation of steel supplier and the basic information of steel supplier, and the search result is obtained.

[0071] S104, determining the price trend of the target material according to the historical price and the supplier's quotation, and determining the supplier's comprehensive supply capacity according to the supplier's basic information;

[0072] The comprehensive supply capacity of a supplier can be a comprehensive assessment of the supplier's delivery speed, the quality of the materials provided, and the selling price of the materials, so as to determine the advantages and disadvantages of each supplier and enable staff to select the best supplier for transactions based on procurement needs.

[0073] The price trend of the target material can be determined by calculating and analyzing the historical price of the target material and the change in the quotations of each supplier over time, obtaining a functional relationship that fits the historical price and the year-on-year change trend of the supplier's quotation, and displaying the price trend of the target material through the specified coefficient in the functional relationship. For example, the historical price change trend of the target material is fitted with a power function, in which the size of the year independent variable coefficient can represent the annual growth rate of the target material price.

[0074] The way to determine the comprehensive supply capacity of suppliers can be to score the basic information of suppliers, and use the sum of the scores as the representation data of the comprehensive supply capacity of suppliers. For example, supplier A has a small production scale and slow material delivery, with a score of 25, and a qualified rate of 99% of the materials produced, with a score of 42; supplier B has a large production scale and faster material delivery, with a score of 37, and a qualified rate of 98% of the materials produced, with a score of 38; then the comprehensive supply capacity score of supplier A is 67, and the comprehensive supply capacity score of supplier B is 75. For example, Figure 3 : is a schematic diagram of a display screen of the comprehensive supply capability of a supplier provided in the first embodiment of the present application, such as Figure 3 As shown, the comprehensive supply capabilities of supplier a, supplier b and supplier c of the target material received scores of 95, 84 and 66 respectively after being scored by the AI ​​large model. The supplier names and their comprehensive supply capability scoring results will be sent by the server to the display for display.

[0075] S105: Display the price trend of the target material and the comprehensive supply capacity of the supplier to the user to assist the user in completing the purchase of the target material.

[0076] The method of displaying price trends and comprehensive supply capabilities to users is that after determining the price trend of the target material and the comprehensive supply capabilities of each supplier, the price trend and at least one comprehensive supply capability are laid out and displayed to the user through a display device so that the user can view relevant information of the target material.

[0077] Based on the above solution, optionally, collecting material information and storing the material information in a database includes:

[0078] Obtain material information from the resource management system according to a preset cycle, or receive material information uploaded by users;

[0079] Identify missing values ​​and outliers in material information, delete material information with missing values ​​or outliers, and store the deleted material information in the database.

[0080] The preset cycle may be a predetermined cycle for obtaining material information. The staff may determine the preset cycle according to the market price update speed of the material or the purchase cycle of the material, thereby ensuring that the latest material information can be obtained when performing material inquiries.

[0081] The resource management system can be a management system used by an enterprise to record the purchase and consumption of materials. The resource management system can record in real time the specific procurement information of various materials of the enterprise over the years, including the purchase time, quantity, price, etc.

[0082] The method of obtaining material information from the resource management system according to a preset period can be that after the preset period is reached, the intelligent terminal sends a material information acquisition request to the resource management library, and after the resource management library responds, the material information stored in the preset period is sorted and sent to the intelligent terminal.

[0083] The method of receiving the material information uploaded by the user can be that the staff organizes the material information to be entered into a table, and uploads the table to the smart terminal through the display device for storage.

[0084] Missing values ​​may be a situation where a certain data in the received material information is missing. For example, in the steel procurement data, the unit purchase price of steel in 2021 is missing.

[0085] Abnormal values ​​can be data with values ​​outside the normal range or garbled characters in the received material information. For example, the purchase price of steel in 2020 is recorded as 1,000,000 yuan / kg or abnormal characters such as "??&" appear.

[0086] The material information can be stored in the database by obtaining the standard storage format of the material information, identifying the data format of the obtained material information, and determining that the data is an abnormal value when the data format of the material information is inconsistent with the standard storage format. At the same time, it is detected whether there is a null value in the material information. If so, the value is determined to be a missing value, and the information record where the missing value and the abnormal value are located is obtained, and the information is deleted. For example, the purchase price of steel in 2020 is recorded as 1,000,000 yuan / kg, of which 1,000,000 yuan / kg exceeds the normal steel price range and is an abnormal value, so the material information "the purchase price of steel in 2020 is recorded as 1,000,000 yuan / kg" where 1,000,000 yuan / kg is located is deleted.

