Data classification and storage method for electronic commerce

Abstract

The invention relates to the technical field of data storage, in particular to a data classification and storage method for electronic commerce, which comprises an analysis module, a classification module, an encryption module, a processor and a database. According to the method, data input from the outside are graded and marked according to the importance degree of the data, then the data marked with category labels are input into the classification module according to different category labels to be audited and classified by an auditor, the auditor audits the data at a time according to classification, and when the data content is different from the category labels, the auditor performs classification according to the category labels. According to the technical scheme, the type labels of the data are changed, then the audited data are classified according to the type labels, important data in the same time can be quickly found out only according to the labels and the importance degree during query, and data query is facilitated.

Description

Technical Field

[0001] The present invention belongs to the technical field of data storage, and particularly relates to a method for classifying and storing data for e-commerce. Background Art

[0002] E-commerce generally refers to a new business operation model in which, in extensive commercial trade activities around the world, under the open network environment of the Internet, based on the client-server application mode, the buyer and seller conduct various business activities without meeting face to face, realizing consumers' online shopping, online transactions between merchants, online electronic payment, and various business activities, transaction activities, financial activities, and related comprehensive service activities.

[0003] During the process of e-commerce, a large amount of data will be generated. These data information will be repeatedly retrieved during the business activities. The existing e-commerce storage system records the data according to the time when the data is generated. When querying the data, it can only be queried according to the input time. When there is a large amount of data recorded at the same time, a large amount of useless data will be retrieved by the retrieval system synchronously, which will affect the speed of querying some important and frequently used data, and waste time in the data query work. Summary of the Invention

[0004] The purpose of the present invention is to solve the deficiencies existing in the prior art, and to propose a method for classifying and storing data for e-commerce.

[0005] In order to achieve the above purpose, the present invention adopts the following technical solutions:

[0006] Design a method for classifying and storing data for e-commerce, including an analysis module, a classification module, an encryption module, a processor, and a database, comprising the following steps:

[0007] S1. First, input the externally input data into the analysis module for analysis. The analysis module extracts the keywords in the data information, separates the types of data according to the set keywords, and at the same time marks the type tags on the data, and at the same time classifies and marks according to the importance degree of the data;

[0008] S2. Input the data with type tags into the classification module for the reviewer to review and classify. The reviewer reviews the data according to the classification one by one. When the data content is different from the type tag, change the type tag of the data, and then classify the reviewed data according to the type tag;

[0009] S3. Classify and store the data according to the tags and importance degree of the data in multiple servers respectively, and back up the data when storing in different servers;

[0010] S4. Meanwhile, the encryption module encrypts and stores the data with the importance level marked as above high, sets different access permissions according to the importance level, and prevents important data from being leaked.

[0011] Preferably, the classification module includes a keyword search module and a label marking module. The keyword search module sets keywords for the data, then searches for the keywords in the data through the keyword search module to identify the information of the data, and the label marking module corresponds the set labels with the keywords and marks the labels on the data according to the keywords.

[0012] Preferably, the classification module includes a manual review module and a data label option module. The manual review module reviews the labels of the marked data, and at the same time reviews the importance level of the data. The data label option module sets the importance level of the data to facilitate the reviewer to mark the importance degree of the data.

[0013] Preferably, the encryption module sets access permissions according to the importance level, and at the same time sets access permissions for the access accounts, and the types of data that different accounts can access are restricted.

[0014] Preferably, the processor is connected to the analysis module, the classification module, the encryption module and the database, and separate processors are provided in the analysis module, the classification module, the encryption module and the database.

[0015] Preferably, the database includes a plurality of storage servers separately arranged, and different types of data are stored in different storage servers.

[0016] The beneficial effects of the present invention: The present invention classifies and marks the externally input data according to the importance level of the data, and then inputs the data with the type labels into the classification module according to different type labels for the reviewer to review and classify. The reviewer reviews the data according to the classification one by one. When the data content is different from the type label, the type label of the data is changed, and then the reviewed data is classified according to the type label. When querying, only by selecting according to the label and the importance level, the important data in the same time can be quickly found, which facilitates the data query. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a schematic flow chart of a data classification and storage method for e-commerce proposed by the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0018] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments.

