A data management system, method, and device for terminology and corpus in translation projects.

Abstract

This invention provides a data management system for terminology and corpus in translation projects. It includes a terminology identification and organization module for extracting terms from the source text to be translated and obtaining a first high-frequency terminology; a corpus extraction and organization module for crawling monolingual corpus data of the same language type from relevant websites based on the first high-frequency terminology using web crawling technology, and inputting the monolingual corpus into the organization module to obtain a second high-frequency terminology; a terminology and corpus translation module for merging all high-frequency terms and monolingual corpus into a single monolingual file and translating it to obtain a bilingual file; and a database creation and maintenance module for creating a bilingual database of bilingual terms and corpus, storing bilingual terminology pairs and bilingual corpus pairs in the relevant database using a bilingual parallel structure. This solution solves the problem in existing technologies where it is impossible to continuously expand the relevant corpus based on terms from a specific domain identified in the source text, resulting in inaccurate translation results and low translation efficiency.

Description

Technical Field

[0001] This invention belongs to the field of translation technology, specifically relating to a data management system, method, and device for terminology and corpus in translation projects. Background Technology

[0002] With the deepening of globalization, the need to improve translation efficiency in translation projects is becoming increasingly urgent. Currently, professionals utilize various translation technologies, such as Computer-Assisted Translation (CAT), Machine Translation (MT), terminology management, corpora and corpus query tools, and cloud-based collaborative translation platforms, to enhance the quality and efficiency of large-scale translation projects. However, the rapid growth of bilingual information online and the increasing scale of translation projects place higher demands on terminology and corpus data management.

[0003] Currently, many technologies can automatically extract terms. For example, rule-based methods can automatically extract terms based on word formation characteristics, syntactic features, and domain characteristics, extracting words that match templates from corpora. Methods based on mathematical statistics mainly involve statistical calculations and machine learning. Statistical methods extract terms by calculating statistics such as word frequency, mutual information, and TF-IDF, and have general applicability. Machine learning methods mainly utilize large-scale labeled corpora to train models, predicting unlabeled corpora, transforming the term extraction problem into a sequence labeling or classification problem. With the development of machine learning technology, methods such as Support Vector Machines (SVM) and deep learning are being used to train models for term recognition. In addition, multiple methods mentioned above can be combined to extract terms. Besides automatic term extraction, bilingual term pairs can also be directly obtained from bilingual terminology databases.

[0004] In terms of terminology management, terminology management software such as SDL Multiterm is primarily used to create and manage terminology databases. The main functions of this type of software include terminology entry, editing, validation, retrieval, classification, standardization, sharing, and collaboration, helping users ensure the accuracy and consistency of terminology and supporting multilingual terminology management. Furthermore, it can seamlessly integrate with machine-aided translation tools such as SDL Rados Studio, facilitating the use and management of terminology during the translation process.

[0005] There are two main methods for extracting bilingual corpora. The first method is to directly obtain and align bilingual texts. This involves using parallel corpus collection tools, such as web crawlers, to scrape articles from bilingual websites or using APIs to collect and align bilingual text pairs. Alternatively, bilingual corpora can be downloaded directly from parallel corpus websites such as OPUS (Open Parallel Corpus), Tatoeba, EuroParl, UN Corpora, Linguistic Data Consortium (LDC), GigaWord, and corpora in multilingual databases, either free or paid.

[0006] The second method is to translate monolingual text into bilingual text. Automatic translation tools such as the Google Translate API and Microsoft Translator API can be used to automatically translate monolingual text into another language, and then edited to create bilingual text. Tools such as SDL Trados Studio, MemoQ, and OmegaT that translate memorized bilingual sentence pairs can also be used to create bilingual corpora.

[0007] Currently, the terminology and corpus management process still suffers from the following problems: terms and corpora are typically stored separately, failing to achieve unified management; the corpus cannot be continuously expanded based on terms identified in the original text for a specific domain, and the terminology database cannot be updated in real time; and it lacks integration with emerging technologies such as web crawling and GPT models to achieve bilingual data management of terms and corpora. Therefore, existing management systems can no longer meet the translation efficiency requirements of large-scale translation projects. Summary of the Invention

[0008] To address the problems in existing technologies, such as the inability to continuously expand relevant corpora based on terms from a specific domain identified in the original text, and the inadequate management of terms and corpora, which leads to inaccurate translation results and low translation efficiency, this invention provides a data management system, method, and device for terms and corpora in translation projects.

