File management method and system

Abstract

The invention relates to the technical field of archive management, and discloses an archive management method and system.The method comprises the steps that archive basic data are obtained, and the archive basic data comprise archive forming time, archive content and archive confidentiality deadline; performing classification score calculation according to the archive basic data to obtain archive classification scores; based on the archive classification score and a preset classification scoring standard, obtaining an archive archiving category; calculating an importance rating factor according to the archive basic data and the archive archiving category; performing importance score calculation based on the importance rating factor to obtain an archive importance score; and according to the archive importance score and a preset storage period standard, selecting a storage period for archiving. According to the method, the file storage efficiency can be improved, and the retrieval speed is increased.

Description

Technical Field

[0001] The present invention relates to the technical field of archive management, and in particular to an archive management method and system. Background Art

[0002] In today's era of information explosion, with the rapid development of social economy and the widespread popularization of information technology, the document materials generated by various institutions and individuals have shown unprecedented richness and diversity. These materials include not only traditional paper documents, but also a large number of electronic documents, audio, video materials and other media forms. This diversified development trend has led to a rapid increase in the number of archives, and the demand for storage space has also increased significantly. Traditional physical storage methods, such as filing cabinets and archive boxes, have been unable to cope with such a large amount of data and cannot meet the needs of efficient management and long-term preservation.

[0003] In one existing technology, archive management has begun to turn to digital storage solutions, using electronic archive management systems to manage and save massive amounts of archival materials. These institutions store a large amount of paper archival materials on hard disks, cloud servers or other network platforms through digital processing methods such as scanning and taking photos. This technology not only effectively saves physical space and reduces dependence on physical storage facilities, but also significantly improves the efficiency of archive retrieval. Users can quickly locate the required archival information through a variety of methods such as keyword search and classified browsing, which greatly shortens the search time and improves work efficiency. Digital storage also contributes to the long-term preservation and security protection of archives, reduces the risk of information loss due to physical damage or loss, and ensures the integrity and availability of archival materials.

[0004] Despite this, the current archive management methods still have some shortcomings. The existing management methods often focus on the storage of archives, but fail to adopt differentiated management and preservation strategies according to different types of archives. For example, most archives are simply classified and stored according to the time of generation and the category to which they belong, ignoring factors such as the confidentiality level and integrity of the archives. This makes it impossible to accurately evaluate the actual significance of different archives, thus affecting the specific setting of the archive management period. In addition, due to the relatively single management method, the overall archive management appears to be more chaotic and the information retrieval efficiency is low. Summary of the invention

[0005] The present invention provides a file management method and system to improve the file management efficiency.

[0006] In a first aspect, in order to solve the above technical problems, the present invention provides a method for managing archives, comprising:

[0007] Obtaining basic data of the archive, the basic data of the archive including: the time when the archive was created, the content of the archive and the confidentiality period of the archive;

[0008] Perform classification scoring calculation based on the basic data of the archive to obtain the archive classification score;

[0009] Based on the archive classification score and the preset classification score standard, the archive filing category is obtained;

[0010] Calculate the importance rating factor based on the basic data of the archive and the archive category of the archive;

[0011] Performing importance scoring calculation based on the importance rating factor to obtain a file importance score;

[0012] According to the archive importance score and the preset retention period standard, a retention period is selected for archiving.

[0013] In an optional implementation, performing classification score calculation according to the basic data of the archive to obtain the archive classification score includes:

[0014] The archive creation time score is calculated using the following formula:

[0015] A=100-Y now +Y Start

[0016] Among them, A is the score of the time when the archive was formed, Y now is the current year, Y Start The year in which the archive was created;

[0017] The archive classification score is calculated using the following formula:

[0018] W=A+B+C

[0019] Among them, W is the file classification score, B is the file content score, and C is the file confidentiality score;

[0020] The archive confidentiality score is calculated based on the confidentiality level of the archive.

[0021] In an optional implementation, the calculation of the archive content score includes:

[0022] Extract keywords from the archive content to obtain a preset number of archive keywords;

[0023] Based on the keyword scores preset in the keyword database, finding the keyword scores corresponding to the archive keywords;

[0024] The keyword scores are summed to obtain the archive content score.

[0025] In an optional implementation, obtaining the archive filing category based on the archive classification score and a preset classification score standard includes:

[0026] The archive filing categories include: general archives, confidential archives, and top secret archives;

[0027] When the file classification score exceeds the preset top secret file score threshold, the file classification category is top secret file.

