A book archive updating method based on reader demand

Abstract

The application discloses a book archive updating method based on reader demand, comprising the following steps: acquiring a book classification number based on a book title and a corresponding book archive; inputting the book title into a cloud computing system, and generating a preset classification number based on the book title by all cloud computing sub-nodes; comparing the preset classification number and the book classification number to obtain a high-performance node; obtaining the high-performance node for generating the preset classification number based on different book titles, and constructing a title analysis node group; acquiring a reader search book title record in a library, and obtaining a supplement priority of an uncatalogued book in the library; acquiring a possible classification number based on the supplement priority of the uncatalogued book; supplementing a book in the library based on the possible classification number, and establishing a book archive of the supplemented book. The problems of inaccuracy of reader reading demand and insufficient rationality of supplemented books are solved. The reasonable supplement of books is achieved, and the effect of constructing a book archive based on the supplemented outstanding rationality is achieved.

Description

Technical Field

[0001] This application relates to the field of cloud computing technology, specifically, a method for updating book archives based on reader needs. Background Technology

[0002] Library catalogs contain a variety of information, including classification numbers, search history, and categories, serving as essential identifiers for books and requiring effective updates. However, in current library operations, some readers have raised new demands regarding the catalog, requiring book purchases to be based on reader needs and subsequently updated effectively. The main problem is that while libraries do purchase books based on reader search results, this is often done solely based on titles. Some books with similar titles may have significantly different content, leading readers to find that similar titles don't meet their needs, resulting in lower service quality. Furthermore, this mismatch between catalog updates and book replenishment strategies contributes to the low rationality of catalog updates.

[0003] Therefore, how to determine the books that the library needs to replenish and then carry out the work of updating the book archives is a technical problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0004] The purpose of this application is to provide a book archive updating method based on reader needs, solving the problem in existing technologies where the identification of readers' book needs is unclear, leading to an inability to reasonably determine readers' book requirements. Specifically:

[0005] A method for updating book archives based on reader needs, the method comprising:

[0006] Obtain the book classification number based on the book title and corresponding book information;

[0007] The book title is input into the cloud computing system, and all cloud computing sub-nodes generate the book's classification number based on the book title to obtain the preset classification number;

[0008] Compare the preset classification number and the book classification number, sort the preset classification number, and obtain high-performance nodes;

[0009] The high-performance nodes are classified to obtain high-performance nodes that generate preset classification numbers based on different book titles, and a title parsing node group is constructed.

[0010] Obtain the library's records of book titles searched by readers, and determine the priority for adding unlisted books to the library's database;

[0011] Based on the priority of supplementing the unlisted books, obtain the probability classification number;

[0012] Based on the aforementioned probability classification numbers, supplement the library's books and establish book archives for the supplemented books.

[0013] Optionally, obtaining the book classification number based on the book title and corresponding book file includes:

[0014] Obtain library book information, including book titles and corresponding book files;

[0015] Based on the corresponding book files, obtain the book classification number;

[0016] Also includes:

[0017] Establish the correspondence between the book titles and the book classification numbers.

[0018] Optionally, the step of inputting the book title into the cloud computing system, and having all cloud computing sub-nodes generate a book classification number based on the book title to obtain a preset classification number, includes:

[0019] The book title is sent to the cloud computing system, and all cloud computing sub-nodes of the cloud computing system obtain the book classification number based on the book title.

[0020] Obtain the book classification number output by the cloud computing sub-node to get the output classification number;

[0021] The output classification numbers are identified, and those with the same output classification numbers are included in the same classification number data group;

[0022] Obtain the number of output classification numbers in the classification number data group, and sort the classification number data group based on the number of output classification numbers;

[0023] When the sorting sequence number of the classification number data group is higher than the sorting sequence number of the preset classification number data group, the classification number data group corresponding to the sorting sequence number of the classification number data group is obtained, and the preset classification number is obtained.

[0024] Optionally, comparing the preset classification number and the book classification number, and sorting the preset classification number to obtain high-performance nodes, includes:

[0025] The resolution accuracy of the preset classification number is obtained by comparing the preset classification number with the book classification number.

[0026] Based on the parsing precision of the preset classification number, the parsing precision of the preset classification number is sorted to obtain the classification number precision sorting.

[0027] Based on the classification number precision sorting, obtain a high-precision preset classification number;

[0028] Obtain the cloud computing sub-node corresponding to the high-precision preset classification number to obtain the high-performance node.

[0029] Optionally, the classification of the high-performance nodes to obtain high-performance nodes that generate preset classification numbers based on different book titles, and the construction of a title parsing node group, includes:

[0030] Obtain the keywords of the book titles, and obtain the keyword combination relationships of the book titles to establish keyword data groups;

[0031] Obtain the frequency of keyword occurrence within all the keyword data groups, and establish a correspondence between keywords and high-performance nodes based on the keyword occurrence frequency;

[0032] Based on the correspondence between the keywords and high-performance nodes, the high-performance nodes corresponding to the keywords are constructed into the node data group to obtain the title parsing node group.

[0033] Optionally, obtaining the keyword occurrence frequency within all the keyword data groups and establishing a correspondence between keywords and high-performance nodes based on the keyword occurrence frequency includes:

[0034] Obtain the book title and the corresponding book classification number, and merge the keyword data groups of book titles with the same book classification number to obtain a high-dimensional keyword data group;

[0035] Obtain the keywords from the high-dimensional keyword data group, and obtain the synonyms of the keywords;

[0036] Obtain the frequency of occurrence of keywords and synonyms of keywords in the high-dimensional keyword data group to obtain the keyword frequency.

[0037] Based on the frequency of occurrence of the keywords, keywords with a frequency of occurrence not lower than a preset frequency are obtained to obtain high-frequency keywords;

[0038] Establish the correspondence between the high-frequency keywords and high-performance nodes to obtain the correspondence between keywords and high-performance nodes.

[0039] Optionally, obtaining the reader's search book title records in the library and retrieving books not included in the library's catalog includes:

[0040] Obtain readers' search records within the library and retrieve feedback information about those records;

[0041] Obtain the unlisted books from the feedback information and record their titles;

[0042] Obtain the retrieval frequency of the titles of the unlisted books, and based on the retrieval frequency, obtain the priority for supplementing the unlisted books.

