Intelligent file cabinet management method based on RFID technology

Abstract

The invention discloses an intelligent file cabinet management method based on the RFID technology, and relates to the technical field of intelligent file management. According to the method, intelligent retrieval is adopted, file positioning is fast and accurate through double indexing of content attributes and RFID tags, and a user only needs to input conditions such as keywords, themes or dates, so that the file can be rapidly and accurately positioned; according to the method, relevant archives can be screened out through similarity matching, the actual storage positions of the archives can be positioned, the retrieval efficiency is remarkably improved, meanwhile, a virtual digital library is established to conduct digital mapping on the archives, and dependence on actual storage space is reduced; under the condition of dense storage, the position information of the archives is recorded through the RFID tags, so that the archives can be flexibly put on a shelf or readjusted in position without influencing the management and positioning of the archives, meanwhile, the archives are digitized when being put in storage, and all content attributes, classification tags and position information are synchronously stored in a virtual digital library; even if the paper archives are actually damaged or lost, the digital information of the paper archives is still completely stored in the digital library.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent file management, in particular to an intelligent file cabinet management method based on RFID technology. Background Art

[0002] Current filing cabinet management relies on manual classification and paper labels to classify files by time, subject or department. However, with the growth of archival data and the diversification of usage needs, the efficiency of manual filing and retrieval is becoming increasingly low.

[0003] In order to improve search efficiency and reduce human errors, some solutions introduce barcodes or electronic tags, enter the file number and location information into the database, and quickly locate the actual location of the file. When the file is put into the warehouse, the barcode can be scanned, and its number and location can be entered into the system one by one, forming a basic file directory in the database, and the file can be located more quickly with the help of barcode scanning and digital records; in addition, some management systems are equipped with classification directories to make archiving operations more structured; however, such solutions only provide certain conveniences in actual location management, but the barcode and numbering system itself is static and cannot adapt to the update of file content and classification information, nor can it provide detailed content or related data of the file, which affects the archive retrieval effect.

[0004] However, barcodes or numbers only identify the actual location of the archives, and lack management of the attributes of the archive content. When the archive content changes or needs to be reclassified, the administrator can only manually adjust it by relabeling or re-archiving. The process is cumbersome and time-consuming, and it is difficult to meet the needs of high-frequency updates. Secondly, the above solution relies on static tags and cannot provide content-level retrieval. When searching, manual confirmation is still required to determine whether the content matches, and it is difficult to directly locate specific content in the directory. Therefore, an intelligent archive cabinet management method based on RFID technology is urgently needed to solve such problems. Summary of the invention

[0005] In view of the above existing problems, the present invention is proposed.

[0006] The present invention provides an intelligent filing cabinet management method based on RFID technology to solve the problem that traditional barcode and directory systems cannot meet the requirements of intelligent and dynamic filing management.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0008] The present invention provides an intelligent filing cabinet management method based on RFID technology, which comprises:

[0009] Step S1: file storage and intelligent identification.

[0010] When the archives are stored in the warehouse, the paper archives are digitized using scanning equipment, and the text content is recognized using OCR optical character recognition technology; natural language processing (NLP) and semantic analysis are used to extract the content attributes of the archives and generate corresponding classification labels;

[0011] Step S2, RFID smart tag binding,

[0012] According to the content attributes extracted in step S1, a unique RFID smart label is generated for each paper file, and the content attributes and classification information are written into the label, and the classification information includes the filing time, file number and classification label;

[0013] Step S3: Dynamic update management of archives.

[0014] During the archive storage and management process, if the archive content changes or the classification is adjusted, its classification label and content attributes will be automatically updated, and the information in the RFID tag will be updated synchronously;

[0015] Step S4: intelligent retrieval of archives.

[0016] When searching for archives, users can enter keywords, subjects or date information, and use content attributes and RFID tags for dual indexing to locate the archives in the digital library and their planned location.

[0017] Furthermore, in step S1, the content attributes include: subject, category, date and keyword.

