An intelligent management system and method for a book lending and reading machine

Abstract

The present invention relates to the technical field of intelligent management of book data, and specifically to an intelligent management system and method for a book lending integrated machine, comprising building a book management cloud platform, analyzing readers' borrowing tendency for books of different book types in a library, and obtaining the library's marked borrowing tendency data; screening historical book return records, and obtaining target historical book return records; analyzing readers' book demand levels for books of different book types in the library, and obtaining the library's marked book demand data; acquiring the library's collection data stored in the book management cloud platform in the current cycle, analyzing the influence of readers' borrowing behavior on the books in the library's collection in the current cycle, and obtaining the target book type; based on the target book type, issuing a prompt to library staff in the current cycle, and performing intelligent management on the book lending integrated machine in the library in the current cycle.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent management of book data, and in particular to an intelligent management system and method for an all-in-one book lending machine. Background Art

[0002] The all-in-one book lending machine is an integrated automatic device that integrates the functions of self-service book borrowing, self-service return, self-service inquiry and self-service renewal. Users can borrow books by themselves through the all-in-one book lending machine without human intervention, which greatly saves manpower time and labor costs. Therefore, the all-in-one book lending machine has been widely used in many public places such as libraries and schools.

[0003] At present, the library is one of the main places where the book lending machine is used. Through the book lending machine in the library, a variety of information such as library collection information, book reservation information, user borrowing history and book borrowing information in the library can be obtained. However, in real life, this information is rarely used. As a result, due to the lack of intelligent management measures for the book lending machine, it is impossible to track the library borrowing data in the library. This will cause the library to be unable to understand the user's borrowing preferences, and it is difficult to purchase new books according to the user's needs. It may also lead to a large waste of resources in the library, causing the library to purchase a large number of books that users are not interested in, thereby greatly reducing the circulation rate of books and the reader borrowing rate. Summary of the invention

[0004] The purpose of the present invention is to provide an intelligent management system and method for a book lending machine to solve the problems existing in the above-mentioned background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: an intelligent management method for a book lending machine, the method comprising:

[0006] Step S100: constructing a book management cloud platform, obtaining readers' historical book borrowing records from the book borrowing machine, obtaining marked historical book borrowing data from the historical book borrowing records, analyzing readers' borrowing tendencies for books of different book types in the library, and obtaining the library's marked borrowing tendency data;

[0007] Step S200: obtaining the historical book return records of the readers recorded in the book lending machine, obtaining the marked historical book data from the historical book return records, and filtering the historical book return records according to the marked borrowing tendency data to obtain the target historical book return records;

[0008] Step S300: Obtain the target historical book return record of the library, obtain the marked book return data from the target historical book return record, and analyze the degree of readers' book demand for books of different book types in the library in combination with the historical book borrowing record to obtain the marked book demand data of the library;

[0009] Step S400: Obtain the library collection data of the library stored in the book management cloud platform in the current cycle, and combine it with the marked book demand data to analyze the impact of readers' borrowing behavior in the current cycle on the books in the library collection, obtain the target book type, and based on the target book type, issue a prompt to the library staff in the current cycle, and perform intelligent management of the book borrowing and reading machines in the library in the current cycle.

[0010] Furthermore, step S100 includes:

[0011] Step S101: constructing a book management cloud platform. When a reader uses a book lending machine in a library to borrow books, the book lending machine records the reader's book borrowing behavior and obtains the reader's historical book borrowing record recorded in the book lending machine.

[0012] Step S102: obtaining each historical book borrowing record recorded by the book lending machine, and extracting marked historical book borrowing data from the historical book borrowing records, wherein the marked historical book borrowing data includes the borrowing time point of the book borrowed by the reader recorded by the book lending machine and the book type corresponding to the book borrowed by the reader;

[0013] Step S103: Analyze readers' borrowing tendency for books of various types in the library, wherein the specific analysis process for the borrowing tendency of books of type a is to obtain historical book borrowing records of books of type a borrowed by readers in each historical period, and calculate the characteristic book borrowing ratio of type a in each historical period, wherein the characteristic book borrowing ratio of type a in the bth historical period is calculated.

