A dynamic library management method and system based on artificial intelligence

Abstract

The present invention discloses a dynamic library management method and system based on artificial intelligence, which specifically relates to the technical field of library management, including dividing the library into initial areas according to the characteristics of books stored in the library, collecting book information and environmental information in the areas according to the initial areas of the library, establishing a regional judgment model for the library area division through a logistic regression algorithm, optimizing the library area division, determining the borrowing information of books in the area through a clustering algorithm according to the areas of the library division, collecting the management information of the books through monitoring equipment, comprehensively evaluating the borrowing information and the management information, determining the location of the book management point, dynamically adjusting the location of the book management point according to the current location of the book management point of the library and comparing it with the location of the book management point of the library in the past, the present invention is helpful to dynamically adjust the layout of each area, improve resource utilization, and improve operational efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of library management, and more specifically, to a dynamic library management method and system based on artificial intelligence. Background Art

[0002] At present, many libraries have introduced computer management systems, using barcodes, RFID technology, loan management systems and other means to manage books. However, how to use artificial intelligence technology to divide libraries into regions and dynamically adjust them to achieve more refined management is still a direction worthy of in-depth research.

[0003] Library management adjustments are often based on manual experience and lack scientific data analysis and model support, making it difficult to achieve accurate and efficient optimization. Once the existing area divisions are determined, they are often not adjusted for a long time and cannot adapt to changes in readers' needs and dynamic changes in book circulation, resulting in inefficient management.

[0004] In order to solve the above defects, a technical solution is now provided. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, the embodiments of the present invention provide a dynamic library management method and system based on artificial intelligence to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A dynamic library management method based on artificial intelligence specifically comprises the following steps:

[0008] S1: According to the characteristics of the books stored in the library, the books are divided into different categories, and the books are placed according to their categories, and the library is divided into initial areas;

[0009] S2: According to the initial division of the library area, collect the book information and environmental information in the area, establish the regional judgment model of the library area division through the logistic regression algorithm, and optimize the library area division;

[0010] S3: According to the areas divided by the library, the borrowing information of books in the area is determined by clustering algorithm, and the management information of books is collected by monitoring equipment. The borrowing information and management information are comprehensively evaluated to determine the location of the book management point;

[0011] S4: Determine the location of the current library's book management point, compare it with the location of the library's book management point in the past, and dynamically adjust the location of the book management point.

[0012] In a preferred embodiment, the book information and environmental information in the collection area include:

[0013] Book information is represented by the book richness coefficient, and environmental information is represented by the circulation coefficient and space coefficient, and the monitoring interval is set;

[0014] The logic for obtaining the book richness coefficient is as follows: within the monitoring interval, obtain the number of book types in the initial area of ​​the library, and mark the number of book types in the initial area of ​​the library as: ZL; obtain the number of books with different book IDs in the initial area of ​​the library, and mark the number of books with different book IDs in the initial area of ​​the library as: ID i , where i=1, 2, 3, ..., I, I is a positive integer, and i is the number of different book IDs;

[0015] Get the average number of books with different book IDs in the initial area of ​​the library, and mark the average number of books with different book IDs in the initial area of ​​the library as: ID avg ,in,

[0016] Calculate the book richness coefficient. The calculation formula for the book richness coefficient is: FF ts =ID avg ×I zl ; Among them, FF ts is the book richness coefficient;

[0017] The logic for obtaining the space coefficient is as follows: obtain the architectural plan and bookshelf layout of the library, calculate the area of ​​the area enclosed by each bookshelf according to the layout of the bookshelf, obtain the area of ​​each initial area of ​​the library, and mark the area of ​​each initial area of ​​the library as: S q , where q = 1, 2, 3, ..., Q, Q is a positive integer, and q is the number of the area initially divided by the library;

[0018] Obtain the average area of ​​the regions initially divided by the library, and mark the average area of ​​the regions initially divided by the library as: S avg ,in,

[0019] Calculate the space coefficient. The calculation formula of the space coefficient is: Among them, KJ ts is the space coefficient, S ～ is the area of ​​the initial region;

[0020] The logic for obtaining the circulation coefficient is as follows: within the monitoring interval, the number of people entering the initial area is obtained, and the length of time each person stays in the initial area is obtained, and the length of time each person stays in the initial area is marked as: SJn , where n = 1, 2, 3, ..., N, N is a positive integer, and n is the number of each person entering the initial area;

[0021] Set a time length threshold, compare the length of time each person stays in the initial area with the time length threshold, obtain the length of time each person who stays in the initial area longer than the time length threshold, and re-mark the length of time each person who stays in the initial area longer than the time length threshold as: SJ m , where m = 1, 2, 3, ..., M, M is a positive integer, and m is the number of the length of time that each person who enters the initial area stays for a period greater than the time length threshold;

[0022] Calculate the circulation coefficient. The calculation formula of the circulation coefficient is: Among them, LT ts is the circulation coefficient.

[0023] In a preferred embodiment, a regional judgment model for library regional division is established by a logistic regression algorithm, including:

[0024] Define the output label of the region judgment model. The output label is the target variable to be classified by the region judgment model. There is a linear relationship between the input feature information and the output label. Use the logic function to map the linear output to the probability value. The logic function in the region judgment model is expressed as: Among them, σ(z) is the probability of the output label, the probability of the output label is marked as the rationality coefficient, z is the linear combination of the input features, z = α1FF ts +α2LT ts -α3KJ ts , α1, α2, and α3 are the proportional coefficients of book richness coefficient, circulation coefficient, and space coefficient, and α1, α2, and α3 are all greater than 0.

