Borrowing management system suitable for digital library

Abstract

The invention relates to the technical field of digital libraries, in particular to a borrowing management system suitable for a digital library. The system comprises a retrieval module, a borrowing module and an expiration automatic book returning module, the retrieval module carries out resource retrieval according to user index keywords and then locates digital resources meeting conditions, and the borrowing module carries out borrowing guidance and updates a borrowing state according to user conditions. And the expiration automatic book returning module automatically completes returning operation and updates database records when the digital resources borrowed by the user reach the returning deadline. According to the method, distributed identity verification based on the block chain is combined with a zero-knowledge proof algorithm, unauthorized access is effectively prevented, and user information security is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of digital libraries, and particularly to a borrowing management system applicable to digital libraries. Background Art

[0002] With the rapid development of information technology, digital libraries play an increasingly important role in knowledge dissemination and cultural inheritance. However, there are many problems in the existing borrowing management of digital libraries: Low retrieval efficiency: Multi-dimensional combined retrieval is not realized, and the query response time exceeds 3 seconds; Fragmented borrowing process: Lack of management processes consistent with paper books (such as reservation queues, renewal rules); Blank in life cycle management: There is no automatic reminder for return and expiration release mechanism, and the resource recovery rate is less than 60%; Lack of copy management: There is no concurrency control mechanism for electronic resources, resulting in copyright risks caused by multiple people downloading simultaneously; Weak security control: Modern authentication mechanisms are not adopted, and there is a risk of unauthorized access; The reservation function is imperfect: The reservation process is cumbersome and opaque, and it is difficult for users to know the reservation status and the expected borrowing time; Lack of intelligent reminder for return: Traditional reminder methods for return are often not timely and personalized enough, easily leading to overdue books and affecting the borrowing of other users. Summary of the Invention

[0003] To solve the above-mentioned problems, the present invention provides a borrowing management system applicable to digital libraries.

[0004] In a first aspect, a borrowing management system applicable to digital libraries provided by the present invention adopts the following technical solutions: A borrowing management system applicable to digital libraries includes: A retrieval module, a borrowing module, and an automatic return module upon expiration. The retrieval module locates digital resources that meet the conditions after retrieving resources according to user index keywords. The borrowing module guides borrowing according to user conditions and updates the borrowing status. The automatic return module upon expiration automatically completes the return operation and updates the database record when the digital resources borrowed by the user reach the return deadline.

[0005] Furthermore, the retrieval module includes a data index construction unit, a retrieval syntax design unit, an intelligent association and recommendation unit, and a retrieval result sorting and display unit; wherein, the retrieval module extracts key attribute information from each resource of the digital library and indexes the key attribute information; according to the user's retrieval conditions and based on the constructed index, digital resources are filtered from the index data through the retrieval syntax; and the retrieval results are sorted and displayed after intelligent association of the digital resources.

[0006] Furthermore, the borrowing module includes a user identity authentication unit, a borrowing guidance unit and a borrowing status display unit, wherein the user identity authentication unit verifies the user's identity through unified identity recognition. After the verification is passed, the borrowing guidance unit pops up a prompt box to inform the user of key borrowing information based on the number of copies of the resource and the user's borrowing authority, guides the user to borrow, and displays the detailed status of the user's current borrowed resources through the borrowing status display unit, including the resource name, saving time, return deadline and whether it can be renewed.

[0007] Furthermore, it also includes a reservation module, which includes a reservation rule unit, a reservation reminder unit and a reservation status management unit. Among them, the reservation rule unit generates reservation rules based on the number of copies of the resource and the current borrowing queue situation. When a user reserves a resource, the user reservation request is added to the reservation queue and sorted according to the rules. When the number of resource copies is available, the reservation reminder unit sends a reminder message to the user and updates the reservation status information in real time.

[0008] Furthermore, the system further includes a renewal module, which includes a renewal timing judgment unit, a renewal condition judgment unit, and a renewal statistics unit. The renewal timing judgment unit sets a book return reminder time node in advance based on the borrowing period and resource nature of the user's borrowed resources, reminds the user to return the book at the time node, and receives a notification from the user whether to renew the loan. When the user initiates a renewal request, the renewal condition judgment unit determines whether the resource meets the renewal conditions, including whether the maximum number of renewals has been exceeded and whether there are other users who have made reservations, and records the renewal operation.

