Data field uniform standard naming method and apparatus

Abstract

The application provides a data field uniform standard naming method and device, the method comprises the following steps: obtaining a field name input by a user and a business attribution label to which the field name belongs; searching a standard field library for a standard field that is completely matched with the field name according to the field name; if there is no standard field that is completely matched with the field name in the standard field library, selecting a corresponding business library and a basic library according to the obtained business attribution label to perform root cutting on the field name to obtain field root combination information; judging whether the roots in the field root combination information are all valid roots; if the roots in the field root combination information are all valid roots, storing the field root combination information into the standard field library as a standard field; if the roots in the field root combination information have invalid roots, adjusting the roots according to the field root combination information and inputting the adjusted roots into the standard field library again for matching. The application effectively improves data quality.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a method and apparatus for a unified standard naming of data fields. Background Technology

[0002] As online and offline businesses continue to integrate, data quality requirements are constantly increasing. Addressing issues such as difficulties in data interoperability between departments, inconsistent data quality, and lack of transparency in business processes has become particularly important. Data capability building has become a core performance indicator for the digital transformation of the financial industry, and standardized naming management of data fields is a crucial cornerstone of data standards governance.

[0003] Currently, the standard naming method used for data fields is the maximum matching word segmentation method. The advantages of this method are that it is simple to implement, fast in word segmentation, low in system investment, and quick to implement compared to other word segmentation methods. The disadvantages are that the number of words in the dictionary directly affects the accuracy and efficiency of word segmentation, there are word segmentation ambiguities, and it is difficult to reflect the context. Summary of the Invention

[0004] This invention provides a method and apparatus for unified standard naming of data fields, aiming to improve the accuracy of data segmentation and enhance data quality.

[0005] In a first aspect, embodiments of the present invention provide a unified standard naming method for data fields. The method includes: obtaining a field name input by a user and a business affiliation tag for the field name, wherein candidate values ​​for the tag are divided into a basic tag and multiple business tags; searching a corresponding standard field library for a standard field that completely matches the field name; if no standard field completely matches the field name in the standard field library, selecting a corresponding business library and basic library based on the obtained business affiliation tag to perform root word segmentation on the field name to obtain field root word combination information, wherein the field root word combination information represents multiple roots obtained after the field name is segmented; determining whether all roots in the field root word combination information are valid roots; if all roots in the field root word combination information are valid roots, generating a standard field from the field root word combination information and storing it in the standard field library; if there are invalid roots in the field root word combination information, readjusting the roots based on the field root word combination information and re-inputting the adjusted roots into the standard field library for matching.

[0006] Optionally, before searching the standard field library based on the field name, the process includes creating a standard field library. Specifically, creating the standard field library includes: splitting the word roots previously mixed in the root word library into multiple business word roots and one basic word root, with each word root corresponding to a business affiliation tag; assigning each word root to either a business library or a basic library based on the business affiliation tag, wherein multiple business word roots sharing a single business affiliation tag are assigned to the basic library, and business-specific word roots are assigned to their respective business libraries; and hierarchically managing each word assigned to a library based on its usage frequency.

[0007] Optionally, the hierarchical management includes multiple different levels, the size of which is determined by the statistical frequency of word root usage, with the higher the statistical frequency of word root usage, the larger the level.

[0008] Optionally, the step of selecting the corresponding business library and basic library based on the obtained business affiliation tag to perform root word segmentation on the field name to obtain field root combination information specifically includes: performing maximum matching segmentation on the root sets in the business library and basic library in descending order of root level.

[0009] Optionally, if the root combination information of the field contains invalid root words, the method further includes: enabling all business libraries and basic libraries, and using all business libraries and basic libraries as word segmentation libraries to perform root word segmentation on the field name.

[0010] Optionally, if invalid word roots are still found after using all business libraries and basic libraries as word segmentation libraries to segment the field names, the method further includes: applying for word roots for the invalid word roots and waiting for the approval result notification; if the approval is successful, storing the approved word roots in the word root library.

[0011] Optionally, the root word library and the standard field library are subject to an add-only policy, wherein the root words can be reassigned to a business library or basic library and their level.