[0014]

[0015] in, Indicates the total number of historical book borrowing records of the a-th book type that readers borrowed in the b-th historical period; R b is the total number of historical book borrowing records in the bth historical period;

[0016] Step S104: obtaining an average value of the borrowing ratio of characteristic books of the a-th book type in each historical period, and when the average value is greater than a preset average value threshold, determining that the reader has a borrowing tendency for books of the a-th book type in the library, and recording the a-th book type as a borrowing tendency book type;

[0017] Step S105: obtaining several types of books with borrowing tendency of readers in the library, and aggregating the several types of books with borrowing tendency to obtain the marked borrowing tendency data of the library;

[0018] The above steps obtain the book borrowing behavior of readers by obtaining the book lending machine, obtain the historical book borrowing records of readers recorded in the book lending machine, thereby obtaining the borrowing situation of books in the library, and by calculating the characteristic book borrowing ratio value, analyzing the types of books that readers are more inclined to borrow in the library. The larger the proportion of historical book borrowing records of a certain type of book in the library, the more users are inclined to borrow this type of book. At the same time, the specific analysis method is also clarified, so that the intelligent management of the book lending machine in the library is more scientific and reasonable, thereby greatly increasing readers' interest in reading.

[0019] Further, step S200 includes:

[0020] Step S201: When a reader returns a book using a book lending machine in a library, the book lending machine records the reader's book returning behavior and obtains the reader's historical book returning record recorded in the book lending machine;

[0021] Step S202: obtaining each historical book return record in each historical period, and obtaining marked historical book data from the historical book return record, wherein the marked historical book data is the book type of the book returned by the reader through the book lending machine in the historical book return record;

[0022] Step S203: Obtain the marked borrowing tendency data of the library, extract the borrowing tendency book types in the library from the marked borrowing tendency data, and when the type of books returned by readers through the book borrowing integrated machine in a certain historical book return record is the same as the type of books of a certain borrowing tendency book type in the marked borrowing tendency data, record the certain historical book return record as the target historical book return record.

[0023] Furthermore, step S300 includes:

[0024] Step S301: Acquire each target historical book return record of the library, and extract the marked book return data from the target historical book return record, wherein the marked book return data includes the international standard book number of the book returned by the reader in the target historical book return record;

[0025] Step S302: obtaining the return time point of the book returned by the reader through the book lending machine in the target historical book return record, obtaining each historical book borrowing record in the library, obtaining the international standard book number of the borrowed book in each historical book borrowing record, obtaining the identity of the reader in the library, and when a target historical book return record and another historical book borrowing record of the reader under the same identity have the same international standard book number, the target historical book return record and the other historical book borrowing record are collected to obtain a historical borrowing and returning record set corresponding to the book returned by the reader in the target historical book return record, and based on the borrowing time point of the historical book borrowing record in the historical borrowing and returning record set, obtaining the historical period to which the historical borrowing and returning record set belongs:

[0026] Step S303: Obtain each historical borrowing and returning record set of each book in the library, and calculate the characteristic borrowing duration of each historical borrowing and returning record set of each book, where the characteristic borrowing duration T of the dth historical borrowing and returning record set of the cth book is c,d =F c,d -U c,d , F c,d is the return time point of the target historical book return record in the dth historical borrowing and returning record set of the cth book, U c,d The borrowing time point of the historical book borrowing record in the dth historical borrowing and returning record set of the cth book;

[0027] Step S304: obtaining a number of books of various book types in the library, and collecting historical borrowing and returning record sets of books of different book types according to the book types of the books, obtaining historical borrowing and returning record sets of different book types, and sorting the historical borrowing and returning record sets of different book types, wherein the sorting process of the historical borrowing and returning record set of the g-th book type is to obtain the borrowing time points of the historical book borrowing records in the historical borrowing and returning record set, and sort the historical borrowing and returning record set of the g-th book type in chronological order according to the borrowing time points;

[0028] Step S305: Analyze the degree of readers' demand for books of different book types in the library. The specific process of analyzing the degree of readers' demand for books of the vth book type in the library is to calculate the characteristic book borrowing demand value of the vth book type in each historical period, wherein the characteristic book borrowing demand value E of the vth book type in the qth historical period is v,q :

[0029]