[0028] In an optional implementation manner, calculating the importance rating factor according to the archive basic data and the archive filing category includes:

[0029] The importance rating factors include category factor, integrity factor, and confidentiality factor;

[0030] The categorical factor is calculated by the following formula:

[0031]

[0032] Among them, α is the category factor, m is the number of categories of archived data, and A i is the corresponding importance weight of the i-th category, C i is the classification factor of the i-th category;

[0033] The confidentiality factor is calculated by the following formula:

[0034]

[0035] Among them, S is the confidentiality factor, L is the current file confidentiality level, and M is the maximum limit of the preset confidentiality level;

[0036] The integrity factor is calculated using the following formula:

[0037]

[0038] Among them, η is the completeness factor, T is the completeness of the archive data, and μ is the amount of archived data.

[0039] In an optional implementation, the importance score calculation is performed based on the importance rating factor to obtain the archive importance score, including:

[0040] The archive importance score is calculated using the following formula:

[0041] I=α×(S×β-η) / t

[0042] Among them, I is the archive importance score, α is the category factor, η is the completeness factor, S is the confidentiality factor, t is the normalization factor, and β is the importance parameter.

[0043] In an optional implementation, selecting a retention period for archiving according to the archive importance score and a preset retention period standard includes:

[0044] The storage period standard classifies the storage period as: permanent, long-term or short-term;

[0045] Among them, when the archive importance score is greater than a first score threshold, the retention period is permanent.

[0046] In a second aspect, the present invention provides a file management system, comprising:

[0047] The archive acquisition module is used to acquire basic archive data, including: archive formation time, archive content and archive confidentiality period;

[0048] A classification scoring module is used to calculate the classification score according to the basic data of the archive to obtain the archive classification score;

[0049] An archive classification module, used to obtain an archive filing category based on the archive classification score and a preset classification score standard;

[0050] A factor calculation module, used to calculate the importance rating factor according to the basic archive data and the archive filing category;

[0051] A scoring calculation module, used to calculate the importance score based on the importance rating factor to obtain the archive importance score;

[0052] The archive archiving module is used to select a retention period for archiving based on the archive importance score and a preset retention period standard.

[0053] In a third aspect, the present invention further provides an electronic device, comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, it implements an archive management method as described in any one of the above.

[0054] In a fourth aspect, the present invention further provides a computer-readable storage medium, the computer-readable storage medium comprising a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute an archive management method as described in any one of the above.

[0055] Compared with the prior art, the present invention has the following beneficial effects: the present invention discloses a method and system for managing archives, the method comprising obtaining basic archive data, the basic archive data comprising: the time of archive formation, archive content and confidentiality period of archive; calculating the archive classification score according to the basic archive data through a classification scoring formula; obtaining the archive filing category based on the archive classification score and a preset classification scoring standard; calculating the importance rating factor according to the basic archive data and the archive filing category; calculating the archive importance score based on the importance rating factor combined with the importance scoring formula; selecting the storage period for filing according to the archive importance score and the preset storage period standard. The present invention proposes a management system for classifying, scoring and filing archives through a scientific method, which significantly improves the efficiency and accuracy of archive management. The basic data of the archive, such as the time of formation, content and confidentiality period, are processed through an automated process, and the archive classification score is calculated using a classification scoring formula, and then the filing category is determined according to the scoring standard, thereby achieving an objective evaluation of the significance and importance of the archive. Specifically, the importance score of archives is calculated through a formula. This method comprehensively considers the category, confidentiality, completeness, normalization factor and importance parameters of the archives, and realizes an accurate assessment of the importance of archives. At the same time, this method enhances the security of information, especially for archives with high confidentiality levels, more stringent security measures are taken to prevent the leakage of sensitive information. In addition, through scientific classification and importance assessment, this method can better meet the needs of different users and provide personalized information services. Users can adapt to different usage scenarios by setting weights by themselves. In summary, this calculation method greatly improves the efficiency and security of archive management.

[0056] According to the importance score of the archive and the preset retention period standard, the retention period is selected for archiving. By classifying archives into permanent, long-term and short-term storage, resource allocation can be optimized to ensure that archives of high importance and sensitivity (such as national laws and records of major historical events) are kept for a long time for future reference and research; archives of certain importance are properly kept for a certain period of time, while archives of lower importance are destroyed in a timely manner after being kept for a short period of time to release storage space.

[0057] In summary, this method proposes a specific scientific calculation method, which can optimize the allocation of storage resources based on the importance and retention period of archives, ensure the security of information, and establish a complete information index system, which greatly facilitates the retrieval and use of archives, and improves the storage efficiency and retrieval efficiency of archives. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 It is a schematic flow chart of a file management method provided by the first embodiment of the present invention;

[0059] Figure 2 It is a schematic diagram of the structure of an archive management system provided by the second embodiment of the present invention. DETAILED DESCRIPTION

[0060] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0061] In today's era of information explosion, with the rapid development of social economy and the widespread popularization of information technology, the document materials generated by various institutions and individuals have shown unprecedented richness and diversity. These materials include not only traditional paper documents, but also a large number of electronic documents, audio, video materials and other media forms. This diversified development trend has led to a rapid increase in the number of archives, and the demand for storage space has also increased significantly. Traditional physical storage methods, such as filing cabinets and archive boxes, have been unable to cope with such a large amount of data and cannot meet the needs of efficient management and long-term preservation.

