Digital cultural book management method and system, terminal and medium

Abstract

The invention relates to the field of digital books, in particular to a digital cultural book management method and system, a terminal and a medium, and the method comprises the steps: obtaining user reading information; generating user preference information based on the user reading information; obtaining a digital cultural book library; and performing personalized recommendation based on the digital culture book library and the user preference information. According to the method, personalized recommendation can be performed on the user, and the reading interest of the user is kept.

Description

Technical Field

[0001] This application relates to the field of digital books, and in particular to a method, system, terminal and medium for managing digital cultural books. Background Art

[0002] With the rapid development of digital technology, the digital management of classic cultural books has become increasingly important. Traditional digital management methods often simply convert the content of books into electronic formats for easy storage and transmission, and establish a digital cultural book library.

[0003] When retrieving an existing digital cultural book library, a special retrieval system is required for searching. However, common retrieval systems only classify the popularity of books in the digital cultural book library and recommend the books with high popularity to users on the retrieval interface. Since this method lacks the function of analyzing user personal habits, it is difficult to make personalized recommendations according to the reading habits of different users. Summary of the Invention

[0004] In a first aspect, in order to make personalized recommendations for users and maintain the effect of users' reading interest, this application provides a method for managing digital cultural books.

[0005] The method for managing digital cultural books provided by this application adopts the following technical solutions: A method for managing digital cultural books includes: Obtain user reading information; Generate user preference information based on the user reading information; Obtain a digital cultural book library; Make personalized recommendations based on the digital cultural book library and the user preference information.

[0006] By adopting the above technical solutions, personalized recommendations are generated according to the user's reading information and preferences, which can more accurately match the user's interests and reading habits. Such recommendations not only improve the efficiency of users discovering new books, but also increase the user's satisfaction with the recommended books, thereby maintaining the user's reading interest. Based on the user preference information, the system can recommend book content and themes suitable for different users' preferences, making the reading suggestions more personalized and targeted, and avoiding the limitations of traditional general recommendations.

[0007] Preferably, the method for generating user preference information based on the user reading information includes: Obtain user reading information, where the user reading information includes the types of books the user reads, the frequency of reading each type of book, and the time; Calculate the added value of each book category based on the user's reading information and additional parameters, where the frequency and time of reading each category of books are positively correlated with the added value; Arrange the order of all book categories based on the added values of all book categories; Generate user preference information based on the order of all book categories.

[0008] By adopting the above technical solution, the system calculates the added value of each book category according to the user's reading information, then arranges based on the added values of all book categories, and finally generates user preference information through the order of all book categories. By analyzing the types, frequencies, and reading times of books read by users, the system can accurately understand the user's reading preferences and interests. The user preference information generated in this way is more accurate and detailed, and can provide personalized recommendation services for users.

[0009] Preferably, the method further includes: Obtain the user's purchased book information; Generate user preference information based on the user's purchased book information; Obtain the digital cultural book library; Conduct personalized recommendations based on the digital cultural book library and user preference information.

[0010] By adopting the above technical solution, in addition to generating user preference information through the user's reading information, it is also possible to conduct personalized recommendations for users through the information of the books they purchase. Among them, the purchase behavior can reflect the user's deeper preferences and actual choices. Combined with the analysis of the reading behavior, it can provide more accurate personalized recommendation services for users.

[0011] Preferably, the method for obtaining the user's reading information includes: Obtain a login instruction; Based on the login instruction, display a login control on the human-computer interaction interface; Obtain the trigger instruction of the login control; Log in to the target user account based on the trigger instruction of the login control; Obtain the user's reading information based on the target user account.

[0012] By adopting the above technical solution, the user can log in to their own account through the login control, and the system can obtain the user's reading information from the user's account, thereby obtaining their reading information through the user's login information.

[0013] Preferably, the method further includes: Obtain a scoring instruction; Generate multiple book category controls according to the scoring instruction; Obtain the trigger instruction of the book category control; Generate a rating box for the book category on the human - machine interaction page based on the trigger instruction of the book category control; Obtain the ratings of each book category; Generate a rating list based on the ratings of each book category; Conduct personalized recommendations based on the rating list.