[0012] Secondly, embodiments of the present invention provide a unified standard naming device for data fields, comprising an acquisition unit, a search unit, a word segmentation unit, a judgment unit, a storage unit, and an adjustment unit. The acquisition unit acquires a field name input by a user and the business affiliation tag of the field name; the candidate values ​​of the tag are divided into a basic tag and multiple business tags. The search unit searches the corresponding standard field library for a standard field that completely matches the field name. The word segmentation unit, if no standard field completely matches the field name is found in the standard field library, selects the corresponding business library and basic library based on the acquired business affiliation tag to perform word segmentation on the field name to obtain field word root combination information, where the field word root combination information represents multiple word roots obtained after the field name is segmented. The judgment unit judges whether all word roots in the field word root combination information are valid word roots. The storage unit, if all word roots in the field word root combination information are valid word roots, generates a standard field from the field word root composition information and stores it in the standard field library. The adjustment unit is used to readjust the word roots according to the word root combination information if there are invalid word roots in the word root combination information of the field, and then input the adjusted word roots into the standard field library for matching again.

[0013] Optionally, the unified standard naming device for data fields further includes a splitting unit, a classification unit, and a hierarchical unit. The splitting unit is used to split the word roots originally mixed in the word root library into multiple business word roots and one basic word root, with each word root corresponding to a business affiliation tag. The classification unit is used to classify each word root into either a business library or a basic library according to the business affiliation tag, wherein multiple business word roots sharing a single business affiliation tag are classified into the basic library, and business-specific word roots are classified into their respective business libraries. The hierarchical unit is used to hierarchically manage each word split into a library based on its usage frequency.

[0014] Thirdly, embodiments of the present invention provide a computer device, including a memory and a processor. The memory is used to store a computer-executable program. The processor is used to execute the computer-executable program to implement the unified standard naming method for data fields as described above.

[0015] In the above embodiments, by obtaining the random field name input by the user and the business affiliation tag to which the field name belongs, the field name is input into a standard field library for field matching. If the matching fails, the field name is segmented into words based on the business library and basic library corresponding to the business affiliation tag. If all the segmented words are valid words, that is, all the words in the field name can be found in all business libraries or basic libraries, the words are stored in the standard field library. If any word in the field name cannot be found in any business library or basic library, the words are readjusted and input into the standard field library again for matching. Simultaneously, when segmenting the field name into words, the words in the field name are segmented in descending order of word level within the same business library or basic library. The word level is determined by the user's usage frequency, with higher-frequency words having higher levels. This segmentation method effectively improves the accuracy and speed of word segmentation, while also significantly improving data quality. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the structures shown in these drawings without creative effort.

[0017] Figure 1 A schematic diagram of the data field unified standard naming method provided in the first embodiment of the present invention.

[0018] Figure 2 This is a schematic diagram of the first sub-process of the unified standard naming method for data fields provided in the first embodiment of the present invention.

[0019] Figure 3 This is a flowchart illustrating the unified standard naming method for data fields provided in the second embodiment of the present invention.

[0020] Figure 4 A schematic diagram of a data field unified standard naming device module provided in the first embodiment of the present invention.

[0021] Figure 5 This is a schematic diagram of the structure of an electronic device provided in the first embodiment of the present invention.

[0022] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without inventive effort are within the scope of protection of this invention.

[0024] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification, claims, and accompanying drawings of this application are used to distinguish similar planned objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data are interchangeable where appropriate; in other words, the described embodiments are implemented according to a sequence other than that illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, may also include other content; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0025] It should be noted that the descriptions involving "first," "second," etc., in this invention are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, features defined with "first" or "second" may explicitly or implicitly include one or more of that feature. Furthermore, the technical solutions of the various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. If the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed by this invention.

[0026] Please refer to Figure 1 This is a flowchart illustrating the unified standard naming method for data fields provided in the first embodiment of the present invention. The method specifically includes the following steps:

[0027] Step S101: Obtain the field name input by the user and the business category tag to which the field name belongs. The candidate values ​​of the tag are divided into a basic tag and multiple business tags. Specifically, the user randomly inputs a field name and selects the business category tag to which the field name belongs based on the actual situation. Understandably, the business category tag is the classification tag of the field name. One field name corresponds to one basic tag or one business tag, but one field name can have multiple business tags to choose from. Further, the category belonging to multiple business tags is one basic tag. It should be noted that each field name is composed of multiple word roots, and each word root is classified and assigned to the corresponding business library and basic library.

