Book recommendation method and device, equipment, storage medium and program product

Abstract

The embodiment of the invention relates to a book recommendation method and device, equipment, a storage medium and a program product. The method comprises the following steps: acquiring a plurality of unread chapter contents of a target book, and determining target chapter contents from the unread chapter contents; generating book recommendation content based on the target chapter content; if the current moment reaches the moment corresponding to the preset attenuation point of the reading interest curve, displaying the book information of the target book and the book recommendation content in a first page; the reading interest curve represents the situation that the reading interest of the book is attenuated along with time. Therefore, the target book is recommended more timely, the interest degree of the user in the target book is improved again, the user is prompted to continue reading the target book, and the reading rate of the target book is improved.

Description

Technical Field

[0001] The present disclosure relates to the technical field of electronic books, and in particular to a book recommendation method, apparatus, device, storage medium and program product. Background Art

[0002] As e-books become more and more popular, there are more and more e-books on the Internet. Book applications / webpages / applets and other clients have launched book recommendation solutions to recommend e-books that users may be interested in. After a user starts reading a recommended e-book, the user may lose interest in reading the book for various reasons, eventually causing the user to stop reading the book, resulting in a lower reading rate of the book. Summary of the invention

[0003] In order to solve the above technical problems, the embodiments of the present disclosure provide a book recommendation method, apparatus, device, storage medium and program product.

[0004] In a first aspect, an embodiment of the present disclosure provides a book recommendation method, the method comprising:

[0005] Acquire multiple unread chapter contents of a target book, and determine the target chapter content from the unread chapter contents;

[0006] Generate book recommendation content based on the target chapter content;

[0007] If the current moment reaches the moment corresponding to the preset attenuation point of the reading interest curve, the book information of the target book and the book recommendation content are displayed on the first page; wherein the reading interest curve represents the decay of the reading interest of the book over time.

[0008] In a second aspect, the present disclosure also provides a book recommendation device, the device comprising:

[0009] A target chapter content determination module is used to obtain a plurality of unread chapter contents of a target book and determine the target chapter content from each of the unread chapter contents;

[0010] A book recommendation content generation module, used to generate book recommendation content based on the target chapter content;

[0011] The book recommendation content display module is used to display the book information of the target book and the book recommendation content on the first page if the current moment reaches the moment corresponding to the preset attenuation point of the reading interest curve; wherein the reading interest curve represents the situation in which the reading interest of the book decays over time.

[0012] In a third aspect, an embodiment of the present disclosure further provides an electronic device, the electronic device comprising:

[0013] processor;

[0014] A memory for storing executable instructions;

[0015] The processor is used to read executable instructions from the memory and execute the executable instructions to implement the book recommendation method described in any embodiment of the present disclosure.

[0016] In a fourth aspect, an embodiment of the present disclosure further provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the processor implements the book recommendation method described in any embodiment of the present disclosure.

[0017] In a fifth aspect, an embodiment of the present disclosure further provides a computer program product, which is used to execute the book recommendation method described in any embodiment of the present disclosure.

[0018] The book recommendation method, apparatus, device, storage medium and program product of the embodiments of the present disclosure can obtain the contents of multiple unread chapters of a target book, and determine the contents of a target chapter from the contents of each unread chapter; generate book recommendation contents based on the contents of the target chapter; if the target unread time corresponding to the preset attenuation point of the reading interest curve is reached at the current moment, the book information and book recommendation contents of the target book are displayed on the first page; the reading interest curve represents the decay of the reading interest of a book over time; according to the rule that the user's reading interest in a book decays as the time of stopping reading increases, at the preset attenuation point of the reading interest curve, the target book that the user has read is recommended to the user again, so that the user is reminded of the target book again before the user has a high probability of forgetting the read content of the target book, thereby preventing the user from completely forgetting the target book and providing a good memory basis for the book content for subsequent users to continue reading the target book; and by displaying the book recommendation contents, the user is conveyed the main contents of the unread part of the target book, thereby further enhancing the user's interest in the target book, prompting the user to continue reading the target book, thereby improving the reading rate of the target book.

[0019] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in the embodiments of the present disclosure are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards of relevant countries and regions, and provide corresponding operation entrances for users to choose to authorize or refuse. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. Throughout the accompanying drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic and that components and elements are not necessarily drawn to scale.

[0021] Figure 1 A flowchart of a book recommendation method provided by an embodiment of the present disclosure;

[0022] Figure 2 A schematic diagram of a reading interest curve provided by an embodiment of the present disclosure;

[0023] Figure 3 A schematic diagram of displaying book recommendation content in a bookshelf page provided in an embodiment of the present disclosure;

[0024] Figure 4 A schematic diagram of displaying book recommendation content in another bookshelf page provided in an embodiment of the present disclosure;

[0025] Figure 5 A schematic diagram of the structure of a book recommendation device provided by an embodiment of the present disclosure;

[0026] Figure 6 A schematic diagram of the structure of an electronic device provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0027] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as being limited to the embodiments described herein, which are instead provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not intended to limit the scope of protection of the present disclosure.