[0043] Optionally, obtaining the probability classification number based on the priority of supplementing the unlisted books and the titles of the unlisted books includes:

[0044] Based on the priority of supplementing the unlisted books, obtain the titles of the books corresponding to the priority of supplementing the unlisted books, and obtain the titles of the books to be supplemented first;

[0045] Obtain the keywords of the priority supplementary book titles, obtain the synonyms of the priority supplementary book titles keywords, and obtain the priority supplementary book keyword data group;

[0046] Input the priority supplementary book keyword data group into the title parsing node group to obtain the parsing classification number;

[0047] Based on the frequency of occurrence of the parsed classification number, a probabilistic classification number is obtained.

[0048] Optionally, obtaining the probability classification number based on the occurrence frequency of the parsed classification number includes:

[0049] Based on the frequency of occurrence of the parsed classification number, obtain the high-frequency parsed classification number;

[0050] Based on the high-frequency parsing classification number, the corresponding high-performance node is obtained, thus obtaining the high-performance parsing node;

[0051] Based on the correspondence between the keywords and high-performance nodes, the preset keywords corresponding to the high-performance parsing nodes are obtained;

[0052] Based on the preset keywords and the keyword combination relationships, candidate book titles are obtained;

[0053] Retrieve the candidate book titles; if the candidate book titles exist, obtain the classification number of the candidate book titles.

[0054] The candidate book titles are selected based on their classification number frequency, which is not lower than a preset classification number frequency. The classification number of the candidate book titles is a probability classification number.

[0055] Optionally, the step of supplementing the library's books based on the probability classification number and establishing a book archive for the supplemented books includes:

[0056] Based on the probability classification number, obtain the corresponding optional book titles;

[0057] Based on the corresponding candidate book titles, the library's books are supplemented;

[0058] Establish book archives for the supplemented books and update the book archives for the supplemented books during library operation.

[0059] The beneficial effects of this application include:

[0060] 1. This application enables the rational analysis of book resources that need to be supplemented. Based on cloud computing technology, this application successfully utilizes book classification numbers to classify and analyze the books currently retrieved by readers. Then, based on the classification results, books are supplemented, and corresponding book archives are established based on the supplemented books. This allows libraries to create and update book archives based on the supplemented book information.

[0061] 2. The method for determining book categories has been achieved. In the technical solution of this application, book resources are not supplemented directly based on the book titles retrieved by the reader. Instead, the possible classification numbers of the retrieved book titles are obtained, and then the book categories are supplemented based on the classification numbers, thereby expanding the scope of supplementary book resources and fully meeting the reader's needs for relevant books.

[0062] 3. Personalized updates of book archives are achieved. In the technical solution of this application, a dedicated book archive is established for the acquired book archives. Then, based on this archive, the book archives of newly added books in the library are continuously updated, thereby ensuring that a dedicated book archive can be established for each book and that the book archives are continuously updated. Attached Figure Description

[0063] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the accompanying drawings used in the embodiments of this application or the prior art will be briefly introduced below. Obviously, the following description is only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. The drawings are used to provide a further understanding of this disclosure and constitute a part of the specification. They are used together with the following detailed description to explain this disclosure, but do not constitute a limitation of this disclosure. In the drawings:

[0064] Figure 1 A flowchart illustrating a book archive updating method based on reader needs, provided for embodiments of this application;

[0065] Figure 2 This application provides a cloud-based book archive display interface. Detailed Implementation

[0066] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application. Furthermore, in the embodiments of this application, "first," "second," etc., are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0067] In updating book archives, libraries have recognized the need for continuous updates to analyze the borrowing frequency of various book resources. For example, archives can be created based on the book's information and then updated accordingly, including the number of borrowings and return dates. Furthermore, for all resources, this method can be used to analyze readers' borrowing needs for certain books, laying a better foundation for supplementing and updating book resources. However, relatively speaking, this method has lower accuracy in analyzing reader needs, and libraries typically do not use it. Currently, the main method for supplementing book resources is to determine the necessary supplementary resources based on readers' search results. The problem is that most readers enter only keywords related to book titles during their searches, not the exact titles. If the library were to purchase all search keywords, it would obviously consume a large amount of resources, leading to excessive operational pressure. On the other hand, selecting only one book can easily result in a situation where, although the book title matches the reader's needs, the content does not match the reader's actual needs, leading to low accuracy in identifying the reader's actual needs and failing to improve service levels. Clearly, for the library to provide good service to readers continuously, it needs to supplement book archives based on readers' actual needs, then establish book archives based on the specific information in the supplementary resources, and continuously update the archives in subsequent work.

[0068] To address the current problems in reader needs analysis in libraries, this application discloses a method for updating book archives based on reader needs, such as... Figure 1 The diagram shown is a flowchart of a book archive updating method based on reader needs, provided in an embodiment of this application. The specific content includes:

[0069] S110. Obtain the book classification number based on the book title and the corresponding book file;

[0070] S120. Input the book title into the cloud computing system, and generate the book's classification number based on the book title by all cloud computing sub-nodes to obtain the preset classification number;

[0071] S130. Compare the preset classification number and the book classification number, sort the preset classification number, and obtain high-performance nodes;

[0072] S140. Classify the high-performance nodes to obtain high-performance nodes that generate preset classification numbers based on different book titles, and construct a title parsing node group;

[0073] S150. Obtain the book title records searched by readers in the library, and obtain the priority of supplementing unlisted books in the library;

[0074] S160. Based on the priority of supplementing the unlisted books, obtain the probability classification number;

[0075] S170. Supplement the library’s books based on the aforementioned probability classification number, and establish and update the book archives of the supplemented books.

[0076] The purpose of the above steps is to determine the book resources that the library needs to supplement based on cloud computing technology, and to supplement the corresponding books based on the results to meet the reading needs of readers. After the book resources are supplemented, the book archives are built and updated to establish effective book archives.

[0077] The following will explain the above steps in detail:

[0078] As described in step S110, the purpose of this step is to acquire the existing book resource archives in the library, thereby obtaining the correspondence between book titles and book classification numbers, and based on this correspondence, laying the foundation for the subsequent implementation of cloud computing technology and the analysis and verification of book classification numbers. Specifically:

[0079] S111. Obtain the library's book information, which includes the book title and the corresponding book file.

[0080] The purpose of this step is to obtain the library's book information and corresponding book archives. The book archives include various information, such as book classification number, number of searches, book overview, and book lending information. Among these, the book title is the most common search information for readers, so it is necessary to establish a correspondence between book titles and book archives.

[0081] For each book title, a corresponding book file has already been created, so you can directly use the book file corresponding to the book title.

[0082] S112. Based on the corresponding book archives, obtain the book classification number.

