Data management system, method and equipment for terms and corpora in translation project

Abstract

The invention provides a data management system for terms and corpora in translation items. The data management system comprises a term recognition and arrangement module used for extracting terms in an original text to be translated and obtaining first high-frequency terms; the corpus extraction and arrangement module is used for crawling monolingual corpus data with the same language type as the first high-frequency term on a related website by using a web crawler technology according to the first high-frequency term, and inputting the monolingual corpus data into the arrangement module to obtain a second high-frequency term; the term corpus translation module is used for combining all high-frequency terms and monolingual corpora into a monolingual file and translating the monolingual file to obtain a bilingual file; the database creation and maintenance module is used for creating a bilingual database of bilingual terms and corpora, and bilingual term pairs and bilingual corpus pairs are stored in a related database by adopting a bilingual contrast structure. According to the scheme, the problems that in the prior art, related corpora cannot be continuously expanded according to terms, recognized in an original text, of a certain field, so that the translation result is not accurate enough, and the translation efficiency is low are solved.

Description

Technical Field

[0001] The invention belongs to the field of translation technology, and in particular relates to a data management system, method and device for terminology and corpus in a translation project. Background Art

[0002] With the deepening of globalization, translation projects have an increasingly urgent need to improve translation efficiency. At present, industry professionals use various translation technologies, such as Computer-Assisted Translation (CAT), Machine Translation (MT), terminology management, corpus and corpus query tools, cloud translation collaboration platforms, etc., to improve the translation quality and efficiency in large-scale translation projects. However, with the rapid growth of bilingual information on the Internet and the continuous increase in the scale of translation projects, higher requirements are placed on terminology and corpus data management.

[0003] At present, many technologies can automatically extract terms, such as rule-based methods, which automatically extract terms based on word formation characteristics, syntactic characteristics, and domain characteristics, and extract words that match the template from the corpus. Methods based on mathematical statistics are mainly statistical calculation and machine learning methods. The statistical method extracts terms by calculating statistics such as word frequency, mutual information, TF-IDF, etc., and is universal. The machine learning method mainly uses large-scale annotated corpora to train models, predicts unannotated corpora through models, and converts the term extraction problem into a sequence labeling problem or classification problem. With the development of machine learning technology, methods such as support vector machines (SVM) and deep learning have begun to be used to train models and perform term recognition. In addition, the above methods can also be combined to extract terms. In addition to automatically extracting terms, bilingual term pairs can also be directly obtained from the bilingual term library.

[0004] In the aspect of terminology management, terminology management software such as SDL Multiterm is mainly used to create and manage terminology bases. The main functions of this type of software include terminology entry, editing, verification, retrieval, classification, standardization, sharing and collaboration, helping users to ensure the accuracy and consistency of terminology and supporting multilingual terminology management. In addition, it can be seamlessly integrated with machine-assisted translation tools such as SDL Trados Studio to facilitate the use and management of terminology in the translation process.

[0005] There are two main methods for extracting bilingual corpora. The first method is to directly obtain bilingual texts and align them. Use parallel corpus collection tools, such as web crawler tools to crawl articles from bilingual websites or use APIs to collect bilingual text pairs and align them, or directly download bilingual corpora from parallel corpus websites such as OPUS (Open Parallel Corpus), Tatoeba, EuroParl, UN Corpora, Linguistic Data Consortium (LDC), GigaWord, and corpora in multilingual databases for free or for a fee.

[0006] The second method is to translate monolingual text into bilingual text. Automatic translation tools such as Google Translate API and Microsoft Translator API can be used to automatically translate monolingual text into another language, and then post-edit it to form a bilingual text. Bilingual sentence pairs in translation memory in some tools such as SDL Trados Studio, MemoQ, and OmegaT can also be used to form a bilingual corpus.

[0007] At present, the terminology and corpus management process still has the following problems: usually, terminology and corpus are stored separately, and unified management of terminology and corpus is not achieved; it is impossible to continuously expand the relevant corpus based on the terminology of a certain field identified in the original text, and update the terminology library in real time; it is not combined with a variety of emerging technologies such as web crawler technology and GPT model to achieve bilingual data management of terminology corpus. Therefore, the existing management system can no longer meet the translation efficiency requirements of large-scale translation projects. Summary of the invention

[0008] In order to solve the problems in the prior art that it is impossible to continuously expand relevant corpus based on the terms in a certain field identified in the original text, and that the management of terms and corpus is not reasonable, resulting in inaccurate translation results and low translation efficiency, the present invention provides a data management system, method and device for terminology and corpus in a translation project.