[0018] Furthermore, in step S1, the text content is processed using natural language processing (NLP) and semantic analysis technology, specifically:

[0019] Preprocess the text recognized by OCR, split the text content into word sequences, remove common meaningless words from the word sequences, obtain the processed word sequences, restore the words in the word sequences to stems, and then extract the topics;

[0020] The SVM and BERT models were used for archive training and classification, and the TF-IDF statistical method was used for keyword extraction;

[0021] Regular expressions are used to extract the required content attributes from the text. Based on the extracted content attributes, the classification labels of the archives are generated. Let the subject, category, keyword and date be θ T 、c * , K and d, the classification label is expressed as: L = {θ T ,c * ,d,K}.

[0022] Furthermore, in step S2, the paper archives bound with RFID tags are placed in the virtual digital library, and the actual archives are put on the shelves and stored in the library according to the planned location, and the planned location is matched with the location in the digital library; in the virtual digital library, the digitized information of all paper archives is recorded synchronously with the RFID tag data, and the digital library serves as a digital mapping of the archives, saving the classification label, content attributes and storage location information of each archive.

[0023] Furthermore, in step S2, a unique RFID smart label is generated for each paper file, specifically:

[0024] Suppose the file number of the file is F id , the filing time is T arch , generate a unique identifier UID:

[0025] UID=Hash(F id +T arch ), where Hash(·) represents a hash function, and MD5 and SHA256 hash algorithms are selected;

[0026] The storage information structure of each RFID tag includes: identifier UID, content attributes and classification information;

[0027] Let the content attribute set be Classification information is Then the RFID tag data set R is expressed as: The process of writing the content in R to the RFID tag is as follows:

[0028] Activate the RFID tag and divide its memory area into multiple fields to store UID, content attributes and classification information respectively. Write the unique identifier UID generated in step S1 into the unique identification field of the tag. T Category c * , keyword K and date d are written into the corresponding fields of the tag, and the archiving time T arch 、File No. F id The generated classification label L is written into the classification information area of ​​the RFID tag.

[0029] Furthermore, in step S2, a virtual digital library of archives is created, in which the RFID tag data of each archive and its location mapping are recorded:

[0030] Assume that the unique identifier of the file is UID, and the position of each file in the virtual digital library is P virt , synchronously storing the content attributes of step S1 and the RFID tag data set R into the virtual digital library;

[0031] Suppose the archive information set of the digital library is D virt , then for each file there is: Dvirt ={UID,θ T ,c * ,d,K,T arch ,F id ,L}, where θ T For the theme, c * is the category, d is the date, K is the keyword, T arch F is the filing time. id is the file number, L is the classification label;

[0032] The files are placed in the planned location and are linked to the virtual location P virt Correspondingly, let the actual storage location be P phys , put each file on the shelf according to its planned location;

[0033] Establish a mapping relationship between virtual and actual locations: P map =(P virt ,P phys ), where P map A mapping between virtual location and actual location;

[0034] The actual storage location P phys Updates to the digital library;

[0035] If the archive content attributes or classification labels are changed during management, the classification label L and content attribute set in the RFID tag are updated synchronously.

[0036] Furthermore, in step S3, when the actual location of the archive is adjusted, the location information of the RFID tag is updated to keep the location information in the digital library consistent with the actual location.

[0037] Furthermore, in step S3, when the archive content is changed or the classification is adjusted, the classification label and content attributes are updated, specifically:

[0038] Monitor the archive content in real time and trigger the update process when changes or classification adjustments are detected in the archive content;

[0039] Suppose the changed file text is T ′ , re-perform natural language processing (NLP) and semantic analysis on it, and re-extract the topic θ according to the process of extracting content attributes in step S1 ′ T Category c ′* , Date ′ , and the keyword set K ′ ;

[0040] Generate an updated classification label L based on the re-extracted content attributes ′, let the updated content attribute set be The new classification label is expressed as: L ′ ={θ ′ T ,c ′* ,d ′ ,K ′};

[0041] Find the unique identifier UID of the corresponding archive in the virtual digital library, update the content attributes and classification labels to the newly extracted values, and set the archive information set of the virtual digital library as D virt , then the update operation is: D virt ={UID,θ ′ T ,c ′* ,d ′ ,K ′ ,T arch ,F id ,L ′}, where the filing time is T arch and file number F id Remain unchanged, only update the content attributes and category labels;

[0042] Using wireless communication protocols to transfer new content attributes and the classification label L ′ Write to the RFID tag. Let the information stored in the RFID tag be R. Then the update operation is: R = {UID, θ ′ T ,c ′* ,d ′ ,K ′ ,T arch ,F id ,L ′}, keep the RFID tag content consistent with the virtual digital library information;

[0043] Then perform synchronization verification to check the D virt If the data is consistent with the R tag data, the update is complete; if they are inconsistent, a warning is triggered and resynchronization is performed.