[0087] The advantage of this setting of the scheme is that material information can be obtained in a variety of ways and the stored material information can be cleaned, which is conducive to broadening the channels for obtaining material information and effectively avoiding the problem of data not being recognized during subsequent analysis of material information.

[0088] On the basis of the above solution, optionally, the comprehensive supply capacity of the supplier is determined according to the basic information of the supplier, including:

[0089] Obtaining basic information of historical suppliers, and predicting the comprehensive supply capacity of suppliers based on the basic information of historical suppliers to obtain training samples;

[0090] Performing supervised training on the training samples to build a comprehensive supply capacity analysis model;

[0091] The basic information of the supplier is input into a pre-built comprehensive supply capacity analysis model, and the comprehensive supply capacity of the supplier is predicted by the comprehensive supply capacity analysis model.

[0092] The method for obtaining training samples is to randomly select a part of the historical suppliers of the current material as samples, obtain the basic information of the sample suppliers, and have the staff conduct a comprehensive supply capacity evaluation on the basic information of each sample supplier, and use the basic information of the sample suppliers and the corresponding evaluation results as training samples.

[0093] A comprehensive supply capability analysis model can be constructed by using the basic information of sample suppliers in the training samples as input variables and the corresponding comprehensive supply capability evaluation results as labels, conducting supervised training, obtaining the correlation between the basic information of suppliers and their comprehensive supply capabilities, and then constructing a comprehensive supply capability analysis model that can predict the comprehensive supply capability based on the basic information of suppliers.

[0094] The method for obtaining the comprehensive supply capability of a supplier is to input the obtained basic information of the supplier into a pre-built comprehensive supply capability analysis model, and the comprehensive supply capability analysis model predicts the comprehensive supply capability of the supplier based on the correlation between the learned basic information of the supplier and the comprehensive supply capability of the supplier, and uses the output result of the comprehensive supply capability analysis model as the comprehensive supply capability of the current supplier.

[0095] The benefit of setting up this solution is that the comprehensive supply capacity of suppliers can be predicted through the comprehensive supply capacity analysis model, which is helpful for users to determine the best supplier and to filter out suppliers with slow delivery and poor reputation to a certain extent, thereby improving the quality of material procurement.

[0096] In an embodiment of the present application, material information is collected and stored in a database; wherein the material information includes material name, historical price, supplier quotation and supplier basic information; a target material input by a user is received; the historical price, supplier quotation and supplier basic information corresponding to the target material are retrieved from the material information pre-stored in the database; the price trend of the target material is determined based on the historical price and the supplier quotation, and the comprehensive supply capacity of the supplier is determined based on the supplier basic information; the price trend of the target material and the comprehensive supply capacity of the supplier are displayed to the user to assist the user in completing the purchase of the target material. Through the above-mentioned method of displaying procurement-related information based on an AI large model, relevant information of the materials that the user needs to purchase can be counted, sorted and displayed, so that the user can quickly understand the price trend of the material and the relevant information of the supplier, thereby determining the comprehensive supply capacity of each supplier, and significantly improving procurement efficiency and decision-making quality.

[0097] Embodiment 2

[0098] Figure 4 This is a flow chart of a method for displaying procurement-related information based on an AI big model provided in Example 2 of the present application. This solution makes a better improvement on the above-mentioned embodiment, and the specific improvement is: after retrieving the historical price, supplier quotation and supplier basic information corresponding to the target material from the material information pre-stored in the database, the method also includes: when the historical price, supplier quotation or supplier basic information is missing, the corresponding missing information is retrieved through big data, and the material information is supplemented.

