CN113657955A - Chinese-medicinal material supply and demand resource allocation integration system based on big data - Google Patents
Chinese-medicinal material supply and demand resource allocation integration system based on big data Download PDFInfo
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Abstract
The invention discloses a Chinese medicinal material supply and demand resource allocation and integration system based on big data, which belongs to the technical field of medicinal material transaction and comprises a medicinal material information base, a seller input module, a buyer input module, an encryption transmission module, a seller storage module, a buyer storage module and a pairing module; the seller entry module is used for the seller to enter the information of the medicinal materials to be sold, and the specific method comprises the following steps: set up the standard template of medicinal material information, the seller compiles the medicinal material information that needs to sell according to the standard template of medicinal material information, set up the medicinal material information verification model, acquire seller information, the medicinal material information that will need to sell and seller information input the medicinal material information verification model in and obtain the verification result, through verifying seller information, ensure that the seller is not suspicious merchant, guarantee buyer's interests and the reputation of platform, because the phishing is more and more rampant now, and most buyers do not understand how to distinguish these suspicious merchants, consequently, just need the platform side to verify, guarantee buyer interests.
Description
Technical Field
The invention belongs to the technical field of medicinal material transaction; in particular to a Chinese medicinal material supply and demand resource allocation and integration system based on big data.
Background
In the traditional Chinese medicine market, a buyer often cannot find a proper goods source and a seller cannot find a proper buyer, along with the rapid development of the internet, the acquisition, aggregation, storage, transmission, processing, analysis and the like of a large amount of data become more and more convenient, and the analysis of large data becomes a hot topic. The key of big data analysis is to find hidden association from massive data, thereby helping people to make correct decision; however, when network transaction is carried out, the risk of information leakage of the buyer and the seller is increased, and how to ensure the economic safety and the information safety of the buyer and the seller is also important, so the Chinese herbal medicine supply and demand resource allocation and integration system based on big data is provided, the buyer can easily find the goods source information, the seller can easily find the proper buyer information, and the economic safety and the information safety of the buyer and the seller are protected.
Disclosure of Invention
The invention aims to provide a Chinese medicinal material supply and demand resource allocation and integration system based on big data, and solves the following problems:
1. the buyer can not find a proper goods source, and the seller can not find a proper buyer;
2. how to guarantee the economic safety and the information safety of the buyer and the seller in the transaction process.
The purpose of the invention can be realized by the following technical scheme:
a big data-based traditional Chinese medicine supply and demand resource allocation and integration system comprises a medicine information base, a seller input module, a buyer input module, an encryption transmission module, a seller storage module, a buyer storage module and a pairing module;
the seller entry module is used for the seller to enter the information of the medicinal materials to be sold, and the specific method comprises the following steps: setting a medicinal material information standard template, compiling medicinal material information to be sold by a seller according to the medicinal material information standard template, setting a medicinal material information verification model, acquiring seller information, inputting the medicinal material information to be sold and the seller information into the medicinal material information verification model to obtain a verification result, prohibiting uploading the medicinal material information to be sold when the verification result is that the seller is a suspicious merchant, and sending the medicinal material information to be sold and the seller information to a seller storage module when the verification result is that the seller is not a suspicious merchant;
the buyer entry module is used for a buyer to enter the information of the medicinal materials to be purchased, and the specific method comprises the following steps: setting a medicinal material information standard template, compiling medicinal material information to be purchased by a buyer according to the medicinal material information standard template, verifying the identity of the buyer, and uploading the buyer identity information and the medicinal material information to be purchased to a buyer storage module when the verification is passed;
the encryption transmission module is used for carrying out encryption transmission on the buyer identity information and the seller information;
the pairing module is used for matching the information of the medicinal materials needing to be purchased with the information of the medicinal materials needing to be sold, and the specific method comprises the following steps: acquiring buyer comprehensive data and seller comprehensive data, matching the medicinal material information to be purchased with the medicinal material information to be sold to acquire matching degrees Qi, arranging the matching degrees Qi according to a descending order, selecting the seller comprehensive data corresponding to the first N matching degrees Qi, sending the selected first N seller comprehensive data to the buyer, replying rejection information when the buyer is not satisfied with the sent seller comprehensive data, and selecting a satisfied seller when the buyer is satisfied with the sent seller comprehensive data.