[0014] By adopting the above - mentioned technical solution, when each user uses the system, they can rate each book category. The system generates a rating list based on the ratings of each book category for feedback, and conducts personalized recommendations for users through the rating list, thereby improving the user experience.

[0015] Preferably, after the step of generating a rating list based on the ratings of each book category, it includes: Obtain the rating list of each user; Rank the books of each category based on the rating list of each user; Display the ranking list on the human - machine interaction interface based on the book category ranking.

[0016] By adopting the above - mentioned technical solution, the system records after each user rates. The system ranks the books of each category based on the rating list of each user and displays the ranking list on the human - machine interaction interface, thereby facilitating the operation of users.

[0017] Preferably, the step of conducting personalized recommendations based on the digital cultural book library and user preference information includes: Obtain cultural book categories based on the digital cultural book library; Based on the cultural book categories and user preference information, conduct correlation analysis between the user preference information and the cultural book categories and generate a correlation table; Display a personalized recommended book list on the human - machine interaction interface based on the correlation table.

[0018] By adopting the above - mentioned technical solution, conduct correlation analysis between the user preference information and the cultural book categories. The generated correlation table will show which cultural book categories have a high correlation with the user preferences. The personalized recommendation results obtained based on the correlation table are displayed on the human - machine interaction interface. These recommended book lists can recommend cultural book categories that are relevant to the user's interests and that the user may be interested in according to the user's specific preferences. Through these steps, the system can utilize the information in the digital cultural book library and the user's preference data to provide personalized and highly relevant cultural book recommendation services for users. This not only improves the user's reading experience but also helps to promote the dissemination and understanding of cultural books.

[0019] In a second aspect, in order to provide personalized recommendations to users and maintain the effect of users' reading interest, the present application provides a digital cultural book management system.

[0020] A digital cultural book management system includes: An information acquisition module for acquiring users' reading information; A preference information generation module for generating users' preference information based on users' reading information; A book library acquisition module for acquiring a digital cultural book library; A personalized recommendation module for making personalized recommendations based on the digital cultural book library and users' preference information.

[0021] In a third aspect, in order to provide personalized recommendations to users and maintain the effect of users' reading interest, the present application provides an intelligent terminal, adopting the following technical solution: An intelligent terminal includes a memory and a processor, and a computer program capable of being loaded and executed by the processor for the above-mentioned digital cultural book management method is stored on the memory.

[0022] In a fourth aspect, in order to provide personalized recommendations to users and maintain the effect of users' reading interest, the present application provides a computer-readable storage medium, adopting the following technical solution: A computer-readable storage medium stores a computer program capable of being loaded and executed by the processor for any of the above digital cultural book management methods.

[0023] In summary, the present application includes at least one of the following beneficial technical effects: 1. Generating personalized recommendations based on users' reading information and preferences can more accurately match users' interests and reading habits. Such recommendations not only improve the efficiency of users discovering new books but also increase users' satisfaction with the recommended books, thereby maintaining users' reading interest. Based on users' preference information, the system can recommend book contents and themes suitable for their preferences to different users, making the reading suggestions more personalized and targeted, and avoiding the limitations of traditional general recommendations; 2. The system calculates the added value of each book category based on users' reading information, then arranges them based on the added values of all book categories, and finally generates users' preference information through the order of all book categories. By analyzing the types, frequencies, and reading times of the books read by users, the system can accurately understand users' reading preferences and interests. The user preference information generated in this way is more accurate and detailed, and can provide personalized recommendation services for users; 3. The system can utilize the information in the digital cultural book library and the user's preference data to provide users with personalized and highly relevant cultural book recommendation services. This not only enhances the user's reading experience but also helps to promote the dissemination and understanding of cultural books. Description of the Drawings

[0024] Figure 1 is a flowchart of a method for managing digital cultural books according to an embodiment of the present application, mainly showing steps S100 - S400.

[0025] Figure 2 is a flowchart of a method for managing digital cultural books according to an embodiment of the present application, mainly showing steps SA1 - SA4.