[0083] The purpose of this step is to identify multiple books with similar content and corresponding book classification numbers. Considering that readers search for books by title, and that books with similar titles may have vastly different content, it is necessary to obtain the correspondence between book titles and book classification numbers, as well as the predictive relationship based on cloud computing. This will allow for the determination of book demand in subsequent analysis.

[0084] For book archives already obtained based on book titles, it is necessary to extract the book classification number from the book archives.

[0085] Subsequently, the book classification number can be directly obtained from the book archives.

[0086] S113 also includes:

[0087] Establish the correspondence between the book titles and the book classification numbers.

[0088] The purpose of this step is, in the application of cloud computing technology, the ultimate goal of this application is to obtain the corresponding classification number based on the book title input by the reader, then supplement the corresponding book resources based on the classification number, and establish the corresponding book archive based on the obtained book resources. Therefore, it is necessary to establish a correspondence between book titles and classification numbers for the training of cloud computing models.

[0089] Among them, based on the correspondence between book titles and book files, and the correspondence between book files and classification numbers, the correspondence between book titles and book classification numbers can be directly obtained.

[0090] As described in step S120, the purpose of this step is to use the cloud computing system to perform a pre-defined analysis of the book classification numbers based on the book titles, given the already obtained correspondence between book titles and classification numbers. Then, it selects the correct child nodes, thereby enabling the analysis of books that need to be added to the library based on the obtained child nodes. Specifically:

[0091] S121. The book title is sent to the cloud computing system, and all cloud computing sub-nodes of the cloud computing system obtain the book classification number based on the book title.

[0092] The purpose of this step is to analyze the obtained book information, thereby establishing corresponding calculation results from the available book titles. Based on the book titles, we can analyze the possible book classification numbers to obtain the corresponding analytical relationships.

[0093] The configured cloud computing system includes cloud computing sub-nodes in the team, each of which uses a different algorithm to ensure that different sub-nodes use different algorithms to obtain book classification numbers.

[0094] After the book title is sent to the cloud computing system, different cloud computing sub-nodes parse the same book title, and then the cloud computing sub-nodes obtain the book classification number calculated for the same book title.

[0095] In this system, after obtaining the book title, the cloud computing system directly distributes the book title to all cloud computing sub-nodes.

[0096] S122. Obtain the book classification number output by the cloud computing sub-node to get the output classification number.

[0097] The purpose of this step is to output all the book classification numbers obtained by the cloud computing system during the processing of the child nodes for one year, and to process the obtained book classification numbers accordingly.

[0098] This involves outputting all book classification numbers, and the resulting output is the classification number.

[0099] S123. Identify the output classification number and include the same output classification number into the same classification number data group.

[0100] The purpose of this step is that, although the obtained output classification numbers are the same, they may be calculated from different child nodes. In order to obtain a more complete group of child nodes and to perform accurate analysis of the classification numbers of book titles based on the group of child nodes, it is necessary to classify the obtained classification numbers themselves.

[0101] In this process, all the obtained classification numbers are analyzed, and those with the same classification numbers are grouped into the same classification number data group to obtain the classification number data group.

[0102] In the process of generating output classification numbers from child nodes, the correspondence between child nodes and corresponding output classification numbers is determined to establish the correspondence between output classification numbers and child nodes, thereby obtaining the correspondence between classification number data groups and multiple child node groups.

[0103] S124. Obtain the number of output classification numbers in the classification number data group, and sort the classification number data group based on the number of output classification numbers.

[0104] The purpose of this step is to determine the correspondence between the data groups and book titles based on the number of classification numbers in each data group, since the number of classification numbers in each data group is different but the classification numbers are the same. Thus, the accurate book classification number can be obtained based on the book title using the cloud computing system.

[0105] Specifically, the number of output category numbers in each category number data group is determined, and the obtained numbers are sorted.

[0106] Specifically, the number of data groups for each classification number and the corresponding relationship between the classification number data groups are obtained, so as to obtain the sorting relationship of the classification number data groups based on the sorting relationship of the numbers.

[0107] S125. When the sorting sequence number of the classification number data group is higher than the sorting sequence number of the preset classification number data group, the classification number data group corresponding to the sorting sequence number of the classification number data group is obtained, and the preset classification number is obtained.

[0108] The purpose of this step is to determine the most reasonable correspondence between the output classification number and the book title among the classification number data groups that have been obtained. Therefore, when the sorting number of the classification number data group is high, the output classification number corresponding to the classification number data group can be determined as the preset classification number, that is: the book classification number that can be obtained based on the book title.

[0109] This involves analyzing the sorting position of the sorted classification number data groups, determining the corresponding classification number data groups based on the sorting position, and setting the classification numbers within these classification number data groups as preset classification numbers.

[0110] Among them, a preset sequence number is set for the sorting sequence number of the obtained data groups. Only when the sorting sequence number of the classification number data group is higher than the preset sequence number can the classification number in the corresponding classification number data group be considered as the preset classification number.

[0111] In some embodiments, the number of classification numbers within different classification number data groups can be analyzed, and a threshold for number interpolation can be set. Classification numbers in classification number data groups with differences below this threshold are then set as preset classification numbers. For example, if the number of classification numbers in the classification number data groups are 10, 9, 7, 3, and 1, and the set difference threshold is 3, then the classification numbers in the classification number data groups with 10, 9, and 7 are determined as preset classification numbers. Furthermore, this process also determines the order of the preset classification numbers; for those values ​​lower than the highest selectable value, they are removed, and the corresponding classification numbers in the corresponding classification number data groups are determined as non-preset classification numbers.

[0112] As described in step S130, the purpose of this step is to obtain the correct book classification number based on the book title from the corresponding sub-nodes of the obtained preset classification number, which is obtained from different cloud computing sub-nodes. Thus, after obtaining the cloud computing sub-nodes, the correct book classification number can be obtained based on the book title during the library's book replenishment process. In other words, after obtaining the sub-nodes, a foundation can be laid for subsequent book replenishment work.

[0113] S131. Compare the preset classification number with the book classification number to obtain the resolution accuracy of the preset classification number.

[0114] The purpose of this step is to identify similar book classification numbers when comparing the obtained preset classification numbers with the book classification numbers. This allows the cloud computing sub-nodes corresponding to the obtained preset classification numbers to be used to determine the book resources that the library needs to supplement.

[0115] The process involves comparing the obtained preset classification number with the book classification number, and if the comparison results meet the requirements, the preset classification number that meets the requirements is determined as the high-precision classification number.

[0116] Specifically, based on the array structure of book classification numbers, the specific content of the classification number is determined, and the parsing accuracy of the preset classification number is determined by comparing all the information corresponding to the classification number.