[0028] For example, if the input field is named "Credit Card Application", users can choose from categories such as credit card services, loan services, and wealth management services. Users can then select the credit card service based on their specific needs.

[0029] Step S102: Based on the field name, search the corresponding standard field library to see if there is a standard field in the standard field library that completely matches the field name. Specifically, the standard field library is a repository containing a large number of fields pre-set by the developers. In this embodiment, the fields in the standard field library at least include common field content collected from all projects of the company. According to step S101, the field name randomly entered by the user is matched with the fields in the standard field library to see if there is a field in the standard field library that completely matches the field name entered by the user. The creation process of the standard field library will be explained in detail in the following steps and will not be repeated here.

[0030] For example, if the user enters the field name as "credit card application", the successful matching results will be the two fields: [credit card] and [application].

[0031] Step S103: If there is no standard field in the standard field library that completely matches the field name, select the corresponding business library and basic library according to the obtained business affiliation tag to perform word root segmentation on the field name to obtain field word root combination information. The field word root combination information represents multiple word roots obtained after the field name is segmented.

[0032] Specifically, according to step S102, if no matching field for the field name is found in the standard field library, the business affiliation tag selected by the user is used as a locating query basis. Understandably, according to step S101, a field name includes several root words, and the business library and the basic library are two categories of root word libraries pre-set by developers. The root words in the business library are dedicated business root words, while root words belonging to multiple businesses are classified into the basic library. In this embodiment, when no suitable field for the field name is matched in the standard field library, the matching field is searched based on the business affiliation tag selected by the user. The corresponding business database or basic database performs word segmentation on the field name. That is, the field name is input into the corresponding business database or basic database for word segmentation. In other words, word segmentation of the field name generates word root combination information. Furthermore, when performing word segmentation on the field name, word segmentation is performed sequentially according to the word root level in the corresponding database. That is, in the same business database or basic database, the word root with higher priority level will be segmented and matched first. The word root level is determined by the usage frequency counted by the developers. Among them, the word root with higher usage frequency has a higher level.

[0033] For example, if the user inputs the field name as "Offshore RMB Settlement", and the user selects the business category label as investment and wealth management business, then when performing word segmentation on the field name, the investment and wealth management business database will be selected. In the investment and wealth management business database, word segmentation will start from the word root with the highest word root level and the word segmentation order will still be the word root order of the field name itself. The final result will be 3 word roots: [Offshore][RMB][Settlement].

[0034] Step S104: Determine whether all the roots in the field root combination information are valid roots. Specifically, according to step S103, the purpose of root segmentation of the field name is to verify whether the input field name is entirely composed of roots. When performing root segmentation on the field name, field root combination information is generated. At this time, it is necessary to determine whether there are valid or invalid roots in the field root combination information. Understandably, a root that can be found in the business database or the basic database to match the root of the field name is called a valid root, and a root that cannot be found in the business database or the basic database is called an invalid root.

[0035] For example, if the user inputs the field name "Offshore RMB Settlement", and the word segmentation result is [Offshore][People's] Currency [Settlement], then the valid word roots are [Offshore], [People's], and [Settlement], while the invalid word root is "currency".

[0036] Step S105: If all the roots in the field root combination information are valid roots, the field root composition information is used to generate a standard field and stored in the standard field library. Specifically, the word segmentation result is the field root combination information. According to the example "offshore RMB settlement" in step S103, the final segmentation result is three roots: [offshore][RMB][settlement]. These three roots are then used to generate a standard field and stored in the standard field library.

[0037] Step S106: If there is an invalid word root in the word root combination information, the word roots are readjusted according to the word root combination information, and the adjusted word roots are re-entered into the standard field library for matching. Specifically, according to step S104, if there is an invalid word root in the word segmentation result, the word root is discarded, and the valid word roots are combined and re-entered into the standard field library for matching.

[0038] For example, if the user inputs the field name "Offshore RMB Settlement", the word segmentation result is [Offshore][People's] Currency [Settlement]. The valid word root [Offshore][People's][Settlement] is readjusted to "Offshore People's Settlement", the invalid word root "currency" is discarded, and the adjusted word root is then entered into the standard field library for matching again.