[0009] In order to achieve the above object, the present invention provides the following technical solutions:

[0010] A data management system for terminology and corpus in translation projects, including:

[0011] A term recognition and sorting module is used to extract terms from the original text to be translated, and screen and sort out first high-frequency terms, wherein the first high-frequency terms include terms whose frequency of appearance in the original text exceeds a set threshold;

[0012] A corpus extraction and sorting module is used to crawl monolingual corpus data of the same language as the first high-frequency term on a relevant website using a web crawler technology, and input the monolingual corpus as the original text into a term identification and sorting module to obtain second high-frequency terms, wherein the second high-frequency terms include terms whose appearance frequency in the monolingual corpus exceeds a set threshold;

[0013] A 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, and translate the monolingual file to obtain a bilingual file required by the user, wherein the bilingual file includes a bilingual term pair and a bilingual corpus pair;

[0014] The database creation and maintenance module is used to create a bilingual database about bilingual term pairs and bilingual corpus pairs, store the bilingual term pairs and bilingual corpus pairs in the bilingual files in the relevant database using a bilingual comparison structure, and maintain and share them.

[0015] Furthermore, it also includes a situational assistance module, which is used to provide professional background knowledge of relevant terms as reference information through the GPT model during the management of the bilingual database, or to give translation suggestions, or to assist in solving technical problems in the creation and maintenance of relevant databases.

[0016] Furthermore, in the terminology recognition and sorting module, a scenario-assisted module is used to obtain professional background information; in the terminology corpus translation module, a scenario-assisted module is used to obtain professional background knowledge and translation suggestions; in the terminology base creation and maintenance module, a scenario-assisted module is used to obtain solutions to technical problems in the process of creating and maintaining related databases.

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

[0018] According to the original text to be translated, the natural language processing technology is used to automatically extract the terms in the original text to obtain the automatic recognition results of the terms;

[0019] Checking the context of the automatic recognition results of the term through a keyword context retrieval system, and processing duplicate, partially overlapping, and incomplete recognition results in the automatic recognition results;

[0020] The terms whose frequency of occurrence exceeds the set threshold are selected through sorting to obtain the first high-frequency term based on the original text.

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

[0022] Get authoritative websites in related fields;

[0023] On the authoritative website, the first high-frequency term extracted in the term identification and sorting module is input, and the latest monolingual corpus data related to the first high-frequency term is crawled and saved using a web crawler 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] Merging the first high-frequency terms, the second high-frequency terms and the monolingual corpus into a monolingual file;

[0026] Pre-translate the merged monolingual files into bilingual files through a machine translation engine;

[0027] The GPT model in the scenario assistance module is used to assist translators in post-editing and translation quality testing of bilingual documents.

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

[0029] Use bilingual comparison structure to store bilingual terminology pairs and bilingual corpus pairs in MySQL database to create bilingual terminology and bilingual corpus database;

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

[0031] Regularly update and share bilingual databases that store bilingual terminology and bilingual corpora.

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

[0033] Extracting terms from the original text to be translated, and screening and sorting out first high-frequency terms, wherein the first high-frequency terms include terms whose frequency of appearance in the original text exceeds a set threshold;

[0034] Based on the first high-frequency term, crawling monolingual corpus data of the same language as the first high-frequency term on a relevant website using web crawler technology, taking the monolingual corpus as the original text, and inputting it into a term recognition and sorting module to obtain second high-frequency terms, wherein the second high-frequency terms include terms whose appearance frequency in the monolingual corpus exceeds a set threshold;

[0035] 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 a bilingual file required by the user, wherein the bilingual file includes a bilingual term pair and a bilingual corpus pair;

[0036] Create a bilingual database about bilingual term pairs and bilingual corpus pairs, use a bilingual comparison structure in the relevant database to store the bilingual term pairs and bilingual corpus pairs in the bilingual files, and maintain and share them.

[0037] A computer device comprises a memory and a processor, wherein the memory stores computer-executable instructions and data, and the processor reads and executes the computer-executable instructions and data stored in the memory and writes the results back to the memory, so as to implement any of the above-mentioned methods for data management of terminology and corpus in a translation project.