[0009] To achieve the above objectives, the present invention provides the following technical solution:

[0010] A data management system for terminology and corpus in a translation project, comprising:

[0011] The terminology recognition and organization module is used to extract terms from the original text to be translated and to filter and organize the first high-frequency terms, which include terms that appear more frequently in the original text than a set threshold.

[0012] The corpus extraction and organization module is used to crawl monolingual corpus data of the same language type as the first high-frequency term on relevant websites using web crawling technology, and input the monolingual corpus as the original text into the term recognition and organization module to obtain the second high-frequency term. The second high-frequency term includes terms that appear in the monolingual corpus with a frequency exceeding a set threshold.

[0013] The terminology corpus translation module is used to merge the first high-frequency term, the second high-frequency term, and the corresponding monolingual corpus into a monolingual file. After translating the monolingual file, a bilingual file required by the user is obtained. The bilingual file includes bilingual terminology pairs and bilingual corpus pairs.

[0014] The database creation and maintenance module is used to create bilingual databases of bilingual terminology pairs and bilingual corpus pairs. The databases store bilingual terminology pairs and bilingual corpus pairs from bilingual files in a bilingual parallel structure, and maintain and share them.

[0015] Furthermore, it also includes a scenario-assisted module, which provides relevant professional background knowledge of terms as reference information through the GPT model during the management of bilingual databases, or gives translation suggestions, or assists in solving technical problems related to the creation and maintenance of related databases.

[0016] Furthermore, in the terminology recognition and organization module, the scenario assistance module is used to obtain professional background information; in the terminology corpus translation module, the scenario assistance module is used to obtain professional background knowledge and translation suggestions; and in the terminology database creation and maintenance module, the scenario assistance module is used to obtain solutions to technical problems encountered during the creation and maintenance of the relevant database.

[0017] Furthermore, the step of extracting terms from the original text to be translated and filtering and organizing the first high-frequency terms includes:

[0018] Based on the original text to be translated, natural language processing technology is used to automatically extract terms from the original text, resulting in automatic term recognition results;

[0019] The context of the automatic recognition results of the term is viewed through the keyword context retrieval system, and duplicate, partially overlapping, and incomplete recognition results are processed.

[0020] By sorting and filtering terms whose frequency exceeds a set threshold, the first high-frequency term based on the original text is obtained.

[0021] Furthermore, the step of using web crawling technology to crawl monolingual corpus data of the same language as the first high-frequency term on relevant websites includes:

[0022] Access authoritative websites in the relevant field;

[0023] On the authoritative website, the first high-frequency term extracted by the terminology recognition and organization module is input, and the latest monolingual corpus data related to the first high-frequency term is crawled and saved using web crawling technology.

[0024] Furthermore, the step of merging the first high-frequency term, the second high-frequency term, and the corresponding monolingual corpus into a monolingual file, and translating the monolingual file to obtain the bilingual file required by the user includes:

[0025] The first high-frequency term, the second high-frequency term, and the monolingual corpus are merged into a single monolingual file.

[0026] The merged monolingual files are pre-translated into bilingual files using a machine translation engine;

[0027] The GPT model in the scenario assistance module helps translators perform post-translation editing of bilingual documents and translation quality detection.

[0028] Furthermore, the steps of creating a bilingual database of bilingual terminology pairs and bilingual corpus pairs, storing the bilingual terminology pairs and bilingual corpus pairs in the relevant database using a bilingual comparison structure, and maintaining and sharing them include:

[0029] In a MySQL database, bilingual terms and bilingual corpus pairs are stored using a bilingual parallel structure to create a bilingual term and corpus database.

[0030] Create indexes on the terminology and translation fields in the MySQL database;

[0031] Regularly update and share the bilingual database containing bilingual terminology and bilingual corpora.

[0032] A data management method for terminology and corpus in a translation project includes:

[0033] Extract terms from the original text to be translated, and filter and sort out the first high-frequency terms, which include terms that appear more frequently in the original text than a set threshold.