[0009] Furthermore, it also includes a copy number setting module, which includes a copy number policy formulation unit and a database, wherein the copy number policy formulation unit classifies resources according to the type and copyright ownership of digital resources, and generates corresponding copy number setting policies based on different categories; the database establishes a copy number record field for each digital resource and stores its set static copy number, and when a user initiates a borrowing request, the copy number record of the resource is provided through the database.

[0010] Furthermore, it also includes an automatic reminder module. The automatic reminder module generates a reminder time strategy according to the borrowing periods of different resources and the user's borrowing history, including reminder time nodes and reminder frequencies, and pushes reminder information to users through system messages. For users who have not returned the borrowed resources beyond the due date, the system will transfer them to the automatic return module at the due date for automatic return.

[0011] Furthermore, when the borrowing period of the digital resources borrowed by the user reaches the return date, the automatic return module at the due date automatically completes the return operation and updates the database record. This includes real-time monitoring of the return date of each user's borrowed resources according to the timer set in the background. When the return date is reached, the return operation is automatically triggered, the borrowing status is updated to "returned", and the corresponding number of copies of the resources is released. At the same time, the transaction processing mechanism is used to ensure the data consistency of the database and the borrowing table in the database.

[0012] Furthermore, the retrieval module extracts key attribute information from each resource in the digital library and constructs an index for the key attribute information. This includes using a multi-modal index method to construct an inverted index for text attributes and fuse the feature vectors extracted from image, audio, and video resources to construct a vector index. The locality-sensitive hashing algorithm is used to accelerate the approximate nearest neighbor search of high-dimensional vectors to obtain the indexed resources. For the text inverted index, the BM25 algorithm is used to calculate the document relevance score, which is expressed as: where Q is the query statement, d is the document, n is the number of query terms, IDF(qi) is the inverse document frequency of the query term qi, f(qi,d) is the term frequency of the query term qi in the document d, k1 and b are adjustment parameters, dl is the length of the document d, and avgdl is the average length of all documents.

[0013] Furthermore, after performing intelligent association on the digital resources, the retrieval results are sorted and displayed. This includes performing semantic understanding and feature extraction on the text content of the digital resources through the Transformer architecture of deep learning, calculating the semantic similarity between the user's query and the resources through intelligent association and recommendation, calculating the text relevance score of the user based on the PageRank algorithm, the click-through rate and borrowing rate scores based on the user's behavior, and then obtaining the final sorting score using the weighted summation method. The sorting is expressed as: where α, β, γ, and δ are weight coefficients, which are optimized through machine learning algorithms.

[0014] In summary, the present invention has the following beneficial technical effects: The present invention utilizes multi-modal indexing technology, complex retrieval syntax, and a ranking mechanism combining multiple algorithms to significantly improve the retrieval efficiency. The retrieval response time is shortened from the traditional over 3 seconds to within an average of 1 second, enabling multi-dimensional combined retrieval, and allowing users to quickly locate the required resources. At the same time, based on deep learning intelligent association and recommendation algorithms, personalized recommendations are made according to the user's historical behavior and resource semantic associations, with the recommendation accuracy rate increased by [X]% compared to the past, meeting the diverse needs of users and facilitating the efficient dissemination of knowledge. Construct a borrowing management process consistent with that of paper books, covering reservation queues, renewal rules, etc. By means of queuing theory models to predict waiting times and dynamic programming to optimize the sorting of reservation queues, etc., the borrowing process becomes more scientific and reasonable. The automatic reminder module formulates personalized reminder strategies in combination with survival analysis algorithms, and the due date automatic return module ensures timely return, with the resource recovery rate increased from less than 60% to over 80%, improving the circulation efficiency and overall utilization rate of resources. Adopt blockchain-based distributed identity authentication combined with zero-knowledge proof algorithms to effectively prevent unauthorized access and ensure user information security. In terms of replica management, a replica number strategy is formulated through multi-objective optimization algorithms, and the replica information is stored in a distributed database, avoiding copyright risks caused by multiple people downloading simultaneously, providing a solid guarantee for the sustainable development of digital libraries. Brief Description of the Drawings

[0015] Figure 1 It is a schematic diagram of a borrowing management system applicable to a digital library in Embodiment 1 of the present invention. Detailed Embodiment

[0016] The present invention will be further described in detail below with reference to the accompanying drawings.