[0062] In one existing technology, archive management has begun to turn to digital storage solutions, using electronic archive management systems to manage and save massive amounts of archival materials. These institutions store a large amount of paper archival materials on hard disks, cloud servers or other network platforms through digital processing methods such as scanning and taking photos. This technology not only effectively saves physical space and reduces dependence on physical storage facilities, but also significantly improves the efficiency of archive retrieval. Users can quickly locate the required archival information through a variety of methods such as keyword search and classified browsing, which greatly shortens the search time and improves work efficiency. Digital storage also contributes to the long-term preservation and security protection of archives, reduces the risk of information loss due to physical damage or loss, and ensures the integrity and availability of archival materials.

[0063] Despite this, the current archive management methods still have some shortcomings. The existing management methods often focus on the storage of archives, but fail to adopt differentiated management and preservation strategies according to different types of archives. For example, most archives are simply classified and stored according to the time of generation and the category to which they belong, ignoring factors such as the confidentiality level and integrity of the archives. This makes it impossible to accurately evaluate the actual significance of different archives, thus affecting the specific setting of the archive management period. In addition, due to the relatively single management method, the overall archive management appears to be more chaotic and the information retrieval efficiency is low.

[0064] To solve the above problems, refer to Figure 1The first embodiment of the present invention provides a method for managing archives, comprising the following steps:

[0065] S11, obtaining basic data of the archive, wherein the basic data of the archive includes: the time when the archive was formed, the content of the archive and the confidentiality period of the archive;

[0066] S12, performing classification scoring calculation based on the basic data of the archive to obtain the archive classification score;

[0067] S13, obtaining the archive filing category based on the archive classification score and the preset classification score standard;

[0068] S14, calculating an importance rating factor according to the basic archive data and the archive category;

[0069] S15, performing importance scoring calculation based on the importance rating factor to obtain a file importance score;

[0070] S16, selecting a retention period for archiving based on the archive importance score and a preset retention period standard.

[0071] In step S11, basic archive data is obtained, and the basic archive data includes: archive creation time, archive content and archive confidentiality period.

[0072] In one embodiment, the basic data of the electronic version of the archive, including the time of archive formation, content and confidentiality period, can be obtained by directly reading the creation date, modification date and other information from the common electronic document format through metadata extraction technology. For example, for documents in PDF format, PyPDF2 or pdfminer and other libraries in Python can be used to extract the metadata of the document. These libraries provide rich APIs that can easily read the title, author, creation date, modification date and other attributes of the document. Similarly, for Microsoft Office documents (such as DOCX, XLSX, etc.), Java libraries such as Apache POI or Python's python-docx library can be used to access and read the metadata information of the file. These tools not only support reading the basic information of the document, but also help identify the version history, revision record, etc. of the document, so as to improve the accuracy and integrity of the archive. In addition, for electronic archives stored in the database, the required information can be directly obtained by means such as SQL query. The archive management system provides an API interface, allowing third-party applications to call to automatically obtain archive data. In the case where the technology cannot be fully automated, manual input or verification methods can be used.

[0073] In another embodiment, for scanned documents or other documents in non-text formats, using optical character recognition (OCR) technology is an effective means to convert them into editable and searchable text. OCR technology can automatically identify the text content in the document through image processing and pattern recognition technology, and convert it into a computer-readable text format. For example, using the Tesseract OCR engine, not only can text in multiple languages ​​be recognized, but also multiple operating systems are supported, and the recognition effect of specific fonts or scenes can be improved through training. In addition, commercial software such as Adobe Acrobat Pro DC also integrates advanced OCR functions, which can efficiently process complex documents, such as documents containing charts, tables and different fonts, to ensure that the converted text is both accurate and complete. Through OCR technology, this method can extract key content from documents in non-text formats as a data source for subsequent document classification, archiving and retrieval.

[0074] It is worth noting that the basic data of the archives include: the time when the archives were formed, the content of the archives and the confidentiality period of the archives. For example, scientific research papers and policy documents are two very typical types of archives. Scientific research papers usually contain research objectives, research methods, experimental data, analysis results, conclusions and references. For example, a research paper on the impact of climate change will detail the selection of the research area, the climate model used, the type of data collected, the data analysis method, the main trends found and the significance for future climate predictions. Policy documents record the policy regulations, implementation guidelines, and relevant legal provisions issued by the government or organization. For example, a new environmental protection policy document includes information such as the background of the policy, the scope of application, the main measures, the implementing agency, the supervision mechanism, and the penalties for violations.

[0075] In step S12, a classification score is calculated based on the basic data of the archive to obtain the archive classification score.