[0028] It should be understood that the various steps described in the method embodiments of the present disclosure may be performed in different orders and / or in parallel. In addition, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present disclosure is not limited in this respect.

[0029] The term "including" and its variations used herein are open inclusions, i.e., "including but not limited to". The term "based on" means "based at least in part on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". The relevant definitions of other terms will be given in the following description.

[0030] It should be noted that the concepts such as "first" and "second" mentioned in the present disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0031] It should be noted that the modifications of "one" and "plurality" mentioned in the present disclosure are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0032] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0033] The book client in the related art will recommend e-books that the user may be interested in. After the user reads a certain amount of content in a recommended e-book, the user may stop reading the book midway due to various reasons such as not having time to read or the update progress of serialized books is too slow. As the time of stopping reading becomes longer and longer, the user may gradually reduce or even lose interest in reading the book, and eventually stop reading the book. However, given that the user has a certain amount of historical reading records of the book or has been added to the user's bookshelf, the client will not continue to recommend the book to the user. In this way, the book will eventually be forgotten by the user, resulting in a lower reading rate of the book.

[0034] Based on the above situation, the embodiment of the present disclosure provides a book recommendation solution, which formulates a secondary distribution book recommendation strategy for target books that have user reading records, so that when it is determined that the length of time that the user has not read the target book triggers an obvious reading interest decline point on the reading interest curve, the target book can be recommended to the user again in a timely manner, so as to enable the user to continue reading the target book as much as possible while still remembering what he has read, thereby improving the reading rate of the target book.

[0035] The book recommendation method provided in the embodiment of the present disclosure can be applied to the scenario of electronic book recommendation. The method can be performed by a book recommendation device, which can be implemented by software and / or hardware, and the device can be integrated in an electronic device where a client with a book reading function (such as a book application, a browser, an application that can load a small program, etc.) is located. The electronic device can include but is not limited to a smart phone, a personal digital assistant (PDA), a tablet PC (Tablet Personal Computer, Tablet PC), a wearable device, a smart home device such as a digital TV, a laptop or a desktop computer, etc.

[0036] Figure 1 FIG. 2 is a flow chart of a book recommendation method provided by an embodiment of the present disclosure. Figure 1 As shown, the book recommendation method may include the following steps:

[0037] S110: Acquire multiple unread chapter contents of a target book, and determine target chapter contents from the unread chapter contents.

[0038] The target book is a book with historical reading behavior that the user has not read to the end of the book (i.e., has not finished reading), and is a book to be redistributed. The unread chapter content is the book content of the unread chapters in the target book. The target chapter content is one of the multiple unread chapter contents, and is the unread chapter content that is more likely to arouse the user's interest in continuing to read the book.

[0039] Specifically, the electronic device may predetermine target books that are likely to be redistributed to the current user, and then extract the contents of unread chapters from the target book according to the most recent historical reading progress in the historical reading behavior corresponding to the target book, that is, obtain multiple unread chapter contents.

[0040] Then, the electronic device can select a high-quality dimensional chapter content that is more likely to arouse the user's reading interest from the obtained unread chapter contents as the target chapter content. For example, the electronic device can evaluate each unread chapter content from the perspective of content quality (whether the content is detailed, whether the writing is fluent, whether the plot development is reasonable, etc.), and obtain an unread chapter content with the highest content quality evaluation value as the target chapter content. Content quality assessment can be implemented using models or algorithms in related technologies. For another example, the electronic device can select the one with the best feedback results from each unread chapter content based on the user's feedback results on the unread chapter content (such as comments, notes, number of readings, etc.), as the target dimensional chapter.

[0041] In some embodiments, S110 includes: determining target chapter content from each unread chapter content based on the chapter comment information.

[0042] The chapter review information is the review information corresponding to the content of a chapter of the book. The review information may include the review content, the number of reviews, whether the review content is a positive review praising the chapter content or a negative review devaluing the chapter content, etc. The review content here can be at least one of short reviews, long reviews, discussion content, secondary creation content based on the chapter content, and fan fiction. The short reviews and / or long reviews here can be all the review content, or they can be the key review content extracted according to the importance of the review, or they can be the popular review content extracted according to the interactive data of the review, etc.