[0025] In a preferred embodiment, optimizing the library division area includes:

[0026] A rationality coefficient threshold is set, and the rationality coefficient of each initial area in the library is compared with the rationality coefficient threshold. If the rationality coefficient is greater than the rationality coefficient threshold, the area is marked as a rational area; if the rationality coefficient is less than the rationality coefficient threshold, the area is marked as an unreasonable area;

[0027] Obtain the number of reasonable areas and the number of unreasonable areas, calculate the partition evaluation coefficient, and mark the partition evaluation coefficient as: HF pg ,in, In the formula, SL bh l is the number of unreasonable areas in the library, SL h 1is the number of reasonable areas in the library.

[0028] Set the partition evaluation coefficient threshold, and compare the partition evaluation coefficient with the partition evaluation coefficient threshold. If the partition evaluation coefficient is less than the partition evaluation coefficient threshold, it means that the initial area of ​​the library division is good and there is no need to re-divide the area. If the partition evaluation coefficient is greater than the partition evaluation coefficient threshold, it means that the initial area of ​​the library division is poor and the library needs to be re-divided. The partition evaluation coefficient of the library after re-division is obtained and compared with the partition evaluation coefficient threshold repeatedly until the partition evaluation coefficient is less than the partition evaluation coefficient threshold.

[0029] In a preferred embodiment, the borrowing information of books in a region is determined by a clustering algorithm, and the management information of the books is collected by a monitoring device, including:

[0030] The borrowing information of books in the area is represented by the borrowing heat coefficient, and the management information of books in the area is represented by the book regularization coefficient.

[0031] The logic for obtaining the borrowing heat coefficient is as follows: obtaining the number of books borrowed in different areas of the library within the monitoring interval, and taking the number of books borrowed in each area within the monitoring interval as the data point of each area, clustering the number of books borrowed in each area using the K-means clustering method according to the data points of each area, determining the number of clusters by using the silhouette coefficient method, and obtaining the cluster center of the library;

[0032] Get the total number of books borrowed by the library during the monitoring period, and mark the total number of books borrowed by the library during the monitoring period as: JY all , get the number of library division areas, and mark the number of library division areas as: QY sl , get the average number of regional borrowed books, and mark the average number of regional borrowed books as: JY avg ,in,

[0033] Get the number of books borrowed by the cluster center and mark the number of books borrowed by the cluster center as: JY zx , calculate the borrowing heat coefficient, the calculation formula of the borrowing heat coefficient is:

[0034] The logic for obtaining the book regularization coefficient is as follows: obtaining the number of times books are incorrectly placed in different areas of the library within the monitoring interval, obtaining the number of missing books in different areas of the library within the monitoring interval, and setting standard values ​​for the number of times books are incorrectly placed and the number of missing books;

[0035] The standard value of the number of wrongly placed books is compared with the number of wrongly placed books in different areas of the library within the monitoring interval to obtain the deviation of the number of wrongly placed books in different areas of the library within the monitoring interval, and the standard value of the number of missing books is compared with the number of missing books in different areas of the library within the monitoring interval to obtain the deviation of the number of missing books in different areas of the library within the monitoring interval;

[0036] Calculate the book regularization coefficient. The calculation formula of the book regularization coefficient is: Among them, GZ ts is the book regularization coefficient, CW cs To monitor the number of times books are incorrectly placed in different areas of the library within the monitoring interval, QS cs To monitor the number of missing books in different areas of the library within the interval, CW pc To monitor the deviation of the number of times books are incorrectly placed in different areas of the library within the monitoring interval, QS pc It is the deviation in the number of missing books in different areas of the library within the monitoring interval.

[0037] In a preferred embodiment, the borrowing information and the management information are comprehensively evaluated to determine the location of the book management point, including:

[0038] The evaluation coefficient of the book management point is generated by weighted calculation of the borrowing heat coefficient and the book regularization coefficient. The calculation formula of the evaluation coefficient of the book management point is: PG gl =β1RD jy -β2GZ ts Among them, PG gl is the evaluation coefficient of the book management point, β1 and β2 are the proportional coefficients of the borrowing popularity coefficient and the book regularization coefficient, and both β1 and β2 are greater than 0;

[0039] Set the library management point evaluation coefficient threshold, compare the area's library management point evaluation coefficient with the book management point evaluation coefficient threshold, if the book management point evaluation coefficient is less than the book management point evaluation coefficient threshold, then the area is not marked as a book management point, if the book management point evaluation coefficient is greater than the book management point evaluation coefficient threshold, then the area is marked as a book management point.

[0040] In a preferred embodiment, dynamically adjusting the location of the book management point includes:

[0041] Determine the location of the library book management point in the previous monitoring interval, obtain the location of the current library book management point, obtain the book management point whose location is the same as the location of the library book management point in the previous monitoring interval, obtain the number of the current library book management points, compare the number of book management points whose location is the same as the location of the library book management point in the previous monitoring interval with the number of the current library book management points, and obtain the book management point change evaluation coefficient;

[0042] Set the library management point change assessment coefficient threshold, compare the library management point change assessment coefficient with the book management point change assessment coefficient threshold, if the book management point change assessment coefficient is greater than the book management point change assessment coefficient threshold, it means that the current book management point can continue to be used, if the book management point change assessment coefficient is less than the book management point change assessment coefficient threshold, it means that the book management point needs to be replaced.