[0026] Figure 3 is a flowchart of a method for managing digital cultural books according to an embodiment of the present application, mainly showing steps SB1 - SB3.

[0027] Figure 4 is a flowchart of a method for managing digital cultural books according to an embodiment of the present application, mainly showing steps SD1 - SD5.

[0028] Figure 5 is a flowchart of a method for managing digital cultural books according to an embodiment of the present application, mainly showing steps SE1 - SE7.

[0029] Figure 6 is a flowchart of a method for managing digital cultural books according to an embodiment of the present application, mainly showing steps SF1 - SF3. Detailed Embodiment

[0030] The following further describes the present application in detail with reference to all the drawings.

[0031] The acquisition of instructions can be obtained by the way triggered by a mechanical button or by the way triggered by a virtual button; for the way triggered by a mechanical button, it can be automatically obtained by pressing the power - on button after power - on, or the current behavior information can be obtained by pressing the corresponding trigger button again after power - on; for the way triggered by a virtual button, it can be achieved by pressing the relevant virtual trigger button in the interface of the corresponding software.

[0032] An embodiment of the present application discloses a method for managing digital cultural books. Referring to Figure 1 , a method for managing digital cultural books includes: Step S100: Obtain user reading information; Specifically, the user reading information includes the types of books the user reads, the frequency of reading books of each type, and the time. The types of books include the following major categories and sub-categories. Fiction: including biographies, science fiction, love novels, historical novels, adventure novels, etc. Non-fiction: including essays, poems, essays, prose essays, etc. Academic: including academic books in philosophy, social sciences, natural sciences, humanities, economics, law, etc. Guide: including travel guides, life guides, health guides, recipe guides, etc. Education: including academic education, technical education, family education, psychological education, etc. Children's: including children's books suitable for children to read, such as picture books for toddlers, children's literature, fairy tales, etc. Art: including art books in painting, music, dance, sculpture, etc. Humanities: including books related to humanities such as history, philosophy, literature, art, etc. Life: including life books in beauty, health, home, fashion, etc. Business and Economics: including economic management-related books in management, marketing, finance, economics, etc.

[0033] Step S200: Generate user preference information based on the user reading information; Refer to Figure 2 Specifically, the steps of generating user preference information based on the user reading information include: Step SA1: Obtain the user reading information, where the user reading information includes the types of books the user reads, the frequency of reading books of each type, and the time; Step SA2: Calculate the added value of each book type based on the user reading information and additional parameters, and the frequency and time of reading books of each type are positively correlated with the added value; Specifically, when the frequency and time of reading books of each type are higher, due to the positive correlation, the added value of this book type is higher. The positive correlation coefficients of the frequency and time of reading books of each type are different. For example, if the frequency of reading books of each type is A and its positive correlation coefficient is a, then the added value is Aa; if the time of reading books of each type is B and its positive correlation coefficient is b, then the added value is Bb. Finally, the added value of each book type is Aa + Bb.

[0034] Step SA3: Arrange the order of all book types based on the added values of all book types; Specifically, arrange the order of all book types according to the magnitudes of the added values of each book type.

[0035] Step SA4: Generate user preference information based on the order of all book types.

[0036] Specifically, obtain the preference of each user for each book type based on the order of all book types.

[0037] Step S300: Obtain a digital cultural book library; Step S400: Perform personalized recommendation based on the digital cultural book library and user preference information.

[0038] Specifically, the digital cultural book library can be obtained through the network. The digital cultural book library is a library formed by designers converting physical cultural books into e-books. Refer to Figure 3 , and the specific steps for performing personalized recommendation based on the digital cultural book library and user preference information include: Step SB1: Obtain the categories of cultural books based on the digital cultural book library; Step SB2: Based on the categories of cultural books and user preference information, conduct an association analysis between the user preference information and the categories of cultural books and generate an association table; Step SB3: Display a personalized recommended book list on the human-computer interaction interface based on the association table.