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

[0039] The management system of this solution includes a terminology recognition and sorting module for extracting terms from the original text to be translated and screening out the first high-frequency terms; a corpus extraction and sorting module for crawling monolingual corpus data of the same language as the high-frequency terms on relevant websites using web crawler technology based on the first high-frequency terms, and inputting the monolingual corpus as the original text into the terminology recognition and sorting module to obtain the second high-frequency terms; a terminology corpus translation module for merging all high-frequency terms and the corresponding monolingual corpus into a monolingual file, and translating the monolingual file to obtain the bilingual file required by the user; a database creation and maintenance module for creating a bilingual database about bilingual terms and bilingual corpus, and using a bilingual comparison structure in the relevant database to store the bilingual term pairs and bilingual corpus pairs in the bilingual files, and maintain and share them.

[0040] The terminology recognition and sorting module is used to extract terms from the original text to be translated and the monolingual corpus crawled from the Internet, and obtain high-frequency terms with higher frequency by analyzing the frequency of use, context and changes of the terms, thereby realizing dynamic management and updating of the terms, ensuring the timeliness of the terms, and improving the overall translation quality.

[0041] The corpus extraction and collation module uses web crawler technology to collect terminology and corpus data. By crawling content based on relevant high-frequency keywords on the Internet, the corpus can be expanded multiple times and quickly to keep pace with new industry trends.

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

[0043] In summary, the data management system of the present invention combines automatic terminology extraction technology and web crawler technology to provide translation teams with efficient, accurate and dynamic terminology management solutions, significantly improving translation efficiency and quality and adapting to the growing translation needs in the context of globalization. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the embodiment of the present invention and its design scheme, the following briefly introduces the drawings required for this embodiment. The drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0045] Figure 1 Schematic diagram of the system framework of the system embodiment of the present invention.

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

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

[0048] Figure 4 This is a schematic diagram of the result of the scenario assistance module of the system embodiment of the present invention assisting in solving technical problems. DETAILED DESCRIPTION

[0049] In order to enable those skilled in the art to better understand the technical solution of the present invention and implement it, the present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and cannot be used to limit the scope of protection of the present invention.

[0050] Example 1

[0051] The present invention provides a data management system for terminology and corpus in a translation project, specifically Figure 1 As shown, the management system includes: a terminology recognition and sorting module, a corpus extraction and sorting module, a terminology corpus translation module, a database creation and maintenance module and a scenario assistance module.

[0052] 1)Terminology identification and sorting module.

[0053] It is used to automatically identify terms and perform manual screening and sorting. Figure 2 As shown, the steps of this module include:

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

[0055] S2: Check the context of the automatic recognition results through the keyword context (KWIC) retrieval system, check and organize them, and obtain the terms.

[0056] S3: Sort and filter out terms with higher frequency of occurrence to obtain high-frequency terms based on the original text.

[0057] S4: With the assistance of the GPT model, organize the terms and determine their meanings 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 the present embodiment, the high-frequency terms sorted and screened out in the third step S3 include word-type terms and phrase-type terms, from which the theme of the original text can be roughly understood. For example, a whole book to be translated is imported into the system in plain text format, and high-frequency terms are automatically identified and manually screened and sorted out. Specifically, in the present embodiment, in the fourth step S4, with the assistance of the GPT model, the translator can more accurately and conveniently understand the meaning of the terms and sort out and improve the terms by searching for professional background information. For example, the GPT model is asked about the meaning of the extraction result "localization", and combined with the content of the original text, 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 corpus. 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: Input the high-frequency terms extracted in the term recognition and sorting module.

[0064] S7: Use web crawler technology to crawl the latest monolingual corpus data related to high-frequency terms on authoritative websites in related fields and save them. Inputting the monolingual corpus as the original text into the term recognition and sorting module can obtain more high-frequency terms.

[0065] 3) Terminology corpus translation module.

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

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

[0068] S9: pre-translate the merged monolingual files into bilingual files through a machine translation engine.

[0069] S10: The GPT model in the scenario assistance module is used to assist translators in post-editing and translation quality testing of bilingual pre-translated documents.

[0070] 4) Database creation and maintenance module.

[0071] Used for storage, retrieval, maintenance and sharing of terminology corpus data. 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 term pairs and Chinese-English bilingual corpus pairs in two fields, such as Figure 3 You can also attach other data such as the frequency of occurrence and explanation information of bilingual terms and bilingual corpora to create a bilingual term and corpus database.

[0073] S12: Create an index in the MySQL database to more efficiently retrieve bilingual data.