Further, the method for the encrypted transmission module to perform the encrypted transmission on the buyer identity information and the seller information includes: acquiring buyer identity information and seller information, and marking the buyer identity information and the seller information as identity data;
acquiring a preset segmentation condition, establishing a data segmentation model, inputting the identity data and the preset segmentation condition into the data segmentation model to obtain a plurality of data segments, and inputting the plurality of data segments into a coding model to obtain corresponding data segment codes;
the method comprises the steps of setting an encryption model, inputting data segment codes into the encryption model, obtaining encryption data, obtaining medicinal material information needing to be purchased and medicinal material information needing to be sold, integrating corresponding encryption data with the medicinal material information needing to be purchased and the medicinal material information needing to be sold respectively to form buyer comprehensive data and seller comprehensive data, and sending the buyer comprehensive data and the seller comprehensive data to a medicinal material information base for storage.
Further, the method for establishing the data segmentation model comprises the following steps: acquiring a plurality of groups of historical segmentation data, setting preset segmentation conditions, constructing an artificial intelligence model, integrating the historical segmentation data and the preset segmentation conditions into input data, setting corresponding segmentation results for the input data, inputting the plurality of groups of historical segmentation data, the preset segmentation conditions and the corresponding segmentation results into the artificial intelligence model for learning training, and dividing the plurality of groups of historical segmentation data, the corresponding preset segmentation conditions and the corresponding segmentation results into a training set, a test set and a check set according to a set proportion; training, testing and checking the artificial intelligence model through the training set, the testing set and the checking set, and marking the trained artificial intelligence model as a data segmentation model.
Furthermore, after the buyer selects a satisfactory seller, a discussion unit is established, and the buyer communicates with the corresponding seller through the discussion unit, and the communication records in the discussion unit are respectively transmitted to the seller storage module and the buyer storage module for storage.
The invention has the beneficial effects that: by verifying the seller information, the seller is not a suspicious merchant, and the benefit of the buyer and the credit of the platform are guaranteed, because the phishing is more and more rampant nowadays, and most buyers do not know how to distinguish the suspicious merchants, so that the platform side is required to verify and the benefit of the buyer is guaranteed; the identity information of the buyers is verified, so that the benefits of the sellers and the reputation of the platform are guaranteed, because the online frauds are more and more rampant nowadays, and most sellers do not know how to distinguish the suspicious merchant buyers, so that the platform side is required to verify, and the benefits of the sellers are guaranteed; the buyer and the seller store the respective private information in the respective storage module, so that the safety of the private information is guaranteed, the information leakage is avoided, and the private information is utilized by lawbreakers; by carrying out encryption transmission on the identity information of the buyer and the information of the seller, the information leakage of the buyer and the seller is avoided, the information security of the buyer and the seller is further improved, the utilization by lawless persons is avoided, and the trust and the approval of the buyer and the seller to the system platform are increased; the method and the system can solve the problem that the buyer can not find a proper goods source and the seller can not find a proper buyer, and help the buyer and the seller to complete the transaction quickly.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic block diagram of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, a Chinese herbal medicine supply and demand resource allocation and integration system based on big data includes a herbal medicine information base, a seller entry module, a buyer entry module, an encryption transmission module, a seller storage module, a buyer storage module and a pairing module.
The seller inputs the module and is used for seller to type the medicinal material information that needs to sell, and the medicinal material information includes medicinal material variety, specification, place of production and quantity, and concrete method includes: the method comprises the steps that a medicinal material information specification template is set and used for standardizing the publishing of user information and is set by an administrator, a seller edits medicinal material information to be sold according to the medicinal material information specification template, a medicinal material information verification model is set, seller information is obtained and comprises company information, transaction records and customer scores, the medicinal material information to be sold and the seller information are input into the medicinal material information verification model to obtain a verification result, when the verification result is that the seller is a suspicious merchant, the suspicious merchant is a cheater and is prohibited to upload the medicinal material information to be sold, and when the verification result is that the seller is not a suspicious merchant, the medicinal material information to be sold and the seller information are sent to a seller storage module; through verifying the seller information, the seller is not a suspicious merchant, and the benefit of the buyer and the credit of the platform are guaranteed, because the phishing is more and more rampant nowadays, most buyers do not know how to distinguish the suspicious merchants, and therefore the platform side is required to verify and the benefit of the buyer is guaranteed.
The method for setting the medicinal material information verification model comprises the following steps: acquiring historical data of medicinal material information verification; the medicinal material information verification historical data comprises medicinal material information needing to be sold and seller information; setting a verification result for the historical data of the verification of the medicinal material information; the verification result comprises that the seller is a suspicious merchant and that the seller is not a suspicious merchant; constructing an artificial intelligence model; the artificial intelligence model comprises an error reverse propagation neural network, an RBF neural network and a deep convolution neural network; dividing the historical data of the verification of the medicinal material information and the corresponding verification result into a training set, a test set and a check set according to a set proportion; the set proportion comprises 4: 1: 1. 3: 2: 1 and 3: 1: 1; training, testing and verifying the artificial intelligent model through a training set, a testing set and a verifying set; and marking the trained artificial intelligence model as a medicinal material information verification model.