[0017] Embodiment 1 Refer to Figure 1 , a borrowing management system applicable to a digital library in this embodiment specifically includes the following content: S1. Advanced Retrieval 1. Function Overview This retrieval module aims to provide users with efficient and accurate digital library resource retrieval services. In addition to supporting conventional simple keyword retrievals, it focuses on creating an advanced retrieval function to meet the diverse and complex retrieval needs of users. Through this module, users can flexibly combine retrievals based on multiple attributes of resources, such as book titles, authors, publishers, publication years, subject classifications, content keywords, etc., and quickly locate digital resources that meet specific requirements.

[0018] 2. Technical Implementation Details (1)Data index construction: In the system background, for each resource in the digital library, extract its key attribute information, including various types of metadata mentioned above, and then use professional indexing techniques to construct an index for this information. For example, for each keyword, record the positions and frequencies of its occurrences in each resource so that relevant resources can be quickly matched during retrieval. In this way, when a user enters a retrieval condition, the system can quickly screen out a set of resources that initially meet the requirements based on the constructed index. Among them, Adopt multimodal indexing technology. In addition to constructing an inverted index for text attributes (title, author, keywords, etc.), extract feature vectors for resources such as images, audio, and video to construct a vector index. Use the Locality-Sensitive Hashing (LSH) algorithm to accelerate the approximate nearest neighbor search of high-dimensional vectors and improve the efficiency of multimodal retrieval.

[0019] For the text inverted index, use the BM25 algorithm to calculate the document relevance score. The BM25 formula is: where Q is the query statement, d is the document, n is the number of query terms, IDF(qi) is the inverse document frequency of the query term qi, f(qi,d) is the term frequency of the query term qi in the document d, k1 and b are adjustment parameters, dl is the length of the document d, and avgdl is the average length of all documents.

[0020] (2)Retrieval syntax design: Design a set of concise and powerful retrieval syntax that supports the use of logical operators, facilitating users to combine multiple retrieval conditions. The system can accurately parse this expression and screen out digital resources that meet all three conditions from the index data according to the corresponding rules.

[0021] (3)Intelligent Association and Recommendation: During the process of users entering search keywords, the system performs intelligent association in real time based on the existing index data and the partial content entered by users, and recommends information such as complete keywords, author names, and book names that may be relevant to users, helping users enter search conditions more accurately and reducing the deviation of search results caused by inaccurate input. At the same time, on the search result page, other resources similar to the resources retrieved by users are recommended according to the resource characteristics of the user's search, further expanding the ways for users to obtain resources. Among them, a pre-trained model using the Transformer architecture based on deep learning (such as BERT) is used to perform semantic understanding and feature extraction on the text content of digital resources. Through calculating the semantic similarity between the user query and the resources, intelligent association and recommendation are carried out. A collaborative filtering algorithm based on deep learning (NeuralCollaborative Filtering, NCF) is used for personalized recommendation. The NCF model inputs the embedding vectors of users and items into a multi-layer neural network to learn the complex interaction relationship between users and items and predict the interest scores of users for unborrowed resources.

[0022] (4)Sorting and Display of Search Results: For the retrieved resource results, they are comprehensively sorted according to factors such as relevance and popularity (such as the number of views), and the resources that best meet the user's needs and are popular are preferentially displayed at the front. Moreover, the key information of each search result, such as the book name, author, and introduction, is clearly displayed, facilitating users to quickly judge whether it is the resource they really need. Clicking on the corresponding resource link can view the detailed content and perform subsequent borrowing and other operations. Among them, by combining multiple sorting algorithms, such as the resource importance score based on the PageRank algorithm, the text relevance score based on the TF - IDF and BM25 algorithms, and the click-through rate and borrowing rate scores based on user behavior, the final sorting score is obtained by using the weighted summation method.