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

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

[0076] 5) Scenario assistance module.

[0077] like Figure 2 As shown in Figure 1, this module provides reference background information, translation suggestions and assists in solving technical problems related to database creation and maintenance. In specific application examples, this module runs through the entire terminology and corpus management process.

[0078] First, in the process of term identification and corpus translation, the translator can determine and translate the terms based on the professional background knowledge provided by the GPT model in the scenario-assisted module. For example, how should "land logic", "institutional logic", "capital logic" and "market logic" be translated? The word "logic" means "the way of thinking and argumentation of a certain type of people and a specific field". Looking at the context "Therefore, if rural revitalization is to be achieved, it must follow the development logic of the market economy, including capital logic, land logic, and institutional logic", combined with the reference information generated by the scenario-assisted module, the translator may consider translating "land logic" as "land-oriented development logic". For example, the question is: What is "land logic"? The answer from the scenario-assisted module is: "Land logic" refers to the way of thinking and analysis related to land. It is a logical reasoning and thinking method based on the characteristics, planning, management and utilization of land. Land logic is a logical thinking process involving the rational use, 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, land management and sustainability. It helps people take various factors into consideration in land-related decisions to achieve optimal land use and development effects.

[0079] Secondly, in the process of translating terminology corpus, the GPT model in the context-assisted module can be used to directly obtain translation suggestions to help translators improve the translation. In different cultural backgrounds, the meaning of terms and the cultural connotations behind them may be different. Based on the background information and translation suggestions provided by the GPT model in the context-assisted module, translators can choose appropriate words to accurately convey the connotation of terms.

[0080] Finally, during the database creation and maintenance process, the GPT model in the scenario assistance module can assist in solving related technical problems. Figure 4 As shown in the figure, the scenario assistance module provides a method to use MySQL to create a table containing terms and their corresponding translations, including the fields and codes that should be included. Of course, the suggestions provided by this module are sometimes one-sided and are only for reference by users.

[0081] Method Embodiment

[0082] The present invention provides a method for data management of terminology and corpus in a translation project, comprising:

[0083] The terms in the original text to be translated are extracted, and the first high-frequency terms are screened and sorted out, wherein the first high-frequency terms include terms whose appearance frequency in the original text exceeds a set threshold.

[0084] Based on the first high-frequency terms, web crawler technology is used to crawl monolingual corpus data in the same language as the first high-frequency terms on relevant websites, and the monolingual corpus is used as the original text and input into the term recognition and sorting module to obtain the second high-frequency terms. The second high-frequency terms include terms whose appearance frequency in the monolingual corpus exceeds a set threshold.

[0085] The first high-frequency terms, the second high-frequency terms and the corresponding monolingual corpus are merged into a monolingual file, and the monolingual file is translated to obtain a bilingual file required by the user, wherein the bilingual file includes a bilingual term pair and a bilingual corpus pair.

[0086] Create a bilingual database about bilingual term pairs and bilingual corpus pairs, use a bilingual comparison structure in the relevant database to store the bilingual term pairs and bilingual corpus pairs in the bilingual files, and maintain and share them.

[0087] Device Embodiment

[0088] The present invention provides a computer device, including a memory and a processor, wherein the memory stores computer-executable instructions and data, and the processor reads and executes the computer-executable instructions and data stored in the memory, and writes the results back to the memory, so as to implement the above-mentioned method for data management of terminology and corpus in a translation project, wherein the method has been described in detail in the method embodiment and will not be repeated here.

[0089] It should be noted that the above-described specific implementation methods can enable those skilled in the art to more fully understand the invention, but do not limit the invention in any way. Therefore, although the present specification and embodiments have described the invention in detail, those skilled in the art should understand that the invention can still be modified or replaced by equivalents; and all technical solutions and improvements that do not deviate from the spirit and scope of the invention are included in the protection scope of the patent for the invention. Any figure mark in the claims should not be regarded as limiting the claims involved.