[0030] in, is the characteristic borrowing duration of the i-th historical borrowing and returning record set of the v-th book type in the q-th historical period; j is the total number of historical borrowing and returning record sets of the v-th book type in the q-th historical period;

[0031] Step S306: Calculate the borrowing demand value H of the marked book of the vth book type v :

[0032]

[0033] Where y is the total number of historical cycles recorded by the library management cloud platform; E v is the characteristic book borrowing demand value of the vth book type in the xth historical period;

[0034] When the borrowing demand value of the marked book of the vth book type is greater than the preset marked borrowing influence threshold, it is determined that the reader has a demand for the book of the vth book type in the library, and the vth book type is recorded as the marked book type;

[0035] Step S307: Acquire and aggregate various marked book types in the library to obtain the marked book demand data of the library.

[0036] Furthermore, step S400 includes:

[0037] Step S401: obtaining the library collection data of the library stored in the library management cloud platform in the current period, where the library collection data is the total number of books of various types in the library collection in the current period;

[0038] Step S402: Obtain the library's marked book demand data in the current cycle, obtain the marked book type from it, obtain the total number M of historical book borrowing records of a certain marked book type in the adjacent historical cycles of the current cycle, and calculate the characteristic borrowing book ratio value of a certain marked book type in the current cycle β is represented by the total number of books of a certain marked book type in the library collection in the current period. When the characteristic borrowed book ratio of a certain marked book type in the current period is greater than the preset characteristic borrowed book ratio threshold, the certain marked book type is marked as the target book type;

[0039] Step S403: Acquire each target book type of the library in the current cycle, and issue a prompt to the library staff in the current cycle, prompting the library staff to increase the total number of books in the collection of each target book type in the current cycle, and perform intelligent management of the book lending machines in the library in the current cycle.

[0040] In order to better implement the above method, an intelligent management system for a book lending machine is also proposed. The intelligent management system for a book lending machine includes a module for marking borrowing tendency data, a module for target historical book return record, a module for marking book demand data, and an intelligent management module.

[0041] The marked borrowing tendency data module is used to analyze readers' borrowing tendency for books of different book types in the library and obtain the marked borrowing tendency data of the library;

[0042] The target historical book return record module is used to filter the historical book return records to obtain the target historical book return records;

[0043] The marked book demand data module is used to analyze the degree of readers' demand for books of different book types in the library and obtain the marked book demand data of the library;

[0044] The intelligent management module is used to issue reminders to library staff within the current cycle based on the target book type, and to perform intelligent management of the book lending machines in the library within the current cycle.

[0045] Furthermore, the marked borrowing tendency data module includes a characteristic book borrowing ratio value unit and a borrowing tendency data unit;

[0046] The characteristic book borrowing ratio value unit is used to analyze readers' borrowing tendency for books of various types in the library and calculate the characteristic book borrowing ratio values ​​of various types in each historical period;

[0047] The borrowing tendency data unit is used to obtain several types of borrowing tendency books with borrowing tendency of readers in the library, and to aggregate several types of borrowing tendency books to obtain the marked borrowing tendency data of the library.

[0048] Further, the target history book return record module includes a target history book return record unit;

[0049] The target historical book return record unit is used to obtain the reader's historical book return record recorded in the book lending machine, obtain the marked historical book data from the historical book return record, and screen the historical book return record according to the marked borrowing tendency data to obtain the target historical book return record.

[0050] Further, the book demand data marking module includes a book demand analysis unit and a book demand data marking unit;

[0051] The book demand analysis unit is used to analyze the degree of readers' book demand for books of different book types in the library;

[0052] The marked book demand data unit is used to obtain and aggregate various marked book types in the library to obtain the marked book demand data of the library.

[0053] Further, the intelligent management module includes an intelligent management unit;

[0054] The intelligent management unit is used to obtain the library collection data of the library stored in the book management cloud platform in the current period, obtain the target book type in the current period, and issue prompts to the library staff in the current period to prompt the library staff to increase the total number of books in the collection of each target book type in the current period, and perform intelligent management of the book lending machine in the library in the current period.