[0043] Specifically, the electronic device can select high-quality chapters based on the degree of attention paid to the chapter content by most users, so that the target chapter content obtained by screening is more in line with the reading interests of most users, and high-quality chapters recognized by most users can be screened out. Therefore, the electronic device can obtain chapter comment information that is almost available for each unread chapter content. Then, by analyzing the chapter comment information, the most suitable high-quality target chapter content is screened out.

[0044] In some embodiments, the above-mentioned determining the target chapter content from each unread chapter content based on the chapter comment information includes: determining at least one candidate chapter content from each unread chapter content based on the chapter comment information; and determining the candidate chapter content with the smallest number of chapters between it and the historical reading progress of the target book as the target chapter content.

[0045] The candidate chapter contents are high-quality chapter contents among the unread chapter contents.

[0046] Specifically, the electronic device can filter out one or more high-quality unread chapter contents, called candidate chapter contents, according to the chapter comment information of each unread chapter content. Although these candidate chapter contents are all high-quality chapters, they are not necessarily chapters that can arouse the user's interest in reading. Therefore, the electronic device can filter again from them. In view of the fact that the user still has a certain memory of the historical reading content, the content related to the memory is more likely to arouse the user's interest in continuing to read books. Based on this, the electronic device can obtain the most recent historical reading progress of the target book and determine its corresponding chapter identification. Then, the candidate chapter content with the smallest difference in the number of chapters between its chapter identification and the chapter identification of the historical reading progress is selected from multiple candidate chapter contents as the target chapter content. That is, the target chapter content is the content of the next high-quality chapter next to the chapter where reading is stopped. In this way, the user's memory of the historical reading content and the continuity of the book content can be used to obtain the target chapter content that is more likely to arouse the user's interest in continuing to read, thereby improving the success rate of subsequent secondary recommendation of target books.

[0047] In some embodiments, the above-mentioned determining at least one candidate chapter content from each unread chapter content based on chapter comment information includes: determining the number of chapter comments corresponding to the unread chapter content and the proportion of positive comments in each chapter comment; if the number of comments on any unread chapter content exceeds a preset number, and the proportion of comments exceeds a preset proportion, the corresponding unread chapter content is determined as the candidate chapter content.

[0048] The preset number is a preset value corresponding to the critical value of the number of comments on the high-quality chapters. The preset ratio is a preset ratio value corresponding to the critical value of the ratio of positive comments on the high-quality chapters.

[0049] Specifically, considering that the better the chapter content, the more comments the user posts, and the more positive comments there are, in this embodiment, the number of chapter comments corresponding to each unread chapter content (i.e., the number of comments) can be counted and compared with the preset number. If the number of comments does not exceed the preset number, it means that the unread chapter content is not of high interest to the user and is not a high-quality chapter, and the unread chapter content is filtered out.

[0050] If the number of comments exceeds the preset number, it means that the unread chapter content is sufficiently concerned by the user, and it may belong to a high-quality chapter. Then, the natural language model in the relevant technology can be further used to understand the content of all the comments on the unread chapter content to determine whether each comment content belongs to a positive comment or a negative comment. After that, the proportion of positive comments in all comments (i.e., the comment proportion) is calculated. If the comment proportion does not exceed the preset proportion, it means that although the unread chapter content has more users paying attention, most of the comments are negative comments, indicating that these users are not optimistic about the chapter content, then the unread chapter content does not belong to a high-quality chapter, and the unread chapter content is filtered out. On the contrary, if the comment proportion exceeds the preset proportion, it means that the unread chapter content not only has more users paying attention, but also these users are optimistic about the chapter content, then the unread chapter content belongs to a high-quality chapter, and it can be determined as a candidate chapter content. In this way, the high-quality chapter content can be screened out by the user's positive attention, and the degree of fit between the target chapter content of the subsequent screening and the user's reading interest can be further improved.

[0051] It should be noted that the electronic device can mark the candidate chapters obtained by the above screening in the catalog page of the target book to mark them as high-quality chapters, such as "high quality", "positive comments" or their corresponding icons, etc. This can provide a basis for users to locate chapters of their interest, thereby improving the user's reading experience.

[0052] In some embodiments, before S110 , the method may also predetermine the target book in the following manner: select a book that meets a preset condition from a plurality of candidate books and determine it as the target book.

[0053] The preset conditions include that the book has not been read to the end and there is preset reading behavior data. The preset reading behavior data includes behavior data of stopping reading after the number of chapters read in the past exceeds the set number of chapters and / or behavior data of stopping reading after the reading time in the past exceeds the preset time.

[0054] Specifically, the electronic device can pre-screen the target book from the candidate books corresponding to the user. The candidate books are the books that the user has added to the bookshelf and / or has the user's historical reading records. That is, the candidate books are the books that the user has a certain degree of attention / interest.