[0044] Furthermore, in step S4, keywords, topics or date information are input, and the virtual and actual locations of the archives in the digital library are located using the dual index of content attributes and RFID tags. Specifically:

[0045] The user enters keywords, topics or date information as search conditions, and the input information is set to Q, where: k is a keyword set, q θ For the theme, d For the date, retrieve the query vector V QDefined as V Q = {q k ,q θ ,q d};

[0046] In the virtual digital library, the content attributes of the archives are stored in advance. The content attribute vector of each archive is represented by V virt , where K is the keyword set, θ T is the subject, d is the date, and the content attribute vector of the archive UID is represented as, V virt ={K,θ T ,d};

[0047] Calculate the query vector V Q and the file content attribute vector V virt , and filter out the files that meet the conditions.

[0048] Furthermore, in step S4, the method of locating the virtual location and the actual location of the archive in the digital library also includes:

[0049] The similarity is calculated using weighted cosine similarity, where the weights of keywords, topics, and dates are w and k 、w θ and w d , satisfying w k +w θ +w d =1;

[0050] Perform keyword set similarity S k calculate: Where S k Indicates the similarity of keyword sets, |q k ∩K| represents the number of common keywords, |q k ∪K| represents the total number of keywords;

[0051] Topic matching results S θ Defined as a binary function: If q θ =θ T , then S θ =1, otherwise S θ =0,

[0052] Date Matching Results d Defined as: If q d = d, then S d =1, otherwise S d =0,

[0053] Calculate the overall similarity S according to the weight total :S total =w k ·S k+w θ ·S θ +w d ·S d , set the similarity threshold τ, and filter out the total Archive set UID ≥τ result , for the filtered archive collection UID result , using RFID tag information to locate its actual location and digital library location;

[0054] In the digital library, find the virtual location of each file, find the actual location of each file based on the RFID tag, and output the virtual location and actual location of each file.

[0055] The beneficial effects of the present invention are:

[0056] The present invention adopts intelligent retrieval and realizes fast and accurate file positioning through dual indexing of content attributes and RFID tags. Users only need to enter conditions such as keywords, topics or dates to filter out related files through similarity matching and locate their actual storage locations. The retrieval efficiency is significantly improved, the search time is shortened several times, and the search cost is greatly reduced.

[0057] The present invention establishes a virtual digital library to digitally map archives, reducing dependence on actual storage space; in the case of dense storage, the archive location information is recorded through RFID tags, so that the archives can be flexibly put on the shelf or repositioned without affecting their management and positioning, and the storage efficiency and flexibility of the archives are greatly improved.

[0058] In the present invention, archives are digitized when they are put into storage, and all content attributes, classification labels and location information are synchronously stored in the virtual digital library; even if the paper archives are actually damaged or lost, their digitized information is still completely preserved in the digital library; in addition, the unique identifier of the RFID tag reduces the risk of the archives being taken by mistake, lost or misplaced.

[0059] The present invention combines automatic monitoring and triggering mechanisms to automatically update classification labels and content attributes when archive content changes, and synchronize them to RFID tags and virtual digital libraries; archive information is always kept up to date, ensuring consistency between the digital library and actual archive information.

[0060] The present invention uses automated means to simplify the filing, retrieval and maintenance of archives. When the actual position is adjusted, the location information of the RFID tag is automatically synchronized to the digital library, and there is no need to manually update the archive information, making the management process more efficient.

[0061] The present invention allows users to simply input search conditions when searching for archives, and quickly feedback results through content attribute matching, and directly provide the virtual and actual locations of the archives, which is simpler and faster and optimizes the user's operating experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0063] Figure 1 It is a flow chart of the intelligent filing cabinet management method based on RFID technology of the present invention. DETAILED DESCRIPTION

[0064] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0065] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0066] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0067] Example 1, reference Figure 1 This embodiment provides a smart filing cabinet management method based on RFID technology, comprising the following steps:

[0068] Step S1: file storage and intelligent identification.

