A book push method, a book push text generation method, a device and an electronic device

Abstract

The present disclosure provides a book push method, a book push text generation method, a device and an electronic device. The book push method comprises: obtaining a first book, the first book is the book currently being read by the reader, determining a target book in at least one second book according to the relevant features of the first book, the second book and the first book are both written by the same author; determining a recommendation text according to the content of the target book and / or the first book; generating a book push text of the target book according to the recommendation text and the relevant information of the target book; and pushing the book push text to the reader. The method establishes an association with the target book according to the relevant features of the first book currently being read by the reader, and generates a book push text containing the recommendation text. Since the target book recommended in the book push text is relevant to the first book, the pushed target book is more targeted, thereby improving the success rate of book push and ensuring that the number of readers of the pushed book does not decrease.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a book push method, a book push text generation method, a device and an electronic device. Background Art

[0002] E-book reading has replaced traditional paper book reading and has become a popular reading method because of its advantages such as large book storage capacity, convenient carrying, and cost saving. Users can read books, novels, articles and other books anytime and anywhere through mobile phones, tablets, e-books and other devices.

[0003] For a reading app, it is necessary to maintain a certain number of readers and attract more readers to read and use it, and then actively recommend other books to the reader when the reader is about to or has finished reading the current book, such as recommending a new book to the current reader. Currently, the only way to push other books is to display the covers of several other books on the last page or at the end of the current book. This recommendation method is single and cannot effectively attract readers to continue reading, and the book push effect is poor. Summary of the invention

[0004] In order to attract readers to continue reading and improve the efficiency of book recommendation, the embodiments of the present invention provide a book push method, a recommended text generation method, a device and an electronic device. Specifically, the technical solution is as follows:

[0005] In a first aspect, an embodiment of the present invention provides a method for pushing books, the method comprising:

[0006] Obtain a first book, where the first book is the book currently being read by the reader;

[0007] determining a target book from at least one second book according to the relevant features of the first book, wherein the second book and the first book are both written by the same author;

[0008] Determining a recommended text according to the content of the target book and / or the first book;

[0009] A book recommendation text for the target book is generated according to the recommendation text and relevant information of the target book, and the book recommendation text is pushed to the reader.

[0010] In a second aspect, an embodiment of the present invention further provides a method for generating a book recommendation text, the method comprising:

[0011] receiving a book recommendation text, wherein the book recommendation text includes a recommendation text and relevant information of a target book, wherein the target book and the first book are written by the same author;

[0012] Obtaining a relevant position of the first book in an editable area of ​​the display interface;

[0013] The author's editing operation is received, and the book recommendation text is inserted into a relevant position of the first book.

[0014] In a third aspect, an embodiment of the present invention further provides a book pushing device, the device comprising:

[0015] An acquiring unit, configured to acquire a first book, wherein the first book is a book currently being read by the reader;

[0016] a determination unit, configured to determine a target book from at least one second book according to the relevant features of the first book, wherein the second book and the first book are both written by the same author;

[0017] A processing unit, configured to determine a recommended text according to the content of the target book and / or the first book;

[0018] A generating unit, configured to generate a book recommendation text of the target book according to the recommendation text and relevant information of the target book;

[0019] A push unit is used to push the recommended book text to the reader.

[0020] In a fourth aspect, an embodiment of the present invention further provides a device for generating a book recommendation text, the device comprising:

[0021] A receiving unit, configured to receive a book recommendation text, wherein the book recommendation text includes a recommendation text and relevant information of a target book, wherein the target book and the first book are written by the same author;

[0022] An acquisition unit, configured to acquire a relevant position of the first book on an editable area of ​​a display interface;

[0023] The inserting unit is used to insert the book recommendation text into the relevant position of the first book based on the author's editing operation.

[0024] In a fifth aspect, an embodiment of the present invention further discloses an electronic device, comprising a memory and a processor, wherein the memory stores computer program instructions;

[0025] When the processor executes the computer program, the method described in the first aspect or the second aspect is implemented.

[0026] Optionally, the electronic device is a terminal device or a network device, such as a server.

[0027] In addition, optionally, a computer-readable storage medium is also provided, on which a computer program is stored. When the computer program is executed by a processor, the method steps described in the first aspect or the second aspect above can be implemented.