[0055] In order to improve the success rate of secondary book recommendations and reduce interference to users. The electronic device can further extract reading behavior data corresponding to the candidate books from the reading behavior data. Then, the books corresponding to the preset reading behavior data are screened from these reading behavior data. The preset reading behavior data, whether the user has read more chapters of the candidate book, or the user has read the candidate book continuously or occasionally for a long time, indicates that the user has a stronger interest in the candidate book, but has not continued to read the candidate book recently, then the candidate book can be determined as the target book. In this way, the books that the user is more interested in but has interrupted reading can be automatically screened for the user, so that the target book can be recommended to the user later, avoiding the process of the user searching for the book again by himself, and improving the convenience of the user to find the target book, thereby improving the user experience and the reading rate of the target book.

[0056] S120: Generate book recommendation content based on the target chapter content.

[0057] Among them, the book recommendation content is the reason for recommending the book again.

[0058] Specifically, according to the above description, the target chapter content is the book content that is likely to cause the user to continue reading the target book. However, the content of a chapter is often long, which is not suitable for simple display as a recommendation reason for the book, nor is it conducive to the user quickly obtaining the recommendation reason for the recommended book. Therefore, the electronic device can extract and organize the information of the target chapter content to obtain more concise book recommendation content.

[0059] In some embodiments, the electronic device may use a key information extraction algorithm in related technologies to automatically extract the core content from the target chapter content as book recommendation content.

[0060] In some other embodiments, S120 includes: extracting key content of at least one preset dimension from the target chapter content as book recommendation content.

[0061] The preset dimension is a pre-set information dimension, which is a content dimension determined based on the reading behavior data or reading preference settings of multiple users and can reflect the user's reading interest. Exemplarily, the preset dimension includes at least a plot dimension and / or a character dimension.

[0062] Specifically, the electronic device can extract information from the target chapter content from the plot dimension to obtain concise book recommendation content related to the plot of the target book. For example, the electronic device can use the natural language model in the relevant technology to analyze the target chapter content to output the storyline contained therein. The storyline can be a climax / hot plot in the target chapter content, or an important plot with a turning point or continuity in the target chapter content that has a story development context, or a plot with a conflict / contradiction relationship between characters or between characters and the environment, or a key plot with suspense or foreshadowing, etc. The above-mentioned natural language model is obtained by training in advance using relevant content of various representative novel plots. In this way, when the user has a reading preference in terms of the plot, the book recommendation content of the target book can be made more in line with the user's preference, further improving the user's interest to a certain extent, and then further improving the reading rate of the target book to a certain extent.

[0063] In addition, the electronic device can also extract information from the target chapter content from the role dimension to obtain book recommendations related to the role. For example, the electronic device can match the target chapter content according to the roles involved in the target book, popular roles that many users like, or key roles that appear in the content of the read book, so as to extract relevant information about the roles that the user may be interested in and that are contained in the target chapter content. In this way, when the user has a reading preference in terms of roles, the book recommendations of the target book can be made more in line with the user's preferences, which can also further improve the user's interest and the reading rate of the target book.

[0064] S130: If the current moment reaches the target unread time corresponding to the preset decay point of the reading interest curve, the book information and book recommendation content of the target book are displayed on the first page.

[0065] The reading interest curve represents the decline of interest in reading books over time. Figure 2 As shown, the reading interest curve can be presented as a curve graph of user retention rate and the length of time after stopping reading. The preset attenuation point is a pre-set point on the reading interest curve where the user's interest in reading decreases significantly. In one example, the preset attenuation point is a point artificially configured in advance based on the characteristics of the curve. For example, the preset attenuation point can be directly set to the point on the curve corresponding to the xth day after stopping reading. In another example, the preset attenuation point is a point in the reading interest curve where the rate of change of the absolute value of the slope exceeds the preset rate of change. Figure 2, the point with a larger change rate of the absolute value of the slope in the reading interest curve indicates that the user's reading interest has obviously decreased. Therefore, a slope change rate, i.e., a preset change rate, can be set in advance. Then, the electronic device can compare the change rate of the absolute value of the slope at each point in the reading interest curve with the preset change rate, and filter out the points that exceed the preset change rate, such as Figure 2 The points on the curve corresponding to the 8th, 15th and 22nd days can be used as preset attenuation points. This can more automatically determine the moment when the user's reading interest changes and improve the timeliness of the second recommendation of books.

[0066] Among them, the first page is a pre-selected page related to books so that relevant information of recommended books can be displayed. Exemplarily, the first page includes at least one of a bookshelf page, a book recommendation page, a book screening page and a book reading page. The book recommendation page is a page in the client that is mainly used to recommend books, for example, it can be a bookstore page, the homepage of the client, etc. The book screening page is a page that provides a book screening function. The book reading page is a page of a reader module that displays the content of a book, for example, it can be a page corresponding to the end of the book (referred to as the last page of the book). Book information is relevant information that introduces the target book. Given that the target book is a book that the user has read in the past and the user has a certain degree of understanding of it, the book information can be simple information to distinguish the book. For example, the book information can be basic information such as pictures, titles, authors, etc. of the target book.