[0117] Among them, the parsing accuracy level is different due to the position of different array information in the array of preset classification numbers. The earlier the array information is in the array, the lower the parsing accuracy, and the later the array information is in the array, the higher the parsing accuracy. The parsing accuracy is the highest when the preset classification number and the book classification number are the same. For example, the book "Structural Dynamics Theory and Its Application in Earthquake Engineering" has the classification number TU311.3. Here, "TU" represents architectural science, "TU3" represents structural mechanics, "TU311" represents structural dynamics, and ".3" indicates a sub-field, specifically referring to dynamic analysis methods. Clearly, the degree of influence of information from beginning to end differs. If the results obtained from a certain sub-node do not begin with "TU," the accuracy of that classification number is obviously extremely low because the book's field does not match the actual requirements. Analyzing the sub-node "TU311" implies higher analytical accuracy. For specific sub-fields, such as ".4," it will also refer to the corresponding field or method. For example, the classification number "TU311.4" may include books such as "Finite Element Method in Structural Dynamics" and "Structural Vibration Testing and Modal Analysis," which essentially belong to the same field as the book in this case, differing only in the algorithms or tools used. Therefore, obtaining the sub-node with the classification number "TU311.4" can be considered to also have extremely high analytical accuracy. In other words, in the analysis of parsing accuracy, the parsing accuracy can be sorted according to the order of field, discipline, discipline branch and sub-field, and the parsing accuracy corresponding to this order increases from front to back.

[0118] S132. Based on the parsing accuracy of the preset classification number, sort the parsing accuracy of the preset classification number to obtain the classification number accuracy sort.

[0119] The purpose of this step is to sort the obtained preset classification numbers based on their resolution accuracy. Based on the resolution accuracy and the sorting results, the obtained data results can be applied to the analysis of whether the corresponding preset classification numbers can be applied.

[0120] Among these steps, the obtained classification numbers need to be sorted to determine the specific precision of the corresponding preset classification numbers.

[0121] Specifically, for the classification accuracy of the preset classification number, the obtained values ​​are sorted based on the method for determining the preset accuracy, such as percentage, numerical sequence, etc. Based on the obtained processing results, the parsing accuracy is further sorted, and the sorting result is obtained.

[0122] S133. Based on the precision sorting of the classification numbers, obtain high-precision preset classification numbers.

[0123] The purpose of this step is to ensure higher efficiency and accuracy in the process of obtaining the corresponding book classification number based on the book title. Therefore, it is necessary to sort the classification numbers by accuracy and select the preset classification numbers that can be applied and have higher accuracy.

[0124] Among these steps, the obtained classification numbers are sorted according to their precision, and the sorting results are then determined.

[0125] The sorting result of the obtained classification number precision is compared with the preset classification number, and a corresponding sequence number threshold is set. When the obtained preset classification number precision sorting result is higher than the threshold, the preset classification number corresponding to the sequence number is the high-precision preset classification number.

[0126] S134. Obtain the cloud computing sub-node corresponding to the high-precision preset classification number to obtain the high-performance node.

[0127] The purpose of this step is to effectively supplement library resources based on book titles. Therefore, it is necessary to determine the cloud computing sub-nodes used in the book title analysis process to improve the accuracy of determining the corresponding book classification number. Thus, it is necessary to determine the sub-nodes that can be used in this process, and these sub-nodes are high-performance nodes.

[0128] This involves obtaining the cloud computing sub-nodes corresponding to various preset classification numbers during the acquisition process, and based on this correspondence, obtaining all generated cloud computing sub-nodes for the preset classification numbers.

[0129] Among them, the high-precision preset classification number obtained can be used to directly identify the corresponding cloud computing sub-node as a high-performance node.

[0130] As described in step S140, the purpose of this step is to establish a correspondence between different types of book title content and corresponding cloud computing sub-node data groups, considering that different cloud computing sub-nodes have preset classification numbers calculated based on book titles. In this way, in specific book supplementation, the optional book classification number can be obtained based on the book title searched by the reader, and then book resources can be supplemented based on the book classification number.

[0131] S141. Obtain the keywords of the book title and the keyword combination relationship of the book title, and establish a keyword data group.

[0132] The purpose of this step is that, for books, their naming usually involves the relationship between words and phrases, and the bibliography cannot be determined simply based on the book classification number. Therefore, in the technical solution of this application, the supplementation of books is selected based on the relationship between the keywords in the book classification number and the book title. Thus, the purpose of this step is to obtain the keyword relationship in the book in order to establish a keyword data group.

[0133] This involves extracting content words from book titles and determining the combination relationships between these content words to obtain keywords and their combination relationships.

[0134] In some embodiments, the combination of keywords does not limit the position of the keywords, but only constructs keyword data groups based on the content of the keywords.

[0135] In some embodiments, synonyms of keywords are also obtained and uniformly established into keyword data groups. For example, in the subject of "Engineering Mechanics", the keywords include both "engineering" and "mechanics", so the keyword data group would be [engineering, engineering scheme, construction engineering, water conservancy engineering, power engineering, mechanics].

[0136] S142. Obtain the frequency of keyword occurrence in all the keyword data groups, and establish a correspondence between keywords and high-performance nodes based on the keyword frequency.

[0137] The purpose of this step is that, since the cloud computing system of this application uses multiple sub-nodes and the sub-nodes employ different algorithms, different cloud computing sub-nodes are better at analyzing book titles. To ensure reasonable analysis of book resources, it is necessary to determine the book titles that different sub-nodes are better at analyzing, and then utilize these sub-nodes to analyze book titles and thus mine book classification numbers. Specifically:

[0138] S1421. Obtain the book title and the corresponding book classification number, and merge the keyword data groups of book titles with the same book classification number to obtain a high-dimensional keyword data group.

[0139] The purpose of this step is to determine the correspondence between book titles and corresponding cloud computing sub-nodes, since it is necessary to establish the relationship between book titles, book classification numbers, and book titles. At the same time, the association between book classification numbers and sub-nodes has already been obtained.

[0140] The obtained book titles and classification numbers can be determined directly based on the library's existing book resources.

[0141] This involves referencing book titles in the form of keyword data groups and establishing a correspondence between keyword data groups and book classification numbers.

[0142] For all book resources, the corresponding book classification number is obtained, and the book titles with the same classification number are integrated into the same book title data group to obtain a high-dimensional book title data group.

[0143] Specifically, the book titles in the high-dimensional book title data group are obtained and then stored in the form of keyword data groups. The resulting new keyword data group is the high-dimensional keyword data group.