[0028] The book push method provided in the present embodiment determines a target book from a plurality of second books according to relevant features of a first book currently being read by a reader, generates a recommendation text based on the contents of the target book and the first book, and a book push text containing the recommendation text and relevant information of the target book, and finally pushes the book push text to the reader. The present method establishes an association with the target book according to relevant features of the first book currently being read by the reader, and generates a book push text containing the recommendation text according to the contents of the first book and the target book. Since the target book recommended in the book push text is relevant to the first book, the pushed target book is more targeted, thereby improving the success rate of book push and ensuring that the number of readers of the pushed book does not decrease. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0030] Figure 1 An architecture diagram of a network system provided in an embodiment of the present invention;

[0031] Figure 2 A flowchart of a book push method provided in an embodiment of the present invention;

[0032] Figure 3 A flowchart of a method for generating a book recommendation text provided in an embodiment of the present invention;

[0033] Figure 4 A schematic diagram of inserting a book recommendation text at the end of a chapter or at the end provided by an embodiment of the present invention;

[0034] Figure 5 A schematic diagram of an editor recommendation provided in an embodiment of the present invention;

[0035] Figure 6 A schematic diagram of a method for an author to edit and generate a book text provided in an embodiment of the present invention;

[0036] Figure 7 A flowchart of another book push method provided in an embodiment of the present invention;

[0037] Figure 8 It is a structural block diagram of a book pushing device provided in an embodiment of the present invention;

[0038] Fig. 9It is a structural block diagram of a device for generating a book recommendation text provided in an embodiment of the present invention;

[0039] Fig.10 The present invention is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0040] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0041] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0042] The technical solution of the embodiments of the present application is described in detail below.

[0043] The present application embodiment provides a method for pushing books. The method can be applied to a Figure 1 The network system shown in Figure 1 , the system includes: a terminal device 100 and a server 200. The terminal device 100 and the server 200 can be connected to each other through a network 300, and the server 200 can be used to provide services (such as application services, etc.) for the terminal device or the client installed on the terminal. A database can be set on the server 200 or independently of the server 200 to provide data storage services for the server 200. In addition, a processing engine can be run in the server 200, and the processing engine can be used to execute the steps executed by the server 200.

[0044] Optionally, the terminal device 100 may be, but is not limited to, a terminal that can calculate data, such as a mobile terminal (e.g., a mobile phone, a tablet computer), a laptop, a PC (Personal Computer), etc. The network 300 may include, but is not limited to, a wireless network or a wired network. The wireless network includes: Bluetooth, WIFI (Wireless Fidelity) and other networks that implement wireless communication. The wired network may include, but is not limited to: a wide area network, a metropolitan area network, and a local area network. The server 200 may include, but is not limited to, any hardware device that can perform calculations.

[0045] In addition, in this embodiment, the above search method can also be applied to an independent processing device with strong processing capabilities, but not limited to, without data interaction. For example, the processing device can be, but not limited to, a terminal device with strong processing capabilities, that is, each operation in the above book push method can be integrated in an independent processing device. The above is only an example, and this embodiment does not make any limitation to this.

[0046] Optionally, in this embodiment, the above-mentioned book push method and book push text generation method can be executed by the server 200, or by the terminal device 100, or by the server 200 and the terminal device 100. Among them, the terminal device 100 executes the book push method and book push text generation method of the embodiment of the present application, or it can be executed by the client installed thereon.

[0047] This embodiment takes the operation on the server 200 as an example. Figure 2 is a flow chart of a book push process provided according to an embodiment of the present application, such as Figure 2 As shown, the process of the method may include the following steps:

[0048] Step 101: Obtain a first book, where the first book is the book currently being read by the reader.

[0049] For example, the reader reads the first book through an e-book APP on a terminal device. The first book is any book that can be provided by the e-book APP.

[0050] Step 102: determining a target book from at least one second book according to the relevant features of the first book, wherein the second book and the first book are written by the same author.

[0051] The relevant features of the first book include information such as the book content, book type, and reader comments of the first book. The at least one second book may be a completed book or a book in serialization.

[0052] Specifically, step 102 includes: determining a book that is identical or similar to the first book in at least one second book according to the relevant features of the first book as the target book. For example, the relevant features of the first book (such as book content, book type, reader review content) can be represented by attribute values, each second book also corresponds to an attribute value, and according to the attribute value of the first book and the attribute value of at least one second book, if the attribute values ​​calculated by a preset algorithm are identical or similar, the target book can be determined.

[0053] For example, the first attribute value represents the content of the first book. For example, if the first book is a work, such as a certain version of "Dream of Red Mansions", then a book with the same / similar first attribute value is searched in at least one book. For example, after searching, it is determined that the target book is other versions of "Dream of Red Mansions", or books related to its content such as comments related to "Dream of Red Mansions" and Zhi Yanzhai's comments on "Dream of Red Mansions".

[0054] For another example, the second attribute value represents the book type of the first book. If the first book is a fantasy novel and its corresponding attribute value is "01", then a second book with an attribute value of "01" is searched for in the attribute values ​​corresponding to at least one second book, and the second book is used as the target book.

[0055] For another example, the third attribute value represents the content information of the reader's review of the first book. For example, the third attribute value is determined based on the comprehensive score of the reader after reading, such as 7.5 points (out of 10 points), and then a book with a higher third attribute value is selected from at least one second book as the target book. The attribute value corresponding to each second book can be determined by the platform based on factors such as the reader's impression, comments, and ratings, or can be calculated by an algorithm after statistics of all reader ratings. This embodiment does not limit the specific scoring method.