[0043] In a preferred embodiment, a dynamic library management system based on artificial intelligence includes an initial area division module, a data acquisition module, a logistic regression model module, a comprehensive evaluation module and a dynamic adjustment module, and the modules are signal-connected;

[0044] The initial area division module is used to extract the characteristic information of books, classify the books using the classification algorithm, generate classification labels, and divide the library into initial areas according to the classification results of the books;

[0045] The data collection module is used to collect the book information and environmental information of each area, and to extract and process the collected information;

[0046] Logistic regression model module, used to establish a regional judgment model using a logistic regression algorithm, and optimize the regional division of the library based on the model output results;

[0047] Comprehensive evaluation module, used to obtain borrowing information and management information, and comprehensively analyze the borrowing information and management information to determine the optimal location of book management points;

[0048] The dynamic adjustment module is used to record and analyze the location and effect of historical book management points, and dynamically adjust the location of book management points based on real-time data and historical comparison.

[0049] Technical effects and advantages of the present invention:

[0050] 1. The present invention constructs a regional judgment model of the library based on a logistic regression algorithm, repeatedly divides the library into regions, and determines the result of the library regional division according to the output result of the regional judgment model, which helps to dynamically adjust the layout of each region and improve the management efficiency of the library;

[0051] 2. The present invention divides the library into regions, determines the borrowing information of books in the region through the K-means clustering method, comprehensively evaluates the borrowing information and management information of books in the region, determines the location of the book management point, and optimizes the book management point adjustment plan, which helps to improve resource utilization and enhance operational efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to facilitate understanding by those skilled in the art, the present invention is further described below in conjunction with the accompanying drawings;

[0053] Figure 1 A schematic diagram of a flow chart of a dynamic library management method based on artificial intelligence according to the present invention;

[0054] Figure 2 The present invention is a structural schematic diagram of a dynamic library management system based on artificial intelligence. DETAILED DESCRIPTION

[0055] 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.

[0056] Example 1

[0057] The present invention provides Figure 1 The flowchart of a dynamic library management method based on artificial intelligence is shown, which specifically includes the following steps:

[0058] S1: According to the characteristics of the books stored in the library, the books are divided into different categories, and the books are placed according to their categories, and the library is divided into initial areas;

[0059] S2: According to the initial division of the library area, collect the book information and environmental information in the area, establish the regional judgment model of the library area division through the logistic regression algorithm, and optimize the library area division;

[0060] S3: According to the areas divided by the library, the borrowing information of books in the area is determined by clustering algorithm, and the management information of books is collected by monitoring equipment. The borrowing information and management information are comprehensively evaluated to determine the location of the book management point;

[0061] S4: Determine the location of the current library's book management point, compare it with the location of the library's book management point in the past, and dynamically adjust the location of the book management point.

[0062] In order to effectively manage the large number of books in the library and meet the users' demand for book borrowing, the library area is reasonably divided. The division of areas makes it more convenient to store, find and borrow books. This includes utilizing the library's existing classification system, collecting existing classification labels as training data, automatically annotating new books, and placing books of the same type together, thereby achieving efficient management of a large number of books.

[0063] Advantages of grouping books of the same type together include:

[0064] Easy to search: users can find the books they need more quickly and reduce the search time;

[0065] Improve borrowing rate: Grouping related books together can help users discover new books and increase borrowing opportunities;

[0066] Optimize space utilization: Reasonable classification and placement can maximize the use of library space and improve overall layout efficiency.

[0067] The initial division of the library area requires consideration of the layout and flow of the space to ensure smooth connections between areas and to ensure that the same types of books are contained in each area to avoid the same types of books appearing in different areas.

[0068] According to the areas initially divided by the library, the book information and environmental information in the area are collected. The book information is represented by the book richness coefficient, and the environmental information is represented by the circulation coefficient and the space coefficient. The book richness coefficient, circulation coefficient and space coefficient are used as input features of the regional judgment model.

[0069] Book information is obtained through the library's data management system, which records the types of books, book IDs, and the number of book IDs stored in the library. Book types indicate the main classification system to which the books belong, such as literature, social sciences, children's books, etc. Book IDs indicate a specific book under a certain book type, for example, books in the literature category include book IDs SJ1, SJ2, SJ3, etc. SJ1, SJ2, and SJ3 are book IDs, and the number of book IDs indicates the number of identical book IDs.

[0070] By obtaining the book types, book IDs, and the number of book IDs in the initial area, the book richness coefficient is determined. The advantages of using the book richness coefficient as the input feature of the regional judgment model include:

[0071] High-richness areas usually gather books that users are interested in, which can better meet readers' reading needs. Rich book types and genres attract more readers, promote borrowing behavior, and improve library utilization.

[0072] By analyzing the richness of each area, the location of books can be reasonably arranged to maximize the use of library space, which will help library managers to more effectively monitor book circulation and optimize inventory management.

[0073] Set a monitoring interval. The monitoring interval is a specific length of time, usually one day. The monitoring interval can reflect the book borrowing situation in the library and is specifically set by professional staff.