[0144] S1422. Obtain the keywords in the high-dimensional keyword data group and obtain the synonyms of the keywords.

[0145] The purpose of this step is to expand the obtained high-dimensional keyword data set so that it can include more keywords of the same type. This ensures that when expanding library resources in the future, the book classification number can be analyzed more accurately based on the title information.

[0146] In this process, for all keywords in the high-dimensional keyword data group, their synonyms are identified, and the identified synonyms are directly added to the high-dimensional keyword data group.

[0147] S1423. Obtain the frequency of occurrence of keywords and synonyms of keywords in the high-dimensional keyword data group to obtain the frequency of occurrence of keywords.

[0148] The purpose of this step is to analyze the frequency of keyword occurrences, considering that there are usually multiple keywords in the established keyword data set. In order to ensure that the final data set can be well applied in the subsequent cloud computing system, it is necessary to determine the highest frequency keyword obtained by the cloud computing sub-node.

[0149] In this process, all keywords are counted to identify all different types of keywords. The equation for calculating keyword frequency is as follows:

[0150] ;

[0151] in, Word frequency; This indicates the number of keywords that are synonyms. This indicates the number of keywords in the high-dimensional keyword data group; i A thesaurus representing words that are synonyms; j This indicates the total number of synonym indexes.

[0152] In some embodiments, only the frequency of occurrence of keywords is determined, without considering the frequency of occurrence of synonyms of each keyword.

[0153] S1424. Based on the frequency of occurrence of the keywords, obtain keywords whose frequency of occurrence is not lower than a preset frequency of occurrence, and obtain high-frequency keywords.

[0154] The purpose of this step is to determine the frequency of all the keywords obtained. Once high-frequency keywords are obtained, it means that the high-accuracy book classification number corresponding to the book title can be obtained in the supplementation of book resources based on the correspondence between the high-frequency keywords and the sub-nodes.

[0155] The preset frequency of occurrence can be determined based on work experience.

[0156] In some embodiments, the average frequency of keyword occurrence can be obtained and applied as a preset frequency of occurrence.

[0157] In this process, all keywords with a frequency higher than the preset frequency are treated as high-frequency keywords, while keywords with a frequency lower than the preset frequency are simply removed from the category number data group.

[0158] S1425. Establish the correspondence between the high-frequency keywords and high-performance nodes to obtain the correspondence between keywords and high-performance nodes.

[0159] The purpose of this step is to establish a child node data group for high-performance child nodes. Although a unique book classification number can be obtained based on the corresponding keywords, it is not certain whether the high-performance nodes can obtain a stable book classification number. In order to obtain more accurate data in the subsequent determination of book classification numbers, it is necessary to determine the correspondence between high-frequency keywords and high-performance nodes.

[0160] The relevance can be obtained directly based on the frequency of occurrence of high-frequency keywords; the frequency of occurrence of high-frequency keywords can be used directly as the relevance.

[0161] In some embodiments, the relevance between high-frequency keywords and child nodes is further processed, for example, by introducing the weight of a specific keyword among keywords of the same type (i.e., multiple keywords with synonym relationships), resulting in the following equation:

[0162] ;

[0163] in, This indicates the degree of correlation between high-frequency keywords and child nodes; This indicates the number of a specific keyword among multiple keywords that are synonyms. This indicates the number of keywords that are synonyms.

[0164] After obtaining the relevance, the high-frequency keywords need to be ranked based on the obtained relevance. Only when the obtained relevance is higher than the set threshold can the correspondence be considered applicable.

[0165] In some embodiments, it is necessary to establish a correspondence between relevant keywords and the labels of specific cloud computing sub-nodes, so as to ensure that in the subsequent work of determining the book classification number based on the book title, the book title and keywords are processed, and the corresponding book classification number is obtained based on the keywords.

[0166] S143. Based on the correspondence between the keywords and high-performance nodes, the high-performance nodes corresponding to the keywords are constructed into the node data group to obtain the title parsing node group.

[0167] The purpose of this step is to consider that cloud computing sub-nodes have different processing performance for different types of keywords. Therefore, it is necessary to include cloud computing sub-nodes with similar performance, especially those with similar performance for the same type of keywords, into the same data group. This will result in multiple sub-node data groups, which will enable the parsing of book classification numbers by using sub-nodes within different node data groups based on the keyword type in the book title during the updating of book resources.

[0168] In this process, the child nodes corresponding to the high-frequency keywords are all included in the same child node data group, resulting in a small-scale parsing node group corresponding to the keywords.

[0169] Specifically, the high-frequency keywords covered in all high-frequency keyword data groups are included in the same sub-node data group, resulting in a parsing node group.

[0170] Specifically, for all parsing node groups, it is necessary to ensure that the cloud computing sub-nodes in the parsing node group meet the correlation determination results, thereby obtaining the parsed data group.

[0171] As described in step S150, the purpose of this step is to identify the library's unlisted book resources, and this identification needs to be based on the reader's specific needs for related books. In subsequent processing, the established parsing node group can effectively analyze the book classification number corresponding to the title of the book requested by the reader. Specifically:

[0172] S151. Obtain the reader search records in the library and obtain feedback information on the search records.

[0173] The purpose of this step is to analyze the specific needs of readers in the library for relevant books, and then to obtain the corresponding book demand priority based on these specific needs.

[0174] This involves obtaining reader input information from the current library's book retrieval system to obtain reader retrieval records.

[0175] This includes obtaining and recording book information that the library failed to effectively provide, as indicated in the reader's search records.

[0176] In some embodiments, the search frequency of books that were not included is ranked to determine the priority of readers' demand for relevant books.

[0177] S152. Obtain the unlisted books from the feedback information and record the titles of the unlisted books.

[0178] The purpose of this step is to obtain the current demand of readers for different types of books, especially the titles of the books that readers demand, so that the library can determine the book resources that need to be supplemented based on the obtained book titles.

[0179] This includes identifying the books not included in the feedback information and determining the titles of those books.

[0180] In some embodiments, for the titles of uncollected books, synonyms are obtained from the keywords in the book titles, thereby expanding the coverage of the book titles.

[0181] In some embodiments, after obtaining the book title that has been replaced with a synonym, the new book title is compared with the existing book titles in the library. If the corresponding book title is found in the library, then the book does not need to be supplemented.

[0182] S153. Obtain the retrieval frequency of the titles of the unlisted books, and based on the retrieval frequency, obtain the priority for supplementing the unlisted books.