The buyer entry module is used for a buyer to enter the information of the medicinal materials to be purchased, and the specific method comprises the following steps: the method comprises the steps that a medicinal material information standard template is set, a buyer compiles medicinal material information needing to be purchased according to the medicinal material information standard template, the identity of the buyer is verified, namely real-name verification is carried out, the buyer who operates is verified whether the buyer is the buyer who is real-name verified, and when verification passes, the buyer storage module is uploaded with the medicinal material information needing to be purchased and the buyer identity information. The identity information of the buyers is verified, so that the benefits of the sellers and the reputation of the platform are guaranteed, because the online fraud is more and more rampant nowadays, most sellers do not know how to distinguish the suspicious merchant buyers, and the platform side is required to verify, so that the benefits of the sellers are guaranteed.
The private information is stored in the storage module of the buyer and the seller, so that the safety of the private information is guaranteed, the information leakage is avoided, and the private information is utilized by lawbreakers.
The encryption transmission module is used for carrying out encryption transmission on the buyer identity information and the seller information, and the specific method comprises the following steps: acquiring buyer identity information and seller information, marking the buyer identity information and the seller information as identity data, acquiring preset segmentation conditions, wherein the preset segmentation conditions are the basis for data segmentation, and are discussed and set by an expert group according to grammar and an identity information format, and when the identity information is encrypted, the buyer identity information and the seller information are separately performed but are not integrated for encryption, establishing a data segmentation model, inputting the identity data and the preset segmentation conditions into the data segmentation model to obtain a plurality of data segments, inputting the data segments into a coding model to obtain corresponding data segment codes, setting the encryption model, inputting the data segment codes into the encryption model to obtain encryption data, acquiring the medicinal material information to be purchased and the medicinal material information to be sold, and integrating the corresponding encryption data with the medicinal material information to be purchased and the medicinal material information to be sold into comprehensive buyer data and the medicinal material information to be sold And the seller comprehensive data sends the buyer comprehensive data and the seller comprehensive data to the medicinal material information base for storage.
By carrying out encryption transmission on the identity information of the buyer and the information of the seller, the information leakage of the buyer and the seller is avoided, the information security of the buyer and the seller is further improved, the use by lawless persons is avoided, and the trust and the approval of the buyer and the seller to the system platform are increased.
The method for establishing the data segmentation model comprises the following steps: acquiring a plurality of groups of historical segmentation data, wherein the historical segmentation data is data which needs to be segmented once, setting preset segmentation conditions, constructing an artificial intelligence model, the artificial intelligence model comprises an error reverse propagation neural network, an RBF neural network and a deep convolution neural network, integrating the historical segmentation data and the preset segmentation conditions into input data, setting corresponding segmentation results for the input data, wherein the segmentation results are data sections formed after data segmentation, inputting the plurality of groups of historical segmentation data, the preset segmentation conditions and the corresponding segmentation results into the artificial intelligence model for learning and training, and dividing the plurality of groups of historical segmentation data, the corresponding preset segmentation conditions and the corresponding segmentation results into a training set, a test set and a check set according to a set proportion; the set proportion comprises 4: 1: 1. 4: 3: 1 and 3: 2: 2; training, testing and checking the artificial intelligence model through the training set, the testing set and the checking set, and marking the trained artificial intelligence model as a data segmentation model.
The method for establishing the coding model comprises the following steps: acquiring a plurality of groups of historical data segments, summarizing the historical data segments, deleting repeated data segments, sequencing the deleted historical data segments according to the division time and the data size, sequencing according to the division time, sequencing according to the data size at the same division time, randomly sequencing all the same, and encoding the sequenced historical data segments, wherein the encoding labels have a rule, for example, according to 1, 2, 3, … …; or a1, a2, a3 and … … in a certain sequence, preferably, a sorting function can be used to automatically generate codes, and further confidentiality is increased; establishing a coding table, namely summarizing the coded historical data segments and the corresponding codes into the table, setting a matching unit for matching the input data segments with the coding table, inputting the input data segments into the coding table for storage when the input data segments are not successfully matched with the coding table, and generating the corresponding data segment codes according to the coding sequence; and when the input data segment is successfully matched with the coding table, obtaining the corresponding data segment code.