[0034] Based on the first high-frequency term, web crawler technology is used to crawl monolingual corpus data of the same language as the first high-frequency term from relevant websites. The monolingual corpus is used as the original text and input into the term recognition and processing module to obtain the second high-frequency term. The second high-frequency term includes terms that appear more frequently than a set threshold in the monolingual corpus.

[0035] The first high-frequency term, the second high-frequency term, and the corresponding monolingual corpus are merged into a monolingual file. After translating the monolingual file, the bilingual file required by the user is obtained. The bilingual file includes bilingual term pairs and bilingual corpus pairs.

[0036] Create a bilingual database of bilingual terminology pairs and bilingual corpus pairs. Store the bilingual terminology pairs and bilingual corpus pairs in the relevant database using a bilingual comparison structure, and maintain and share them.

[0037] A computer device includes a memory and a processor, wherein the memory stores computer execution instructions and data, and the processor reads and executes the computer execution instructions and data stored in the memory, and writes the results back to the memory, thereby implementing a data management method for terminology and corpus in a translation project as described in any of the preceding claims.

[0038] The data management system for terminology and corpus in translation projects provided by this invention has the following beneficial effects:

[0039] The management system of this solution includes a terminology recognition and organization module for extracting terms from the original text to be translated and filtering out the first high-frequency terms; a corpus extraction and organization module for using web crawling technology to crawl monolingual corpus data of the same language as the high-frequency terms from relevant websites based on the first high-frequency terms, and inputting the monolingual corpus as the original text into the terminology recognition and organization module to obtain the second high-frequency terms; a terminology corpus translation module for merging all high-frequency terms and their corresponding monolingual corpus into a monolingual file, translating the monolingual file to obtain the bilingual file required by the user; and a database creation and maintenance module for creating a bilingual database of bilingual terms and bilingual corpus, storing bilingual terminology pairs and bilingual corpus pairs in the bilingual file in the relevant database using a bilingual parallel structure, and maintaining and sharing them.

[0040] The terminology recognition and organization module is used to extract terms from the original text to be translated and from monolingual corpora crawled from the Internet. By analyzing the frequency of use, context and changes of the terms, it identifies high-frequency terms, thereby enabling dynamic management and updating of terms, ensuring the timeliness of terms and improving the overall translation quality.

[0041] The corpus extraction and organization module utilizes web crawling technology to collect terminology and corpus data. By crawling content based on relevant high-frequency keywords from the internet, the corpus can be rapidly expanded multiple times, keeping it in sync with the latest industry developments.

[0042] The database creation and maintenance module stores terms and corpora in a bilingual structure, achieving unified management of terms and corpora, and utilizing network resources to update and maintain terms and corpora.

[0043] In summary, the data management system of this invention, combining automatic terminology extraction technology and web crawling technology, provides translation teams with an efficient, accurate, and dynamic terminology management solution, significantly improving translation efficiency and quality, and adapting to the ever-growing translation needs in the context of globalization. Attached Figure Description

[0044] To more clearly illustrate the embodiments and design schemes of the present invention, the accompanying drawings required for this embodiment will be briefly described below. 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 these drawings without creative effort.

[0045] Figure 1 This is a schematic diagram of the system framework of an embodiment of the present invention.

[0046] Figure 2 This is a schematic diagram illustrating the specific module principle of an embodiment of the system of the present invention;

[0047] Figure 3 A schematic diagram of the bilingual storage structure of the database creation and maintenance module in an embodiment of the present invention;

[0048] Figure 4 This is a schematic diagram illustrating the result of the scenario assistance module in an embodiment of the present invention helping to solve technical problems. Detailed Implementation

[0049] To enable those skilled in the art to better understand and implement the technical solutions of the present invention, the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. The following embodiments are only used to more clearly illustrate the technical solutions of the present invention and should not be construed as limiting the scope of protection of the present invention.

[0050] Example 1

[0051] This invention provides a data management system for terminology and corpus in translation projects, specifically as follows: Figure 1 As shown, this management system includes: a terminology recognition and organization module, a corpus extraction and organization module, a terminology corpus translation module, a database creation and maintenance module, and a scenario assistance module.

[0052] 1) Terminology recognition and organization module.

[0053] Used for automatic terminology identification, followed by manual screening and organization. For example... Figure 2 As shown, the steps of this module include:

[0054] S1: Input the original text, and use natural language processing technology to automatically extract the terms from the original text to obtain the automatic term recognition results.