[0023] The sorting formula is: Among them, α, β, γ, and δ are weight coefficients, which are optimized through machine learning algorithms.

[0024] S2. Borrowing Module 1. Functional Overview The borrowing module is one of the core functional modules of the entire digital library borrowing management system, aiming to provide users with a convenient and smooth borrowing operation process, and at the same time, provide users with clear and accurate borrowing status information in real time, facilitating users to manage the digital resources they have borrowed.

[0025] 2. Technical Implementation Details (1)User authentication: When a user initiates a borrowing request, strict authentication is first carried out, supporting multiple authentication methods such as account password login verification and unified identity recognition verification to ensure the legality and security of the borrowing operation. After successful verification, the system obtains the user's relevant information, borrowing history records, browsing footprints, my bookshelf, my comments, my collections, reservation records, etc., for subsequent borrowing process judgment.

[0026] (2)Simplification and guidance of the borrowing process: Optimize the borrowing operation interface and simplify the borrowing process into several simple operations. For example, the user only needs to click the "Borrow" button on the resource details page, and the system automatically determines whether the number of copies of the resource, the user's borrowing permission, etc. meet the requirements. If they meet, the borrowing operation is directly completed, and a prompt box pops up to inform the user of the successful borrowing and key information such as the borrowing period; if not, the user is prompted with the specific reasons (such as insufficient number of copies, the user has reached the borrowing limit, etc.), guiding the user to make a reservation or other operations. The whole process does not require the user to perform cumbersome page jumps and repeated information filling operations, improving the borrowing efficiency. Among them, the queuing theory model is introduced (in this embodiment, the M / M / 1 queuing model is adopted) to predict the user's waiting time. When the number of resource copies is insufficient, according to the length of the current borrowing queue and the borrowing rate, calculate the expected waiting time of the new user and inform the user in the prompt box.

[0027] In the M / M / 1 queuing model, the formula for calculating the average waiting time Wq is: where λ is the user arrival rate and μ is the service rate, that is, the resource return rate.

[0028] (3)Real-time update and display of borrowing status: In the system background, establish a real-time borrowing status tracking mechanism. Whenever a user completes operations such as borrowing, returning, or renewing, the borrowing status record of the corresponding resource in the database is updated in a timely manner. At the same time, on the user's personal center page, the detailed status of the resources currently borrowed by the user is displayed in a clear and intuitive manner, including information such as the resource name, borrowing time, return deadline, and whether it can be renewed. And the user can click on the corresponding resource entry to view more details, facilitating the user to keep track of their borrowing situation at any time and avoiding problems such as overdue returns due to forgetting.

[0029] S3. Reservation module 1. Function overview The reservation module provides users with the function of making an advance reservation for digital resources that are temporarily unavailable for borrowing, and through a scientific and reasonable reservation management mechanism and reminder function, ensures the fairness and effectiveness of the reservation, improves the overall utilization rate of resources, and reduces the time for users to wait for resources.

[0030] 2. Technical implementation details (1)Reservation rule formulation: Based on factors such as the number of copies of resources, the current borrowing queue situation, and the order of users' reservation times, detailed reservation rules are formulated. When a user reserves a certain resource, the system adds their reservation request to the reservation queue and sorts it according to the rules. For example, for the same resource, it is first sorted in the order of reservation time. If the reservation times are the same, the order is further determined according to factors such as user level (member users first) or the user's historical borrowing credit situation (users with good credit first), ensuring the fairness and reasonableness of the reservation.

[0031] (2)Reservation reminder setting: After the user successfully reserves a resource, the system sends a reminder message to the user in advance according to the reminder method set by the user (such as SMS reminder, system message reminder, email reminder, etc.) when the resource is about to have an available copy (for example, when the number of copies becomes available after the previous borrower returns it), informing the user that they can perform the borrowing operation, avoiding the user missing the borrowing opportunity due to forgetting, etc., and improving the actual utilization rate of the reserved resources.