[0074] The logic for obtaining the book richness coefficient is as follows: within the monitoring interval, obtain the number of book types in the initial area of ​​the library, and mark the number of book types in the initial area of ​​the library as: ZL; obtain the number of books with different book IDs in the initial area of ​​the library, and mark the number of books with different book IDs in the initial area of ​​the library as: ID i , where i=1, 2, 3, ..., I, I is a positive integer, and i is the number of different book IDs;

[0075] It should be noted that the existence of the same book ID indicates that there are multiple copies of the book. The same book ID may exist in the library. The more books with the same book ID there are, the more likely each copy can be borrowed by different users at the same time, which helps improve the utilization rate of books.

[0076] Get the average number of books with different book IDs in the initial area of ​​the library, and mark the average number of books with different book IDs in the initial area of ​​the library as: ID avg ,in,

[0077] Calculate the book richness coefficient. The calculation formula for the book richness coefficient is: FF ts =ID avg ×I zl ; Among them, FF ts is the book richness coefficient.

[0078] From the formula, we can see that the larger the book richness coefficient is, the more types of books, the more book IDs, and the more copies of the same book ID are stored in the area divided by the library, which means that the planning of books in this area is better.

[0079] Environmental information is obtained by deploying monitoring equipment, including infrared sensors, video surveillance and other monitoring equipment. For example, infrared sensors are installed at the entrance and exit of each area to count the number of people entering and leaving, and cameras are installed to use video analysis technology to count the number of people entering each area and the length of their stay.

[0080] The circulation coefficient is determined by the flow of people in the initial area of ​​the library within the monitoring range. The advantages of using the circulation coefficient as the input feature of the regional judgment model include:

[0081] The circulation coefficient provides objective data support, making the regional division more scientific and accurate, avoiding the bias of subjective judgment. By monitoring the circulation coefficient, the regional division can be adjusted dynamically to ensure that the functions and layout of each area always meet the actual needs;

[0082] The circulation coefficient can help identify areas with high and low circulation, thereby optimizing the placement of books and facilities and improving space utilization efficiency;

[0083] The circulation coefficient reflects readers' behaviors and preferences, helps libraries understand user needs, improve services and facilities, realize automated management of area division and resource allocation, and reduce the workload of managers.

[0084] The logic for obtaining the circulation coefficient is as follows: within the monitoring interval, the number of people entering the initial area is obtained, and the length of time each person stays in the initial area is obtained, and the length of time each person stays in the initial area is marked as: SJ n , where n = 1, 2, 3, ..., N, N is a positive integer, and n is the number of each person entering the initial area;

[0085] Set a time length threshold, compare the length of time each person stays in the initial area with the time length threshold, obtain the length of time each person who stays in the initial area longer than the time length threshold, and re-mark the length of time each person who stays in the initial area longer than the time length threshold as: SJ m , where m = 1, 2, 3, ..., M, M is a positive integer, and m is the number of the length of time that each person who enters the initial area stays for a period greater than the time length threshold;

[0086] It should be noted that the time length threshold is a specific time length, which is set by professional staff. Some areas in the library are near the entrance and exit of the library, so the flow of people in these areas may be greater than that in other areas. If the user stays in an area for more than the time length threshold, it means that the user is interested in the area. If the user stays in an area for less than the time length threshold, it means that the user may pass by the area.

[0087] Calculate the circulation coefficient. The calculation formula of the circulation coefficient is: Among them, LT ts is the circulation coefficient.

[0088] From the formula, we can see that the larger the circulation coefficient is, the more likely it is that the flow of people in the area divided by the library is larger, and the longer the time users stay, which means that the initial area division of the library is better.

[0089] The logic for obtaining the space coefficient is as follows: obtain the architectural plan and bookshelf layout of the library, calculate the area of ​​the area enclosed by each bookshelf according to the layout of the bookshelf, obtain the area of ​​each initial area of ​​the library, and mark the area of ​​each initial area of ​​the library as: S q , where q = 1, 2, 3, ..., Q, Q is a positive integer, and q is the number of the area initially divided by the library;

[0090] Obtain the average area of ​​the regions initially divided by the library, and mark the average area of ​​the regions initially divided by the library as: S avg ,in,

[0091] Calculate the space coefficient. The calculation formula of the space coefficient is: Among them, KJ ts is the space coefficient, S~ is the area of ​​the initial region.

[0092] From the formula, we can see that the smaller the space coefficient is, the more the area of ​​the library is roughly the same, and the more even and reasonable the library area division is, which means that the initial area division of the library is better.

[0093] The regional judgment model of library area division is established through the logistic regression algorithm. The input features are normalized to have the same scale in the logistic regression algorithm and the input features in the logistic regression algorithm are between 0 and 1. The input features include the book richness coefficient, circulation coefficient and space coefficient. The input feature information is marked as Y = (FF ts , LT ts , KJ ts );

[0094] Define the output label of the regional judgment model. The output label is the target variable to be classified by the regional judgment model, that is, to judge the rationality of regional division. There is a linear relationship between the input feature information and the output label. The linear output is mapped to the probability value using a logical function. The logical function in the regional judgment model is expressed as: Among them, σ(z) is the probability of the output label, the probability of the output label is marked as the rationality coefficient, z is the linear combination of the input features, z = α1FF ts +α2LT ts -α3KJ ts , α1, α2, α3 are the proportional coefficients of book richness coefficient, circulation coefficient, and space coefficient, and α1, α2, α3 are all greater than 0;

[0095] A rationality coefficient threshold is set, and the rationality coefficient of each initial area in the library is compared with the rationality coefficient threshold. If the rationality coefficient is greater than the rationality coefficient threshold, the area is marked as a rational area; if the rationality coefficient is less than the rationality coefficient threshold, the area is marked as an unreasonable area.