[0055] S2: Use the Keyword Context (KWIC) retrieval system to view the context of the automatically identified results, verify and organize them to obtain the terminology.

[0056] S3: Sort and filter out the terms that appear most frequently to obtain high-frequency terms based on the original text.

[0057] S4: With the assistance of the GPT model, organize the terminology and determine its meaning based on the professional background information it provides.

[0058] Specifically, in this embodiment, the second step S2 should use KWIC to view and filter out duplicate, partially overlapping, and incomplete recognition results in the automatic recognition results.

[0059] Specifically, in this embodiment, the high-frequency terms sorted and filtered in step S3 include single-word terms and phrase terms, from which the main theme of the original text can be roughly understood. For example, when the entire book to be translated is imported into the system in plain text format, high-frequency terms are automatically identified and manually selected. Specifically, in this embodiment, in step S4, with the assistance of the GPT model, the translator can more accurately and conveniently understand the meaning of terms and refine the terminology by searching for professional background information. For example, by querying the GPT model for the meaning of the extracted result "localization" and combining it with the original text content, the translator finally determines the complete term as "localized household registration management model".

[0060] 2) Corpus extraction and organization module.

[0061] Used for automatic extraction and manual processing of corpora. For example... Figure 2 As shown, the steps of this module include:

[0062] S5: Obtain a list of authoritative website URLs in the relevant field.

[0063] S6: High-frequency terms extracted from the input terminology recognition and processing module.

[0064] S7: Use web crawling technology to crawl and save the latest monolingual corpus data related to high-frequency terms from authoritative websites in the relevant field. Using the monolingual corpus as the original text input, the term recognition and processing module can obtain even more high-frequency terms.

[0065] 3) Terminology Corpus Translation Module.

[0066] Used for pre-translation, post-editing, and quality control of terminology corpora. For example... Figure 2 As shown, the steps of this module include:

[0067] S8: Merge the high-frequency monolingual terms and monolingual corpora obtained by the above modules into a single monolingual file.

[0068] S9: Pre-translates the merged monolingual files into bilingual files using a machine translation engine.

[0069] S10: Use the GPT model in the scenario assistance module to assist translators in post-translation editing of bilingual pre-translation files and translation quality detection.

[0070] 4) Database creation and maintenance module.

[0071] Used for storing, retrieving, maintaining, and sharing terminology corpus data. For example... Figure 2 As shown, the steps of this module include:

[0072] S11: In the MySQL database, a bilingual structure is used to store Chinese-English bilingual terminology pairs and Chinese-English bilingual corpus pairs in two fields, such as... Figure 3 As shown. Additional data, such as the frequency of occurrence and explanatory information of bilingual terms and corpora, can be added to create a bilingual terminology and corpus database.

[0073] S12: Create an index in the MySQL database to enable more efficient retrieval of bilingual data.

[0074] S13: Regularly update and share bilingual terminology and corpus databases.

[0075] Select the latest literature as the source text and update the bilingual database regularly through steps S1-S12 above. Share the updated bilingual terminology database and corpus with team members to ensure that all team members can access and use the latest terminology and corpus. Sharing can be achieved through shared folders, using a version control system, or uploading the terminology database and corpus to a team collaboration platform.

[0076] 5) Scenario-assisted module.

[0077] like Figure 2 As shown, this module provides background information, translation suggestions, and assistance in resolving technical issues related to database creation and maintenance. In specific application examples, this module is integrated throughout the entire terminology and corpus management process.

[0078] First, during the process of terminology identification, organization, and translation, translators can determine and translate terms based on the professional background knowledge provided by the GPT model in the context-assisted module. For example, how should "land logic," "institutional logic," "capital logic," and "market logic" be translated? The word "logic" implies "a way of thinking and arguing for a certain type of person or a specific field." Considering the context "Therefore, for rural areas to achieve revitalization, they must follow the development logic of the market economy, including capital logic, land logic, and institutional logic," and combining this with the reference information generated by the context-assisted module, translators can consider translating "land logic" as "land-oriented development logic." For example, the question is: What is "land logic"? The context-assisted module answers: "Land logic" refers to the way of thinking and analysis related to land. It is a logical reasoning and way of thinking based on the characteristics, planning, management, and utilization of land. Land logic involves the logical thinking process of the rational utilization, planning, and development of land resources. The basic concepts of land logic include the following aspects: land planning and use, land assessment and valuation, land transactions and investment, and land management and sustainability. It helps people to consider various factors in land-related decisions in order to achieve the best land use and development results.