[0067] Specifically, after the electronic device obtains the book information and book recommendation content of the target book, it can obtain the current moment in real time, and calculate the time difference between the current moment and the historical reading moment corresponding to the most recent historical reading progress as the unread duration. Then, the unread duration is compared with the unread duration corresponding to the preset decay point of the reading interest curve (i.e., the target unread duration). If the unread duration corresponding to the current moment does not reach the target unread duration, it means that the time for the user to not read the target book is relatively short and has not reached the time for the user's interest to decrease. At this time, pushing the target book again may interfere with the user, so it is not recommended, but continues to execute S130. If the unread duration corresponding to the current moment reaches the target unread duration, it means that the time for the user to not read the target book has triggered a point where the reading interest has obviously decreased, then the target book can be recommended to the user again, that is, the book information and book recommendation content of the target book are packaged and placed in the first page. The display position and display style of the book information and book recommendation content in the first page can be unrestricted.

[0068] It should be noted that if there are multiple preset attenuation points, the electronic device can perform judgment and target book recommendation processing according to the above process for each preset attenuation point. Figure 2For example, when the unread time corresponding to the current moment reaches the 8th day, the book information and book recommendations of the target book are displayed once on the first page, and the prompt "unread time is up to 8 days" can be superimposed. Then, as time goes by, when the unread time corresponding to the current moment reaches the 15th day, the book information and book recommendations of the target book are displayed for the second time on the first page, and the prompt "unread time is up to 15 days" can be superimposed. After that, as time goes by, when the unread time corresponding to the current moment reaches the 22nd day, the book information and book recommendations of the target book are displayed for the third time on the first page, and the prompt "unread time is up to 22 days" can be superimposed. After that, it can be considered that the user has completely lost interest in reading the target book, and the target book will no longer be recommended. In this way, the target book will have multiple recommendation processes until it is determined that the user is completely uninterested in it, and then it will no longer be recommended to avoid disturbing the user.

[0069] It should also be noted that in the above process, if the user starts to read the target book continuously after repeatedly recommending the target book, the stop reading time of the target book can be reset to zero to restart the overall process of the book recommendation method for the target book.

[0070] In some embodiments, “displaying the book information and the book recommendation content of the target book on the first page” in S130 includes: displaying the book information and the book recommendation content in a preset area on the first page.

[0071] Specifically, see Figure 3 If the first page is a bookshelf page 300 or a book recommendation page such as a bookstore, the electronic device can display a content display control 310 in the top area of ​​the bookshelf page, and display the book information and book recommendation information of the target book in the display area of ​​the content display control 310, such as "the unread chapters of the books to be updated will have ** plots / ** characters" etc. In addition, in order to improve the convenience of the user to continue reading the target book, the interactive controls corresponding to the book reading function can be displayed in the preset area or its surrounding positions, such as Figure 3 The user can trigger the "read" control 320 to jump directly from the bookshelf page 300 to the book reading page of the reader of the target book, so that the user can continue to read the target book from the most recent historical reading progress.

[0072] See also Figure 4 If the first page is a bookshelf page or a book recommendation page 400, the electronic device can arrange and display multiple recommended books in the book recommendation page 400. At the first or second book arrangement position, the electronic device can display the secondary distribution target book 410, and the remaining book arrangement positions still display other recommended books 420 according to the original book recommendation order. Figure 4 As can be seen in the figure, the electronic device can replace the recommendation reason in the target book 410 with the book recommendation content of the target book, such as "Books to follow, unread chapters will have ** plots / ** characters", while other recommended books 420 still display their original book introductions or recommendation reasons, such as "xxxxxxxxxxxxxxxxxxxxxxxxxxxxxx".

[0073] If the first page is a book reading page, the electronic device may display the book information and book recommendation information of the target book in an area of ​​the page that displays recommended content.

[0074] In some embodiments, the reading interest curve is obtained in the following manner: displaying book information and test recommendation content of multiple test books with different unread time and not read to the end of the book on the first page of multiple clients; determining the click rate of each test book, and constructing a corresponding relationship between the unread time and the click rate; generating a reading interest curve based on the corresponding relationship.