[0039] Specifically, extract the category information of various cultural books from the digital cultural book library, such as history, art, literature, philosophy, etc. Conduct an association analysis between the user's preference information and the category information of cultural books. Data mining techniques such as association rule mining and collaborative filtering can be used to generate an association table, listing the recommended list of cultural books under each category preferred by the user, which can be sorted according to relevance or score. Display the personalized recommended book list on the human-computer interaction interface. Users can choose to view a certain category in the recommended book list according to their interests, or directly browse the entire book list.

[0040] In addition to generating user preference information through the user's reading information, personalized recommendation can also be performed on the user based on the information of the books purchased by the user. The specific steps include: Step SC1: Obtain the information of the books purchased by the user; Specifically, the information of the books purchased by the user can be collected through the network, shopping websites, offline bookstores or other channels, including the types, quantities, and purchase times of the books purchased.

[0041] Step SC2: Generate user preference information based on the information of the books purchased by the user; Specifically, according to the information of the books purchased by the user, analyze the user's purchase preferences, including the types of books, authors, themes, etc. that the user likes. Data analysis and machine learning techniques can be used to process a large amount of purchase information and extract the user's preference information from it.

[0042] Step SC3: Obtain the digital cultural book library; Step SC4: Perform personalized recommendation based on the digital cultural book library and user preference information.

[0043] Refer to Figure 4, in addition, the methods for obtaining user reading information include: Step SD1: Obtain a login instruction; Specifically, the user can trigger the login instruction by triggering it on the human-computer interaction interface of the terminal.

[0044] Step SD2: Display a login control on the human-computer interaction interface based on the login instruction; Specifically, the system obtains the login instruction and displays a login control on the human-computer interaction interface. The login control is displayed as a login interface, including a login account and a login password. Step SD3: Obtain a trigger instruction for the login control; Specifically, after the user enters the login account and password and clicks to confirm the login, the system obtains the trigger instruction for the login control.

[0045] Step SD4: Log in to the target user account based on the trigger instruction of the login control; Step SD5: Obtain the user's reading information based on the target user account.

[0046] Specifically, after successful login, the system obtains the reading information stored in the account, and can also obtain the user's shopping information by associating with shopping websites, etc.

[0047] Refer to Figure 5 , and can also rank book categories based on user ratings. The specific method includes: Step SE1: Obtain a rating instruction; Step SE2: Generate multiple book category controls according to the rating instruction; Step SE3: Obtain a trigger instruction for the book category control; Step SE4: Generate a rating box for this book category on the human-computer interaction page based on the trigger instruction of the book category control; Step SE5: Obtain the ratings of each book category; Step SE6: Generate a rating list based on the ratings of each book category; Step SE7: Perform personalized recommendations based on the rating list.

[0048] Specifically, the rating function is triggered by a certain button or menu option on the user interface. Based on the previously obtained cultural book category information, corresponding book category controls are generated. Each book category control is displayed as a button with category text. The system listens for the user's click or selection operations on each book category control to obtain the book category triggered by the user. When the user triggers a certain book category, a rating box for that category, such as a 5-star rating or a slider, is dynamically generated on the page. The rating situations of the user for each book category are recorded, the average rating or total rating of each book category is sorted, a rating list is generated, and in combination with the user's preference information, the book categories that meet the user's interests are screened out from the rating list, and relevant books are recommended on the page.

[0049] Refer to Figure 6 , and it can also display a ranking list on the terminal page according to the ratings: Step SF1: Obtain the rating list of each user; Step SF2: Rank the books of each category based on the rating list of each user; Step SF3: Display the ranking list on the human-computer interaction interface based on the book category ranking.

[0050] Specifically, record the rating situations of each user for each book category, generate the rating list of each user. For each book category, calculate the average rating or total rating of the books in this category according to the rating situations of all users, sort them according to the average rating or total rating of each book category, obtain the ranking of each book category, and display the ranking list of each book category on the user interface, which can be arranged from high to low according to the ratings. Users can view the ranking situations of each book category and understand which categories of books are more popular.

[0051] This application provides a digital cultural book management system.