[0099] like Figure 4 As shown, specifically including the following:

[0100] S401, collecting material information and storing the material information in a database; wherein the material information includes material name, historical price, supplier quotation and supplier basic information;

[0101] S402, receiving target materials input by a user;

[0102] S403, searching the material information pre-stored in the database for the historical price, supplier quotation and basic information of the supplier corresponding to the target material;

[0103] S404. When there is a missing historical price, supplier quotation or supplier basic information, the corresponding missing information is retrieved through big data, and the material information is supplemented;

[0104] The material information can be supplemented by checking the historical price, supplier quotation and basic information of the target material in chronological order after retrieving the historical price, supplier quotation and basic information of the supplier, and identifying the basic information of the supplier associated with each supplier quotation. If there is a missing historical price or supplier quotation value in the year of verification, or there is a supplier who has provided a quotation but has no record of the relevant supplier basic information, it is determined that there is missing information in the material information, and the intelligent terminal obtains the missing information through big data and fills it in the corresponding material information in the database. For example, the material information of steel from 2019 to 2024 is retrieved, and it is identified that the price data of steel and the basic information of supplier a are missing in 2020. Then, the market transaction price of steel in 2020 and the industry reputation of supplier a and other related information are searched through big data, and the missing information is filled in the steel information in the database.

[0105] S405, determining the price trend of the target material according to the historical price and the supplier's quotation, and determining the supplier's comprehensive supply capacity according to the supplier's basic information;

[0106] S406: Display the price trend of the target material and the comprehensive supply capacity of the supplier to the user to assist the user in completing the purchase of the target material.

[0107] The advantage of setting up this solution is that when there is missing material information included in the database, the missing information can be supplemented through big data, so that there will be sufficient data support for subsequent predictions of the price trend of the target material and the comprehensive supply capacity of the supplier.

[0108] Embodiment 3

[0109] Figure 5 It is a flow chart of a method for displaying procurement-related information based on an AI large model provided in Example 3 of the present application. This solution makes a better improvement on the above-mentioned embodiment, and the specific improvement is: determining the price trend of the target material according to the historical price and the supplier's quotation, including: inputting the historical price and the corresponding year into a pre-built price prediction model, and obtaining the predicted price of the predicted year through the price prediction model; marking the historical price and the predicted price in the price trend chart of the target material according to the corresponding year, and drawing a material price curve; marking each supplier's quotation in the price trend chart of the target material according to the corresponding year, and drawing a supplier quotation curve.

[0110] like Figure 5 As shown, specifically including the following:

[0111] S501. Collect material information and store the material information in a database; wherein the material information includes material name, historical price, supplier quotation and supplier basic information;

[0112] S502, receiving target materials input by the user;

[0113] S503, searching the material information pre-stored in the database for the historical price, supplier quotation and supplier basic information corresponding to the target material;

[0114] S504, inputting the historical prices and corresponding years into a pre-built price prediction model, and obtaining a predicted price for the predicted year through the price prediction model;

[0115] The pre-built price prediction model may be a pre-built learning model that can predict subsequent material prices based on historical prices of target materials.

[0116] The forecast year can be the year when the user wants to purchase the target material, or the year when the user is querying the target material and its subsequent years. For example, you can set the price forecast for the target material in the next five years.

[0117] The method for obtaining the predicted price is to input the historical prices and year data of the target material into a pre-built price prediction model, and have the price prediction model predict the price of the target material in the prediction year based on its pre-learned related algorithms, and use the output result of the price prediction model as the predicted price of the target material in the prediction year.

[0118] S505, marking the historical prices and the predicted prices in the price trend graph of the target material according to the corresponding years, and drawing a material price curve;

[0119] The way to draw the material price curve is to use the year value as the horizontal axis and the price value as the vertical axis to establish a rectangular coordinate system as a price trend chart, mark the historical price and predicted price values ​​on the corresponding years in the price trend chart, and connect each marked price with a smooth curve in the order of the year to obtain the material price curve. At this time, the trend of the material price curve can represent the upward and downward trend of the target material price. For example, Figure 6 : is a schematic diagram of a material price curve display screen provided in Example 3 of the present application, such as Figure 6 As shown in the figure, after the AI ​​big model draws the material price curve, the server sends the price trend chart and the material price curve to the display and displays them to the user through the display.