[0075] Specifically, the process of constructing a reading interest curve may be: push to the first page of the client of multiple users the unread test books that the corresponding users have read in the past and have stopped reading, and the distribution of the unread time of these test books when they stopped reading may be different. For example, push test books whose unread time is in the range of x1 to x2 to multiple users. Then, collect the click behaviors of these users on which test books they viewed or read, and count the click rates of test books corresponding to different unread time. Afterwards, the click rate corresponding to the unread time can be used as the retention rate of the corresponding user, and construct the following. Figure 2 The reading interest curve shown in the figure can make the reading interest curve more consistent with the reading behavior of online users, improve the accuracy of the reading interest curve, and thus improve the timeliness of the target books recommended based on it, thereby further improving the recommendation success rate of the target books and the reading rate of the target books.

[0076] The book recommendation method provided by the embodiment of the present disclosure can obtain the contents of multiple unread chapters of the target book, and determine the contents of the target chapter from the contents of each unread chapter; generate book recommendation contents based on the contents of the target chapter; if the current moment reaches the target unread time corresponding to the preset attenuation point of the reading interest curve, the book information and book recommendation contents of the target book are displayed on the first page; the reading interest curve represents the decay of the reading interest of the book over time; according to the rule that the user's reading interest in the book decays as the time of stopping reading increases, at the preset attenuation point of the reading interest curve, the target book that the user has read is recommended to the user again, so that the user is reminded of the target book again before the user has a high probability of forgetting the read content of the target book, thereby preventing the user from completely forgetting the target book, and providing a good memory basis for the book content for subsequent users to continue reading the target book; and by displaying the book recommendation content, the user is conveyed the main contents of the unread part of the target book, thereby further enhancing the user's interest in the target book, prompting the user to continue reading the target book, thereby improving the reading rate of the target book.

[0077] The following is an embodiment of a book recommendation device provided by an embodiment of the present invention. The device and the book recommendation methods of the above embodiments belong to the same inventive concept. For details not described in detail in the embodiment of the book recommendation device, reference can be made to the embodiment of the above book recommendation method.

[0078] Figure 5 FIG. 2 shows a schematic diagram of the structure of a book recommendation device provided by an embodiment of the present disclosure. Figure 5 As shown, the book recommendation device 500 may include:

[0079] The target chapter content determination module 510 is used to obtain a plurality of unread chapter contents of the target book and determine the target chapter content from the unread chapter contents;

[0080] A book recommendation content generating module 520 is used to generate book recommendation content based on the target chapter content;

[0081] The book recommendation content display module 530 is used to display the book information and book recommendation content of the target book on the first page if the current moment reaches the moment corresponding to the preset decay point of the reading interest curve; wherein the reading interest curve represents the decay of the reading interest of the book over time.

[0082] The book recommendation device provided by the embodiment of the present disclosure can obtain the contents of multiple unread chapters of a target book, and determine the contents of a target chapter from the contents of each unread chapter; generate book recommendation contents based on the contents of the target chapters; if the current moment reaches the target unread time corresponding to the preset decay point of the reading interest curve, the book information and book recommendation contents of the target book are displayed on the first page; the reading interest curve represents the decay of the reading interest of a book over time; according to the rule that the user's reading interest in a book decays as the time of stopping reading increases, at the preset decay point of the reading interest curve, the target book that the user has read is recommended to the user again, so that the user is reminded of the target book again before the user has a high probability of forgetting the read content of the target book, thereby preventing the user from completely forgetting the target book and providing a good memory basis for the content of the book for subsequent users to continue reading the target book; and by displaying the book recommendation contents, the user is informed of the main contents of the unread part of the target book, thereby further enhancing the user's interest in the target book, prompting the user to continue reading the target book, thereby improving the reading rate of the target book.

[0083] In some embodiments, the preset attenuation point is a point where the rate of change of the absolute value of the slope in the reading interest curve exceeds a preset rate of change.

[0084] In some embodiments, the book recommendation device 500 further includes a reading interest curve generating module for:

[0085] If the target unread time corresponding to the preset attenuation point of the reading interest curve is reached at the current moment, before displaying the book information and book recommendation content of the target book on the first page, the book information and test recommendation content of multiple test books with different unread time and not read to the end of the book are displayed on the first pages of multiple clients;

[0086] Determine the click-through rate of each test book and build a corresponding relationship between unread time and click-through rate;

[0087] Generate a reading interest curve based on the correspondence.

[0088] In some embodiments, the target chapter content determination module 510 is specifically used to:

[0089] Based on the chapter review information, target chapter content is determined from the unread chapter contents.

[0090] In some embodiments, the target chapter content determination module 510 specifically includes:

[0091] A candidate chapter content determination submodule, used to determine at least one candidate chapter content from each unread chapter content based on the chapter comment information;

[0092] The target chapter content determination submodule is used to determine the candidate chapter content with the smallest number of chapters between the candidate chapter content and the historical reading progress of the target book as the target chapter content.

