Intelligent material inquiry system and method based on Internet order transaction

Abstract

The invention belongs to the technical field of material online inquiry, and particularly relates to an intelligent material inquiry system and method based on Internet order transaction. According to the method, multi-level and multi-dimensional comprehensive evaluation is carried out on the supply information of the suppliers, it is ensured that the screened optimal suppliers not only have competitive power in price, but also have high reliability in the aspects of service quality, credit rating, transaction history and the like, and through a normalization processing mode, the quality of the supplier is improved. The method can effectively eliminate the dimension difference between different evaluation indexes, guarantees the fairness and accuracy of an evaluation result, can efficiently determine the communication level of suppliers through setting a multi-level communication mechanism, guarantees the preferential communication of suppliers matched with the material demands of an enterprise, and improves the purchasing efficiency of the materials of the enterprise.

Description

Technical Field

[0001] The present invention belongs to the technical field of online material price inquiry, and in particular relates to an intelligent material price inquiry system and method based on Internet order transactions. Background Art

[0002] With the rapid development of Internet technology and the popularization of e-commerce, traditional material inquiry methods can no longer meet the efficient and accurate needs of modern enterprises. When purchasing materials, enterprises often face problems such as complicated supplier information, opaque quotations, and difficult credit assessment, which makes it difficult to optimize procurement efficiency and cost control. Correspondingly, it will also bring many inconveniences in supply chain management. Therefore, the development of intelligent and systematic material inquiry methods has become an inevitable trend.

[0003] The intelligent material inquiry methods in the existing technology still have some shortcomings. For example, some methods rely too much on a single data dimension in the supplier evaluation process and fail to fully consider the comprehensive capabilities of suppliers. Other methods lack effective priority division in the communication link, which makes the inquiry efficiency low and unable to quickly match the best supplier related to the enterprise, which will undoubtedly waste the company's time and resources. Based on this, this solution provides an intelligent material inquiry method based on Internet order transactions to solve the above problems. Summary of the invention

[0004] The purpose of the present invention is to provide an intelligent material inquiry system and method based on Internet order transactions, which can effectively integrate the multi-dimensional data of suppliers and improve the accuracy and efficiency of material inquiries.

[0005] The technical solution adopted by the present invention is as follows:

[0006] An intelligent material price inquiry method based on Internet order transaction, comprising:

[0007] Obtain material demand information, publish it through the Internet platform, and receive and compile statistics on quotation information from various suppliers in real time;

[0008] Collecting supply information of each supplier, wherein the supply information includes transaction history data and credit rating of the supplier;

[0009] Evaluate suppliers based on their supply information, select suppliers that are suitable for cooperation based on the evaluation results, and record them as preferred suppliers;

[0010] Classify the preferred suppliers according to the quotation information, and determine the communication level of each preferred supplier according to the classification results;

[0011] Communicate with each preferred supplier based on the communication level, collect material prices after communication with the preferred supplier, and then summarize the material prices, supply information and communication levels of the preferred suppliers into a material inquiry report.

[0012] In a preferred solution, the material demand information is obtained by means of internal provision by the enterprise, provision by the supply chain collaboration platform, and manual entry;

[0013] When receiving the quotation information from suppliers, it includes active push and passive reception. The active push automatically sends the inquiry request to the matching suppliers through the Internet platform, and the passive reception directly counts the active quotations submitted by the suppliers;

[0014] When counting the quotation information of the supplier, a timestamp is synchronously added to the quotation information of the supplier to determine the time characteristics of the quotation information.

[0015] In a preferred solution, under the active push, suppliers in the Internet platform are actively matched according to the material demand information, and the specific process is as follows:

[0016] Obtaining the material demand information and the supplier's supply information;

[0017] Performing vectorization processing on the material demand information and the supply information to obtain a demand feature vector corresponding to the material demand information and a supply feature vector corresponding to the supply information;

[0018] Obtaining a matching function, and inputting the demand feature vector and the supply feature vector into the matching function, and recording the output result of the matching function as a matching score;

[0019] Obtaining a matching threshold, and comparing the matching score with the matching threshold;

[0020] When the matching score is greater than the matching threshold, it indicates that the supply information corresponding to the matching score meets the user's needs, and the supplier corresponding to the supply information is matched with the material demand information;

[0021] When the matching score is less than or equal to the matching threshold, it indicates that the supply information corresponding to the matching score does not meet the user's needs, and no matching is performed on the supplier corresponding to the supply information.