[0069] When the archives are stored in the warehouse, the paper archives are digitized using scanning equipment, and the text content is recognized using OCR optical character recognition technology; natural language processing (NLP) and semantic analysis are used to extract the content attributes of the archives and generate corresponding classification labels;

[0070] In step S1, the content attributes include: subject, category, date and keywords;

[0071] In step S1, the text content is processed using natural language processing (NLP) and semantic analysis technology, specifically:

[0072] Preprocess the text recognized by OCR, split the text content into word sequences, remove common meaningless words from the word sequences, obtain the processed word sequences, restore the words in the word sequences to stems, and then extract the topics;

[0073] The SVM and BERT models were used for archive training and classification, and the TF-IDF statistical method was used for keyword extraction;

[0074] Regular expressions are used to extract the required content attributes from the text. Based on the extracted content attributes, the classification labels of the archives are generated. Let the subject, category, keyword and date be θ T 、c * , K and d, the classification label is expressed as: L = {θ T ,c * ,d,K};

[0075] Specifically, OCR and NLP technologies are used to automatically digitize and classify paper archives when they are stored. OCR technology can quickly identify text content and extract the subject, category, and keyword content attributes of the archives through semantic analysis, and then generate classification labels, thereby improving the accuracy and speed of archive entry.

[0076] Step S2, RFID smart tag binding,

[0077] According to the content attributes extracted in step S1, a unique RFID smart label is generated for each paper file, and the content attributes and classification information are written into the label, and the classification information includes the filing time, file number and classification label;

[0078] In step S2, the paper archives bound with RFID tags are placed in the virtual digital library, and the actual archives are put on the shelves and stored in the library according to the planned location, and the planned location is matched with the location in the digital library; in the virtual digital library, the digitized information of all paper archives is recorded synchronously with the RFID tag data, and the digital library serves as a digital mapping of the archives, saving the classification label, content attributes and storage location information of each archive;

[0079] In step S2, a unique RFID smart label is generated for each paper file. Specifically:

[0080] Suppose the file number of the file is F id , the filing time is T arch , generate a unique identifier UID:

[0081] UID=Hash(F id +T arch), where Hash(·) represents a hash function, and MD5 and SHA256 hash algorithms are selected;

[0082] The storage information structure of each RFID tag includes: identifier UID, content attributes and classification information;

[0083] Let the content attribute set be Classification information is Then the RFID tag data set R is expressed as: The process of writing the content in R to the RFID tag is as follows:

[0084] Activate the RFID tag and divide its memory area into multiple fields to store UID, content attributes and classification information respectively. Write the unique identifier UID generated in step S1 into the unique identification field of the tag. T Category c * , keyword K and date d are written into the corresponding fields of the tag, and the archiving time T arch 、File No. F id and write the generated classification label L into the classification information area of ​​the RFID tag;

[0085] In step S2, a virtual digital library of archives is created, in which the RFID tag data of each archive and its location mapping are recorded:

[0086] Assume that the unique identifier of the file is UID, and the position of each file in the virtual digital library is P virt , synchronously storing the content attributes of step S1 and the RFID tag data set R into the virtual digital library;

[0087] Suppose the archive information set of the digital library is D virt , then for each file there is: D virt ={UID,θ T ,c * ,d,K,T arch ,F id ,L}, where θ T For the theme, c * is the category, d is the date, K is the keyword, T arch F is the filing time. id is the file number, L is the classification label;

[0088] The files are placed in the planned location and are linked to the virtual location P virt Correspondingly, let the actual storage location be P phys , put each file on the shelf according to its planned location;

[0089] Establish a mapping relationship between virtual and actual locations: P map =(Pvirt ,P phys ), where P map A mapping between virtual location and actual location;

[0090] The actual storage location P phys Updates to the digital library;

[0091] If the archive content attributes or classification labels are changed during management, the classification label L and content attribute set in the RFID tag are updated synchronously.