[0120] S506, marking the quotations of each supplier in the price trend chart of the target material according to the corresponding year, and drawing a supplier quotation curve;

[0121] The supplier quotation curve can be drawn by marking the quotations of different suppliers with different graphics on the corresponding years in the price trend chart, and connecting the same marked graphics with smooth curves in the order of years to obtain the quotation curves of each supplier. At this time, in the price trend chart, the position difference of the same horizontal axis of the quotation curves of each supplier can represent the difference in the quotations of each supplier in the same year; the direction of the same curve can represent the changing trend of the quotation of the same supplier for the target material in different years.

[0122] S507, determining the comprehensive supply capacity of the supplier according to the basic information of the supplier;

[0123] S508: Display the price trend of the target material and the comprehensive supply capacity of the supplier to the user to assist the user in completing the purchase of the target material.

[0124] The benefit of this scheme is that a price trend chart can be drawn based on the historical price of the target material and the supplier's quotation, which helps users to more intuitively obtain the price change trend of the target material and compare the quotations of various suppliers, thereby gaining an advantage in price negotiations.

[0125] Based on the above solution, optionally, before inputting the historical prices and corresponding years into the pre-built price prediction model, the method further includes:

[0126] The prices of preset years in historical prices are used as labels, and the remaining prices and their years are used as input variables for supervised training to build a price prediction model.

[0127] The preset year can be a year that is preset as a learning object when training the price prediction model. For example, the fifth year of the historical price of the target material in the past five years is used as the preset year. In the training of the price prediction model, the price prediction model needs to learn a method for predicting the price data of the fifth year through the price data of the first four years of the target material.

[0128] The way to build a price prediction model is to obtain the historical prices of the target material and the corresponding years as samples, use the price data of the preset year in the sample as labels, and the price data of the remaining years and the corresponding year data as input variables, and conduct supervised training to obtain the change relationship of the price data of the target material as the year increases, and then build a price prediction model that can predict the price of subsequent years based on the price of the target material in historical years.

[0129] The benefit of this setting is that the historical price trend of the target material can be used to build a price prediction model that can predict future prices, which is conducive to making the price prediction of the target material more in line with the actual price fluctuation law and enabling users to obtain more accurate predicted price values.

[0130] Embodiment 4

[0131] Figure 4 It is a flow chart of a method for displaying procurement-related information based on an AI big model provided in Example 4 of the present application. This solution makes a better improvement on the above-mentioned embodiment, and the specific improvement is: before showing the price trend of the target material and the comprehensive supply capacity of the supplier to the user, the method includes: determining the recommended supplier based on the supplier's comprehensive supply capacity prediction results, and generating price negotiation suggestions based on the price trend chart; accordingly, showing the price trend of the target material and the supplier's comprehensive supply capacity to the user includes: showing the price trend chart, the supplier's comprehensive supply capacity prediction results, the recommended supplier, and the price negotiation suggestions to the user.

[0132] like Figure 4 As shown, specifically including the following:

[0133] S701. Collect material information and store the material information in a database; wherein the material information includes material name, historical price, supplier quotation and supplier basic information;

[0134] S702, receiving target materials input by the user;

[0135] S703, searching the material information pre-stored in the database for the historical price, supplier quotation and supplier basic information corresponding to the target material;

[0136] S704, determining the price trend of the target material according to the historical price and the supplier's quotation, and determining the supplier's comprehensive supply capacity according to the supplier's basic information;

[0137] S705, determining a recommended supplier according to the supplier comprehensive supply capacity forecast result, and generating a price negotiation suggestion according to the price trend chart;

[0138] The method for determining the recommended supplier may be to select the supplier with the strongest comprehensive supply capacity in the supplier comprehensive supply capacity forecast results as the recommended supplier; or, the method for determining the recommended supplier may also be to obtain the user's purchasing needs, and identify the supplier that best meets the user's purchasing needs in the supplier comprehensive supply capacity forecast results as the recommended supplier. For example, if the user's purchasing need is to deliver the goods as soon as possible, then among the suppliers with stronger comprehensive supply capabilities, the supplier with a large production scale or more spot goods may be preferred as the recommended supplier.

[0139] A method for generating price negotiation suggestions based on the price trend chart may be to obtain the highest price and the lowest price of the target material over the years based on the price trend chart, analyze the price adjustment range this year, and then determine the price adjustment range of the current target material, and determine the price negotiation range based on the predicted price and the price adjustment range.