[0022] In a preferred solution, when collecting the supply information of each supplier, the supply information of each supplier is preprocessed simultaneously, and the preprocessing step includes:

[0023] Obtaining the supply information of each supplier, and performing deduplication processing to eliminate the supply information of the supplier that appears repeatedly;

[0024] Perform data cleaning on the deduplicated supply information to remove outliers and invalid data in the supply information;

[0025] The cleaned supply information is arranged in chronological order and simultaneously aggregated into the preset reference database.

[0026] In a preferred solution, the step of evaluating suppliers according to their supply information, selecting suppliers that are allowed to cooperate according to the evaluation results, and recording them as preferred suppliers includes:

[0027] Retrieving the preprocessed supply information from the reference database;

[0028] Based on the sending node of the logistics demand information, the evaluation period is reversely constructed, and the transaction history data in the supply information within the evaluation period is collected;

[0029] Performing trend evaluation processing on the transaction history data to obtain transaction trend parameters of the supplier;

[0030] Extracting the transaction volume from the transaction history data, and combining it with the transaction trend parameter and the credit rating of the supplier to comprehensively calculate a comprehensive evaluation score of the supplier;

[0031] An evaluation threshold is set, the comprehensive evaluation score is compared with the evaluation threshold, and suppliers whose comprehensive scores are greater than the evaluation threshold are screened as preferred suppliers.

[0032] In a preferred solution, the transaction volume is extracted from the transaction history data, and then normalized after combining the transaction trend parameter and the credit rating output of the supplier. The specific process is as follows:

[0033] Obtain transaction volume, transaction trend parameters and credit ratings;

[0034] Obtaining a normalization function, and outputting the transaction volume, transaction trend parameter, and credit rating to the normalization function respectively, to obtain a first condition parameter corresponding to the transaction volume, a second condition parameter corresponding to the transaction trend parameter, and a third condition parameter corresponding to the credit rating;

[0035] Among them, the transaction volume and credit rating are only statistically analyzed within the evaluation period.

[0036] In a preferred solution, the step of grading the preferred suppliers according to the quotation information and determining the communication level of each preferred supplier according to the grading result includes:

[0037] Extracting material quotations of various preferred suppliers from the quotation information and recording them as grading condition parameters;

[0038] Obtaining grading intervals, wherein each grading interval corresponds to a communication level;

[0039] Compare the grading condition parameters with the grading intervals to match the communication level of the supplier corresponding to each grading condition parameter;

[0040] The communication levels are arranged in descending order, and the communication order of each preferred supplier is determined according to the arrangement order of the communication levels.

[0041] In a preferred solution, the step of communicating with each preferred supplier according to the communication level and collecting the material price after communicating with the preferred supplier includes:

[0042] Obtain communication ratings from preferred suppliers;

[0043] Communicate with the preferred suppliers in order of priority of the communication levels;

[0044] Collect material prices, communication time and supplier feedback information during the communication process, then summarize all material prices, communication time and supplier feedback information after all communications to form a material inquiry report and submit it to the management end.

[0045] The present invention also provides an intelligent material price inquiry system based on Internet order transactions, using the above-mentioned intelligent material price inquiry method based on Internet order transactions, comprising:

[0046] An initialization module, which is used to obtain material demand information, publish it through an Internet platform, and receive and count quotation information from various suppliers in real time;

[0047] A data collection module, the data collection module is used to collect supply information of each supplier, wherein the supply information includes the supplier's transaction history data and credit rating;

[0048] An evaluation module, which is used to evaluate suppliers according to their supply information, and select suppliers that are allowed to cooperate according to the evaluation results, and record them as preferred suppliers;

[0049] A grading module, the grading module is used to grade the preferred suppliers according to the quotation information, and determine the communication level of each preferred supplier according to the grading result;

[0050] A summary output module is used to communicate with each preferred supplier based on the communication level, collect material prices after communication with the preferred supplier, and then summarize the material prices, supply information and communication level of the preferred supplier into a material inquiry report.

[0051] And, an electronic device, the electronic device comprising:

[0052] at least one processor;

[0053] and a memory communicatively coupled to the at least one processor;

[0054] Wherein, the memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the above-mentioned intelligent material inquiry method based on Internet order transactions.