[0079] Secondly, during the translation of terminology corpora, translation suggestions can be directly obtained using the GPT model in the context-assisted module. ， This module helps translators improve their translations. The meanings and underlying cultural connotations of terms can differ across cultural contexts. Translators can use the background information and translation suggestions provided by the GPT model in the context-aid module to select appropriate vocabulary to accurately convey the meaning of terms.

[0080] Finally, during the database creation and maintenance process, the GPT model in the scenario assistance module can help solve related technical problems. For example... Figure 4 As shown, the Context Assistance module provides a method for creating a table containing terms and their corresponding translations using MySQL, including the fields to be included and the corresponding code. However, the suggestions provided by this module are sometimes somewhat limited and are for reference only.

[0081] Method Implementation Examples

[0082] This invention provides a data management method for terminology and corpus in translation projects, including:

[0083] The terminology is extracted from the original text to be translated, and the first high-frequency terminology is selected and sorted out. The first high-frequency terminology includes terms that appear more frequently than a set threshold in the original text.

[0084] Based on the first high-frequency term, web crawling technology is used to crawl monolingual corpus data of the same language as the first high-frequency term from relevant websites. The monolingual corpus is used as the original text and input into the term recognition and processing module to obtain the second high-frequency term. The second high-frequency term includes terms that appear more frequently than a set threshold in the monolingual corpus.

[0085] The first high-frequency term, the second high-frequency term, and the corresponding monolingual corpus are merged into a monolingual file. After translating the monolingual file, the bilingual file required by the user is obtained. The bilingual file includes bilingual term pairs and bilingual corpus pairs.

[0086] Create a bilingual database of bilingual terminology pairs and bilingual corpus pairs. Store the bilingual terminology pairs and bilingual corpus pairs in the relevant database using a bilingual comparison structure, and maintain and share them.

[0087] Equipment Examples

[0088] This invention provides a computer device, including a memory and a processor. The memory stores computer execution instructions and data. The processor reads and executes the computer execution instructions and data stored in the memory, and writes the results back to the memory, thereby realizing the data management method for terminology and corpus in a translation project described above. This method has been described in detail in the method embodiments and will not be repeated here.

[0089] It should be noted that the specific embodiments described above enable those skilled in the art to more fully understand the present invention, but do not limit the present invention in any way. Therefore, although the present invention has been described in detail in this specification and embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the present invention; and all technical solutions and improvements that do not depart from the spirit and scope of the present invention are covered within the protection scope of the patent of the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

Claims

1. A data management system for translating terms and corpora in a project, characterized by, The application comprises: a term identification and arrangement module for extracting terms in the original text to be translated and screening and arranging first high-frequency terms, wherein the first high-frequency terms include terms with a frequency exceeding a set threshold in the original text; a corpus extraction and arrangement module for using web crawler technology to crawl monolingual corpus data of the same language category as the first high-frequency terms from relevant websites according to the first high-frequency terms, inputting the monolingual corpus as the original text into the term identification and arrangement module to obtain second high-frequency terms, wherein the second high-frequency terms include terms with a frequency exceeding a set threshold in the monolingual corpus; a term corpus translation module for merging the first high-frequency terms, the second high-frequency terms and the corresponding monolingual corpus into a monolingual file, and obtaining a bilingual file required by the user after translating the monolingual file, wherein the bilingual file includes bilingual term pairs and bilingual corpus pairs; a database creation and maintenance module for creating a bilingual database about the bilingual term pairs and the bilingual corpus pairs, storing the bilingual term pairs and the bilingual corpus pairs in the bilingual database in a bilingual contrast structure, and maintaining and sharing the bilingual database; a scenario auxiliary module for providing professional background knowledge of relevant terms as reference information or giving translation suggestions or assisting in solving technical problems in the process of managing the bilingual database through the GPT model; the step of using web crawler technology to crawl monolingual corpus data of the same language category as the first high-frequency terms from relevant websites according to the first high-frequency terms comprises: obtaining websites in the relevant field; inputting the first high-frequency terms extracted in the term identification and arrangement module on the websites, using web crawler technology to crawl the latest monolingual corpus data related to the first high-frequency terms and saving them; the step of merging the first high-frequency terms, the second high-frequency terms and the corresponding monolingual corpus into a monolingual file, and obtaining a bilingual file required by the user after translating the monolingual file comprises: merging the first high-frequency terms, the second high-frequency terms and the monolingual corpus into a monolingual file; pre-translating the merged monolingual file into a bilingual file through a machine translation engine; assisting translators in post-editing and translation quality detection of the bilingual file with the help of the GPT model in the scenario auxiliary module.