[0019] Reference Figure 1 , a data classification and storage method for e-commerce, including an analysis module, a classification module, an encryption module, a processor, and a database, comprising the following steps:

[0020] S1. First, input the externally entered data into the analysis module for analysis. The analysis module extracts keywords in the data information, separates the types of data according to the set keywords, and at the same time marks the type tags on the data, and grades and marks according to the importance of the data;

[0021] S2. Input the data with type tags into the classification module for the auditor to review and classify according to different type tags. The auditor reviews the data one by one according to the classification. When the data content is different from the type tag, change the type tag of the data, and then classify the audited data according to the type tag;

[0022] S3. Classify according to the label and importance of the data and then store them separately in multiple servers. When the data is stored, it is backed up and stored in different servers;

[0023] S4. At the same time, encrypt and store the data with the importance level marked as above high level through the encryption module, set different access permissions according to the importance level, and prevent important data from being leaked.

[0024] The classification module includes a keyword search module and a label marking module. Set keywords for the data through the keyword search module, and then identify the information of the data by searching for keywords in the data through the keyword search module. Corresponding the set labels with the keywords through the label marking module, and mark the labels on the data according to the keywords.

[0025] The classification module includes a manual review module and a data label option module. The manual review module reviews the labels of the marked data, and at the same time reviews the importance of the data. Set the importance level of the data through the data label option module to facilitate the auditor to mark the importance of the data.

[0026] The encryption module sets access permissions according to the importance level, and at the same time sets access permissions for the access accounts. The types of data that different accounts can access are restricted.

[0027] The processor is connected to the analysis module, the classification module, the encryption module, and the database. Separate processors are set in the analysis module, the classification module, the encryption module, and the database.

[0028] The database includes multiple storage servers set separately. Different types of data are stored in different storage servers.

[0029] Specifically: First, the externally input data is input into the analysis module for analysis. The analysis module extracts keywords from the data information, separates the types of data according to the set keywords, and at the same time marks the type labels on the data. At the same time, it classifies and marks according to the importance of the data. The data with type labels is input into the classification module for the reviewer to review and classify. The reviewer reviews the data one by one according to the classification. When the data content is different from the type label, the type label of the data is changed, and then the reviewed data is classified according to the type label. It is classified according to the label and importance of the data and then stored in multiple servers respectively. When the data is stored, it is backed up and stored in different servers. At the same time, the data with the importance level marked as above high level is encrypted and stored by the encryption module, and different access permissions are set according to the importance level to prevent important data from being leaked.

[0030] The above is only a preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, according to the technical solution of the present invention and its inventive concept, makes equivalent substitutions or changes, and should be covered by the protection scope of the present invention.

Claims

1. A data classification and storage method for e-commerce, characterized in that: It includes an analysis module, a classification module, an encryption module, a processor, and a database, and the following steps are included: S1. First, input the externally entered data into the analysis module for analysis. The analysis module extracts keywords in the data information, separates the types of data according to the set keywords, and at the same time marks the type labels on the data, and marks the classification according to the importance degree of the data; S2. Input the data with type labels into the classification module according to different type labels for the reviewer to review and classify. The reviewer reviews the data one by one according to the classification. When the data content is different from the type label, change the type label of the data, and then classify the reviewed data according to the type label; S3. Classify according to the label and importance degree of the data and then store them separately in multiple servers. When the data is stored, it is backed up and stored in different servers; S4. At the same time, encrypt and store the data with the importance degree marked as above high level through the encryption module, set different access permissions according to the importance degree, and prevent important data from being leaked.

2. The method for classifying and storing data for e-commerce according to claim 1, characterized in that: The classification module includes a keyword search module and a label marking module. Set keywords for the data through the keyword search module, and then identify the information of the data by searching for keywords in the data through the keyword search module. Corresponding the set labels with the keywords through the label marking module, and mark the labels on the data according to the keywords.

3. A data classification and storage method for e-commerce according to claim 1, characterized in that: The classification module includes a manual review module and a data label option module. The manual review module reviews the labels of the marked data and at the same time reviews the importance degree of the data. Set the importance degree of the data through the data label option module to facilitate the reviewer to mark the importance degree of the data.

4. A data classification and storage method for e-commerce according to claim 1, characterized in that: The encryption module sets access permissions according to the importance degree, and at the same time sets access permissions for the access accounts, and the types of data that different accounts can access are restricted.

5. A data classification and storage method for e-commerce according to claim 1, characterized in that: The processor is connected to the analysis module, the classification module, the encryption module, and the database, and separate processors are set in the analysis module, the classification module, the encryption module, and the database.

6. The data classification and storage method for e-commerce according to claim 1, characterized in that: The database includes multiple storage servers that are separately set, and different types of data are stored in different storage servers.

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