[0055] The technical effects achieved by the present invention are:

[0056] The present invention conducts a multi-level and multi-dimensional comprehensive evaluation of the supplier's supply information to ensure that the selected preferred suppliers are not only competitive in price, but also have high reliability in terms of service quality, credit rating and transaction history. Through normalization processing, the dimensional differences between different evaluation indicators can be effectively eliminated to ensure the fairness and accuracy of the evaluation results. In addition, by setting a multi-level communication mechanism, the communication level of the supplier can be efficiently determined to ensure that the supplier who is compatible with the enterprise's material needs can get priority communication, thereby improving the enterprise's material procurement efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 It is a schematic flow chart of the method of the present invention;

[0058] Figure 2 It is a schematic diagram of the system module of the present invention;

[0059] Figure 3 It is a schematic diagram of the structure of an electronic device of the present invention. DETAILED DESCRIPTION

[0060] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0061] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0062] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure or characteristic that may be included in at least one implementation of the present invention. The phrase "in a preferred embodiment" that appears in different places in this specification does not refer to the same embodiment, nor is it a separate or selective embodiment that is mutually exclusive with other embodiments.

[0063] See also Figure 1 As shown, the present invention provides an intelligent material price inquiry system and method based on Internet order transactions, including:

[0064] S1. Obtain material demand information, publish it through the Internet platform, and receive and count the quotation information of each supplier in real time;

[0065] In step S1, when an enterprise needs to make an online inquiry for the required materials, it will first obtain material demand information, including the required quantity of materials, material specifications, and expected price range, etc., and then publish the material demand information through the Internet platform so that more suppliers can see and participate in the quotation. After the material demand information is published, the quotation information of each supplier will be received and counted in real time to ensure the timeliness and accuracy of the information. The material demand information can be obtained by providing it internally, providing it on the supply chain collaboration platform, and entering it manually;

[0066] When receiving the quotation information from suppliers, it includes active push and passive reception. Active push automatically sends inquiry requests to matching suppliers through the Internet platform, and passive reception directly counts the active quotations submitted by suppliers;

[0067] When counting the supplier's quotation information, add a timestamp to the supplier's quotation information to determine the time characteristics of the quotation information;

[0068] Specifically, in the process of obtaining material demand information, this goal can be achieved through a variety of ways. First, the enterprise can provide relevant material demand information, which usually involves coordination and communication between various departments to ensure the accuracy and timeliness of the information. Secondly, the supply chain collaboration platform can also provide material demand information, which usually integrates the information of upstream and downstream enterprises and can realize real-time sharing and updating of information. Finally, manual entry is also a common method. Although this method may have certain errors and delays, it is still necessary in some cases. When receiving supplier quotation information, there are two main ways: active push and passive reception. Active push refers to automatically sending inquiry requests to suppliers that match the company's needs through the Internet platform. This method can greatly save time and labor costs and improve efficiency. Passive reception refers to directly counting the quotation information actively submitted by the supplier. When counting the supplier's quotation information, a timestamp will be added to the supplier's quotation information simultaneously. The addition of a timestamp can determine the time characteristics of the quotation information. Through the timestamp, the company can understand the timeliness of the quotation information and judge whether it still has reference value.

[0069] In addition, under active push, suppliers on the Internet platform are actively matched based on material demand information. The specific process is as follows:

[0070] Obtain material demand information and supplier supply information;

[0071] The material demand information and the supply information are vectorized to obtain a demand feature vector corresponding to the material demand information and a supply feature vector corresponding to the supply information;

[0072] Obtain a matching function, input the demand feature vector and the supply feature vector into the matching function, and record the output result of the matching function as a matching score;

[0073] Obtain a matching threshold, and compare the matching score with the matching threshold;

[0074] When the matching score is greater than the matching threshold, it indicates that the supply information corresponding to the matching score meets the user's needs, and the supplier corresponding to the supply information is matched with the material demand information;

[0075] When the matching score is less than or equal to the matching threshold, it indicates that the supply information corresponding to the matching score does not meet the user's needs, and no matching is performed on the supplier corresponding to the supply information.