[0183] The purpose of this step is that this application is based on both the priority of book supplementation and the book classification number. Therefore, in the specific processing, the technical solution required for the book classification number has been determined in the technical solution disclosed above. Therefore, it is also necessary to determine the corresponding priority of book supplementation in order to determine the subsequent supplementary books.

[0184] This involves obtaining the frequency of readers' searches for book titles and establishing supplementary priorities based on the search frequency.

[0185] The higher the retrieval frequency, the higher the priority of supplementation.

[0186] In some embodiments, the search frequency can be determined periodically or irregularly, and a corresponding preset search frequency can be set. Only when the search frequency is higher than the preset search frequency can the corresponding book title be considered as a priority supplementary book.

[0187] In some embodiments, after determining the priority of relevant books for supplementation and identifying those that need to be prioritized, synonyms are obtained from the keywords of the book titles, and all the resulting book titles are identified as books that need to be prioritized for supplementation.

[0188] As described in step S160, the purpose of this step is that, when it is determined that books need to be supplemented, the information is actually only the book title. Therefore, it is necessary to determine the corresponding probability classification number based on the book title with high precision. Only then can the books to be supplemented be purchased based on the high-precision probability classification number to supplement the library's book resources.

[0189] S161. Based on the priority of supplementing the unincluded books, obtain the book titles corresponding to the priority of supplementing the unincluded books, and obtain the titles of the books to be supplemented first.

[0190] The purpose of this step is to determine the book titles that need to be supplemented, and then, based on the obtained book titles, to determine the priority books to be supplemented.

[0191] The library determines the priority based on the obtained book retrieval frequency, and thus can determine the priority replenishment needs of books based on the currently obtained priority parameters.

[0192] For books that require supplementation, the keywords in the titles of these books are expanded, and processing is done by obtaining synonyms and other methods.

[0193] In this process, all book titles that need to be supplemented are included in the corresponding book supplement data group, and the book titles are determined based on this data group.

[0194] In some embodiments, keywords are extracted from all book titles and all the obtained keywords are included in the keyword data group of the supplementary bibliography. Then, based on this data group, the possible classification number of the books can be determined.

[0195] S162. Obtain the keywords of the priority supplemented book titles, obtain the synonyms of the priority supplemented book titles keywords, and obtain the priority supplemented book keyword data group.

[0196] The purpose of this step is to analyze the keywords of the priority supplementary book titles to obtain keyword data groups, considering that this application ultimately establishes a correspondence between keywords and cloud computing sub-nodes, rather than a direct correspondence between book titles and cloud computing sub-nodes.

[0197] The method in this step is the same as the method in step S161, that is: for the keywords of the book title that are prioritized for supplementation, synonyms are obtained, and then the obtained synonyms are added to the keyword data group to achieve the purpose of expansion.

[0198] S163. Input the priority supplementary book keyword data group into the title parsing node group to obtain the parsing classification number.

[0199] The purpose of this step is to take into account the different understanding and processing performance of different title parsing node groups for different keywords. Therefore, in the process of prioritizing the supplementation of book keyword data groups, in order to obtain more accurate book classification numbers, it is necessary to send different types of book keyword data groups to the corresponding title parsing node groups to obtain the parsing classification numbers.

[0200] This involves establishing a correspondence between priority groups of supplementary book keyword data and corresponding title parsing node groups. This process requires obtaining the correlation between the corresponding sub-nodes and keywords. The equation for determining this correlation is:

[0201] ;

[0202] in, m This indicates that priority should be given to supplementing the book's title keyword category index; n This represents the total number of keyword category indexes for the titles of priority supplementary books. The equation implies that, in calculating the title relevance of priority supplementary books, the relevance of all keywords (including the keywords themselves and their synonyms) needs to be determined, and the average value is calculated to obtain the average relevance value.

[0203] Specifically, the obtained relevance values ​​need to be determined based on the relevance calculation results of each keyword and sub-node. Different numerical level ranges are set based on the obtained relevance results of sub-nodes and keywords. When the obtained relevance results fall into the corresponding numerical level range, the parsing node group corresponding to that numerical level range is used as the title parsing data group corresponding to the book keyword data group as a priority supplement.

[0204] After the priority supplementary book keyword data group is input into the corresponding parsing node group, the cloud computing sub-nodes contained in the parsing node group jointly parse the obtained keyword data group, calculate the algorithm of all sub-nodes, and calculate the parsing classification number that can be obtained.

[0205] S164. Based on the frequency of occurrence of the parsed classification number, obtain the probability classification number.

[0206] The purpose of this step is that, since the set of parsing node groups has multiple child nodes, each child node generates a parsing classification number. These generated parsing classification numbers may have significant differences. Furthermore, considering that the same book classification number corresponds to a large number of different books, it is necessary to minimize the number of obtained parsing classification numbers. This allows for the retrieval of corresponding book information based on the parsing classification number, and the supplementation of book information. Specifically:

[0207] S1641. Based on the frequency of occurrence of the parsed classification number, obtain the high-frequency parsed classification number.

[0208] The purpose of this step is to perform frequency analysis on the parsed classification numbers obtained from all child nodes, and to obtain the applicable classification numbers from the obtained parsed classification numbers.

[0209] Among them, for all the obtained parsed classification numbers, the classification numbers are identified, and the occurrence frequency of the same classification number is counted.

[0210] Among them, the counting results based on the number of times the classification number appears are sorted, and the higher the ranking of the preset classification number, the higher its priority.

[0211] In this process, the analytical classification numbers that appear frequently enough to meet the usage requirements are converted into probability classification numbers, and the resulting probability classifications serve as the basis for subsequent applications.

[0212] S1642. Based on the high-frequency parsing classification number, obtain the corresponding high-performance node to obtain the high-performance parsing node.

[0213] The purpose of this step is that, as described in the technical solution above, the correspondence between parsed classification numbers and corresponding cloud computing sub-nodes has already been identified. Therefore, based on the obtained results, high-performance nodes can be determined according to the high-frequency parsed classification numbers. Simultaneously, the number of sub-nodes analyzed can be reduced, allowing the obtained sub-nodes to be used in the analysis process of books based on reader demand.

[0214] In this process, all cloud computing sub-nodes corresponding to high-frequency parsing classification numbers are included in the sub-node data group, thereby directly determining the sub-nodes that generate the parsing classification numbers. The resulting sub-nodes can then be identified as high-performance parsing nodes.

[0215] S1643. Based on the correspondence between the keywords and high-performance nodes, obtain the preset keywords corresponding to the high-performance parsing nodes.