[0039] For example, if the user inputs the field name "Offshore RMB Settlement Procedures", the word segmentation result is: 3 word roots [offshore][RMB][settlement] and 2 invalid word roots "hand" and "continue". The 3 valid word roots [offshore][RMB][settlement] are combined to generate "Offshore RMB Settlement" and input into the standard field library for matching, while the invalid word roots "hand" and "continue" are processed later.

[0040] Furthermore, if neither the corresponding business database nor the basic database can effectively segment the word root of the field name, then all business databases and basic databases will be opened to segment the word root of the field name.

[0041] In the above embodiments, by obtaining the random field name input by the user and the business affiliation tag to which the field name belongs, the field name is input into a standard field library for field matching. If the matching fails, the field name is segmented into words based on the business library and basic library corresponding to the business affiliation tag. If all the segmented words are valid words, that is, all the words in the field name can be found in all business libraries or basic libraries, the words are stored in the standard field library. If any word in the field name cannot be found in any business library or basic library, the words are readjusted and input into the standard field library again for matching. Simultaneously, when segmenting the field name into words, the words in the field name are segmented in descending order of word level within the same business library or basic library. The word level is determined by the user's usage frequency, with higher-frequency words having higher levels. This segmentation method effectively improves the accuracy and speed of word segmentation, while also significantly improving data quality.

[0042] Please refer to Figure 2 This is a first sub-flowchart of the data field unified standard naming method provided in the first embodiment of the present invention. Before searching the standard field library according to the field name, it includes creating the standard field library. Specifically, creating the standard field library includes the following steps:

[0043] Step S201 involves splitting the word roots originally mixed in the word root library into multiple business word roots and one basic word root, with each word root corresponding to a business affiliation tag. Specifically, the word root library contains several word roots in an unordered string. The developers split, combine, classify, and tag these unordered word roots so that each word root has a corresponding business affiliation tag.

[0044] For example, if there are several word roots "funds and credit card applications", then the word roots can be broken down and tagged as: fund---investment and wealth management business, apply---basic business, credit card---credit card business.

[0045] Step S202: Based on the business affiliation tag, each word root is assigned to either a business library or a basic library. Multiple business word roots sharing a single business affiliation tag are assigned to the basic library, while business-specific word roots are assigned to their respective business libraries. Specifically, each business affiliation tag corresponds to one business library and one basic library. If a word root belongs to multiple businesses, it is assigned to the basic library.

[0046] For example, according to step S201, the root word "fund" is classified into the investment and wealth management business database, the root word "credit card" is classified into the credit card business database, and the root word "process" can be classified into both the investment and wealth management business database and the credit card business database. Therefore, the root word "process" is classified into the basic database.

[0047] Step S203: Perform hierarchical management of each word root that has been split into the database based on its usage frequency. Specifically, after each word root is assigned to the corresponding business database, it also needs to be hierarchically managed. The word roots are ranked and sorted according to the frequency of user use. In this embodiment, the higher the usage frequency of the word root, the higher its level.

[0048] In the above embodiments, word roots in the word root library are split and tagged, and then classified into the corresponding business library or basic library according to the tags. Word roots in the same business library or basic library are managed hierarchically according to the frequency of user use of word roots. The higher the frequency of user use, the higher the level of word roots. In this implementation, when word root segmentation is performed in the business library and basic library, word root segmentation is started from the word root with the higher level. The word root segmentation speed is accelerated by utilizing the frequency of user use, and the usage environment and context of word roots are also fully utilized.

[0049] Please refer to Figure 3 This is a schematic flowchart of the unified standard naming method for data fields provided in the second embodiment of the present invention. The difference between the unified standard naming method for data fields provided in the second embodiment and the unified standard naming method for data fields provided in the first embodiment is that the unified standard naming method for data fields provided in the second embodiment further includes applying for invalid word roots. The word root application process specifically includes the following steps:

[0050] Step 301: Submit an application for invalid word roots and wait for the approval result notification.

[0051] Step 302: If the approval is successful, store the approved word roots in the word root database.

[0052] Specifically, according to step S106, if the field name is input into all business databases or basic databases for word root segmentation, and there are still invalid word roots in the returned field word root combination information, then the invalid word roots are applied for, and the successfully applied word roots are directly stored in the word root database.