[0076] Specifically, under the active push mechanism, suitable suppliers will be actively sought on the Internet platform based on the material demand information. First, the material demand information will be obtained, and the supply information from each supplier will also be collected. In order to facilitate the subsequent matching process, the obtained material demand information and the supplier's supply information will be vectorized. In this way, the material demand information can be converted into a demand feature vector, which contains the key features of the material demand. Similarly, the supplier's supply information will also be converted into a supply feature vector, which contains the key features of the supplier's supply. After that, the matching function set by the first line can be introduced to evaluate the matching degree between the demand feature vector and the supply feature vector. The expression of the matching function is: In the formula, R represents the matching score, n represents the number of feature points in the demand feature vector and the supply feature vector, and a i and b i They represent the demand feature vector and the supply feature vector respectively. By inputting the demand feature vector and the supply feature vector into the matching function together, a matching score is obtained after calculation. The matching score reflects the degree of matching between the supplier's supply information and the user's demand. In order to ensure the reliability of the matching result, a matching threshold is introduced. The matching threshold is a pre-set standard used to determine whether the matching score has reached an acceptable level. Then the matching score output by the matching function will be compared with the matching threshold. If the matching score is higher than the matching threshold, it means that the supplier's supply information meets the user's needs. In this case, the supplier will be matched with the material demand information, thereby establishing a connection between the supply and demand parties. On the contrary, if the matching score is lower than or equal to the matching threshold, it means that the supplier's supply information fails to meet the user's demand standards. In this case, the supplier will not be matched with the material demand information, thereby avoiding inappropriate suppliers wasting users' time and resources.

[0077] S2. Collecting supply information of each supplier, wherein the supply information includes the supplier's transaction history data and credit rating;

[0078] In step S2, after the supplier is determined, the supply information of each supplier is collected, including the supplier's transaction history data and credit rating. The transaction history data can reflect the supplier's past transaction performance, and the credit rating can provide an intuitive credit reference, based on which it is helpful to evaluate the reliability of the supplier. When collecting the supply information of each supplier, the supply information of each supplier is preprocessed simultaneously. The preprocessing steps include:

[0079] Obtain the supply information of each supplier and perform deduplication processing to eliminate duplicate supply information of suppliers;

[0080] Perform data cleaning on the deduplicated supply information to remove outliers and invalid data in the supply information;

[0081] Arrange the cleaned supply information in chronological order and simultaneously aggregate it into the preset reference database;

[0082] Specifically, in the process of collecting supply information from suppliers, a series of preprocessing steps need to be performed synchronously to ensure the accuracy and availability of the data. First, the supply information will be deduplicated to eliminate duplicate information and ensure that each piece of information is unique. Then, the deduplicated supply information will be cleaned. This step includes removing outliers and invalid data to ensure the accuracy and reliability of the supply information. Finally, the cleaned supply information will be arranged in chronological order to better track and analyze the supply situation. Finally, the preprocessed supply information will be summarized and stored in a preset reference database for subsequent query and analysis.

[0083] S3. Evaluate suppliers based on their supply information, select suppliers that are allowed to cooperate based on the evaluation results, and record them as preferred suppliers;

[0084] In step S3, the supplier will be evaluated based on the collected supply information. During the evaluation process, the supplier's transaction history data and credit rating will be comprehensively considered. At the same time, the supplier will be comprehensively evaluated in combination with the transaction history data and credit rating. This evaluation result will be used to screen out suppliers that are allowed to cooperate, and the corresponding suppliers will be recorded as preferred suppliers for further subsequent operations. The steps of evaluating the suppliers based on their supply information, screening out suppliers that are allowed to cooperate based on the evaluation results, and recording them as preferred suppliers include:

[0085] Retrieving pre-processed supply information from a reference database;

[0086] Based on the sending node of logistics demand information, the evaluation period is reversely constructed, and the transaction history data in the supply information within the evaluation period is collected;

[0087] Perform trend evaluation on historical transaction data to obtain supplier transaction trend parameters;

[0088] Extract transaction volume from historical transaction data, and then combine transaction trend parameters and supplier's credit rating to calculate the supplier's comprehensive evaluation score;

[0089] Set an evaluation threshold, compare the comprehensive evaluation score with the evaluation threshold, and select suppliers with a comprehensive score greater than the evaluation threshold as preferred suppliers;