[0092] Specifically, after the archive is stored, its content attributes and classification information are synchronously stored in the virtual digital library, and a unique RFID tag is generated and bound to each archive; the virtual digital library not only saves the content attributes and classification information of the archive, but also maps its actual storage location, so that the digital location corresponds to the actual location one by one, forming a complete virtual-real management system;

[0093] The classification and location information of the archives are recorded in RFID tags, and the actual location of the archives can be automatically identified and located through RFID. The dual management system not only improves the convenience of archive tracking and management, but also provides support for the updating and retrieval of archive information.

[0094] Step S3: Dynamic update management of archives.

[0095] During the archive storage and management process, if the archive content changes or the classification is adjusted, its classification label and content attributes will be automatically updated, and the information in the RFID tag will be updated synchronously;

[0096] In step S3, when the actual location of the archive is adjusted, the location information of the RFID tag is updated to keep the location information in the digital library consistent with the actual location;

[0097] In step S3, when the archive content is changed or the classification is adjusted, the classification label and content attributes are updated. Specifically:

[0098] Monitor the archive content in real time and trigger the update process when changes or classification adjustments are detected in the archive content;

[0099] Suppose the changed file text is T ′ , re-perform natural language processing (NLP) and semantic analysis on it, and re-extract the topic θ according to the process of extracting content attributes in step S1 ′ T Category c ′* , Date ′ , and the keyword set K ′ ;

[0100] Generate an updated classification label L based on the re-extracted content attributes ′ , let the updated content attribute set be The new classification label is expressed as: L ′ ={θ ′ T ,c ′* ,d ′ ,K ′};

[0101] Find the unique identifier UID of the corresponding archive in the virtual digital library, update the content attributes and classification labels to the newly extracted values, and set the archive information set of the virtual digital library as D virt , then the update operation is: D virt ={UID,θ ′ T ,c ′* ,d ′ ,K ′ ,T arch ,F id ,L ′}, where the filing time is T arch and file number F id Remain unchanged, only update the content attributes and category labels;

[0102] Using wireless communication protocols to transfer new content attributes and the classification label L ′ Write to the RFID tag. Let the information stored in the RFID tag be R. Then the update operation is: R = {UID, θ ′ T ,c ′* ,d ′ ,K ′ ,T arch ,F id ,L ′}, keep the RFID tag content consistent with the virtual digital library information;

[0103] Then perform synchronization verification to check the D virt Consistency with R tag data. If the two are consistent, the update is complete; if they are inconsistent, a warning is triggered and resynchronization is performed;

[0104] Specifically, in the actual management process, the archive content or classification labels may be adjusted. The present invention supports dynamic updating of archives. When the content or classification information changes, the content attributes are automatically re-extracted and new classification labels are generated, and synchronized to the virtual digital library and RFID tags in real time; at the same time, the synchronization status of the digital library and the RFID tag is automatically verified. If inconsistency occurs, an alarm is automatically issued and resynchronization is triggered.

[0105] Step S4: intelligent retrieval of archives.

[0106] When searching for archives, users can enter keywords, subject or date information, and use content attributes and RFID tags for dual indexing to locate the archives in the digital library and the planned location;

[0107] In step S4, keywords, topics or date information are input, and the virtual and actual locations of the archives in the digital library are located using the dual index of content attributes and RFID tags. Specifically:

[0108] The user enters keywords, topics or date information as search conditions, and the input information is set to Q, where: k is a keyword set, q θ For the theme, d For the date, retrieve the query vector V Q Defined as V Q = {q k ,q θ ,q d};

[0109] In the virtual digital library, the content attributes of the archives are stored in advance. The content attribute vector of each archive is represented by V virt , where K is the keyword set, θ T is the subject, d is the date, and the content attribute vector of the archive UID is represented as, V virt ={K,θ T ,d};

[0110] Calculate the query vector V Q and the file content attribute vector V virt similarity, filter out the files that meet the conditions;

[0111] In step S4, the method of locating the virtual location and the actual location of the archive in the digital library also includes:

[0112] The similarity is calculated using weighted cosine similarity, where the weights of keywords, topics, and dates are w and k 、w θ and w d , satisfying w k +w θ +w d =1;

[0113] Perform keyword set similarity S k calculate: Where S k Indicates the similarity of keyword sets, |q k ∩K| represents the number of common keywords, |q k ∪K| represents the total number of keywords;

[0114] Topic matching results S θ Defined as a binary function: If q θ =θ T , then S θ =1, otherwise S θ =0,