[0096] Obtain the number of reasonable areas and the number of unreasonable areas, calculate the partition evaluation coefficient, and mark the partition evaluation coefficient as: HF pg ,in, In the formula, SL bhl is the number of unreasonable areas in the library, SL hl is the number of reasonable areas in the library.

[0097] Set the partition evaluation coefficient threshold, and compare the partition evaluation coefficient with the partition evaluation coefficient threshold. If the partition evaluation coefficient is less than the partition evaluation coefficient threshold, it means that the initial area of ​​the library division is good and there is no need to re-divide the area. If the partition evaluation coefficient is greater than the partition evaluation coefficient threshold, it means that the initial area of ​​the library division is poor and the library needs to be re-divided. The partition evaluation coefficient of the library after re-division is obtained and compared with the partition evaluation coefficient threshold repeatedly until the partition evaluation coefficient is less than the partition evaluation coefficient threshold.

[0098] It should be noted that reasonable area division of the library can improve the library's management efficiency and user experience, including making it easier for librarians to carry out daily maintenance, shelving and inventory, and dynamically adjusting the layout of each area according to the usage and circulation of the area to improve space utilization.

[0099] This embodiment constructs a regional judgment model for the library based on a logistic regression algorithm. By repeatedly dividing the library into regions and determining the results of the library regional divisions based on the output results of the regional judgment model, it helps to dynamically adjust the layout of each region and improve the management efficiency of the library.

[0100] Example 2

[0101] According to the result of dividing the areas in the above embodiment, multiple areas in the library are obtained, and book management points are set according to the borrowing information and management information of books in different areas, and the positions of the book management points are dynamically adjusted.

[0102] It should be noted that the book management point refers to the area where librarians perform tasks such as shelving, sorting and maintaining books. Book management points are set up in areas with high borrowing frequency to facilitate administrators to handle borrowed and returned books in a timely manner.

[0103] The borrowing information of books in the area is represented by the borrowing heat coefficient, and the management information of books in the area is represented by the book regularization coefficient.

[0104] The logic for obtaining the borrowing heat coefficient is as follows: obtain the number of books borrowed in different areas of the library within the monitoring interval, and use the number of books borrowed in each area within the monitoring interval as the data point of each area, cluster the number of books borrowed in each area using the K-means clustering method based on the data points of each area, determine the number of clusters by using the silhouette coefficient method, and obtain the cluster center of the library.

[0105] It should be noted that the silhouette coefficient is an indicator to measure the quality of clustering. Its value is between -1 and 1. The higher the value, the better the clustering effect. By comparing the silhouette coefficients of different numbers of clusters, the number of clusters with the highest silhouette coefficient is selected as the optimal number of clusters.

[0106] Get the total number of books borrowed by the library during the monitoring period, and mark the total number of books borrowed by the library during the monitoring period as: JY all , get the number of library division areas, and mark the number of library division areas as: QY sl , get the average number of regional borrowed books, and mark the average number of regional borrowed books as: JY avg ,in,

[0107] Get the number of books borrowed by the cluster center and mark the number of books borrowed by the cluster center as: JY zx , calculate the borrowing heat coefficient, the calculation formula of the borrowing heat coefficient is:

[0108] It can be seen from the formula that the larger the borrowing heat coefficient is, the more books are borrowed in the area. Setting up a book management point in this area will help users' borrowing experience and help staff to organize and maintain the area in a timely manner, indicating that there is a higher possibility of setting up a management point in this area.

[0109] The logic for obtaining the book regularization coefficient is as follows: obtaining the number of times books are incorrectly placed in different areas of the library within the monitoring interval, obtaining the number of missing books in different areas of the library within the monitoring interval, and setting standard values ​​for the number of times books are incorrectly placed and the number of missing books;

[0110] It should be noted that incorrect placement of books means that the location where the books are placed is different from the original location or area of ​​the books, which usually occurs after the user returns the books. Missing books means that the books are borrowed without registration or the user fails to return the books on time.

[0111] The standard value of the number of wrongly placed books is compared with the number of wrongly placed books in different areas of the library within the monitoring interval to obtain the deviation of the number of wrongly placed books in different areas of the library within the monitoring interval, and the standard value of the number of missing books is compared with the number of missing books in different areas of the library within the monitoring interval to obtain the deviation of the number of missing books in different areas of the library within the monitoring interval;

[0112] Calculate the book regularization coefficient. The calculation formula of the book regularization coefficient is: Among them, GZ ts is the book regularization coefficient, CW cs To monitor the number of times books are incorrectly placed in different areas of the library within the monitoring interval, QS cs To monitor the number of missing books in different areas of the library within the interval, CW pc To monitor the deviation of the number of times books are incorrectly placed in different areas of the library within the monitoring interval, QS pc It is the deviation in the number of missing books in different areas of the library within the monitoring interval.