[0140] For example, if a construction company needs to purchase cement, the user enters "cement" and the system displays the historical price trend of cement and supplier quotation information. Based on the system's analysis results, the best supplier is recommended and detailed price negotiation suggestions are provided to help users gain an advantage in price negotiations.

[0141] S706: Display the price trend chart, supplier comprehensive supply capacity forecast results, recommended suppliers, and price negotiation suggestions to the user to assist the user in completing the purchase of target materials.

[0142] The method of displaying the price trend chart, the supplier's comprehensive supply capacity forecast results, the recommended suppliers and the price negotiation suggestions to the user can be, on the basis of displaying the price trend chart and the supplier's comprehensive supply capacity forecast results to the user through a display device, marking the price negotiation suggestions next to the price trend chart, and highlighting the recommended suppliers in the supplier's comprehensive supply capacity forecast results.

[0143] The benefit of this scheme is that it can provide users with recommended suppliers and price negotiation suggestions based on price trend charts and supplier comprehensive supply capacity forecast results, which helps users gain an advantage in price negotiations and purchase high-quality materials at lower prices.

[0144] In this proposal, an example of an analysis report for determining recommended suppliers and price negotiation suggestions is provided for reference: Figure 8 : is a flow chart of the AI ​​model provided in the fourth embodiment of the present application providing a procurement auxiliary analysis report, such as Figure 8 As shown:

[0145] First, it is necessary to collect a large amount of material information by receiving user imported files or pulling information from the resource management system. After cleaning and filtering the collected material information, it is stored in the specified database to form a price library, and the data in the price library is synchronized with the data in the vector library. When the user needs to obtain an analysis report on the target material, the name of the target material is input to the AI ​​big model. The AI ​​big model generates corresponding question information based on the target material. The user inputs the constraints of the target material. For example, the historical price of the material in the past five years is used as the data basis for the analysis report, or the supplier with the lowest unit price needs to be obtained. The AI ​​big model extracts feature vectors based on the name of the target material and the constraints, and matches them in the vector library to extract the material information corresponding to the consistent feature vectors. The user's intention is determined according to the constraints entered by the user. For example, the user needs to obtain the supplier with the lowest price or the supplier with the highest quality, etc., and the obtained material information is checked. If there is missing information, the missing information is searched through big data and filled in the material information. The processed material information and user intentions are input into the AI ​​big model, which will output recommended suppliers and price negotiation suggestions that are consistent with the user intentions based on the pre-trained algorithm. An AI analysis report is generated based on the recommended suppliers and price negotiation suggestions output by the AI ​​big model and displayed through the user interface.

[0146] For example, in the purchasing department of a manufacturing company, the user enters "copper material", and the system displays the historical price trend chart of copper material and the comprehensive capability analysis of suppliers. Based on the prediction results of the AI ​​big model, the system generates an analysis report with recommended suppliers and price negotiation suggestions. Users can successfully purchase high-quality copper materials at a lower price based on the suppliers and price negotiation suggestions recommended by the AI ​​big model.

[0147] Embodiment 5

[0148] Fig. 9 It is a structural diagram of the procurement-related information display device based on the AI ​​big model provided in Example 5 of the present application.

[0149] like Fig. 9 As shown, specifically including the following:

[0150] The material information collection module 901 is used to collect material information and store the material information in a database; wherein the material information includes material name, historical price, supplier quotation and supplier basic information;

[0151] The target material determination module 902 is used to receive the target material input by the user;

[0152] The target material retrieval module 903 is used to retrieve the historical price, supplier quotation and supplier basic information corresponding to the target material from the material information pre-stored in the database;

[0153] A retrieval information analysis module 904 is used to determine the price trend of the target material according to the historical price and the supplier's quotation, and to determine the supplier's comprehensive supply capacity according to the supplier's basic information;

[0154] The analysis result display module 905 is used to display the price trend of the target material and the comprehensive supply capacity of the supplier to the user, so as to assist the user in completing the purchase of the target material.