[0076] In one implementation, the archive creation time score is calculated using the following formula:

[0077] A=100-Y now +Y Start

[0078] Among them, A is the score of the time when the archive was formed, Y now is the current year, Y Start The year in which the archive was created;

[0079] The archive classification score is calculated using the following formula:

[0080] W=A+B+C

[0081] Among them, W is the archive classification score, B is the archive content score, and C is the archive confidentiality score;

[0082] The archive confidentiality score is calculated based on the confidentiality level of the archive, and the archive confidentiality score for confidential files is 30 points.

[0083] The calculation of the archive content score includes: extracting keywords from the archive content to obtain a preset number of archive keywords; finding the keyword scores of the archive keywords based on the preset keyword scores in the keyword database; and summing the keyword scores to obtain the archive content score.

[0084] It is worth noting that this formula reflects the historical significance of the archive by calculating the gap between the year the archive was formed and the current year. The earlier the archive was formed, the higher the score. Secondly, the calculation of the archive content score includes keyword extraction of the archive content to obtain a preset number of archive keywords; then based on the preset keyword scores in the keyword database, the keyword scores of the archive keywords are found; finally, the keyword scores are summed to obtain the archive content score. The archive confidentiality score is calculated according to the confidentiality level of the archive. For example, the archive confidentiality score of confidential documents is 30 points, while the confidentiality score of general documents is 10 points. The score is confirmed by the actual use scenario and is not limited by the present invention. For example: there is a scientific research paper archive, which was formed in 2005 and the current year is 2024. First, the archive formation time score is calculated to be 81 points. Next, the archive content is keyword extracted, and the extracted keywords are "climate change", "model prediction", and "data analysis". The scores of these keywords in the keyword database are 20 points, 15 points, and 10 points respectively. Therefore, the archive content score is 45 points. At the same time, the archive is a confidential document, and its confidentiality score is 30 points. The final total score is 156 points.

[0085] In one embodiment, for keyword extraction, a keyword extraction method of a topic model is selected, and the specific steps for keyword extraction of archive content are as follows: First, the archive content is preprocessed, including word segmentation, removal of stop words, etc., to ensure the cleanliness and standardization of the text. Then the preprocessed document set is trained using the LDA (Latent Dirichlet Allocation) model to infer the topic distribution and topic-word distribution of the document. Each topic is represented by a probability distribution of a group of words. By analyzing these probability distributions, the core words under each topic can be determined. Finally, the words with the highest probability are selected from each topic as keywords, and the scores of each keyword are calculated according to the scores in the preset keyword database, and the scores are summed to obtain the archive content score. Keywords in the archive content can be extracted by this method. The preset number is 3 in the example, and this method is not limited. For archive storage keyword databases, the following method can be used: keywords are extracted from the preprocessed text using a topic model (such as LDA) or other keyword extraction techniques (such as TF-IDF, TextRank). The extracted keywords need to be deduplicated and standardized to ensure the consistency and accuracy of the keywords. The extracted keywords and their related attributes (such as frequency of occurrence, importance score, etc.) are then stored in a database. You can choose a relational database (such as MySQL, PostgreSQL) or a NoSQL database (such as MongoDB). The database table structure design should include fields such as keywords, document ID, number of occurrences, TF-IDF values, etc., for subsequent query and analysis. This method can efficiently manage and utilize keywords in archives, improving the retrieval efficiency when analyzing archive content.

[0086] In another embodiment, multiple linear regression is used to calculate the archive classification score. The multiple linear regression is a statistical technique for analyzing the relationship between multiple independent variables and dependent variables. In the archive management system, a prediction model is established mainly by collecting historical data and real-time data of archives such as archive classification, archive content and archive confidentiality level. The core purpose of multiple linear regression is to use these known input variables (independent variables) to predict the target output variable (dependent variable). Specifically, it determines the degree of influence of these variables on the dependent variable by weighted combination of multiple independent variables, thereby deriving a linear equation. The regression coefficients in this equation, such as a1, b1, and c1, are obtained by fitting historical data, and they reflect the contribution of each independent variable to the dependent variable. In the present invention, multiple linear regression is used to predict the classification category of archives. First, by collecting the current basic information of the archives, the system inputs these data as independent variables into the regression model. Then, the model uses these independent variables for calculation, and combines the independent variables into a linear equation through the previously fitted regression coefficients, and finally predicts the classification category of the archives.

[0087] In step S13, the archive filing category is obtained based on the archive classification score and the preset classification score standard.