[0113] From the formula, we can see that the larger the book regularity coefficient is, the more effective the book management in the area is, the more regular the book arrangement is, and the more timely the maintenance work is, which means that the possibility of setting up a management point in this area is lower.

[0114] Comprehensively evaluate the borrowing information and management information, and generate the book management point evaluation coefficient through weighted calculation of the borrowing heat coefficient and the book regularization coefficient. The calculation formula of the book management point evaluation coefficient is: PG gl =β1RD jy -β2GZ ts Among them, PG gl is the evaluation coefficient of the library management point, β1 and β2 are the proportional coefficients of the borrowing popularity coefficient and the book regularization coefficient, and both β1 and β2 are greater than 0.

[0115] Set the library management point evaluation coefficient threshold, and compare the area's library management point evaluation coefficient with the book management point evaluation coefficient threshold. If the book management point evaluation coefficient is less than the book management point evaluation coefficient threshold, the area will not be marked as a book management point, indicating that the number of books borrowed in the area may be small, and the books may be more regular. If the book management point evaluation coefficient is greater than the book management point evaluation coefficient threshold, the area will be marked as a book management point, indicating that the number of books borrowed in the area may be large, and the books may be less regular.

[0116] Determine the location of the library book management point in the previous monitoring interval, obtain the location of the current library book management point, obtain the book management point whose location is the same as the location of the library book management point in the previous monitoring interval, obtain the number of the current library book management points, compare the number of book management points whose location is the same as the location of the library book management point in the previous monitoring interval with the number of the current library book management points, and obtain the book management point change evaluation coefficient;

[0117] Set the library management point change assessment coefficient threshold, compare the library management point change assessment coefficient with the book management point change assessment coefficient threshold, if the book management point change assessment coefficient is greater than the book management point change assessment coefficient threshold, it means that the current book management point can continue to be used, if the book management point change assessment coefficient is less than the book management point change assessment coefficient threshold, it means that the book management point needs to be replaced.

[0118] This embodiment divides the library into regions, determines the borrowing information of books in the region through the K-means clustering method, comprehensively evaluates the borrowing information and management information of books in the region, determines the location of book management points, and optimizes the book management point adjustment plan, which helps to improve resource utilization and enhance operational efficiency.

[0119] Example 3

[0120] The present invention provides Figure 2 The schematic diagram of the structure of a dynamic library management system based on artificial intelligence is shown, which specifically includes an initial area division module, a data acquisition module, a logistic regression model module, a comprehensive evaluation module and a dynamic adjustment module, and the modules are connected by signals;

[0121] The initial area division module is used to extract the characteristic information of books, classify the books using the classification algorithm, generate classification labels, and divide the library into initial areas according to the classification results of the books;

[0122] The data collection module is used to collect the book information and environmental information of each area, and to extract and process the collected information;

[0123] Logistic regression model module, used to establish a regional judgment model using a logistic regression algorithm, and optimize the regional division of the library based on the model output results;

[0124] Comprehensive evaluation module, used to obtain borrowing information and management information, and comprehensively analyze the borrowing information and management information to determine the optimal location of book management points;

[0125] The dynamic adjustment module is used to record and analyze the location and effect of historical book management points, and dynamically adjust the location of book management points based on real-time data and historical comparison.

[0126] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0127] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0128] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0129] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0130] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0131] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0132] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage media include: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks or optical disks.

[0133] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A dynamic library management method based on artificial intelligence, characterized in that: The specific steps include: S1: According to the characteristics of the books stored in the library, the books are divided into different categories, and the books are placed according to their categories, and the library is divided into initial areas; S2: According to the initial division of the library area, collect the book information and environmental information in the area, establish the regional judgment model of the library area division through the logistic regression algorithm, and optimize the library area division; S3: According to the areas divided by the library, the borrowing information of books in the area is determined by clustering algorithm, and the management information of books is collected by monitoring equipment. The borrowing information and management information are comprehensively evaluated to determine the location of the book management point; S4: Determine the location of the current library's book management point, compare it with the location of the library's book management point in the past, and dynamically adjust the location of the book management point; The book information and environmental information in the collection area include: Book information is represented by the book richness coefficient, and environmental information is represented by the circulation coefficient and space coefficient, and the monitoring interval is set; The logic for obtaining the book richness coefficient is as follows: within the monitoring interval, obtain the number of book types in the initial area of ​​the library, and mark the number of book types in the initial area of ​​the library as: ZL; obtain the number of books with different book IDs in the initial area of ​​the library, and mark the number of books with different book IDs in the initial area of ​​the library as: ID i , where i=1, 2, 3, ..., I, I is a positive integer, and i is the number of different book IDs; Get the average number of books with different book IDs in the initial area of ​​the library, and mark the average number of books with different book IDs in the initial area of ​​the library as: ID avg , in, Calculate the book richness coefficient. The calculation formula for the book richness coefficient is: FF ts =ID avg ×I zl ; Among them, FF ts is the book richness coefficient; The logic for obtaining the space coefficient is as follows: obtain the architectural plan and bookshelf layout of the library, calculate the area of ​​the area enclosed by each bookshelf according to the layout of the bookshelf, obtain the area of ​​each initial area of ​​the library, and mark the area of ​​each initial area of ​​the library as: S q , where q = 1, 2, 3, ..., Q, Q is a positive integer, and q is the number of the area initially divided by the library; Obtain the average area of ​​the regions initially divided by the library, and mark the average area of ​​the regions initially divided by the library as: S avg ,in, Calculate the space coefficient. The calculation formula of the space coefficient is: Among them, KJ ts is the space coefficient, S ～ is the area of ​​the initial region; The logic for obtaining the circulation coefficient is as follows: within the monitoring interval, the number of people entering the initial area is obtained, and the length of time each person stays in the initial area is obtained, and the length of time each person stays in the initial area is marked as: SJ n , where n = 1, 2, 3, ..., N, N is a positive integer, and n is the number of each person entering the initial area; Set a time length threshold, compare the length of time each person stays in the initial area with the time length threshold, obtain the length of time each person who stays in the initial area longer than the time length threshold, and re-mark the length of time each person who stays in the initial area longer than the time length threshold as: SJ m , where m = 1, 2, 3, ..., M, M is a positive integer, and m is the number of the length of time that each person who enters the initial area stays for a period greater than the time length threshold; Calculate the circulation coefficient. The calculation formula of the circulation coefficient is: Among them, LT ts is the circulation coefficient.