[0155] In an embodiment of the present application, a material information collection module is used to collect material information and store the material information in a database; wherein the material information includes material name, historical price, supplier quotation and supplier basic information; a target material determination module is used to receive a target material input by a user; a target material retrieval module is used to retrieve the historical price, supplier quotation and supplier basic information corresponding to the target material in the material information pre-stored in the database; a retrieval information analysis module is used to determine the price trend of the target material according to the historical price and the supplier quotation, and to determine the comprehensive supply capacity of the supplier according to the supplier basic information; an analysis result display module is used to display the price trend of the target material and the comprehensive supply capacity of the supplier to the user, so as to assist the user in completing the purchase of the target material. Through the above-mentioned device for displaying procurement-related information based on an AI large model, the relevant information of the materials that the user needs to purchase can be counted, sorted and displayed, so that the user can quickly understand the price trend of the material and the relevant information of the supplier, thereby determining the comprehensive supply capacity of each supplier, and significantly improving procurement efficiency and decision-making quality.

[0156] In the embodiment of the present application, a procurement-related information display device based on an AI large model can be a device, or a component, an integrated circuit, or a chip in a terminal. The device can be a mobile electronic device or a non-mobile electronic device. Exemplarily, the mobile electronic device can be a mobile phone, a tablet computer, a laptop computer, a PDA, an in-vehicle electronic device, a wearable device, an ultra-mobile personal computer (UMPC), a netbook, or a personal digital assistant (PDA), etc. The non-mobile electronic device can be a server, a network attached storage (NAS), a personal computer (PC), a television (TV), a teller machine or a self-service machine, etc., which is not specifically limited in the embodiment of the present application.

[0157] In the embodiment of the present application, a device for displaying procurement-related information based on an AI big model may be a device having an operating system. The operating system may be an Android operating system, an iOS operating system, or other possible operating systems, which are not specifically limited in the embodiment of the present application.

[0158] The device for displaying procurement-related information based on an AI big model provided in an embodiment of the present application can implement each process implemented in the above-mentioned method embodiments. To avoid repetition, it will not be described here.

[0159] Embodiment 7

[0160] like Fig.10 As shown, an embodiment of the present application also provides an electronic device 1000, including a processor 1001, a memory 1002, and a program or instruction stored in the memory 1002 and executable on the processor 1001. When the program or instruction is executed by the processor 1001, each process of an embodiment of a method for displaying procurement-related information based on an AI big model is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0161] It should be noted that the electronic devices in the embodiments of the present application include the mobile electronic devices and non-mobile electronic devices mentioned above.

[0162] Embodiment 8

[0163] An embodiment of the present application also provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, each process of the above-mentioned method embodiment for displaying procurement-related information based on an AI big model is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0164] The processor is a processor in the electronic device described in the above embodiment. The readable storage medium includes a computer readable storage medium, such as a computer read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0165] Embodiment 9

[0166] An embodiment of the present application further provides a chip, which includes a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is used to run programs or instructions to implement the various processes of the above-mentioned method embodiment for displaying procurement-related information based on an AI big model, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0167] It should be understood that the chip mentioned in the embodiments of the present application can also be called a system-level chip, a system chip, a chip system or a system-on-chip chip, etc.

[0168] It should be noted that, in this article, the terms "comprise", "include" or any other variant thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise one..." do not exclude the presence of other identical elements in the process, method, article or device including the element. In addition, it should be pointed out that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in reverse order according to the functions involved, for example, the described method may be performed in an order different from that described, and various steps may also be added, omitted, or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0169] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a computer software product, which is stored in a storage medium (such as ROM / RAM, a disk, or an optical disk), and includes a number of instructions for a terminal (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0170] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present application, ordinary technicians in this field can also make many forms without departing from the purpose of the present application and the scope of protection of the claims, all of which are within the protection of the present application.

[0171] The above are only preferred embodiments of the present application and the technical principles used. The present application is not limited to the specific embodiments described herein, and various obvious changes, readjustments and substitutions that can be made by those skilled in the art will not deviate from the scope of protection of the present application. Therefore, although the present application is described in more detail through the above embodiments, the present application is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present application, and the scope of the present application is determined by the scope of the claims.