[0055] Compared with the prior art, the beneficial effects achieved by the present invention are: the present invention realizes intelligent management of relevant information of the book lending machine, obtains historical book borrowing records and historical book return records in the library according to the book lending machine, thereby analyzing the types of books that readers in the library prefer and are more inclined to borrow, and subsequently analyzes whether books of various types in the library's collection need to be increased according to the readers' book return behavior and the library's book collection situation, which can not only provide a reference for book procurement and collection management, but also provide big data support and big data analysis for library management, which is convenient for subsequent planning and decision-making, so as to be targeted and thus improve the book circulation rate and reader borrowing rate. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] The accompanying drawings are used to provide a further understanding of the present invention and constitute part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0057] Figure 1 It is a method flow chart of an intelligent management system and method of a book lending integrated machine of the present invention;

[0058] Figure 2 The present invention is a module schematic diagram of an intelligent management system and method for a book lending and reading integrated machine. DETAILED DESCRIPTION

[0059] 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.

[0060] See also Figure 1-Figure 2 The present invention provides a technical solution: an intelligent management method for a book lending machine, the method comprising:

[0061] Step S100: constructing a book management cloud platform, obtaining readers' historical book borrowing records from the book borrowing machine, obtaining marked historical book borrowing data from the historical book borrowing records, analyzing readers' borrowing tendencies for books of different book types in the library, and obtaining the library's marked borrowing tendency data;

[0062] Wherein, step S100 includes:

[0063] Step S101: constructing a book management cloud platform. When a reader uses a book lending machine in a library to borrow books, the book lending machine records the reader's book borrowing behavior and obtains the reader's historical book borrowing record recorded in the book lending machine.

[0064] Step S102: obtaining each historical book borrowing record recorded by the book lending machine, and extracting marked historical book borrowing data from the historical book borrowing records, wherein the marked historical book borrowing data includes the borrowing time point of the book borrowed by the reader recorded by the book lending machine and the book type corresponding to the book borrowed by the reader;

[0065] Step S103: Analyze readers' borrowing tendency for books of various types in the library, wherein the specific analysis process for the borrowing tendency of books of type a is to obtain historical book borrowing records of books of type a borrowed by readers in each historical period, and calculate the characteristic book borrowing ratio of type a in each historical period, wherein the characteristic book borrowing ratio of type a in the bth historical period is calculated.

[0066]

[0067] in, Indicates the total number of historical book borrowing records of the a-th book type that readers borrowed in the b-th historical period; R b is the total number of historical book borrowing records in the bth historical period;

[0068] For example, the various types of books include literature, art, history, geography, general natural sciences, mathematical sciences and chemistry, astronomy, earth sciences, biological sciences, medicine, health, agricultural sciences, industrial technology, transportation, aerospace, environmental sciences, etc.;

[0069] For example, the book type of the books borrowed by readers in the first historical period is the total number of historical book borrowing records of the second book type. is 300; the total number of historical book borrowing records in the first historical period R1 is 1000; the borrowing ratio of characteristic books of the a-th book type in the b-th historical period is

[0070] Step S104: obtaining an average value of the borrowing ratio of characteristic books of the a-th book type in each historical period, and when the average value is greater than a preset average value threshold, determining that the reader has a borrowing tendency for books of the a-th book type in the library, and recording the a-th book type as a borrowing tendency book type;

[0071] Step S105: obtaining several types of books with borrowing tendency of readers in the library, and aggregating the several types of books with borrowing tendency to obtain the marked borrowing tendency data of the library;

[0072] Step S200: obtaining the historical book return records of the readers recorded in the book lending machine, obtaining the marked historical book data from the historical book return records, and filtering the historical book return records according to the marked borrowing tendency data to obtain the target historical book return records;

[0073] Wherein, step S200 includes:

[0074] Step S201: When a reader returns a book using a book lending machine in a library, the book lending machine records the reader's book returning behavior and obtains the reader's historical book returning record recorded in the book lending machine;

[0075] Step S202: obtaining each historical book return record in each historical period, and obtaining marked historical book data from the historical book return record, wherein the marked historical book data is the book type of the book returned by the reader through the book lending machine in the historical book return record;

[0076] Step S203: Obtain the marked borrowing tendency data of the library, extract the borrowing tendency book types in the library from the marked borrowing tendency data, and when the type of books returned by readers through the book borrowing integrated machine in a certain historical book return record is the same as the type of books of a certain borrowing tendency book type in the marked borrowing tendency data, record the certain historical book return record as the target historical book return record;