[0088] In one embodiment, the file archiving categories include: general files, confidential files, and top secret files;

[0089] When the file classification score exceeds the preset top secret file score threshold, the file classification category is top secret file. In one embodiment, the classification score standard is set by setting a top secret file threshold. The full score of the file classification score is 100 points. For example, the top secret file threshold is set to 80 points. The classification of files with scores exceeding 80 points is top secret. The present invention does not limit the setting of the top secret file threshold. Similarly, the establishment of confidential files and general files is also determined according to the set threshold. The rationality of this method lies in that by comprehensively considering the file formation time score, file content score and file confidentiality score, the importance and sensitivity of the file can be more comprehensively and accurately reflected. Specifically, the file formation time score reflects the historical significance and timeliness of the file; the file content score evaluates the core content and information significance of the file through keyword extraction technology; the file confidentiality score measures the sensitivity and confidentiality requirements of the file. The scores of these three aspects jointly determine the final classification of the file, ensuring the scientificity and accuracy of the classification. In this way, files of different importance and sensitivity can be reasonably archived, which is convenient for subsequent retrieval and management, and improves the efficiency and security of file retrieval. For example, confidential and top secret files can adopt stricter access control measures, such as multi-factor authentication, access log records, and regular audits, to ensure that only authorized personnel can access these sensitive information, thereby preventing information leakage and abuse. General files can adopt more relaxed access control measures, such as simple username and password verification, allowing more people to easily access and share, thereby improving work efficiency. The present invention does not limit the access control measures.

[0090] In another implementation, in addition to classifying archive categories into general archives, confidential archives, and top secret archives, archives can also be classified according to their frequency of use, such as into commonly used archives, occasionally used archives, and rarely used archives. The specific classification threshold can be set as follows: archives that have been accessed more than 50 times in the past year are classified as commonly used archives; archives that have been accessed 5 to 50 times are classified as occasionally used archives; and archives that have been accessed less than 5 times are classified as rarely used archives. For example, an annual financial report has been consulted and cited many times in the past year, so it is classified as a commonly used archive and stored in an easily accessible location; while a historical project summary report is only consulted under specific circumstances, so it is classified as an occasionally used archive and stored in a secondary storage location; a meeting minutes from ten years ago are almost never consulted, so it is classified as a rarely used archive and stored in cold storage.

[0091] In step S14, an importance rating factor is calculated based on the archive basic data and the archive filing category.

[0092] In one implementation, the importance rating factors include a category factor, a completeness factor, and a confidentiality factor;

[0093] The categorical factor is calculated by the following formula:

[0094]

[0095] Among them, α is the category factor, m is the number of categories of archived data, and A i is the corresponding importance weight of the i-th category, C i is the classification factor of the i-th category;

[0096] The confidentiality factor is calculated by the following formula:

[0097]

[0098] Among them, S is the confidentiality factor, L is the current file confidentiality level, and M is the maximum limit of the preset confidentiality level; the integrity factor is calculated by the following formula:

[0099]

[0100] Among them, η is the completeness factor, T is the completeness of the archive data, and μ is the amount of archived data.

[0101] It is worth noting that the importance rating factor is calculated based on the basic data and archiving categories of the archives, which includes the category factor, integrity factor and confidentiality factor. The category factor is calculated by formula and reflects the relative importance of the category to which the archive belongs. Different archive categories (such as general archives, confidential archives, and top secret archives) have different importance weights, and the classification factor indicates the specific importance of the archive in the category. The confidentiality factor is calculated by formula and reflects the confidentiality requirements and sensitivity of the archive. The higher the confidentiality level, the more sensitive the archive is and the more stringent protection measures are required. The integrity factor is calculated by formula and reflects the integrity and reliability of the archive data. The higher the integrity of the archive data, the more complete and reliable the information in the archive is. Through the comprehensive calculation of these factors, the importance of the archive can be comprehensively evaluated. For example, if a certain archive belongs to a high-importance category (such as top secret archives), its confidentiality level is high (such as top secret level), and its data integrity is good, then its category factor, confidentiality factor and integrity factor will be high, and the final importance rating factor will also be high, indicating that the archive has extremely high management and protection significance.

[0102] In one implementation, data integrity can be obtained through the following steps: First, conduct a comprehensive check on the archive content to confirm whether all necessary information contained in the archive is complete, such as key information such as file title, author, date, content, etc. Secondly, count the missing or incomplete information items in the archive, such as missing signatures, unclear dates, missing parts of the content, etc. Then, calculate the data integrity based on the total number of information items and the number of missing information items in the archive. The specific formula is: data integrity = (total number of information items - number of missing information items) / total number of information items. For example, if a certain archive has 10 information items, of which 2 are missing, the data integrity is (10-2) / 10 = 0.8, i.e. 80%. In this way, the integrity of the archive can be quantified to provide data for subsequent integrity factor calculations.

[0103] In step S15, an importance score is calculated based on the importance rating factor to obtain a file importance score.

[0104] In one implementation, the archive importance score is calculated using the following formula:

[0105] I=α×(S×β-η) / t

[0106] Among them, I is the archive importance score, α is the category factor, η is the completeness factor, S is the confidentiality factor, t is the normalization factor, and β is the importance parameter.