[0216] The purpose of this step is that, in the technical solution of this application, the book title is expanded based on the book title retrieved by the reader. In subsequent processing, the library can identify the book title obtained through the expansion process and supplement book resources based on the obtained book title.

[0217] For high-performance parsing nodes, the generated keywords are further analyzed, which may include keywords from readers' book titles and other keywords, in order to obtain preset keywords.

[0218] In some embodiments, the obtained keywords are validated for synonyms, and all keywords with synonym relationships are uniformly replaced to obtain a specific keyword.

[0219] In some embodiments, during the process of replacing synonyms, it is also necessary to analyze the frequency of occurrence of each keyword that has a synonym relationship, take the keyword with the highest frequency as the standard, and treat all synonyms as the keyword with the highest frequency to process. The result is the preset keyword.

[0220] S1644. Based on the preset keywords and the keyword combination relationships, candidate book titles are obtained.

[0221] The purpose of this step is to ensure that there are connections and relationships between the keywords in a book title. Book titles are not random combinations of keywords. Therefore, the determination of a book title should be based on the combination and relationships between keywords.

[0222] In this process, based on the combination and correspondence of each keyword in the book title, the preset keywords are arranged and combined to obtain the arrangement and combination results, which are the candidate book titles.

[0223] In some embodiments, it is also considered to incorporate all the synonyms obtained therein into the corresponding book titles to obtain alternative book titles.

[0224] S1645. Retrieve the candidate book titles. If the candidate book titles exist, obtain the classification number of the candidate book titles.

[0225] The purpose of this step is to verify whether the candidate book titles correspond to actual books, since the obtained candidate book titles do not correspond to specific books. This will allow us to obtain the classification number of the candidate book titles.

[0226] Among these methods, cloud computing technology or other computer technologies are used to conduct internet searches on the obtained candidate book titles, and based on the search results, it is determined whether the candidate book title actually contains a corresponding book.

[0227] In some embodiments, if the search finds that the book does not exist, an internet search is required for the introduced candidate book titles generated based on synonyms to determine whether the candidate book titles actually exist.

[0228] Specifically, when a book corresponding to a candidate book title is found to actually exist, the share classification number of that book is obtained.

[0229] S1646. Obtain book titles whose classification number frequency is not lower than a preset classification number frequency, wherein the classification number of the candidate book titles is a probability classification number.

[0230] The purpose of this step is that, in the operation of the library, for the obtained possible classification numbers, there may be multiple possible classification numbers that meet the various requirements mentioned above, and there may be multiple corresponding books. In order to ensure the accuracy and quality of book procurement, it is necessary to narrow down the range of classification numbers for book titles to improve the supplementary effect.

[0231] This involves obtaining the classification numbers of the candidate book titles and counting the frequency of occurrence of each classification number.

[0232] Among them, book classification numbers that appear at a frequency no less than a preset frequency are set as probability classification numbers, and the book titles corresponding to these probability classification numbers are directly identified as books that need to be added.

[0233] In some embodiments, the method also includes analyzing the similarity between the titles of the books to be supplemented and the titles of books retrieved by readers. Only if the similarity requirements are met can the books to be supplemented be actually purchased and included in the library's book resource database.

[0234] As described in step S170, the purpose of this step is to establish unique book archives for newly added books after the library has replenished its book resources, and to update these archives during the library's subsequent operations, thereby achieving the establishment and updating of book archives. Specifically...

[0235] S171. Based on the probability classification number, obtain the corresponding optional book title.

[0236] The purpose of this step is that the library needs to replenish its books, and in the specific replenishment process, it needs to be able to accurately determine the titles of candidate books based on the probability classification number.

[0237] Among them, based on the obtained possible classification number, all possible book titles corresponding to that classification number are filtered.

[0238] Among them, for optional book titles, these titles all have corresponding books. Therefore, in the specific processing, the books corresponding to the obtained optional book titles are all considered to be likely to be included in the library's book resource database.

[0239] In some embodiments, it is also necessary to verify the similarity between the optional book titles and the books retrieved by the readers. The higher the similarity and the higher the retrieval frequency, the higher the priority of supplementing the optional book titles, and the books corresponding to the book titles will be purchased and supplemented.

[0240] S172. Based on the corresponding optional book titles, supplement the library's books.

[0241] The purpose of this step is to purchase relevant books from the library's book resources according to the determined available book titles, and to incorporate the purchased books into the library's resource database, thereby supplementing the library's resources.

[0242] In this process, based on the technical solution disclosed in step S172, the optional book titles are determined. It should be noted that optional book titles mean that the library can purchase the book and has the same physical book corresponding to the title. Therefore, the library needs to purchase the book and add it to the library's resource database.

[0243] S173. Establish book archives for the supplemented books and update the book archives for the supplemented books during library operation.

[0244] The purpose of this step is to create corresponding book profiles for the supplementary books and to update the book profiles after they are created.

[0245] Among them, specific information in the obtained book archives needs to be recorded, such as book classification number, international standard identifier, subject terms, physical characteristics, title information, author information, publication information, content summary, book reviews and recommendations, revision records, and related resources. This type of information is fixed in the book archives and cannot be modified.

[0246] Among these, the acquired book archives also need to record the modifiable information, such as the number of times the book has been borrowed, the corrected location in the collection, the borrower's information, the borrowing time, overdue records, reservation information, circulation status, etc., and all such information should be updated in real time.

[0247] like Figure 2 As shown in the illustration, this application provides a cloud-based library archive display interface. The upper section displays basic book information such as title, author, and classification number, which is generally immutable. Therefore, the "Modify" option is grayed out, allowing operation only by authorized personnel. The upper right corner is the login area for library staff. The system can analyze and obtain login permissions and perform corresponding operations. For the function bars corresponding to the book titles, direct input of book titles is supported, while other function bars directly display related information. Alternatively, other function bars can also support direct input of information, displaying potential information and confirming it using the drop-down arrows. The lower section displays real-time information, including borrowing status and lending information. This information cannot be modified by library staff but is automatically updated by the archive update system. A search bar allows library staff to directly search for information such as borrower name, book borrowing time, etc. n Information such as the return date of each borrowing is displayed in "Historical Borrowing Information".

[0248] The beneficial effects of this application include:

[0249] 1. This application enables the rational analysis of book resources that need to be supplemented. Based on cloud computing technology, this application successfully utilizes book classification numbers to classify and analyze the books currently retrieved by readers. Then, based on the classification results, books are supplemented, and corresponding book archives are established based on the supplemented books. This allows libraries to create and update book archives based on the supplemented book information.