[0077] Step S300: Obtain the target historical book return record of the library, obtain the marked book return data from the target historical book return record, and analyze the degree of readers' book demand for books of different book types in the library in combination with the historical book borrowing record to obtain the marked book demand data of the library;

[0078] Wherein, step S300 includes:

[0079] Step S301: Acquire each target historical book return record of the library, and extract the marked book return data from the target historical book return record, wherein the marked book return data includes the international standard book number of the book returned by the reader in the target historical book return record;

[0080] Step S302: obtaining the return time point of the book returned by the reader through the book lending machine in the target historical book return record, obtaining each historical book borrowing record in the library, obtaining the international standard book number of the borrowed book in each historical book borrowing record, obtaining the identity of the reader in the library, and when a target historical book return record and another historical book borrowing record of the reader under the same identity have the same international standard book number, the target historical book return record and the other historical book borrowing record are collected to obtain a historical borrowing and returning record set corresponding to the book returned by the reader in the target historical book return record, and based on the borrowing time point of the historical book borrowing record in the historical borrowing and returning record set, obtaining the historical period to which the historical borrowing and returning record set belongs:

[0081] For example, the identity identifier includes a library card number or an ID number;

[0082] Step S303: Obtain each historical borrowing and returning record set of each book in the library, and calculate the characteristic borrowing duration of each historical borrowing and returning record set of each book, where the characteristic borrowing duration T of the dth historical borrowing and returning record set of the cth book is c,d =F c,d -U c,d , F c,d is the return time point of the target historical book return record in the dth historical borrowing and returning record set of the cth book, U c,dThe borrowing time point of the historical book borrowing record in the dth historical borrowing and returning record set of the cth book;

[0083] Step S304: obtaining a number of books of various book types in the library, and collecting historical borrowing and returning record sets of books of different book types according to the book types of the books, obtaining historical borrowing and returning record sets of different book types, and sorting the historical borrowing and returning record sets of different book types, wherein the sorting process of the historical borrowing and returning record set of the g-th book type is to obtain the borrowing time points of the historical book borrowing records in the historical borrowing and returning record set, and sort the historical borrowing and returning record set of the g-th book type in chronological order according to the borrowing time points;

[0084] Step S305: Analyze the degree of readers' demand for books of different book types in the library. The specific process of analyzing the degree of readers' demand for books of the vth book type in the library is to calculate the characteristic book borrowing demand value of the vth book type in each historical period, wherein the characteristic book borrowing demand value E of the vth book type in the qth historical period is v,q :

[0085]

[0086] in, is the characteristic borrowing duration of the i-th historical borrowing and returning record set of the v-th book type in the q-th historical period; j is the total number of historical borrowing and returning record sets of the v-th book type in the q-th historical period;

[0087] Step S306: Calculate the borrowing demand value H of the marked book of the vth book type v :

[0088]

[0089] Where y is the total number of historical cycles recorded by the library management cloud platform; E v is the characteristic book borrowing demand value of the vth book type in the xth historical period;

[0090] When the borrowing demand value of the marked book of the vth book type is greater than the preset marked borrowing influence threshold, it is determined that the reader has a demand for the book of the vth book type in the library, and the vth book type is recorded as the marked book type;

[0091] Step S307: Obtain and aggregate various marked book types in the library to obtain the marked book demand data of the library;

[0092] Step S400: obtaining the library collection data of the library stored in the book management cloud platform in the current cycle, and combining with the marked book demand data, analyzing the influence of the readers' borrowing behavior in the current cycle on the books in the library collection, obtaining the target book type, and based on the target book type, issuing a prompt to the library staff in the current cycle, and performing intelligent management of the book lending and reading integrated machines in the library in the current cycle;

[0093] Wherein, step S400 includes:

[0094] Step S401: obtaining the library collection data of the library stored in the library management cloud platform in the current period, where the library collection data is the total number of books of various types in the library collection in the current period;

[0095] Step S402: Obtain the library's marked book demand data in the current cycle, obtain the marked book type from it, obtain the total number M of historical book borrowing records of a certain marked book type in the adjacent historical cycles of the current cycle, and calculate the characteristic borrowing book ratio value of a certain marked book type in the current cycle β is represented by the total number of books of a certain marked book type in the library collection in the current period. When the characteristic borrowed book ratio of a certain marked book type in the current period is greater than the preset characteristic borrowed book ratio threshold, the certain marked book type is marked as the target book type;