[0107] It is worth noting that the archive importance score indicates the comprehensive importance of the archive. The category factor is calculated by a formula and reflects the relative importance of the category to which the archive belongs. The completeness factor is calculated by a formula and reflects the integrity and reliability of the archive data. The higher the integrity of the archive data, the more complete and reliable the information in the archive is. The confidentiality factor is calculated by a formula and reflects the confidentiality requirements and sensitivity of the archive. The higher the confidentiality level, the more sensitive the archive is and the more stringent protection measures are required. The normalization factor is used to standardize the importance score so that the same scoring criteria are used for different archives. The importance parameter is used to adjust the weight of the confidentiality factor in the importance score. For example, there is a file whose category is confidential, the importance weight is 0.8, the classification factor is 0.9, so the category factor is 0.72. The confidentiality level of the file is 3, and the preset maximum limit of the confidentiality level is 5, so the confidentiality factor is 0.6. The integrity factor of the file is 0.8. The normalization factor is 0.001 and the importance parameter is 1.5. By substituting these quantities into the formula, we can calculate the importance score to be 72 points, which will be used to determine the subsequent storage period.

[0108] In step S16, a retention period is selected for archiving based on the archive importance score and a preset retention period standard.

[0109] In one embodiment, the storage period standard divides the storage period into: permanent, long-term or short-term; wherein, when the archive importance score is greater than 80 points, the storage period is permanent. The specific contents of the storage period standard are as follows: When the archive importance score is greater than 80 points, the storage period is permanent. Such archives usually have extremely high historical, legal or strategic significance and need to be preserved for a long time for future reference and research. When the archive importance score is between 50 and 80 points, the storage period is long-term, specifically 20 to 50 years. Such archives still have high use significance within a certain period of time, such as long-term cooperation agreements. When the archive importance score is less than 50 points, the storage period is short-term, usually 1 to 10 years. Such archives have a short-term use demand, but the long-term preservation significance is not great, such as weekly work plans.

[0110] It is worth noting that for archives that have exceeded the retention period, the following steps need to be followed: First, the archive management system evaluates and reviews the archives, and the evaluation content includes the actual use of the archives, historical significance, etc. Secondly, based on the evaluation results, the archives are identified and screened. Archives that are really meaningless to continue to be preserved can be destroyed; for archives that are still meaningful to preserve, an application can be made to extend the retention period. The destruction methods can include physical cold destruction (such as storing the storage medium in a warehouse) and electronic destruction (such as deleting electronic files) to ensure that the contents of the archives are not leaked. After destruction, a destruction certificate should be issued and a new archive should be generated. For archives that apply for an extension of the retention period, there should be a reason and period for the extension, and the archive retention period record should be updated to ensure that the management and use of the archives meet the new retention requirements. After the processing is completed, the relevant records will be archived, including evaluation reports, approval documents, destruction certificates, etc. These records are not only an important basis for archive management, but also important information for future auditing and tracing. Through the above steps, it can be ensured that archives that have exceeded the retention period are properly handled and unnecessary waste of storage resources can be avoided.

[0111] In summary, the present invention proposes a file management method and system, which aims to classify, score and archive files through scientific methods to improve the efficiency and accuracy of file management. The method first obtains the basic data of the file, including the time of file formation, the content of the file and the confidentiality period of the file. Through these basic information, the system uses the classification scoring formula to calculate the classification score of the file, and the score comprehensively considers the time of file formation, content and confidentiality level. Based on the classification score and the preset classification scoring standard, the system determines the filing category of the file, including general file, confidential file and top secret file. Subsequently, the system calculates the importance rating factor according to the basic data and filing category of the file, which includes the category factor, the integrity factor and the confidentiality factor. The category factor reflects the relative importance of the category to which the file belongs; the confidentiality factor reflects the confidentiality requirements and sensitivity of the file; and the integrity factor reflects the integrity and reliability of the file data. Based on these importance rating factors, the system further calculates the importance score of the file in combination with the importance scoring formula. Finally, the system selects a suitable retention period for archiving according to the importance score of the file and the preset retention period standard. The storage period standard divides the storage period into permanent, long-term or short-term. When the archive importance score is greater than 80 points, the storage period is permanent. Such archives have extremely high historical significance, legal significance or strategic significance, and need to be preserved for a long time for future reference and research; when the archive importance score is between 50 and 80 points, the storage period is long-term, usually 20 to 50 years, and such archives still have high use significance within a certain period of time, such as long-term cooperation agreements; when the archive importance score is less than 50 points, the storage period is short-term, usually one to ten years, and such archives have a short-term use demand, but the long-term preservation significance is not great, such as weekly work plans. Through this scientific classification and scoring method, the present invention not only optimizes the configuration of archive resources, but also improves the efficiency and security of archive management. In addition, the method also enhances the security of information, especially for archives with high confidentiality levels, stricter security measures are taken to prevent sensitive information leakage. Further, users can adapt to different usage scenarios by setting weights by themselves, thereby improving the storage efficiency and retrieval efficiency of archive management.