[0090] Specifically, before executing the material inquiry work, it is necessary to conduct corresponding evaluation processing on the supplier. First, it is necessary to call the pre-processed supply information from the reference database to ensure the reliability of the data used in the evaluation process. Then, the evaluation period is reversely constructed based on the issuance node of the logistics demand information, so as to collect the supplier's transaction history data during the evaluation period. The selection of the evaluation period is usually based on the peak period of logistics demand or a specific business cycle to ensure that the evaluation result is more representative. After collecting the supply information within the evaluation period, the transaction history data will be trend evaluated. By analyzing the historical transaction data, the supplier's transaction trend parameters are determined to reflect the supplier's activity and stability in the market. When calculating the transaction trend parameters, the evaluation period is divided into multiple mutually staggered and equidistant parallel periods, and the transaction history data in each parallel period is analyzed to capture the trend of changes in historical transaction volume. The calculation formula of the transaction trend parameters is: In the formula, Q represents the trading trend parameter, t represents the length of the parallel period, and M j and M j-1 It represents the material transaction volume under the adjacent statistical nodes, m represents the statistical number of material transaction volumes in the parallel time period. In addition, it is necessary to extract the transaction volume from the transaction history data, and combine the transaction trend parameters and the supplier's credit rating to comprehensively calculate the supplier's comprehensive evaluation score. Finally, an evaluation threshold will be set. The evaluation threshold is set according to the company's specific needs and industry standards. It is used to measure whether the supplier's comprehensive evaluation score meets the cooperation standard. After comparing the comprehensive evaluation score with the evaluation threshold, suppliers with a comprehensive score greater than the evaluation threshold will be screened out and recorded as preferred suppliers. Preferred suppliers will be included in the company's cooperation list and will be given priority for inquiry.

[0091] In addition, the transaction volume is extracted from the transaction history data, and then normalized after combining the transaction trend parameters and the supplier's credit rating output. The specific process is as follows:

[0092] Obtain transaction volume, transaction trend parameters and credit ratings;

[0093] Obtain a normalization function, and output the transaction volume, transaction trend parameter, and credit rating to the normalization function respectively, to obtain a first condition parameter corresponding to the transaction volume, a second condition parameter corresponding to the transaction trend parameter, and a third condition parameter corresponding to the credit rating;

[0094] Among them, transaction volume and credit rating only count the data within the evaluation period;

[0095] When analyzing and processing historical transaction data, it is first necessary to extract transaction volume, transaction trend parameters and supplier's credit rating from the historical transaction data, and then use a normalization function for further processing. By inputting transaction volume, transaction trend parameters and credit rating into the normalization function respectively, it is important to note that the transaction volume and credit rating data only count the data within the evaluation period, and three conditional parameters can be obtained: the first conditional parameter corresponds to the transaction volume, the second conditional parameter corresponds to the transaction trend parameter, and the third conditional parameter corresponds to the credit rating. The expression of the normalization function is: f x represents conditional parameters (including the first conditional parameter, the second conditional parameter and the third conditional parameter, which are determined according to the value of x, x=1, 2, 3), represents the average value of transaction volume, the average value of transaction trend parameters and the average value of credit rating during the evaluation period (determined by the value of x), S max It represents the maximum transaction volume, the maximum transaction trend parameter and the maximum credit rating during the evaluation period. Specifically (determined according to the value of x), through the normalization function, the data of different dimensions and magnitudes can be compared and analyzed under the same standard. After the first condition parameter, the second condition parameter and the third condition parameter are determined, they will be input into the pre-set comprehensive evaluation function to calculate the comprehensive evaluation score of the corresponding supplier. The expression of the comprehensive evaluation function is: R z =αf1+βf2+χf3, where R z represents the comprehensive evaluation score, α, β and χ represent the weight factors of the first condition parameter, the second condition parameter and the third condition parameter respectively, f1, f2 and f3 represent the first condition parameter, the second condition parameter and the third condition parameter respectively, wherein the weight factors of the first condition parameter, the second condition parameter and the third condition parameter are set according to the company's strategic needs and industry best practices to ensure the validity of the evaluation results.