[0052] A digital cultural book management system includes: An information acquisition module for acquiring user reading information; A preference information generation module for generating user preference information based on user reading information; A book library acquisition module for acquiring a digital cultural book library; A personalized recommendation module for making personalized recommendations based on the digital cultural book library and user preference information.

[0053] This application provides an intelligent terminal, adopting the following technical solution: An intelligent terminal includes a memory and a processor, and a computer program capable of being loaded and executed by the processor for the above digital cultural book management method is stored on the memory.

[0054] This application provides a computer-readable storage medium, adopting the following technical solution: A computer-readable storage medium stores a computer program that can be loaded and executed by a processor to perform any of the above digital cultural book management methods.

[0055] The implementation principle of a digital cultural book management method, system, terminal and medium in an embodiment of this application is as follows: personalized recommendations are generated based on the user's reading information and preferences, which can more accurately match the user's interests and reading habits. Such recommendations not only improve the efficiency of users discovering new books, but also increase the user's satisfaction with the recommended books, thus maintaining the user's reading interest. Among them, based on the user preference information, the system can recommend book content and themes suitable for different users' preferences, making the reading suggestions more personalized and targeted, and avoiding the limitations of traditional general recommendations.

[0056] The above are all preferred embodiments of this application. Without restricting the protection scope of this application accordingly, therefore: Any equivalent changes made according to the structure, shape, and principle of this application shall be covered within the protection scope of this application.

Claims

1. A digital cultural book management method, characterized by: include: Get user reading information; Generate user preference information based on user reading information; Access to digital cultural book collections; Personalized recommendations are made based on the digital cultural library and user preference information.

2. A digital cultural book management method according to claim 1, characterized in that: The method for generating user preference information based on user reading information includes: Acquire user reading information, wherein the user reading information includes the types of books read by the user, the frequency and time of reading each type of books; Calculating the added value of each book category based on user reading information and additional parameters, wherein the frequency and time of reading each type of book are positively correlated with the added value; Arrange the order of all book categories based on their added value; Generate user preference information based on the order of all book categories.

3. A digital cultural book management method according to claim 1, characterized in that: The method further comprises: Get information about books purchased by users; Generate user preference information based on user book purchase information; Access to digital cultural book collections; Personalized recommendations are made based on the digital cultural library and user preference information.

4. A digital cultural book management method according to claim 1, characterized in that: The method for obtaining user reading information comprises: Get login instructions; Display login controls on the human-computer interaction interface based on login instructions; Get the trigger instruction of the login control; Log in to the target user account based on the trigger instruction of the login control; Get the user's reading information based on the target user account.

5. A digital cultural book management method according to claim 1, characterized in that: The method further comprises: Get scoring instructions; Generate multiple book category controls based on rating instructions; Get the trigger instruction of the book type control; Generate a rating box for the book category on the human-computer interaction page based on the trigger instruction of the book category control; Get the ratings for each book category; Generate a rating list based on the ratings of each book category; Make personalized recommendations based on the rating list.

6. A digital cultural book management method according to claim 5, characterized in that: The step of generating a rating list based on the rating of each book category includes: Get the rating list of each user; Ranking books in each category based on each user's rating list; The ranking list is displayed on the human-computer interaction interface based on the book category ranking.

7. A digital cultural book management method according to claim 1, characterized in that: The steps of performing personalized recommendation based on the digital cultural book library and user preference information include: Obtain cultural book categories based on the digital cultural book library; Based on the cultural book categories and user preference information, the user preference information is correlated with the cultural book categories and a correlation table is generated; Based on the association table, a personalized recommended book list is displayed on the human-computer interaction interface.

8. A digital cultural book management system, characterized by: include: The information acquisition module is used to obtain user reading information; A preference information generating module, used for generating user preference information based on user reading information; The module for obtaining book library is used to obtain the digital cultural book library; The personalized recommendation module is used to make personalized recommendations based on the digital cultural book library and user preference information.

9. An intelligent terminal, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and execute a digital cultural book management method as claimed in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: A computer program is stored which can be loaded by a processor and execute a digital cultural book management method as claimed in any one of claims 1 to 7.

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