[0250] 2. The method for determining book categories has been achieved. In the technical solution of this application, book resources are not supplemented directly based on the book titles retrieved by the reader. Instead, the possible classification numbers of the retrieved book titles are obtained, and then the book categories are supplemented based on the classification numbers, thereby expanding the scope of supplementary book resources and fully meeting the reader's needs for relevant books.

[0251] 3. Personalized updates of book archives are achieved. In the technical solution of this application, a dedicated book archive is established for the acquired book archives. Then, based on the archive, as well as the subsequent application results and borrowing results of the books, the book archive is continuously updated, thereby ensuring that a dedicated book archive can be established for each book and that the book archive is continuously updated.

[0252] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to computer program instructions. The aforementioned computer program can be stored in a non-volatile storage medium, and when executed, it performs the steps of the above method embodiments. Alternatively, if the integrated unit of the present invention is implemented as a software functional module and sold or used as an independent product, it can also be stored in a non-volatile storage medium. Based on this understanding, the technical solution of the embodiments of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a non-volatile storage medium and includes several instructions to cause an electronic device (which may be a personal computer, server, network device, etc.) to execute all or part of the methods described in the various embodiments of the present invention.

[0253] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for updating book archives based on reader needs, characterized in that, The update method includes: Obtain the book classification number based on the book title and corresponding book information; The book title is input into the cloud computing system, and all cloud computing sub-nodes generate the book's classification number based on the book title to obtain the preset classification number; Comparing the preset classification number and the book classification number, sorting the preset classification number to obtain high-performance nodes, including: The resolution accuracy of the preset classification number is obtained by comparing the preset classification number with the book classification number. Based on the parsing precision of the preset classification number, the parsing precision of the preset classification number is sorted to obtain the classification number precision sorting. Based on the classification number precision sorting, obtain a high-precision preset classification number; Obtain the cloud computing sub-node corresponding to the high-precision preset classification number to obtain the high-performance node; The high-performance nodes are classified to obtain high-performance nodes that generate preset classification numbers based on different book titles, and a title parsing node group is constructed, including: Obtain the keywords of the book titles, and obtain the keyword combination relationships of the book titles to establish keyword data groups; Obtain the keyword frequency within all the aforementioned keyword data groups, and based on the keyword frequency, establish a correspondence between keywords and high-performance nodes, including: Obtain the book title and the corresponding book classification number, and merge the keyword data groups of book titles with the same book classification number to obtain a high-dimensional keyword data group; Obtain the keywords from the high-dimensional keyword data group, and obtain the synonyms of the keywords; Obtain the frequency of occurrence of keywords and synonyms of keywords in the high-dimensional keyword data group to obtain the keyword frequency. Based on the frequency of occurrence of the keywords, keywords with a frequency of occurrence not lower than a preset frequency are obtained to obtain high-frequency keywords; Establish the correspondence between the high-frequency keywords and high-performance nodes to obtain the correspondence between keywords and high-performance nodes; Based on the correspondence between the keywords and high-performance nodes, the high-performance nodes corresponding to the keywords are constructed into the node data group to obtain the title parsing node group; Obtain the library's records of book titles searched by readers, and determine the priority for adding unlisted books to the library's database; Based on the priority of supplementing the unlisted books, a probability classification number is obtained, including: Based on the priority of supplementing the unlisted books, obtain the titles of the books corresponding to the priority of supplementing the unlisted books, and obtain the titles of the books to be supplemented first; Obtain the keywords of the priority supplementary book titles, obtain the synonyms of the priority supplementary book titles keywords, and obtain the priority supplementary book keyword data group; Input the priority supplementary book keyword data group into the title parsing node group to obtain the parsing classification number; Based on the frequency of occurrence of the parsed classification number, obtain the probability classification number; Based on the aforementioned probability classification number, supplement the library's books, and establish and update the book archives of the supplemented books.

2. The method for updating book archives based on reader needs according to claim 1, characterized in that, The process of obtaining the book classification number based on the book title and corresponding book file includes: Obtain library book information, including book titles and corresponding book files; Based on the corresponding book files, obtain the book classification number; Also includes: Establish the correspondence between the book titles and the book classification numbers.

3. The method for updating book archives based on reader needs according to claim 1, characterized in that, The step involves inputting the book title into the cloud computing system, where all cloud computing sub-nodes generate a book classification number based on the book title, resulting in a preset classification number, including: The book title is sent to the cloud computing system, and all cloud computing sub-nodes of the cloud computing system obtain the book classification number based on the book title. Obtain the book classification number output by the cloud computing sub-node to get the output classification number; The output classification numbers are identified, and those with the same output classification numbers are included in the same classification number data group; Obtain the number of output classification numbers in the classification number data group, and sort the classification number data group based on the number of output classification numbers; When the sorting sequence number of the classification number data group is higher than the sorting sequence number of the preset classification number data group, the classification number data group corresponding to the sorting sequence number of the classification number data group is obtained, and the preset classification number is obtained.

4. The method for updating book archives based on reader needs according to claim 1, characterized in that, The process of obtaining the book title records searched by readers in the library and obtaining the priority of supplementing unlisted books in the library includes: Obtain readers' search records within the library and retrieve feedback information about those records; Obtain the unlisted books from the feedback information and record their titles; Obtain the retrieval frequency of the titles of the unlisted books, and based on the retrieval frequency, obtain the priority for supplementing the unlisted books.

5. The method for updating book archives based on reader needs according to claim 1, characterized in that, The step of obtaining the probability classification number based on the occurrence frequency of the parsed classification number includes: Based on the frequency of occurrence of the parsed classification number, obtain the high-frequency parsed classification number; Based on the high-frequency parsing classification number, the corresponding high-performance node is obtained, thus obtaining the high-performance parsing node; Based on the correspondence between the keywords and high-performance nodes, the preset keywords corresponding to the high-performance parsing nodes are obtained; Based on the preset keywords and the relationships between keyword combinations, candidate book titles are obtained; Retrieve the candidate book titles; if the candidate book titles exist, obtain the classification number of the candidate book titles. The candidate book titles are selected based on their classification number frequency, which is not lower than a preset classification number frequency. The classification number of the candidate book titles is a probability classification number.

6. The method for updating book archives based on reader needs according to claim 1, characterized in that, The process of supplementing the library's books based on the probability classification number, and establishing and updating the book archives for the supplemented books, includes: Based on the probability classification number, obtain the corresponding optional book titles; Based on the corresponding candidate book titles, the library's books are supplemented; Establish book archives for the supplemented books and update the book archives for the supplemented books during library operation.

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