2. The data management system for terms and corpora in translation projects according to claim 1, characterized in that, In the term identification and arrangement module, professional background information is obtained using the scenario auxiliary module; in the term corpus translation module, professional background knowledge and translation suggestions are obtained using the scenario auxiliary module; In the term library creation and maintenance module, solutions to technical problems in the process of creating and maintaining the relevant database are obtained using the scenario auxiliary module.

3. The data management system for terms and corpora in translation projects according to claim 1, characterized in that, the step of extracting terms in the original text to be translated and screening and arranging first high-frequency terms comprises: automatically extracting terms in the original text to be translated using natural language processing technology to obtain automatic identification results of the terms; checking the context of the automatic identification results of the terms through a keyword context retrieval system, and processing repeated, partially overlapped and incomplete identification results in the automatic identification results; Screening the terms with the frequency exceeding the set threshold value through sorting to obtain the first high-frequency terms based on the original text.

4. The data management system for terms and corpora in translation projects according to claim 1, characterized in that, The step of creating a bilingual database about bilingual term pairs and bilingual corpus pairs, storing the bilingual term pairs and the bilingual corpus pairs in the bilingual files in a bilingual contrast structure in the related database, and maintaining and sharing includes: Storing the bilingual term pairs and the bilingual corpus pairs in a bilingual contrast structure in the My SQL database to create a bilingual term database and a bilingual corpus database; Creating an index on the term and translation fields in the My SQL database; Periodically updating and sharing the bilingual database storing the bilingual terms and the bilingual corpus.

5. A data management method for terms and corpora in a translation project, applied to the data management system for terms and corpora in a translation project according to claim 1, characterized by, Includes: Extracting the terms in the original text to be translated, and screening and sorting out the first high-frequency terms, which include the terms with the frequency exceeding the set threshold value in the original text; According to the first high-frequency terms, using web crawler technology to crawl monolingual corpus data of the same language category as the first high-frequency terms on the related website, using the monolingual corpus as the original text, inputting the term recognition and sorting module to obtain the second high-frequency terms, which include the terms with the frequency exceeding the set threshold value in the monolingual corpus; Merging the first high-frequency terms, the second high-frequency terms and the corresponding monolingual corpus into a monolingual file, and after translating the monolingual file, obtaining the bilingual file required by the user, which includes bilingual term pairs and bilingual corpus pairs; Creating a bilingual database about bilingual term pairs and bilingual corpus pairs, storing the bilingual term pairs and the bilingual corpus pairs in the bilingual files in a bilingual contrast structure in the related database, and maintaining and sharing; The step of using web crawler technology to crawl monolingual corpus data of the same language category as the first high-frequency terms on the related website according to the first high-frequency terms includes: Obtaining the website of the related field; On the website, input the first high-frequency terms extracted in the term recognition and sorting module, use web crawler technology to crawl the latest monolingual corpus data related to the first high-frequency terms and save them; The step of merging the first high-frequency terms, the second high-frequency terms and the corresponding monolingual corpus into a monolingual file, and after translating the monolingual file, obtaining the bilingual file required by the user includes: Merging the first high-frequency terms, the second high-frequency terms and the monolingual corpus into a monolingual file; Pre-translating the merged monolingual file into a bilingual file through a machine translation engine; With the help of the GPT model in the scenario auxiliary module, the translator performs post-editing and translation quality detection of the bilingual file. 6.A computer device, comprising a memory and a processor, and characterized in that, The memory stores computer execution instructions and data, the processor reads and executes the computer execution instructions and data stored in the memory, and writes the results back to the memory to realize the data management method of terms and corpus in a translation project as claimed in claim 5.

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