[0053] For example, if the user inputs the field name as "Offshore RMB Settlement Procedures", the word segmentation result is: [Offshore][RMB][Settlement] 3 word roots and two invalid word roots "hand" and "continue", so "procedures" is applied as a word root.

[0054] Furthermore, the developers implemented a "only add, no delete" principle for the root word library and standard field library, increasing the number of root words in the root word library and standard field library. This allows the field names to obtain the widest range of word segmentation results when performing root word segmentation, thus improving the accuracy of word segmentation. In addition, the root words can be readjusted to their respective business libraries or basic libraries and levels according to actual needs.

[0055] In the above embodiments, invalid word roots are applied for, and the word roots that pass the application are stored in the word root library to improve the quantity of word roots in the word root library. The developers then decompose and classify the unclassified word roots again, and repeatedly operate on the newly added word roots to increase the coverage of word root classification, so that all subsequent field names can obtain valid word roots, and improve the word root matching accuracy to a greater extent.

[0056] Please refer to Figure 4 This is a schematic diagram of the data field unified standard naming device module provided in the first embodiment of the present invention. The data field unified standard naming device 100 includes: an acquisition unit 101, a search unit 102, a selection unit 103, an adjustment unit 104, a storage unit 105, a splitting unit 106, a classification unit 106, a hierarchical unit 107, and a hierarchical unit 108.

[0057] The acquisition unit 101 is used to acquire the field name input by the user and the business affiliation tag of the field name. The candidate values ​​of the tag are divided into a basic tag and multiple business tags.

[0058] The lookup unit 102 is used to search the corresponding standard field library for a standard field that completely matches the field name.

[0059] The word segmentation unit 103 is used to select the corresponding business library and basic library according to the obtained business affiliation tag to perform word segmentation on the field name to obtain field word root combination information if there is no standard field in the standard field library that completely matches the field name. The field word root combination information represents multiple word roots obtained after the field name is segmented.

[0060] The judgment unit 104 is used to determine whether all the word roots in the word root combination information of the field are valid word roots.

[0061] Storage unit 105 is used to generate a standard field from the field root combination information and store it in the standard field library if all the roots in the field root combination information are valid roots.

[0062] The adjustment unit 106 is used to readjust the word roots according to the word root combination information if there are invalid word roots in the word root combination information of the field, and then input the adjusted word roots into the standard field library for matching again.

[0063] The splitting unit 107 is used to split the word roots that were originally mixed in the word root library into multiple business word roots and one basic word root, with each word root corresponding to a business affiliation tag.

[0064] The classification unit 108 is used to classify each word root into a business library or a basic library according to the business affiliation tag. Multiple business word roots that share a business affiliation tag are classified into the basic library, while business-specific word roots are classified into the corresponding business library.

[0065] Hierarchical unit 109 is used to hierarchically manage each word split into the database based on its usage statistical frequency.

[0066] Those skilled in the art will understand that, for the sake of convenience and brevity, the data field unified standard naming device described in this embodiment can refer to the corresponding process of the data field unified standard naming method described in the above embodiments, and will not be repeated here.

[0067] Please refer to Figure 5 This is a schematic diagram of the internal structure of a computer device provided in the first embodiment of the present invention. The computer device 30 specifically includes a memory 302 and a processor 301. The memory 302 is used to store program instructions, and the processor 301 is used to execute the program instructions to implement the aforementioned unified standard naming device method for data fields.

[0068] In some embodiments, processor 301 may be a central processing unit (CPU), controller, microcontroller, microprocessor or other data processing chip, used to run program instructions stored in memory 302.

[0069] The memory 302 includes at least one type of readable storage medium, including flash memory, hard disk, multimedia card, card-type memory (e.g., SD or DX memory), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 302 can be an internal storage unit of a computer device, such as a hard disk. In other embodiments, the memory 302 can be an external storage device of a computer device, such as a plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, FlashCard, etc., provided on the computer device. Furthermore, the memory 302 can include both internal and external storage units of the computer device. The memory 302 can be used not only to store application software and various types of data installed on the computer device, such as code implementing a unified standard naming method for data fields, but also to temporarily store data that has been output or will be output.