[0096] Step S403: Acquire each target book type of the library in the current cycle, and issue a prompt to the library staff in the current cycle, prompting the library staff to increase the total number of books in the collection of each target book type in the current cycle, and perform intelligent management of the book lending and reading machines in the library in the current cycle;

[0097] In order to better implement the above method, an intelligent management system for a book lending machine is also proposed. The intelligent management system for a book lending machine includes a module for marking borrowing tendency data, a module for target historical book return record, a module for marking book demand data, and an intelligent management module.

[0098] The marked borrowing tendency data module is used to analyze readers' borrowing tendency for books of different book types in the library and obtain the marked borrowing tendency data of the library;

[0099] The target historical book return record module is used to filter the historical book return records to obtain the target historical book return records;

[0100] The marked book demand data module is used to analyze the degree of readers' demand for books of different book types in the library and obtain the marked book demand data of the library;

[0101] The intelligent management module is used to issue reminders to library staff in the current cycle based on the target book type, and to perform intelligent management of the book lending and reading machines in the library in the current cycle;

[0102] Among them, the marked borrowing tendency data module includes a characteristic book borrowing ratio value unit and a borrowing tendency data unit;

[0103] The characteristic book borrowing ratio value unit is used to analyze readers' borrowing tendency for books of various types in the library and calculate the characteristic book borrowing ratio values ​​of various types in each historical period;

[0104] The borrowing tendency data unit is used to obtain several types of borrowing tendency books with borrowing tendency of readers in the library, and to collect several types of borrowing tendency books to obtain the marked borrowing tendency data of the library;

[0105] Wherein, the target history book return record module includes a target history book return record unit;

[0106] The target historical book return record unit is used to obtain the historical book return record of the reader recorded in the book lending machine, obtain the marked historical book data from the historical book return record, and screen the historical book return record according to the marked borrowing tendency data to obtain the target historical book return record;

[0107] Among them, the marked book demand data module includes a book demand analysis unit and a marked book demand data unit;

[0108] The book demand analysis unit is used to analyze the degree of readers' book demand for books of different book types in the library;

[0109] The marked book demand data unit is used to obtain and aggregate various marked book types in the library to obtain the marked book demand data of the library;

[0110] Wherein, the intelligent management module includes an intelligent management unit;

[0111] The intelligent management unit is used to obtain the library collection data of the library stored in the book management cloud platform in the current period, obtain the target book type in the current period, and issue prompts to the library staff in the current period to prompt the library staff to increase the total number of books in the collection of each target book type in the current period, and perform intelligent management of the book lending machine in the library in the current period.

[0112] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0113] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An intelligent management method for a book lending machine, characterized in that: The method comprises: Step S100: constructing a book management cloud platform, obtaining readers' historical book borrowing records from the book borrowing machine, obtaining marked historical book borrowing data from the historical book borrowing records, analyzing readers' borrowing tendencies for books of different book types in the library, and obtaining marked borrowing tendency data of the library; The step S100 includes: Step S101: constructing a book management cloud platform. When a reader uses a book lending machine in a library to borrow books, the book lending machine records the reader's book borrowing behavior and obtains the reader's historical book borrowing record recorded in the book lending machine. Step S102: obtaining each historical book borrowing record recorded by the book lending machine, and extracting marked historical book borrowing data from the historical book borrowing records, wherein the marked historical book borrowing data includes the borrowing time point of the book borrowed by the reader recorded by the book lending machine and the book type corresponding to the book borrowed by the reader; Step S103: Analyze readers' borrowing tendency for books of various types in the library, wherein the specific analysis process for the borrowing tendency of books of type a is to obtain historical book borrowing records of books of type a borrowed by readers in each historical period, and calculate the characteristic book borrowing ratio of type a in each historical period, wherein the characteristic book borrowing ratio of type a in the bth historical period is calculated. in, The book type of the books borrowed by readers in the b-th historical period is the total number of historical book borrowing records of the a-th book type; R d is the total number of historical book borrowing records in the bth historical period; Step S104: obtaining an average value of the borrowing ratio of characteristic books of the a-th book type in each historical period, and when the average value is greater than a preset average value threshold, determining that readers have a borrowing tendency for books of the a-th book type in the library, and recording the a-th book type as a borrowing tendency book type; Step S105: obtaining several types of books with borrowing tendency of readers in the library, and aggregating the several types of books with borrowing tendency to obtain marked borrowing tendency data of the library; Step S200: obtaining the historical book return records of the readers recorded in the book lending machine, obtaining the marked historical book data from the historical book return records, and filtering the historical book return records according to the marked borrowing tendency data to obtain the target historical book return records; Step S300: obtaining the target historical book return record of the library, obtaining the marked book return data from the target historical book return record, and combining with the historical book borrowing record, analyzing the degree of readers' demand for books of different book types in the library, and obtaining the marked book demand data of the library; Step S400: Obtain the library collection data of the library stored in the book management cloud platform in the current cycle, and combine it with the marked book demand data to analyze the impact of readers' borrowing behavior in the current cycle on the books in the library collection, obtain the target book type, and based on the target book type, issue a prompt to the library staff in the current cycle, and intelligently manage the book lending machines in the library in the current cycle.