[0093] In some embodiments, the candidate chapter content determination submodule is specifically used to:

[0094] Determine the number of chapter reviews corresponding to the unread chapter content and the proportion of positive reviews in each chapter review;

[0095] If the number of comments on any unread chapter content exceeds a preset number, and the proportion of comments exceeds a preset proportion, the corresponding unread chapter content will be determined as a candidate chapter content.

[0096] In some embodiments, the book recommendation content generation module 520 is specifically used to:

[0097] Extract key content of at least one preset dimension from the target chapter content as book recommendation content; wherein the preset dimension at least includes a plot dimension and / or a character dimension.

[0098] In some embodiments, the book recommendation apparatus 500 further includes a target book determination module for:

[0099] Before obtaining the contents of multiple unread chapters of a target book, books that meet preset conditions are screened from multiple candidate books to be determined as target books; wherein the preset conditions include not reading to the end of the book and the existence of preset reading behavior data; the preset reading behavior data includes behavior data of stopping reading after the number of chapters read in the history exceeds the set number of chapters, and / or behavior data of stopping reading after the reading time of the history exceeds the preset time.

[0100] In some embodiments, the book recommendation content display module 530 is specifically used to:

[0101] Book information and book recommendation content are displayed in a preset area of ​​a first page; wherein the first page includes at least one of a bookshelf page, a book recommendation page, and a book reading page.

[0102] The book recommendation device provided in the embodiment of the present invention can execute the book recommendation method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0103] It is worth noting that in the embodiment of the above-mentioned book recommendation device, the various units and modules included are only divided according to functional logic, but are not limited to the above-mentioned division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the protection scope of the present disclosure.

[0104] The present disclosure also provides an electronic device, which may include a processor and a memory, wherein the memory may be used to store executable instructions, wherein the processor may be used to read the executable instructions from the memory and execute the executable instructions to implement the book recommendation method in the above embodiment.

[0105] Figure 6 A schematic structural diagram of an electronic device provided by an embodiment of the present disclosure is shown.

[0106] like Figure 6 As shown, the electronic device 600 may include a processing device 601 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 602 or a program loaded from a storage device 608 into a random access memory (RAM) 603. In the RAM 603, various programs and data required for the operation of the electronic device 600 are also stored. The processing device 601, the ROM 602, and the RAM 603 are connected to each other via a bus 604. An input / output interface (I / O interface) 605 is also connected to the bus 604.

[0107] Typically, the following devices may be connected to the I / O interface 605: an input device 606 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; an output device 607 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 608 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 609. The communication device 609 may allow the electronic device 600 to communicate with other devices wirelessly or by wire to exchange data.

[0108] It should be noted that Figure 6 The electronic device 600 shown is only an example and should not limit the functions and scope of use of the embodiments of the present disclosure. Figure 6 The electronic device 600 is shown with various devices, but it should be understood that it is not required to implement or possess all the devices shown. More or fewer devices may be implemented or possessed instead.

[0109] In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a non-transitory computer-readable medium, and the computer program contains program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication device 609, or installed from the storage device 608, or installed from the ROM 602. When the computer program is executed by the processing device 601, the above-mentioned functions defined in the book recommendation method of any embodiment of the present disclosure are executed.

[0110] An embodiment of the present disclosure further provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the processor implements the book recommendation method in any embodiment of the present disclosure.

[0111] It should be noted that the computer-readable medium disclosed above may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, device or device. In the present disclosure, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, in which a computer-readable program code is carried. This propagated data signal may take a variety of forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination of the above. The computer readable signal medium may also be any computer readable medium other than a computer readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer readable medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0112] In some embodiments, the client and server may communicate using any currently known or future developed network protocol such as HTTP, and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), an internet (e.g., the Internet), and a peer-to-peer network (e.g., an ad hoc peer-to-peer network), as well as any currently known or future developed network.

[0113] The computer-readable medium may be included in the electronic device, or may exist independently without being incorporated into the electronic device.

[0114] The computer-readable medium carries one or more programs. When the one or more programs are executed by the electronic device, the electronic device executes the steps of the book recommendation method described in any embodiment of the present disclosure.

[0115] In embodiments of the present disclosure, computer program code for performing the operations of the present disclosure may be written in one or more programming languages ​​or a combination thereof, including but not limited to object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" or similar programming languages. The program code may be executed entirely on a user's computer, partially on a user's computer, as a separate software package, partially on a user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0116] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the equipment, method and computer program product according to various embodiments of the present disclosure. In this regard, each box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0117] The functions described above herein may be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), and the like.