Claims

1. A data management system for terminology and corpus in a translation project, characterized in that: include: A term recognition and sorting module is used to extract terms from the original text to be translated, and screen and sort out first high-frequency terms, wherein the first high-frequency terms include terms whose frequency of appearance in the original text exceeds a set threshold; A corpus extraction and sorting module is used to crawl monolingual corpus data of the same language as the first high-frequency term on a relevant website using a web crawler technology, and input the monolingual corpus as the original text into a term identification and sorting module to obtain second high-frequency terms, wherein the second high-frequency terms include terms whose appearance frequency in the monolingual corpus exceeds a set threshold; A 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, and translate the monolingual file to obtain a bilingual file required by the user, wherein the bilingual file includes a bilingual term pair and a bilingual corpus pair; The database creation and maintenance module is used to create a bilingual database about bilingual term pairs and bilingual corpus pairs, store the bilingual term pairs and bilingual corpus pairs in the bilingual files in the relevant database using a bilingual comparison structure, and maintain and share them.

2. The data management system for terminology and corpus in a translation project according to claim 1, characterized in that: It also includes a situational assistance module, which is used to provide professional background knowledge of relevant terms as reference information through the GPT model during the management of the bilingual database, or to give translation suggestions, or to assist in solving technical problems in the creation and maintenance of related databases.

3. The data management system for terminology and corpus in a translation project according to claim 2, characterized in that: In the terminology recognition and arrangement module, a scenario auxiliary module is used to obtain professional background information; in the terminology corpus translation module, a scenario auxiliary module is used to obtain professional background knowledge and translation suggestions; In the term base creation and maintenance module, use the scenario assistance module to obtain solutions to technical problems in the process of database creation and maintenance.

4. The data management system for terminology and corpus in a translation project according to claim 1, characterized in that: The step of extracting terms from the original text to be translated and screening out the first high-frequency terms includes: According to the original text to be translated, the natural language processing technology is used to automatically extract the terms in the original text to obtain the automatic recognition results of the terms; Checking the context of the automatic recognition results of the term through a keyword context retrieval system, and processing duplicate, partially overlapping, and incomplete recognition results in the automatic recognition results; The terms whose frequency of occurrence exceeds the set threshold are selected through sorting to obtain the first high-frequency term based on the original text.

5. The data management system for terminology and corpus in a translation project according to claim 1, characterized in that: The step of crawling monolingual corpus data in the same language as the high-frequency term on a relevant website using a web crawler technology according to the first high-frequency term comprises: Get authoritative websites in related fields; On the authoritative website, the first high-frequency term extracted in the term identification and sorting module is input, and the latest monolingual corpus data related to the first high-frequency term is crawled and saved using a web crawler technology.

6. The data management system for terminology and corpus in a translation project according to claim 2, characterized in that: 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 comprises: Merging the first high-frequency terms, the second high-frequency terms and the monolingual corpus into a monolingual file; Pre-translate the merged monolingual files into bilingual files through a machine translation engine; The GPT model in the scenario assistance module is used to assist translators in post-editing and translation quality testing of bilingual documents.

7. The data management system for terminology and corpus in a translation project according to claim 1, characterized in that: The steps of creating a bilingual database of bilingual term pairs and bilingual corpus pairs, storing bilingual term pairs and bilingual corpus pairs in bilingual files in a bilingual comparison structure in the relevant database, and maintaining and sharing the bilingual term pairs and bilingual corpus pairs include: Use a bilingual comparison structure in the MySQL database to store bilingual terminology pairs and bilingual corpus pairs, and create a bilingual terminology and bilingual corpus database; Create indexes on the term and translation fields in the MySQL database; Regularly update and share bilingual databases that store bilingual terminology and bilingual corpora.

8. A method for managing terminology and corpus data in a translation project, characterized in that: include: Extracting terms from the original text to be translated, and screening and sorting out first high-frequency terms, wherein the first high-frequency terms include terms whose frequency of appearance in the original text exceeds a set threshold; Based on the first high-frequency term, crawling monolingual corpus data of the same language as the first high-frequency term on a relevant website using web crawler technology, taking the monolingual corpus as the original text, and inputting it into a term recognition and sorting module to obtain second high-frequency terms, wherein the second high-frequency terms include terms whose appearance frequency in the monolingual corpus exceeds a set threshold; 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 a bilingual file required by the user, wherein the bilingual file includes a bilingual term pair and a bilingual corpus pair; Create a bilingual database about bilingual term pairs and bilingual corpus pairs, use a bilingual comparison structure in the relevant database to store the bilingual term pairs and bilingual corpus pairs in the bilingual files, and maintain and share them.

9. A computer device comprising a memory and a processor, characterized in that: The memory stores computer-executable instructions and data, and the processor reads and executes the computer-executable instructions and data stored in the memory and writes the results back to the memory, so as to implement the data management method for terminology and corpus in a translation project as claimed in claim 8.

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