[0070] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

[0071] The above-listed embodiments are merely preferred embodiments of the present invention and should not be construed as limiting the scope of the present invention. Therefore, any equivalent variations made in accordance with the claims of the present invention are still within the scope of the present invention.

Claims

1. A method of naming a data field uniform standard, characterized by, The unified standard naming method for the data fields includes: Obtain the field name input by the user and the business category tag to which the field name belongs. The candidate values ​​of the tag are divided into a basic tag and multiple business tags. Based on the field name, search the corresponding standard field library to see if there is a standard field in the standard field library that exactly matches the field name. The standard field library is a repository with a large number of fields that is pre-set by the developers. If there is no standard field in the standard field library that completely matches the field name, the corresponding business library and basic library are selected according to the obtained business affiliation tag to perform word segmentation on the field name to obtain field word root combination information. The field word root combination information represents multiple word roots obtained after the field name is segmented. The business library and the basic library are two types of word root libraries pre-set by the developers. The word roots in the business library are dedicated business word roots, while word roots belonging to multiple businesses are assigned to the basic library. Determine whether all the word roots in the word root combination information of the field are valid word roots; If all the word roots in the word root combination information of the field are valid word roots, the word root composition information of the field is generated into a standard field and stored in the standard field library; If there are invalid roots in the root combination information of the field, the roots are readjusted according to the root combination information of the field, and the readjusted roots are re-entered into the standard field library for matching. Roots that cannot be found in the business library or the basic library are called invalid roots.

2. The data field unified standard naming method as described in claim 1, characterized in that, Each word split into the database is managed hierarchically based on its usage frequency. The hierarchical management includes multiple different levels, and the size of each level is determined by the usage frequency of the word root. The higher the usage frequency of the word root, the larger its level.

3. The data field unified standard naming method as described in claim 1, characterized in that, The step of selecting the corresponding business library and basic library based on the obtained business affiliation tag to perform word segmentation on the field name to obtain the field word root combination information specifically includes: Based on the root word level, the root word sets in the business database and the basic database are segmented by maximum matching in descending order.

4. The data field unified standard naming method as described in claim 1, characterized in that, The step of if the root combination information of the field contains invalid root words also includes: enabling all business libraries and basic libraries, and using all business libraries and basic libraries as word segmentation libraries to perform root word segmentation on the field name.

5. The data field unified standard naming method as described in claim 4, characterized in that, If invalid word roots are still found after using all business libraries and basic libraries as word segmentation libraries to segment the field names, these include: Submit an application for invalid word roots and wait for the approval result notification; If the approval is successful, the approved word roots will be stored in the word root database.

6. The data field unified standard naming method as described in claim 1, characterized in that, The root word library and the standard field library are subject to the principle of adding only and not deleting. Root words can be readjusted to their respective business libraries or basic libraries and levels.

7. A unified standard naming device for data fields, the unified standard naming device for data fields comprising: The acquisition unit is used to acquire the field name input by the user and the business category tag to which the field name belongs. The candidate values ​​of the tag are divided into a basic tag and multiple business tags. The search unit is used to search the corresponding standard field library for a standard field that completely matches the field name. The standard field library is a repository with a large number of fields that is pre-set by the developers. The word segmentation unit is used to select the corresponding business library and basic library to perform word segmentation on the field name based on the obtained business affiliation tag if there is no standard field in the standard field library that completely matches the field name, so as to obtain field word root combination information. The field word root combination information represents multiple word roots obtained after the field name is segmented. The business library and the basic library are two types of word root libraries that are pre-set by the developers. The word roots in the business library are dedicated business word roots, while word roots that belong to multiple businesses are assigned to the basic library. The judgment unit is used to determine whether all the word roots in the word root combination information of the field are valid word roots; A storage unit is used to generate a standard field from the field root combination information and store it in a standard field library if all the root words in the field root combination information are valid root words. The adjustment unit is used to readjust the word roots according to the word root combination information if there are invalid word roots in the word root combination information of the field, and then input the adjusted word roots back into the standard field library for matching. The word roots that cannot be found in the business library or the basic library are called invalid word roots.

8. A computer device, comprising: Memory, used to store executable programs in a computer. A processor for executing the computer-executable program to implement the data field uniform standard naming method as described in any one of claims 1-6.

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