[0096] S4. Classify the preferred suppliers according to the quotation information, and determine the communication level of each preferred supplier according to the classification results;

[0097] In step S4, after the quotation information is output, the preferred suppliers will be graded to determine the communication level of each preferred supplier, and the subsequent communication priority will be determined based on it. The step of grading the preferred suppliers based on the quotation information and determining the communication level of each preferred supplier based on the grading results includes:

[0098] Extract the material quotations of each preferred supplier from the quotation information and record them as grading condition parameters;

[0099] Obtaining grading intervals, where each grading interval corresponds to a communication level;

[0100] Compare the grading condition parameters with the grading intervals to match the communication level of the supplier corresponding to each grading condition parameter;

[0101] Arrange the communication levels from large to small, and determine the communication order of each preferred supplier based on the order of communication levels;

[0102] Specifically, when performing grading of preferred suppliers, first extract the material quotation of each preferred supplier from the quotation information and record it as a grading condition parameter. Then, it is necessary to obtain the grading interval. The grading interval is pre-set, and each grading interval corresponds to a specific communication level. The setting of the grading interval is usually based on the company's procurement strategy and communication needs to ensure that each supplier can be reasonably classified. Then, compare the extracted grading condition parameters with the grading interval, and determine the communication level of each preferred supplier through a matching process. This matching process needs to ensure that the quotation parameters of each supplier can accurately fall into the corresponding grading interval to obtain the corresponding communication level. Finally, arrange the communication level of each preferred supplier in order from high to low, and use the arrangement order as the basis for subsequent communication work to ensure priority communication with suppliers with higher communication levels.

[0103] S5. Communicate with each preferred supplier based on the communication level, collect the material prices after communication with the preferred suppliers, and then summarize the material prices, supply information and communication levels of the preferred suppliers into a material inquiry report;

[0104] In step S5, communication will be conducted with each preferred supplier based on the communication level. During the communication process, the material prices after communication with the preferred supplier will be collected to ensure that the most favorable price information is obtained. At the same time, the supplier's supply information and communication level will be collected and summarized into a detailed material inquiry report to provide a comprehensive reference for procurement decisions. Among them, the steps of communicating with each preferred supplier based on the communication level and collecting the material prices after communication with the preferred supplier include:

[0105] Obtain communication ratings from preferred suppliers;

[0106] Communicate with preferred suppliers in order of communication priority;

[0107] Collect material prices, communication time and supplier feedback information during the communication process, then summarize all material prices, communication time and supplier feedback information after all communications to form a material inquiry report and submit it to the management end.

[0108] Specifically, in order to ensure the efficiency and quality of communication with each preferred supplier, it is necessary to classify the preferred suppliers according to the communication level and communicate with them in order of priority. During the communication process, the material price, communication time and supplier feedback information will be recorded in detail, and finally summarized into a complete material inquiry report and submitted to the management for review and decision-making. First, it is necessary to obtain the communication level of each preferred supplier. During the communication process, it is necessary to record the changes in material prices in detail, including the initial quotation provided by the supplier, the final price after negotiation, and any possible discounts or preferential conditions. In addition, it is necessary to record the time spent on each communication to facilitate the subsequent analysis of communication efficiency. In addition to price and time, it is also necessary to extract supplier feedback information. This feedback information includes the supplier's views on the current market situation, forecasts on material supply, and expectations and suggestions for cooperation, so as to better understand the supplier's needs and expectations. Finally, all material prices, communication times and supplier feedback information collected during the communication process are summarized and organized to form a detailed material inquiry report for management to review and make decisions.

[0109] See also Figure 2 , an intelligent material price inquiry system based on Internet order transactions, using the above-mentioned intelligent material price inquiry method based on Internet order transactions, comprising:

[0110] Initialization module: The initialization module is used to obtain material demand information, publish it through the Internet platform, and receive and count the quotation information of each supplier in real time;

[0111] A data collection module, which is used to collect supply information of each supplier, wherein the supply information includes the supplier's transaction history data and credit rating;

[0112] Evaluation module: the evaluation module is used to evaluate suppliers according to their supply information, and select suppliers that are allowed to cooperate according to the evaluation results, and record them as preferred suppliers;

[0113] The grading module is used to grade the preferred suppliers according to the quotation information and determine the communication level of each preferred supplier according to the grading results;

[0114] The summary output module is used to communicate with each preferred supplier based on the communication level, collect material prices after communication with the preferred suppliers, and then summarize the material prices, supply information and communication levels of the preferred suppliers into a material inquiry report.