2. The method for dynamic library management based on artificial intelligence according to claim 1, characterized in that: The regional judgment model for library regional division is established through logistic regression algorithm, including: Define the output label of the region judgment model. The output label is the target variable to be classified by the region judgment model. There is a linear relationship between the input feature information and the output label. Use the logic function to map the linear output to the probability value. The logic function in the region judgment model is expressed as: Among them, σ(z) is the probability of the output label, the probability of the output label is marked as the rationality coefficient, z is the linear combination of the input features, z = α1FF ts +α2LT ts -α3KJ ts , α1, α2, and α3 are the proportional coefficients of book richness coefficient, circulation coefficient, and space coefficient, and α1, α2, and α3 are all greater than 0.

3. The method for dynamic library management based on artificial intelligence according to claim 1, characterized in that: Optimize the library area division, including: A rationality coefficient threshold is set, and the rationality coefficient of each initial area in the library is compared with the rationality coefficient threshold. If the rationality coefficient is greater than the rationality coefficient threshold, the area is marked as a rational area; if the rationality coefficient is less than the rationality coefficient threshold, the area is marked as an unreasonable area; Obtain the number of reasonable areas and the number of unreasonable areas, calculate the partition evaluation coefficient, and mark the partition evaluation coefficient as: HF pg ,in, In the formula, SL bhl is the number of unreasonable areas in the library, SL hl The number of reasonable areas in the library; Set the partition evaluation coefficient threshold, and compare the partition evaluation coefficient with the partition evaluation coefficient threshold. If the partition evaluation coefficient is less than the partition evaluation coefficient threshold, it means that the initial area of ​​the library division is good and there is no need to re-divide the area. If the partition evaluation coefficient is greater than the partition evaluation coefficient threshold, it means that the initial area of ​​the library division is poor and the library needs to be re-divided. The partition evaluation coefficient of the library after re-division is obtained and compared with the partition evaluation coefficient threshold repeatedly until the partition evaluation coefficient is less than the partition evaluation coefficient threshold.

4. The method for dynamic library management based on artificial intelligence according to claim 3, characterized in that: The borrowing information of books in the area is determined through clustering algorithms, and the management information of books is collected through monitoring equipment, including: The borrowing information of books in the area is represented by the borrowing heat coefficient, and the management information of books in the area is represented by the book regularization coefficient; The logic for obtaining the borrowing heat coefficient is as follows: obtaining the number of books borrowed in different areas of the library within the monitoring interval, and taking the number of books borrowed in each area within the monitoring interval as the data point of each area, clustering the number of books borrowed in each area using the K-means clustering method according to the data points of each area, determining the number of clusters by using the silhouette coefficient method, and obtaining the cluster center of the library; Get the total number of books borrowed by the library during the monitoring period, and mark the total number of books borrowed by the library during the monitoring period as: JY all , get the number of library division areas, and mark the number of library division areas as: QY sl , get the average number of regional borrowed books, and mark the average number of regional borrowed books as: JY avg ,in, Get the number of books borrowed by the cluster center and mark the number of books borrowed by the cluster center as: JY zx , calculate the borrowing heat coefficient, the calculation formula of the borrowing heat coefficient is: The logic for obtaining the book regularization coefficient is as follows: obtaining the number of times books are incorrectly placed in different areas of the library within the monitoring interval, obtaining the number of missing books in different areas of the library within the monitoring interval, and setting standard values ​​for the number of times books are incorrectly placed and the number of missing books; The standard value of the number of wrongly placed books is compared with the number of wrongly placed books in different areas of the library within the monitoring interval to obtain the deviation of the number of wrongly placed books in different areas of the library within the monitoring interval, and the standard value of the number of missing books is compared with the number of missing books in different areas of the library within the monitoring interval to obtain the deviation of the number of missing books in different areas of the library within the monitoring interval; Calculate the book regularization coefficient. The calculation formula of the book regularization coefficient is: Among them, GZ ts is the book regularization coefficient, CW cs To monitor the number of times books are incorrectly placed in different areas of the library within the monitoring interval, QS cs To monitor the number of missing books in different areas of the library within the interval, CW pc To monitor the deviation of the number of times books are incorrectly placed in different areas of the library within the monitoring interval, QS pc It is the deviation in the number of missing books in different areas of the library within the monitoring interval.