The method for setting the encryption model comprises the following steps: acquiring a high-definition picture or a high-definition picture combined by a plurality of pictures, acquiring a data segment code to be encrypted, marking the data segment code to be encrypted as an encrypted code, wherein the data segment code is a sequenced data segment code, dividing the high-definition picture into a plurality of image blocks, the number of the image blocks is more than that of the encrypted code, marking the number of the encrypted codes as L, wherein L is a positive integer greater than zero, randomly selecting L image blocks from the plurality of image blocks, randomly distributing the acquired encrypted codes into the L image blocks according to the sequence, wherein the sequence is the original arrangement sequence of the encrypted codes or reversed to prevent disorder, avoiding that the sequence is not right during decryption to cause data loss and generating a distribution record, recording the distribution sequence and the position of the encrypted codes in the distribution record, and marking the unselected image blocks in the high-definition picture as a confusion block, marking the number of the obfuscating blocks as P, wherein P is a positive integer larger than zero, randomly selecting P codes from a code table, randomly distributing the selected P codes into the obfuscating blocks, and marking the high-definition pictures as encrypted data; the possibility of password cracking is further reduced, because if only the encryption code is used, after other people obtain the code table, correct data can be listed from the semantics of the encryption code, and the importance of the distribution record is reflected, so that the distribution record can be encrypted to further increase the security, and other people are prevented from obtaining the distribution record.
The pairing module is used for matching the information of the medicinal materials needing to be purchased with the information of the medicinal materials needing to be sold, and the specific method comprises the following steps: acquiring buyer comprehensive data and seller comprehensive data, matching the information of the medicinal materials to be purchased with the information of the medicinal materials to be sold to acquire a matching degree Qi, wherein the matching degree Qi is the similarity between the information of the medicinal materials to be purchased by the buyer and the information of the medicinal materials to be sold by the buyer, because the information of the medicinal materials to be purchased and the information of the medicinal materials to be sold are compiled by using the same template, the acquisition of the matching degree is convenient, so the matching degree Qi is not described in detail, the matching degrees Qi are arranged according to a descending order, the seller comprehensive data corresponding to the first N matching degrees Qi are selected, N is a proportionality coefficient, 10 is more than or equal to N more than or equal to 3, the selected first N seller comprehensive data are transmitted to the buyer, when the buyer is unsatisfied with the transmitted seller comprehensive data, the rejection information is replied, the rejection information comprises unsatisfied and inappropriate information representing negative information, and when the buyer is satisfied with the transmitted seller comprehensive data, selecting a satisfied seller, establishing a discussion unit, and enabling a buyer to communicate with the corresponding seller through the discussion unit and respectively sending communication records in the discussion unit to a seller storage module and a buyer storage module for storage; the communication records in the discussion unit are respectively sent to the seller storage module and the buyer storage module for storage by establishing the discussion unit, and when the economic dispute is sent, a basis is provided for the buyer or the buyer.
When the seller-type medical material selling system is used, a seller inputs information of a medical material to be sold through a seller input module, a medical material information standard template is set, the seller edits the information of the medical material to be sold according to the medical material information standard template, a medical material information verification model is set, seller information is obtained, the information of the medical material to be sold and the seller information are input into the medical material information verification model to obtain a verification result, uploading of the information of the medical material to be sold is forbidden when the verification result is that the seller is a suspicious merchant, and the information of the medical material to be sold and the seller information are sent to a seller storage module when the verification result is that the seller is not a suspicious merchant; the method comprises the steps of setting a medicinal material information standard template, compiling medicinal material information needing to be purchased by a buyer according to the medicinal material information standard template, verifying the identity of the buyer, and uploading the buyer identity information and the medicinal material information needing to be purchased to a buyer storage module when verification is passed.
The method comprises the steps of carrying out encryption transmission on buyer identity information and seller information, obtaining the buyer identity information and the seller information, marking the buyer identity information and the seller information as identity data, obtaining preset segmentation conditions, establishing a data segmentation model, inputting the identity data and the preset segmentation conditions into the data segmentation model, obtaining a plurality of data segments, inputting the data segments into a coding model, obtaining corresponding data segment codes, setting an encryption model, inputting the data segment codes into the encryption model, obtaining encryption data, obtaining the medicinal material information needing to be purchased and the medicinal material information needing to be sold, integrating the corresponding encryption data with the medicinal material information needing to be purchased and the medicinal material information needing to be sold into buyer comprehensive data and seller comprehensive data respectively, and sending the buyer comprehensive data and the seller comprehensive data into a medicinal material information base for storage.