[0112] Reference Figure 2 The second embodiment of the present invention provides a file management method, comprising:

[0113] The archive acquisition module is used to acquire basic archive data, including: archive formation time, archive content and archive confidentiality period;

[0114] A classification scoring module is used to calculate the classification score of the archive according to the basic data of the archive to obtain the archive classification score;

[0115] An archive classification module, used to obtain an archive filing category based on the archive classification score and a preset classification score standard;

[0116] A factor calculation module, used to calculate the importance rating factor according to the basic archive data and the archive filing category;

[0117] A scoring calculation module, used for performing importance scoring calculation based on the importance rating factor to obtain a file importance score;

[0118] The archive archiving module is used to select a retention period for archiving based on the archive importance score and a preset retention period standard.

[0119] Preferably, the archive acquisition module is used to:

[0120] Obtain basic archive data, including: archive creation time, archive content and archive confidentiality period.

[0121] Preferably, the classification scoring module is used to:

[0122] The archive classification score is calculated based on the basic archive data through the classification score formula, including:

[0123] The archive creation time score is calculated using the following formula:

[0124] A=100-Y now +Y Start

[0125] Among them, A is the score of the time when the archive was formed, Y now is the current year, Y Sta rt is the year in which the archive was created;

[0126] The archive classification score is calculated using the following formula:

[0127] W=A+B+C

[0128] Among them, W is the file classification score, B is the file content score, and C is the file confidentiality score;

[0129] The archive confidentiality score is calculated based on the confidentiality level of the archive, and the archive confidentiality score for confidential files is 30 points.

[0130] The calculation of the archive content score includes:

[0131] Extract keywords from the archive content to obtain a preset number of archive keywords;

[0132] Finding the keyword score of the archive keyword based on the keyword score preset in the keyword database;

[0133] The keyword scores are summed to obtain the archive content score.

[0134] Preferably, the archive classification module is used to:

[0135] Based on the archive classification score and the preset classification score standard, the archive filing category is obtained, including:

[0136] The archive filing categories include: general archives, confidential archives, and top secret archives;

[0137] When the file classification score exceeds the preset top secret file score threshold, the file filing category is top secret file.

[0138] Preferably, the factor calculation module is used to:

[0139] According to the basic data of the archive and the archive category of the archive, the importance rating factor is calculated, including:

[0140] The importance rating factors include category factor, integrity factor, and confidentiality factor;

[0141] The categorical factor is calculated by the following formula:

[0142]

[0143] Among them, α is the category factor, m is the number of categories of archived data, and A i is the corresponding importance weight of the i-th category, C i is the classification factor of the i-th category;

[0144] The confidentiality factor is calculated by the following formula:

[0145]

[0146] Among them, S is the confidentiality factor, L is the current file confidentiality level, and M is the maximum limit of the preset confidentiality level; the integrity factor is calculated by the following formula:

[0147]

[0148] Among them, η is the completeness factor, T is the completeness of the archive data, and μ is the amount of archived data.

[0149] Preferably, the scoring calculation module is used to:

[0150] The importance score is calculated based on the importance rating factor to obtain the archive importance score, including:

[0151] The archive importance score is calculated using the following formula:

[0152] I=α×(S×β-η) / t

[0153] Among them, I is the archive importance score, α is the category factor, η is the completeness factor, S is the confidentiality factor, t is the normalization factor, and β is the importance parameter.

[0154] Preferably, the archive archiving module is used to:

[0155] According to the importance score of the archive and the preset retention period standard, select the retention period for archiving, including:

[0156] The storage period standard classifies the storage period as: permanent, long-term or short-term;

[0157] Among them, when the archive importance score is greater than 80 points, the retention period is permanent.

[0158] It should be noted that the archive management system provided in the embodiment of the present invention is used to execute all the process steps of the archive management method in the above embodiment, and the working principles and beneficial effects of the two correspond one to one, so they will not be repeated.

[0159] The embodiment of the present invention further provides an electronic device. The electronic device includes: a processor, a memory, and a computer program stored in the memory and executable on the processor, such as a data acquisition program. When the processor executes the computer program, the steps in the above-mentioned various archive management method embodiments are implemented, such as Figure 1 Alternatively, when the processor executes the computer program, the functions of the modules / units in the above-mentioned device embodiments are realized, such as the archive acquisition module.

[0160] Exemplarily, the computer program may be divided into one or more modules / units, which are stored in the memory and executed by the processor to implement the present invention. The one or more modules / units may be a series of computer program instruction segments capable of implementing specific functions, which are used to describe the execution process of the computer program in the electronic device.