[0032] (3)Reservation status management: The reservation status information is updated in real time, and the detailed situation of the resources reserved by the user is displayed on the user's personal center page, including reservation time, expected borrowing time, current position in the reservation queue, etc., facilitating the user to understand the reservation progress. At the same time, when the user no longer needs to reserve a certain resource, a convenient reservation cancellation function is provided. The user can click the corresponding button to cancel the reservation, and the system automatically adjusts the order of the reservation queue, ensuring the flexibility and efficiency of the reservation management.

[0033] S4. Renewal Module 1. Function Overview The renewal module aims to provide users with a convenient digital resource renewal service. By actively prompting the user about the due time and simplifying the renewal operation process, the user can more flexibly extend the usage time of the borrowed resources, reduce the inconvenience caused by automatic return due to overdue, and ensure the continuous and effective utilization of resources.

[0034] 2. Technical Implementation Details (1)Renewal timing judgment and reminder: The system sets the book return reminder time point in advance in the background according to factors such as the borrowing period of the resources borrowed by the user and the nature of the resources. When approaching this time point, the system automatically sends a book return reminder message to the user. If the user has not finished reading the borrowed book, the user can be notified through the message reminder method on the user's personal center that they can perform the book return or renewal operation. At the same time, on the detailed page of the borrowed resources in the user's personal center, the renewal button will also be prominently displayed and the remaining borrowing time will be prompted, facilitating the user to intuitively know the renewal situation.

[0035] (2)Renewal condition judgment and operation: When the user initiates a renewal request, the system first determines whether the resource meets the renewal conditions, such as whether the maximum number of renewals has been exceeded (different resources can set different maximum renewal numbers), and whether there are current reservations by other users. If the renewal conditions are met, the renewal operation is automatically completed, the borrowing period record of the resource in the database is updated (extended by a certain period of time on the original return date, such as 15 days), and the user is prompted that the renewal is successful and the new return date. If the renewal conditions are not met, the specific reasons are explained to the user to guide the user to make preparations for returning the resource.

[0036] (3)Renewal record and statistics: Detailed records of each renewal operation are made, including information such as the renewal time, the return date after renewal, and the name of the renewed resource, and stored in the system database for the convenience of administrators to conduct data analysis, understand the renewal situation of resources, and then reasonably adjust the renewal policy according to the actual situation to optimize resource management.

[0037] S5. Copy number setting module 1. Function overview The copy number setting module is mainly responsible for uniformly setting the static copy number of various digital resources in the digital library. By reasonably determining the maximum number of copies of each digital resource that can be borrowed simultaneously, it can not only ensure that a large number of users have the opportunity to borrow the resources they need, but also effectively protect intellectual property rights, avoid risks in terms of copyright due to excessive borrowing, and achieve a balance between resource utilization and copyright protection.

[0038] 2. Technical implementation details (1)Resource classification and copy number strategy formulation: First, all resources in the digital library are classified according to factors such as the type of digital resources (such as e-books, academic papers, research reports, etc.), the copyright ownership situation (exclusive copyright, shared copyright, etc.), and the popularity of the resources. For different categories, corresponding copy number setting strategies are formulated. For example, for exclusive copyright and popular e-books, a relatively low copy number is set to strictly protect the rights and interests of the copyright holders; while for some academic papers with shared copyright and a wide audience, a relatively high copy number can be appropriately set to meet the borrowing needs of more users.

[0039] (2)Database Record and Update: In the system database, a dedicated copy number record field is established for each digital resource to store the set static copy number. Whenever a user initiates a borrowing request, the system first queries the copy number record of the resource to determine whether the current available copy quantity is greater than 0. If it is greater than 0, borrowing is allowed, and the copy number record of the resource in the database is synchronously updated (subtracting 1 from the available copy number); if it is equal to 0, the user is prompted that there are no borrowable copies of the resource temporarily, and the user is guided to make a reservation or select other resources. At the same time, when the copyright owner adjusts the copyright situation of the resource or it is found that the copy number needs to be adjusted based on the analysis of resource borrowing data, the system provides a corresponding management interface to facilitate the administrator to update the copy number settings in the database in a timely manner.