[0115] Date Matching Results d Defined as: If q d = d, then S d =1, otherwise S d =0,

[0116] Calculate the overall similarity S according to the weight total :S total =w k ·S k +w θ ·S θ +w d ·S d , set the similarity threshold τ, and filter out the total Archive set UID ≥τ result , for the filtered archive collection UID result , using RFID tag information to locate its actual location and digital library location;

[0117] In the digital library, find the virtual location of each file, find the actual location of each file based on the RFID tag, and output the virtual location and actual location of each file;

[0118] Specifically, in the search process, users can enter conditions such as keywords, topics or dates, and automatically match the input query vector with the content attributes in the digital library, and screen out qualified files through a pre-set weighted similarity calculation; through weighted cosine similarity calculation, it supports customized matching based on different weights of keywords, topics and dates, and more flexibly meets the diverse needs of users; in addition, RFID tag information is used to locate the actual location of the file, which improves the speed and accuracy of file search.

[0119] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. An intelligent filing cabinet management method based on RFID technology, characterized in that: include, Step S1, file storage and intelligent identification. When the files are stored in the warehouse, the paper files are digitized by using scanning equipment, and the text content is recognized by using OCR optical character recognition technology; the text content is processed by natural language processing (NLP) and semantic analysis to extract the content attributes of the files and generate corresponding classification labels; Step S2, RFID smart label binding, based on the content attributes extracted in step S1, a unique RFID smart label is generated for each paper file, and the content attributes and classification information are written into the label, and the classification information includes the filing time, file number and classification label; Step S3, dynamic update management of archives: during the archive storage and management process, if the archive content is changed or the classification is adjusted, its classification label and content attributes are automatically updated, and the information in the RFID tag is updated synchronously; Step S4, intelligent archive retrieval. When retrieving archives, users can enter keywords, topics or date information, and use content attributes and RFID tags for dual indexing to locate the location and planning position of the archives in the digital library.

2. According to the RFID technology-based intelligent filing cabinet management method of claim 1, it is characterized in that: In step S1, content attributes include: subject, category, date and keyword.

3. The intelligent filing cabinet management method based on RFID technology according to claim 2 is characterized in that: In step S1, the text content is processed using natural language processing (NLP) and semantic analysis technology, specifically: Preprocess the text recognized by OCR, split the text content into word sequences, remove common meaningless words from the word sequences, obtain the processed word sequences, restore the words in the word sequences to stems, and then extract the topics; The SVM and BERT models were used for archive training and classification, and the TF-IDF statistical method was used for keyword extraction; Regular expressions are used to extract the required content attributes from the text. Based on the extracted content attributes, the classification labels of the archives are generated. Let the subject, category, keyword and date be θ T 、c * , K and d, the classification label is expressed as: L = {θ T ,c * ,d,K}.

4. The intelligent filing cabinet management method based on RFID technology according to claim 3 is characterized in that: In step S2, the paper archives bound with RFID tags are placed in the virtual digital library, and the actual archives are put on the shelves according to the planned location, and the planned location is matched with the location in the digital library; in the virtual digital library, the digital information of all paper archives is recorded synchronously with the RFID tag data.

5. The intelligent filing cabinet management method based on RFID technology according to claim 4 is characterized in that: In step S2, a unique RFID smart label is generated for each paper file. Specifically: Suppose the file number of the file is F id , the filing time is T arch , generate a unique identifier UID: UID=Hash(F id +T arch ), where Hash(·) represents a hash function, and MD5 and SHA256 hash algorithms are selected; The storage information structure of each RFID tag includes: identifier UID, content attributes and classification information; Let the content attribute set be Classification information is Then the RFID tag data set R is expressed as: Write the content in R to the RFID tag.