2. The intelligent management method of a book lending machine according to claim 1 is characterized in that: The step S200 includes: Step S201: When a reader returns a book using a book lending machine in a library, the book lending machine records the reader's book returning behavior and obtains the reader's historical book returning record recorded in the book lending machine; Step S202: obtaining each historical book return record in each historical period, and obtaining marked historical book data from the historical book return record, wherein the marked historical book data is the book type of the book returned by the reader through the book lending machine in the historical book return record; Step S203: Acquire the marked borrowing tendency data of the library, extract the borrowing tendency book types in the library from the marked borrowing tendency data, and when the type of books returned by a reader through a book borrowing integrated machine in a certain historical book return record is the same as the type of a certain borrowing tendency book type in the marked borrowing tendency data, record the certain historical book return record as the target historical book return record.

3. The intelligent management method of a book lending machine according to claim 2 is characterized in that: The step S300 includes: Step S301: Acquire each target historical book return record of the library, and extract marked book return data from the target historical book return record, wherein the marked book return data includes the international standard book number of the book returned by the reader in the target historical book return record; Step S302: obtaining the return time point of the book returned by the reader through the book lending integrated machine in the target historical book return record, obtaining each historical book borrowing record in the library, obtaining the international standard book number of the borrowed book in each historical book borrowing record, obtaining the identity of the reader in the library, and when a target historical book return record and another historical book borrowing record of the reader under the same identity have the same international standard book number, the target historical book return record and the other historical book borrowing record are collected to obtain a historical borrowing and returning record set corresponding to the book returned by the reader in the target historical book return record, and based on the borrowing time point of the historical book borrowing record in the historical borrowing and returning record set, obtaining the historical period to which the historical borrowing and returning record set belongs: Step S303: Obtain each historical borrowing and returning record set of each book in the library, and calculate the characteristic borrowing duration of each historical borrowing and returning record set of each book, where the characteristic borrowing duration T of the dth historical borrowing and returning record set of the cth book is c,d =F c,d -U c,d , F c,d is the return time point of the target historical book return record in the d-th historical borrowing and returning record set of the c-th book, U c,d The borrowing time point of the historical book borrowing record in the d-th historical borrowing and returning record set of the c-th book; Step S304: obtaining a number of books of various book types in the library, and collecting historical borrowing and returning record sets of books of different book types according to the book types of the books, to obtain historical borrowing and returning record sets of different book types, and sorting the historical borrowing and returning record sets of different book types, wherein the sorting process of the historical borrowing and returning record set of the g-th book type is to obtain the borrowing time points of the historical book borrowing records in the historical borrowing and returning record set, and sort the historical borrowing and returning record set of the g-th book type in chronological order according to the borrowing time points; Step S305: Analyze the degree of readers' demand for books of different book types in the library, wherein the specific process of analyzing the degree of readers' demand for books of the vth book type in the library is to calculate the characteristic book borrowing demand value of the vth book type in each historical period, wherein the characteristic book borrowing demand value E of the vth book type in the qth historical period is v,q : in, is the characteristic borrowing duration of the i-th historical borrowing and returning record set of the v-th book type in the q-th historical period; j is the total number of historical borrowing and returning record sets of the v-th book type in the q-th historical period; Step S306: Calculate the borrowing demand value H of the marked book of the vth book type v : Wherein, y is the total number of historical periods recorded by the library management cloud platform; E v is the characteristic book borrowing demand value of the v-th book type in the x-th historical period; When the marked book borrowing demand value of the v-th book type is greater than a preset marked borrowing influence threshold, it is determined that the reader has a demand for the books of the v-th book type in the library, and the v-th book type is recorded as the marked book type; Step S307: Acquire and aggregate various marked book types in the library to obtain the marked book demand data of the library.