[0040] S6. Automatic Reminder Module 1. Functional Overview The automatic reminder module is mainly responsible for accurately and timely sending reminder messages to users when the digital resources borrowed by users are approaching the return deadline, urging users to return the resources on time, reducing the occurrence of overdue returns, and ensuring the normal circulation of resources in the digital library and the borrowing rights of other users.

[0041] 2. Technical Implementation Details (1)Reminder Time Setting and Strategy: Based on the borrowing periods of different resources and the borrowing history of users, etc., a personalized reminder time strategy is formulated. Parameters such as the time point and frequency of reminder messages can be flexibly configured by the administrator in the system background according to the actual situation.

[0042] (2)Reminder Method: The system message reminder method is adopted to ensure that users can receive reminder messages in a timely manner. When users log in to the digital library system and enter the personal center page, they can see prominent message prompts, improving the effectiveness of reminder messages.

[0043] (3)Reminder Record and Follow-up Processing: Each reminder operation is recorded, including information such as the reminder time, the user being reminded, and the corresponding resource name, and is stored in the system database for subsequent query and statistical analysis. For users who have not returned the resources overdue, the system will automatically return them to maintain the standardization of borrowing management in the digital library.

[0044] S7. Automatic Return Module at Expiration 1. Functional Overview The automatic return module at expiration ensures that when the digital resources borrowed by users reach the return deadline, the system can automatically complete the return operation, update the relevant database records in a timely manner, ensure the accuracy of the data in the borrowing management system and the orderly circulation of resources, and avoid management chaos caused by human negligence or other reasons resulting in resources not being returned on time.

[0045] 2. Technical implementation details Time monitoring and triggering mechanism: Set a timer in the system background to monitor the return deadline time point of the resources borrowed by each user in real time. When the return deadline is reached, the system automatically triggers the return operation, updates the borrowing status of the resource in the database to "returned", and at the same time releases the corresponding number of copies of the resource (increases the available number of copies by 1), so that other users can borrow the resource normally.

[0046] Data consistency guarantee: During the process of automatically returning books when they are due, ensure the consistency and integrity of data through the transaction processing mechanism. That is, ensure that the relevant data updates of multiple database tables involved in the return operation (such as the resource borrowing table, the copy number record table, etc.) are either all successful or all failed, to avoid system failures or management chaos caused by data inconsistency. For example, if the update of the "returned" status in the resource borrowing table is successful, but the update of increasing the available number of copies in the copy number record table fails, the system will automatically roll back the entire operation and retry until the operation is successful.

[0047] The above are all preferred embodiments of the present invention, and the protection scope of the present invention is not limited by this. Therefore, all equivalent changes made according to the structure, shape, and principle of the present invention should be covered within the protection scope of the present invention.

Claims

1. A borrowing management system applicable to digital libraries, characterized in that It includes: A retrieval module, a borrowing module, and an automatic overdue return module. The retrieval module locates eligible digital resources after resource retrieval based on user index keywords. The borrowing module provides borrowing guidance according to user conditions and updates the borrowing status. The automatic overdue return module automatically completes the return operation and updates the database record when the borrowed digital resources reach the return deadline.

2. The borrowing management system applicable to a digital library according to claim 1, characterized in that, The retrieval module includes a data index construction unit, a retrieval syntax design unit, an intelligent association and recommendation unit, and a retrieval result sorting and display unit. Among them, the retrieval module extracts key attribute information from each resource in the digital library and constructs an index for the key attribute information. According to the user's retrieval conditions and based on the constructed index, digital resources are screened from the index data through the retrieval syntax. After intelligent association of the digital resources, the retrieval results are sorted and displayed.

3. The borrowing management system applicable to a digital library according to claim 2, wherein The borrowing module includes a user identity authentication unit, a borrowing guidance unit, and a borrowing status display unit. Among them, the user identity authentication unit verifies the user's identity through unified identity recognition. After successful verification, the borrowing guidance unit pops up a prompt box to inform the user of key borrowing information based on the number of copies of the resource and the user's borrowing privilege, guides the user to borrow, and the borrowing status display unit displays the detailed status of the resources currently borrowed by the user, including the resource name, borrowing time, return deadline, and whether it can be renewed.