6. The intelligent filing cabinet management method based on RFID technology according to claim 5 is characterized in that: In step S2, a virtual digital library of archives is created, in which the RFID tag data of each archive and its location mapping are recorded: Assume that the unique identifier of the file is UID, and the position of each file in the virtual digital library is P virt , synchronously storing the content attributes of step S1 and the RFID tag data set R into the virtual digital library; Suppose the archive information set of the digital library is D virt , then for each file there is: D virt ={UID,θ T ,c * ,d,K,T arch ,F id ,L}, where θ T For the theme, c * is the category, d is the date, K is the keyword, T arch F is the filing time. id is the file number, L is the classification label; The files are placed in the planned location and are linked to the virtual location P virt Correspondingly, let the actual storage location be P phys , put each file on the shelf according to its planned location; Establish a mapping relationship between virtual and actual locations: P map =(P virt ,P phys ), where P map A mapping between virtual location and actual location; The actual storage location P phys Updates to the digital library; If the archive content attributes or classification labels are changed during management, the classification label L and content attribute set in the RFID tag are updated synchronously.

7. The intelligent filing cabinet management method based on RFID technology according to claim 6 is characterized in that: In step S3, when the actual location of the archive is adjusted, the location information of the RFID tag is updated to keep the location information in the digital library consistent with the actual location.

8. The intelligent filing cabinet management method based on RFID technology according to claim 7 is characterized in that: In step S3, when the archive content is changed or the classification is adjusted, the classification label and content attributes are updated. Specifically: Monitor the archive content in real time and trigger the update process when changes or classification adjustments are detected in the archive content; Assume that the changed archive text is T′, re-perform natural language processing (NLP) and semantic analysis on it, and re-extract the topic θ′ according to the process of extracting content attributes in step S1 T Category c ′* , date d′, and keyword set K′; According to the re-extracted content attributes, the updated classification label L′ is generated. Let the updated content attribute set be The new classification label is expressed as: L′={θ′ T ,c′ * ,d′,K′}; Find the unique identifier UID of the corresponding archive in the virtual digital library, update the content attributes and classification labels to the newly extracted values, and set the archive information set of the virtual digital library as D virt , then the update operation is: D virt ={UID,θ′ T ,c′ * ,d′,K′,T arch ,F id ,L′}, where the archiving time is T arch and file number F id Remain unchanged, only update the content attributes and category labels; Using wireless communication protocols to transfer new content attributes and classification label L′ are written into the RFID tag. Let the information stored in the RFID tag be R, then the update operation is: R = {UID, θ′ T ,c′ * ,d′,K′,T arch ,F id ,L′}, keep the RFID tag content consistent with the virtual digital library information; Then perform synchronization verification to check the D virt If the data is consistent with the R tag data, the update is complete; if they are inconsistent, a warning is triggered and resynchronization is performed.

9. The intelligent filing cabinet management method based on RFID technology according to claim 8, characterized in that: In step S4, keywords, topics or date information are input, and the virtual and actual locations of the archives in the digital library are located using the dual index of content attributes and RFID tags. Specifically: The user enters keywords, topics or date information as search conditions, and the input information is set to Q, where: q k is a keyword set, q θ For the theme, d For the date, retrieve the query vector V Q Defined as V Q = {q k ,q θ ,q d }; In the virtual digital library, the content attributes of the archives are stored in advance. The content attribute vector of each archive is represented by V virt , where K is the keyword set, θ T is the subject, d is the date, and the content attribute vector of the archive UID is represented as, V virt ={K,θ T ,d}; Calculate the query vector V Q and the file content attribute vector V virt , and filter out the files that meet the conditions.

10. The intelligent filing cabinet management method based on RFID technology according to claim 9, characterized in that: In step S4, the method of locating the virtual location and the actual location of the archive in the digital library also includes: The similarity is calculated using weighted cosine similarity, where the weights of keywords, topics, and dates are w and k 、w θ and w d , satisfying w k +w θ +w d =1; Perform keyword set similarity S k calculate: Where S k Indicates the similarity of keyword sets, |q k ∩K| represents the number of common keywords, |q k ∪K| represents the total number of keywords; Topic matching results S θ Defined as a binary function: If q θ =θ T , then S θ =1, otherwise S θ =0, Date Matching Results d Defined as: If q d = d, then S d =1, otherwise S d =0, Calculate the overall similarity S according to the weight total :S total =w k ·S k +w θ ·S θ +w d ·S d , set the similarity threshold τ, and filter out the total Archive set UID ≥τ result , for the filtered archive collection UID result , using RFID tag information to locate its actual location and digital library location; In the digital library, find the virtual location of each file, find the actual location of each file based on the RFID tag, and output the virtual location and actual location of each file.

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