5. The method for dynamic library management based on artificial intelligence according to claim 4, characterized in that: Comprehensively evaluate the borrowing information and management information to determine the location of the book management point, including: The evaluation coefficient of the book management point is generated by weighted calculation of the borrowing heat coefficient and the book regularization coefficient. The calculation formula of the evaluation coefficient of the book management point is: PG gl =β1RD jy -β2GZ ts Among them, PG gl is the evaluation coefficient of the book management point, β1 and β2 are the proportional coefficients of the borrowing popularity coefficient and the book regularization coefficient, and both β1 and β2 are greater than 0; Set the library management point evaluation coefficient threshold, compare the area's library management point evaluation coefficient with the book management point evaluation coefficient threshold, if the book management point evaluation coefficient is less than the book management point evaluation coefficient threshold, then the area is not marked as a book management point, if the book management point evaluation coefficient is greater than the book management point evaluation coefficient threshold, then the area is marked as a book management point.

6. The method for dynamic library management based on artificial intelligence according to claim 5, characterized in that: Dynamically adjust the location of the book management point, including: Determine the location of the library book management point in the previous monitoring interval, obtain the location of the current library book management point, obtain the book management point whose location is the same as the location of the library book management point in the previous monitoring interval, obtain the number of the current library book management points, compare the number of book management points whose location is the same as the location of the library book management point in the previous monitoring interval with the number of the current library book management points, and obtain the book management point change evaluation coefficient; Set the library management point change assessment coefficient threshold, compare the library management point change assessment coefficient with the book management point change assessment coefficient threshold, if the book management point change assessment coefficient is greater than the book management point change assessment coefficient threshold, it means that the current book management point can continue to be used, if the book management point change assessment coefficient is less than the book management point change assessment coefficient threshold, it means that the book management point needs to be replaced.

7. A dynamic library management system based on artificial intelligence, used to implement a dynamic library management method based on artificial intelligence as described in any one of claims 1 to 6, characterized in that: It includes an initial area division module, a data acquisition module, a logistic regression model module, a comprehensive evaluation module and a dynamic adjustment module, and signal connections between the modules; The initial area division module is used to extract the characteristic information of books, classify the books using the classification algorithm, generate classification labels, and divide the library into initial areas according to the classification results of the books; The data collection module is used to collect the book information and environmental information of each area, and to extract and process the collected information; Logistic regression model module, used to establish a regional judgment model using a logistic regression algorithm, and optimize the regional division of the library based on the model output results; Comprehensive evaluation module, used to obtain borrowing information and management information, and comprehensively analyze the borrowing information and management information to determine the optimal location of book management points; Dynamic adjustment module, used to record and analyze the location and effect of historical book management points, and dynamically adjust the location of book management points based on real-time data and historical comparison; The data acquisition module is used for: Book information is represented by the book richness coefficient, and environmental information is represented by the circulation coefficient and space coefficient, and the monitoring interval is set; The logic for obtaining the book richness coefficient is as follows: within the monitoring interval, obtain the number of book types in the initial area of ​​the library, and mark the number of book types in the initial area of ​​the library as: ZL; obtain the number of books with different book IDs in the initial area of ​​the library, and mark the number of books with different book IDs in the initial area of ​​the library as: ID i , where i=1, 2, 3, ..., I, I is a positive integer, and i is the number of different book IDs; Get the average number of books with different book IDs in the initial area of ​​the library, and mark the average number of books with different book IDs in the initial area of ​​the library as: ID avg , in, Calculate the book richness coefficient. The calculation formula for the book richness coefficient is: FF ts =ID avg ×I zl ; Among them, FF ts is the book richness coefficient; The logic for obtaining the space coefficient is as follows: obtain the architectural plan and bookshelf layout of the library, calculate the area of ​​the area enclosed by each bookshelf according to the layout of the bookshelf, obtain the area of ​​each initial area of ​​the library, and mark the area of ​​each initial area of ​​the library as: S q , where q = 1, 2, 3, ..., Q, Q is a positive integer, and q is the number of the area initially divided by the library; Obtain the average area of ​​the regions initially divided by the library, and mark the average area of ​​the regions initially divided by the library as: S avg ,in, Calculate the space coefficient. The calculation formula of the space coefficient is: Among them, KJ ts is the space coefficient, S ～ is the area of ​​the initial region; The logic for obtaining the circulation coefficient is as follows: within the monitoring interval, the number of people entering the initial area is obtained, and the length of time each person stays in the initial area is obtained, and the length of time each person stays in the initial area is marked as: SJ n , where n = 1, 2, 3, ..., N, N is a positive integer, and n is the number of each person entering the initial area; Set a time length threshold, compare the length of time each person stays in the initial area with the time length threshold, obtain the length of time each person who stays in the initial area longer than the time length threshold, and re-mark the length of time each person who stays in the initial area longer than the time length threshold as: SJ m , where m = 1, 2, 3, ..., M, M is a positive integer, and m is the number of the length of time that each person who enters the initial area stays for a period greater than the time length threshold; Calculate the circulation coefficient. The calculation formula of the circulation coefficient is: Among them, LT ts is the circulation coefficient.

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