4. The borrowing management system applicable to a digital library according to claim 3, characterized in that, It also includes a reservation module, which includes a reservation rule unit, a reservation reminder unit, and a reservation status management unit. Among them, the reservation rule unit generates reservation rules based on the number of copies of the resource and the current borrowing queue situation. When a user reserves a certain resource, the user's reservation request is added to the reservation queue and sorted according to the rules. The reservation reminder unit sends a reminder message to the user when there are available copies of the resource and updates the reservation status information in real time.

5. The borrowing management system applicable to a digital library according to claim 4, wherein, It also includes a renewal module, which includes a renewal timing judgment unit, a renewal condition judgment unit, and a renewal statistics unit. Among them, the renewal timing judgment unit sets a reminder time node for returning the book in advance according to the borrowing period and nature of the resource borrowed by the user, reminds the user to return the book at the time node and receives the user's notice of whether to renew. When the user initiates a renewal request, the renewal condition judgment unit judges whether the resource meets the renewal conditions, including whether the maximum renewal times have been exceeded and whether there are other users reserving, and records the renewal operation.

6. The borrowing management system applicable to a digital library according to claim 5, wherein, It also includes a copy number setting module, which includes a copy number strategy formulation unit and a database. Among them, the copy number strategy formulation unit classifies resources according to the type and copyright ownership of digital resources and generates corresponding copy number setting strategies based on different categories. In the database, a copy number record field is established for each digital resource and the set static copy number is stored. When a user initiates a borrowing request, the copy number record of the resource is provided through the database.

7. The borrowing management system applicable to a digital library according to claim 6, wherein It also includes an automatic reminder module. The automatic reminder module generates a reminder time strategy according to the borrowing periods of different resources and the user's borrowing history, including reminder time nodes and reminder frequencies, and pushes reminder information to users through system messages. For users who have not returned the resources overdue, it is transferred to the automatic return module at the due date for automatic return.

8. A borrowing management system applicable to a digital library according to claim 7, characterized in that, When the digital resources borrowed by the user reach the return deadline, the automatic return module at the due date automatically completes the return operation and updates the database record. This includes real-time monitoring of the return deadline time points of the borrowed resources of each user according to the background setting timer, automatically triggering the return operation when the return deadline is reached, updating the borrowing status to returned, releasing the corresponding number of copies of the resources, and ensuring the data consistency of the database and the borrowing table in the database through a transaction processing mechanism.

9. The borrowing management system applicable to a digital library according to claim 8, wherein The retrieval module extracts key attribute information from each resource in the digital library and constructs an index for the key attribute information. This includes using a multi-modal index method, constructing an inverted index for text attributes and fusing the feature vectors extracted from image, audio, and video resources to construct a vector index, and using the locality-sensitive hashing algorithm to accelerate the approximate nearest neighbor search of high-dimensional vectors to obtain the indexed resources. Among them, for the text inverted index, the BM25 algorithm is used to calculate the document relevance score, which is expressed as: Where Q is the query statement, d is the document, n is the number of query terms, IDF(qi) is the inverse document frequency of the query term qi, f(qi, d) is the term frequency of the query term qi in the document d, k1 and b are adjustment parameters, dl is the length of the document d, and avgdl is the average length of all documents.

10. A borrowing management system applicable to a digital library according to claim 9, characterized in that, After performing intelligent association on the digital resources, the retrieval results are sorted and displayed. This includes semantic understanding and feature extraction of the text content of the digital resources through the Transformer architecture of deep learning, followed by intelligent association and recommendation by calculating the semantic similarity between the user query and the resources. Based on the PageRank algorithm, the text relevance score of the user, the click-through rate and borrowing rate scores based on user behavior are calculated, and then the final sorting score is obtained by using the weighted summation method. The sorting is expressed as: Among them, α, β, γ, and δ are weight coefficients, which are optimized through machine learning algorithms.

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