Claims

1. A procurement-related information display method based on an AI big model, characterized in that: The method comprises: Collect material information and store the material information in a database; wherein the material information includes material name, historical price, supplier quotation and supplier basic information; Receive target materials input by users; Retrieving historical prices, supplier quotations, and basic supplier information corresponding to the target material from the material information pre-stored in the database; Determine the price trend of the target material according to the historical price and the supplier's quotation, and determine the supplier's comprehensive supply capacity according to the supplier's basic information; The price trend of the target material and the comprehensive supply capacity of the supplier are displayed to the user to assist the user in completing the purchase of the target material.

2. The method for displaying procurement-related information based on an AI big model according to claim 1 is characterized in that: Collecting material information and storing the material information in a database includes: Obtain material information from the resource management system according to a preset cycle, or receive material information uploaded by users; Identify missing values ​​and outliers in material information, delete material information with missing values ​​or outliers, and store the deleted material information in the database.

3. The method for displaying procurement-related information based on an AI big model according to claim 1 is characterized in that: After retrieving the historical price, supplier quotation and supplier basic information corresponding to the target material from the material information pre-stored in the database, the method further includes: When historical prices, supplier quotations or basic supplier information are missing, the corresponding missing information is retrieved through big data and the material information is supplemented.

4. The method for displaying procurement-related information based on an AI big model according to claim 1 is characterized in that: Determining the price trend of the target material according to the historical price and the supplier's quotation, including: Inputting the historical prices and corresponding years into a pre-built price prediction model, and obtaining the predicted price of the predicted year through the price prediction model; Mark the historical prices and the predicted prices in the price trend graph of the target material according to the corresponding years, and draw a material price curve; The quotations of each supplier are marked in the price trend chart of the target material according to the corresponding year, and the supplier quotation curve is drawn.

5. The method for displaying procurement-related information based on an AI big model according to claim 4 is characterized in that: Before inputting the historical prices and corresponding years into a pre-built price prediction model, the method further includes: The prices of preset years in historical prices are used as labels, and the remaining prices and their years are used as input variables for supervised training to build a price prediction model.

6. The method for displaying procurement-related information based on an AI big model according to claim 1 is characterized in that: Determine the supplier's comprehensive supply capacity based on the supplier's basic information, including: Obtaining basic information of historical suppliers, and predicting the comprehensive supply capacity of suppliers based on the basic information of historical suppliers to obtain training samples; Performing supervised training on the training samples to build a comprehensive supply capacity analysis model; The basic information of the supplier is input into a pre-built comprehensive supply capacity analysis model, and the comprehensive supply capacity of the supplier is predicted by the comprehensive supply capacity analysis model.

7. The method for displaying procurement-related information based on an AI big model according to claim 1 is characterized in that: Before presenting the price trend of the target material and the comprehensive supply capacity of the supplier to the user, the method includes: Determining recommended suppliers based on the supplier's comprehensive supply capacity forecast results, and generating price negotiation suggestions based on the price trend chart; Accordingly, the price trend of the target material and the comprehensive supply capacity of the supplier are displayed to the user, including: The price trend chart, supplier comprehensive supply capacity forecast results, recommended suppliers and price negotiation suggestions are displayed to users.

8. A procurement-related information display device based on an AI big model, characterized in that: The device comprises: A material information collection module is used to collect material information and store the material information in a database; wherein the material information includes material name, historical price, supplier quotation and supplier basic information; A target material determination module is used to receive the target material input by the user; A target material retrieval module is used to retrieve the historical price, supplier quotation and supplier basic information corresponding to the target material from the material information pre-stored in the database; A retrieval information analysis module, used to determine the price trend of the target material according to the historical price and the supplier's quotation, and to determine the supplier's comprehensive supply capacity according to the supplier's basic information; The analysis result display module is used to display the price trend of the target material and the comprehensive supply capacity of the supplier to the user, so as to assist the user in completing the purchase of the target material.

9. An electronic device, characterized in that: It includes a processor, a memory, and a program or instruction stored in the memory and executable on the processor. When the program or instruction is executed by the processor, the steps of a method for displaying procurement-related information based on an AI big model are implemented as described in any one of claims 1 to 7.

10. A readable storage medium, characterized in that: The readable storage medium stores programs or instructions, and when the programs or instructions are executed by the processor, the steps of a method for displaying procurement-related information based on an AI big model as described in any one of claims 1-7 are implemented.

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