[0115] As mentioned above, the system includes an initialization module, a data acquisition module, an evaluation module, a grading module and a summary output module. The initialization module is responsible for obtaining material demand information and publishing it through the Internet platform. It can also receive and count the quotation information of each supplier in real time to ensure the timeliness and accuracy of the information. The function of the data acquisition module is to collect the supply information of each supplier. The supply information includes the supplier's transaction history data and credit rating, which provides an important basis for subsequent evaluation and screening. The evaluation module evaluates and processes the supplier's supply information. By comprehensively analyzing the supplier's transaction history, credit rating and other factors, the evaluation module can screen out suppliers that are allowed to cooperate. Suppliers are selected and recorded as preferred suppliers. The grading module grades the preferred suppliers according to the quotation information. By comparing the quotations of various suppliers, the communication level of each preferred supplier can be determined according to the grading results, so as to determine the communication priority between the enterprise and each preferred supplier. The function of the summary output module is to communicate with each preferred supplier according to the communication level. Through communication with the preferred suppliers, the system can collect the material prices after communication with the preferred suppliers. Subsequently, the summary output module summarizes the material prices, supply information and communication levels of the preferred suppliers into a detailed material inquiry report to provide decision-making support for the purchaser and help it make more informed purchasing decisions.

[0116] See also Figure 3 , an electronic device, the electronic device comprising:

[0117] at least one processor;

[0118] and a memory communicatively coupled to the at least one processor;

[0119] Among them, the memory stores a computer program that can be executed by at least one processor, and the computer program is executed by at least one processor so that the at least one processor can execute the above-mentioned intelligent material inquiry method based on Internet order transactions.

[0120] The processor of the above-mentioned electronic device can be one or more high-performance central processing units (CPU), which are responsible for performing complex calculations and data processing tasks. The memory can be a solid-state drive (SSD) or a random access memory (RAM), which is used to store a large amount of data and information to ensure the rapid response of the system and data security. The electronic device can also include an arithmetic unit, an input device and an output device. The arithmetic unit is used to perform various logical operations and mathematical operations. The input devices such as keyboards and mice are used for users to input instructions and data. The output devices such as displays and printers are used to display processing results and print documents.

[0121] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, device, article or method 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, device, article or method. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the presence of other identical elements in the process, device, article or method including the element.

[0122] The above is only a preferred embodiment of the present invention. It should be noted that, for those skilled in the art, several improvements and modifications can be made without departing from the principles of the present invention, and these improvements and modifications should also be considered as the protection scope of the present invention. The structures, devices and operating methods not specifically described and explained in the present invention shall be implemented according to the conventional means in the art unless otherwise specified and limited.

Claims

1. An intelligent material price inquiry method based on Internet order transactions, characterized in that: include: Obtain material demand information, publish it through the Internet platform, and receive and compile statistics on quotation information from various suppliers in real time; Collecting supply information of each supplier, wherein the supply information includes transaction history data and credit rating of the supplier; Evaluate suppliers based on their supply information, select suppliers that are suitable for cooperation based on the evaluation results, and record them as preferred suppliers; Classify the preferred suppliers according to the quotation information, and determine the communication level of each preferred supplier according to the classification results; Communicate with each preferred supplier based on the communication level, collect material prices after communication with the preferred supplier, and then summarize the material prices, supply information and communication levels of the preferred suppliers into a material inquiry report.

2. According to claim 1, a smart material price inquiry method based on Internet order transactions is characterized by: The material demand information is obtained by means of internal enterprise provision, supply chain collaboration platform provision and manual entry; When receiving the quotation information from suppliers, it includes active push and passive reception. The active push automatically sends the inquiry request to the matching suppliers through the Internet platform, and the passive reception directly counts the active quotations submitted by the suppliers; When counting the quotation information of the supplier, a timestamp is synchronously added to the quotation information of the supplier to determine the time characteristics of the quotation information.

3. The intelligent material price inquiry method based on Internet order transaction according to claim 2 is characterized in that: Under the active push, suppliers on the Internet platform are actively matched based on material demand information. The specific process is as follows: Obtaining the material demand information and the supplier's supply information; Performing vectorization processing on the material demand information and the supply information to obtain a demand feature vector corresponding to the material demand information and a supply feature vector corresponding to the supply information; Obtaining a matching function, and inputting the demand feature vector and the supply feature vector into the matching function, and recording the output result of the matching function as a matching score; Obtaining a matching threshold, and comparing the matching score with the matching threshold; When the matching score is greater than the matching threshold, it indicates that the supply information corresponding to the matching score meets the user's needs, and the supplier corresponding to the supply information is matched with the material demand information; When the matching score is less than or equal to the matching threshold, it indicates that the supply information corresponding to the matching score does not meet the user's needs, and no matching is performed on the supplier corresponding to the supply information.