4. The intelligent management method of a book lending and reading machine according to claim 3 is characterized in that: The step S400 includes: Step S401: obtaining the library collection data of the library stored in the book management cloud platform in the current period, wherein the library collection data is the total number of books of various types in the collection of the library in the current period; Step S402: Obtain the marked book demand data of the library in the current cycle, obtain the marked book type from it, obtain the total number M of historical book borrowing records of a certain marked book type in the adjacent historical cycles of the current cycle, and calculate the characteristic borrowing book ratio value of the certain marked book type in the current cycle β represents the total number of books of the certain marked book type in the collection of the library in the current period. When the characteristic borrowed books ratio of the certain marked book type in the current period is greater than the preset characteristic borrowed book ratio threshold, the certain marked book type is marked as the target book type; Step S403: Acquire each target book type of the library in the current cycle, and issue a prompt to the library staff in the current cycle, prompting the library staff to increase the total number of books in the collection of each target book type in the current cycle, and to perform intelligent management of the book lending machines in the library in the current cycle.

5. An intelligent management system for book lending and reading machines using an intelligent management method for book lending and reading machines as described in any one of claims 1 to 4, characterized in that: The intelligent management system of the integrated book lending machine includes a module for marking borrowing tendency data, a module for recording target historical book return, a module for marking book demand data, and an intelligent management module; The marked borrowing tendency data module is used to analyze readers' borrowing tendency for books of different book types in the library to obtain the marked borrowing tendency data of the library; The target historical book return record module is used to screen the historical book return records to obtain the target historical book return records; The marked book demand data module is used to analyze the degree of readers' demand for books of different book types in the library to obtain the marked book demand data of the library; The intelligent management module is used to send reminders to library staff within the current cycle based on the target book type, and to perform intelligent management on the book lending and reading machines in the library within the current cycle.

6. The intelligent management system for book lending and reading machines according to claim 5 is characterized in that: The marked borrowing tendency data module includes a characteristic book borrowing ratio value unit and a borrowing tendency data unit; The characteristic book borrowing ratio unit is used to analyze readers' borrowing tendency for books of various book types in the library and calculate the characteristic book borrowing ratio of various book types in each historical period; The borrowing tendency data unit is used to obtain several types of borrowing tendency books with borrowing tendency of readers in the library, and to collect the several types of borrowing tendency books to obtain the marked borrowing tendency data of the library.

7. The intelligent management system for book lending and reading machines according to claim 5 is characterized in that: The target history book return record module includes a target history book return record unit; The target historical book return record unit is used to obtain the reader's historical book return record recorded in the book lending machine, obtain the marked historical book data from the historical book return record, and filter the historical book return record according to the marked borrowing tendency data to obtain the target historical book return record.

8. The intelligent management system for book lending and reading machines according to claim 5 is characterized in that: The marked book demand data module includes a book demand analysis unit and a marked book demand data unit; The book demand analysis unit is used to analyze the degree of readers' demand for books of different book types in the library; The marked book demand data unit is used to obtain and aggregate various marked book types in the library to obtain the marked book demand data of the library.

9. The intelligent management system for book lending and reading machines according to claim 5 is characterized in that: The intelligent management module includes an intelligent management unit; The intelligent management unit is used to obtain the library collection data of the library stored in the book management cloud platform in the current period, obtain the target book type in the current period, and issue prompts to library staff in the current period to prompt the library staff to increase the total number of books in the collection of each target book type in the current period, and perform intelligent management of the book lending and reading machines in the library in the current period.

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