The method comprises the steps of matching medicinal material information needing to be purchased with medicinal material information needing to be sold, acquiring buyer comprehensive data and seller comprehensive data, matching the medicinal material information needing to be purchased with the medicinal material information needing to be sold, acquiring matching degrees Qi, arranging the matching degrees Qi according to a descending order, selecting seller comprehensive data corresponding to the first N matching degrees Qi, sending the selected first N seller comprehensive data to a buyer, replying rejection information when the buyer is unsatisfied with the sent seller comprehensive data, selecting a satisfied seller when the buyer is satisfied with the sent seller comprehensive data, establishing a discussion unit, communicating the buyer with the corresponding seller through the discussion unit, and respectively sending communication records in the discussion unit to a seller storage module and a seller storage module for storage.
In the description herein, references to the description of "one embodiment," "an example," "a specific example" or the like are intended to mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present invention, "a plurality" means two or more unless specifically defined otherwise.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.
Claims (4)
1. A Chinese medicinal material supply and demand resource allocation and integration system based on big data is characterized by comprising a medicinal material information base, a seller input module, a buyer input module, an encryption transmission module, a seller storage module, a buyer storage module and a pairing module;
the seller entry module is used for the seller to enter the information of the medicinal materials to be sold, and the specific method comprises the following steps: setting a medicinal material information standard template, compiling medicinal material information to be sold by a seller according to the medicinal material information standard template, setting a medicinal material information verification model, acquiring seller information, inputting the medicinal material information to be sold and the seller information into the medicinal material information verification model to obtain a verification result, prohibiting uploading the medicinal material information to be sold when the verification result is that the seller is a suspicious merchant, and sending the medicinal material information to be sold and the seller information to a seller storage module when the verification result is that the seller is not a suspicious merchant;
the buyer entry module is used for a buyer to enter the information of the medicinal materials to be purchased, and the specific method comprises the following steps: setting a medicinal material information standard template, compiling medicinal material information to be purchased by a buyer according to the medicinal material information standard template, verifying the identity of the buyer, and uploading the buyer identity information and the medicinal material information to be purchased to a buyer storage module when the verification is passed;
the encryption transmission module is used for carrying out encryption transmission on the buyer identity information and the seller information;
the pairing module is used for matching the information of the medicinal materials needing to be purchased with the information of the medicinal materials needing to be sold, and the specific method comprises the following steps: acquiring buyer comprehensive data and seller comprehensive data, matching the medicinal material information to be purchased with the medicinal material information to be sold to acquire matching degrees Qi, arranging the matching degrees Qi according to a descending order, selecting the seller comprehensive data corresponding to the first N matching degrees Qi, sending the selected first N seller comprehensive data to the buyer, replying rejection information when the buyer is not satisfied with the sent seller comprehensive data, and selecting a satisfied seller when the buyer is satisfied with the sent seller comprehensive data.
2. The big data-based Chinese herbal medicine supply and demand resource allocation and integration system as claimed in claim 1, wherein the method for the encrypted transmission module to perform the encrypted transmission on the buyer identity information and the seller information comprises: acquiring buyer identity information and seller information, and marking the buyer identity information and the seller information as identity data;
acquiring a preset segmentation condition, establishing a data segmentation model, inputting the identity data and the preset segmentation condition into the data segmentation model to obtain a plurality of data segments, and inputting the plurality of data segments into a coding model to obtain corresponding data segment codes;
the method comprises the steps of setting an encryption model, inputting data segment codes into the encryption model, obtaining encryption data, obtaining medicinal material information needing to be purchased and medicinal material information needing to be sold, integrating corresponding encryption data with the medicinal material information needing to be purchased and the medicinal material information needing to be sold respectively to form buyer comprehensive data and seller comprehensive data, and sending the buyer comprehensive data and the seller comprehensive data to a medicinal material information base for storage.
3. The big data-based Chinese herbal medicine supply and demand resource allocation and integration system as claimed in claim 2, wherein the data segmentation model establishing method comprises: acquiring a plurality of groups of historical segmentation data, setting preset segmentation conditions, constructing an artificial intelligence model, integrating the historical segmentation data and the preset segmentation conditions into input data, setting corresponding segmentation results for the input data, inputting the plurality of groups of historical segmentation data, the preset segmentation conditions and the corresponding segmentation results into the artificial intelligence model for learning training, and dividing the plurality of groups of historical segmentation data, the corresponding preset segmentation conditions and the corresponding segmentation results into a training set, a test set and a check set according to a set proportion; training, testing and checking the artificial intelligence model through the training set, the testing set and the checking set, and marking the trained artificial intelligence model as a data segmentation model.
4. The system as claimed in claim 1, wherein the buyer establishes a discussion unit after selecting a satisfactory seller, and the buyer communicates with the corresponding seller through the discussion unit and sends the communication records in the discussion unit to the seller storage module and the buyer storage module for storage respectively.
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