4. According to claim 1, the intelligent material price inquiry method based on Internet order transaction is characterized in that: When collecting the supply information of each supplier, the supply information of each supplier is preprocessed simultaneously, and the preprocessing step includes: Obtaining the supply information of each supplier, and performing deduplication processing to eliminate the supply information of the supplier that appears repeatedly; Perform data cleaning on the deduplicated supply information to remove outliers and invalid data in the supply information; The cleaned supply information is arranged in chronological order and simultaneously aggregated into the preset reference database.

5. The intelligent material price inquiry method based on Internet order transaction according to claim 4 is characterized in that: The step of evaluating suppliers according to their supply information, selecting suppliers that are allowed to cooperate according to the evaluation results, and recording them as preferred suppliers includes: Retrieving the preprocessed supply information from the reference database; Based on the sending node of the logistics demand information, the evaluation period is reversely constructed, and the transaction history data in the supply information within the evaluation period is collected; Performing trend evaluation processing on the transaction history data to obtain transaction trend parameters of the supplier; Extracting the transaction volume from the transaction history data, and combining it with the transaction trend parameter and the credit rating of the supplier to comprehensively calculate a comprehensive evaluation score of the supplier; An evaluation threshold is set, the comprehensive evaluation score is compared with the evaluation threshold, and suppliers whose comprehensive scores are greater than the evaluation threshold are screened as preferred suppliers.

6. The intelligent material price inquiry method based on Internet order transaction according to claim 5 is characterized by: The transaction volume is extracted from the transaction history data, and then normalized after combining the transaction trend parameter and the credit rating output of the supplier. The specific process is as follows: Obtain transaction volume, transaction trend parameters and credit ratings; Obtaining a normalization function, and outputting the transaction volume, transaction trend parameter, and credit rating to the normalization function respectively, to obtain a first condition parameter corresponding to the transaction volume, a second condition parameter corresponding to the transaction trend parameter, and a third condition parameter corresponding to the credit rating; Among them, the transaction volume and credit rating are only statistically analyzed within the evaluation period.

7. The intelligent material price inquiry method based on Internet order transaction according to claim 1 is characterized by: The step of grading the preferred suppliers according to the quotation information and determining the communication level of each preferred supplier according to the grading result includes: Extracting material quotations of various preferred suppliers from the quotation information and recording them as grading condition parameters; Obtaining grading intervals, wherein each grading interval corresponds to a communication level; Compare the grading condition parameters with the grading intervals to match the communication level of the supplier corresponding to each grading condition parameter; The communication levels are arranged in descending order, and the communication order of each preferred supplier is determined according to the arrangement order of the communication levels.

8. The intelligent material price inquiry method based on Internet order transaction according to claim 1 is characterized by: The step of communicating with each preferred supplier according to the communication level and collecting material prices after communicating with the preferred supplier includes: Obtain communication ratings from preferred suppliers; Communicate with the preferred suppliers in order of priority of the communication levels; Collect material prices, communication time and supplier feedback information during the communication process, then summarize all material prices, communication time and supplier feedback information after all communications to form a material inquiry report and submit it to the management end.

9. An intelligent material inquiry system based on Internet order transactions, characterized by: The intelligent material price inquiry method based on Internet order transaction according to any one of claims 1 to 8 comprises: An initialization module, which is used to obtain material demand information, publish it through an Internet platform, and receive and count quotation information from various suppliers in real time; A data collection module, the data collection module is used to collect supply information of each supplier, wherein the supply information includes the supplier's transaction history data and credit rating; An evaluation module, which is used to evaluate suppliers according to their supply information, and select suppliers that are allowed to cooperate according to the evaluation results, and record them as preferred suppliers; A grading module, the grading module is used to grade the preferred suppliers according to the quotation information, and determine the communication level of each preferred supplier according to the grading result; A summary output module is used to communicate with each preferred supplier based on the communication level, collect material prices after communication with the preferred supplier, and then summarize the material prices, supply information and communication level of the preferred supplier into a material inquiry report.

10. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively coupled to the at least one processor; Wherein, the memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the intelligent material inquiry method based on Internet order transactions as described in any one of claims 1 to 8.

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