[0161] The electronic device may be a computing device such as a desktop computer, a notebook, a PDA, and a smart tablet. The electronic device may include, but is not limited to, a processor and a memory. Those skilled in the art will appreciate that the above components are merely examples of electronic devices and do not constitute a limitation on the electronic device. The electronic device may include more or fewer components than the above components, or may combine certain components, or different components. For example, the electronic device may also include input and output devices, network access devices, buses, etc.

[0162] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the electronic device, and uses various interfaces and lines to connect various parts of the entire electronic device.

[0163] The memory can be used to store the computer program and / or module, and the processor realizes various functions of the electronic device by running or executing the computer program and / or module stored in the memory, and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area can store data created according to the use of the mobile phone (such as audio data, a phone book, etc.), etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0164] Wherein, if the module / unit integrated in the electronic device is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Wherein, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0165] It should be noted that the device embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. In addition, in the accompanying drawings of the device embodiments provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, which may be specifically implemented as one or more communication buses or signal lines. A person of ordinary skill in the art may understand and implement it without paying any creative effort.

[0166] The specific embodiments described above further illustrate the purpose, technical solutions and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. It is particularly pointed out that for those skilled in the art, any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for managing archives, characterized in that: include: Obtaining basic data of the archive, the basic data of the archive including: the time when the archive was created, the content of the archive and the confidentiality period of the archive; Perform classification score calculation based on the basic data of the archive to obtain the archive classification score; Based on the archive classification score and the preset classification score standard, the archive filing category is obtained; Calculate the importance rating factor based on the basic data of the archive and the archive category of the archive; Calculating the importance score based on the importance rating factor to obtain the archive importance score; According to the archive importance score and the preset retention period standard, a retention period is selected for archiving.

2. The file management method according to claim 1, characterized in that: The classification score calculation is performed according to the basic data of the archive to obtain the archive classification score, including: The archive creation time score is calculated using the following formula: A=100-Y now +Y Start Among them, A is the score of the time when the archive was formed, Y now is the current year, Y Start The year in which the archive was created; The archive classification score is calculated using the following formula: W=A+B+C Among them, W is the archive classification score, B is the archive content score, and C is the archive confidentiality score; The archive confidentiality score is calculated based on the confidentiality level of the archive.

3. The file management method according to claim 2, characterized in that: The calculation of the archive content score includes: Extract keywords from the archive content to obtain a preset number of archive keywords; Based on the keyword scores preset in the keyword database, finding the keyword scores corresponding to the archive keywords; The keyword scores are summed to obtain the archive content score.

4. The file management method according to claim 1, characterized in that: The archive filing category is obtained based on the archive classification score and the preset classification score standard, including: The archive filing categories include: general archives, confidential archives, and top secret archives; When the file classification score exceeds the preset top secret file score threshold, the file classification category is top secret file.

5. The file management method according to claim 1, characterized in that: The importance rating factor is calculated based on the basic archive data and the archive filing category, including: The importance rating factors include category factor, integrity factor, and confidentiality factor; The categorical factor is calculated by the following formula: Among them, α is the category factor, m is the number of categories of archived data, and A i is the corresponding importance weight of the i-th category, C i is the classification factor of the i-th category; The confidentiality factor is calculated by the following formula: Among them, S is the confidentiality factor, L is the current file confidentiality level, and M is the maximum limit of the preset confidentiality level; The integrity factor is calculated using the following formula: Among them, η is the completeness factor, T is the completeness of the archive data, and μ is the amount of archived data.

6. The file management method according to claim 5, characterized in that: The importance score calculation is performed based on the importance rating factor to obtain the archive importance score, including: The archive importance score is calculated using the following formula: I=α×(S×β-η) / t Among them, I is the archive importance score, α is the category factor, η is the completeness factor, S is the confidentiality factor, t is the normalization factor, and β is the importance parameter.

7. The file management method according to claim 1, characterized in that: The selecting of a retention period for archiving according to the importance score of the archive and the preset retention period standard includes: The storage period standard classifies the storage period as: permanent, long-term or short-term; Among them, when the archive importance score is greater than a first score threshold, the retention period is permanent.

8. A file management system, characterized in that: include: The archive acquisition module is used to acquire basic archive data, including: archive formation time, archive content and archive confidentiality period; A classification scoring module is used to calculate the classification score according to the basic data of the archive to obtain the archive classification score; An archive classification module, used to obtain an archive filing category based on the archive classification score and a preset classification score standard; A factor calculation module, used to calculate the importance rating factor according to the basic archive data and the archive filing category; A scoring calculation module, used to calculate the importance score based on the importance rating factor to obtain the archive importance score; The archive archiving module is used to select a retention period for archiving based on the archive importance score and a preset retention period standard.

9. An electronic device, characterized in that: The invention comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, the archive management method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored computer program, wherein when the computer program is executed, the device where the computer-readable storage medium is located is controlled to execute the archive management method according to any one of claims 1 to 7.

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