[0118] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0119] The above description is only a preferred embodiment of the present disclosure and an explanation of the technical principles used. Those skilled in the art should understand that the scope of disclosure involved in the present disclosure is not limited to the technical solutions formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above disclosed concept. For example, the above features are replaced with the technical features with similar functions disclosed in the present disclosure (but not limited to) by each other to form a technical solution.

[0120] In addition, although each operation is described in a specific order, this should not be understood as requiring these operations to be performed in the specific order shown or in a sequential order. Under certain circumstances, multitasking and parallel processing may be advantageous. Similarly, although some specific implementation details are included in the above discussion, these should not be interpreted as limiting the scope of the present disclosure. Some features described in the context of a separate embodiment can also be implemented in a single embodiment in combination. On the contrary, the various features described in the context of a single embodiment can also be implemented in multiple embodiments individually or in any suitable sub-combination mode.

[0121] Although the subject matter has been described in language specific to structural features and / or methodological logical actions, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. On the contrary, the specific features and actions described above are merely example forms of implementing the claims.

Claims

1. A book recommendation method, characterized in that: include: Acquire multiple unread chapter contents of a target book, and determine the target chapter content from the unread chapter contents; Generate book recommendation content based on the target chapter content; If the current moment reaches the moment corresponding to the preset attenuation point of the reading interest curve, the book information of the target book and the book recommendation content are displayed on the first page; wherein the reading interest curve represents the decay of the reading interest of the book over time.

2. The method according to claim 1, characterized in that The preset attenuation point is a point where the change rate of the absolute value of the slope in the reading interest curve exceeds a preset change rate.

3. The method according to claim 1 or 2, characterized in that: Before displaying the book information of the target book and the book recommendation content on the first page if the target unread time corresponding to the preset decay point of the reading interest curve is reached at the current moment, the method further includes: Displaying book information and test recommendation contents of a plurality of test books with different unread time lengths and not read to the end of the books on the first pages of the plurality of clients; Determine the click rate of each of the test books, and establish a corresponding relationship between the unread time and the click rate; The reading interest curve is generated based on the corresponding relationship.

4. The method according to claim 1, characterized in that The step of determining the target chapter content from the unread chapter contents includes: Based on the chapter review information, target chapter content is determined from the unread chapter contents.

5. The method according to claim 4, characterized in that The step of determining the target chapter content from the unread chapter contents based on the chapter comment information includes: Based on the chapter review information, determining at least one candidate chapter content from each of the unread chapter contents; The candidate chapter content having the smallest chapter gap with the historical reading progress of the target book is determined as the target chapter content.

6. The method according to claim 5, characterized in that The step of determining at least one candidate chapter content from each of the unread chapter contents based on the chapter comment information includes: Determine the number of chapter reviews corresponding to the unread chapter content and the proportion of positive reviews in each of the chapter reviews; If the number of comments on any of the unread chapter contents exceeds a preset number, and the proportion of the comments exceeds a preset proportion, the corresponding unread chapter content is determined as the candidate chapter content.

7. The method according to claim 1, characterized in that The generating of book recommendation content based on the target chapter content includes: At least one key content of a preset dimension is extracted from the target chapter content as the book recommendation content; wherein the preset dimension at least includes a plot dimension and / or a character dimension.

8. The method according to claim 1, characterized in that Before obtaining the contents of the multiple unread chapters of the target book, the method further includes: Books that meet preset conditions are screened from multiple candidate books and determined as the target books; wherein the preset conditions include not reading to the end of the book and the existence of preset reading behavior data; the preset reading behavior data includes behavior data of stopping reading after the number of chapters read in the past exceeds a set number of chapters, and / or behavior data of stopping reading after the reading time of the past reading exceeds a preset time.

9. The method according to claim 1, characterized in that: The displaying of the book information of the target book and the book recommendation content on the first page includes: The book information and the book recommendation content are displayed in a preset area of ​​the first page; wherein the first page includes at least one of a bookshelf page, a book recommendation page and a book reading page.

10. A book recommendation device, characterized in that: include: A target chapter content determination module is used to obtain a plurality of unread chapter contents of a target book and determine the target chapter content from each of the unread chapter contents; A book recommendation content generation module, used to generate book recommendation content based on the target chapter content; The book recommendation content display module is used to display the book information of the target book and the book recommendation content on the first page if the current moment reaches the moment corresponding to the preset attenuation point of the reading interest curve; wherein the reading interest curve represents the situation in which the reading interest of the book decays over time.

11. An electronic device, characterized in that: include: processor; A memory for storing executable instructions; The processor is used to read the executable instructions from the memory and execute the executable instructions to implement the book recommendation method described in any one of claims 1 to 9.

12. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by a processor, the processor implements the book recommendation method according to any one of claims 1 to 9.

13. A computer program product, characterized in that The computer program product is used to implement the book recommendation method according to any one of claims 1 to 9.

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