[0056] Step 103: Determine a recommended text according to the content of the target book and / or the first book.

[0057] The recommendation text may be determined based on the content, comments, related post content, etc. of the first book and / or the target book, and the recommendation text is used to generate a book recommendation text. The recommendation text may be in the form of text, pictures, cards, animations, etc.

[0058] Optionally, an implementation method includes: based on the content of the first book, extracting highlights, chapters or comments from the first book, and generating the book recommendation text through editing and processing by the author. For example, the following content is extracted from the first book: "There are nine states on the earth, and nine fields in the sky. What are the nine fields? One is the planets inside and outside the solar system, the other is the Kuiper belt and the Oort cloud, ..." and other content as part of the recommendation text. Furthermore, the method of extracting part of the content from the first book can be actively selected by the author, or the chapters and paragraphs in the first book that are forwarded or commented on by readers the most are used as the recommendation text.

[0059] Similarly, in the target book, chapter contents, readers' excellent comments, story plots and reasoning in related posts and forums, etc. can also be selected as the recommended text.

[0060] Step 104: Generate a book recommendation text for the target book based on the recommendation text and relevant information of the target book.

[0061] The target book related information includes: the title of the target book, the type of the target book, the content of the book, etc. In this step, a recommendation text of the target book is generated according to the recommendation text, the title or content, type, summary and introduction of the target book.

[0062] For example Figure 3 As shown in (a) in the figure, according to the recommendation text, the content of the recommendation text includes: the new book "XXX XXX Book" has been put on the shelves, please support it. In the long years of life, the ups and downs of personal destiny are directly subject to the influence of the times, ..., pushing history forward like a long river. The recommendation text can be generated by the above step 103. In addition, the type of the target book is also obtained, such as the type of ancient romance, the title and cover of the target book, and the book recommendation text of "XXX XXX Book" is generated according to the above recommendation text and the relevant information of the target book, such as Figure 3 as shown in (b).

[0063] Optionally, the book recommendation text may be a book recommendation card or a recommendation tag, which is not limited in this embodiment.

[0064] Step 105: Push the recommended book text to the reader.

[0065] A specific implementation method is to automatically insert the book recommendation text into the relevant position of the first book based on the author's insertion operation at the relevant position of the first book, and display and push it to the readers.

[0066] Wherein, the relevant position of the first book includes the end of the first book or the end of the final chapter. Figure 4As shown, at the end of the first book, such as when the progress of the first book reaches 99.99%, or on the last page of the first book, below the comment area, the book recommendation text is inserted, such as the book recommendation card "Author has something to say".

[0067] It should be understood that the book recommendation text may also be inserted into other locations of the first book, such as at the beginning or end of the comment area of ​​the first book.

[0068] The book push method provided in this embodiment establishes an association with a target book based on relevant features of a first book currently being read by a reader, and generates a book push text containing a recommendation text based on the contents of the first book and the target book. Since the target book recommended in the book push text is relevant to the first book, the pushed target book is more targeted, thereby improving the success rate of book push and ensuring that the number of readers of the pushed book does not decrease.

[0069] Among them, the purpose of book push is to add recommendations and personal new books in the last chapter, book reviews, and book circles of completed works, so that readers can click on the book title and directly read the pushed books, such as new books, so that new books can have more readers.

[0070] It should be noted that the first book, the second book, etc. (collectively referred to as "books") described in this embodiment generally refer to a series of books or literary works similar to books, including but not limited to books, novels, abstracts / anthologies, poems, essays, drawings / paintings, etc.

[0071] Optionally, in a possible implementation of this embodiment, the above step 103 specifically includes: obtaining the key text of the first book and / or the key text of the target book; determining the recommended text based on the key text of the first book and / or the key text of the target book.

[0072] The key text refers to content that can be used to generate recommendation text, including but not limited to the content, comments or related posts of the first book and the target book.

[0073] Furthermore, obtaining the key text of the first book and / or the key text of the second book includes: extracting the content, comments or related post content of the first book to obtain the key text of the first book, and / or obtaining the key text of the target book based on the content of the target book and related comments after readers' trial reading.

[0074] For example, the story content or the wonderful chapters of the first book are extracted in advance, and the key text of the first book is generated based on the story content or the wonderful chapters. Similarly, the key text of the target book is also generated based on the selected target book content, such as the introduction of the target book, the wonderful chapter of the first chapter, and the readers' feelings and impressions after trial reading.

[0075] Optionally, in another possible implementation, the above step 103 specifically also includes: determining a recommendation text template based on the category of the first book and the target book, or the work similarity information, wherein the recommendation text template includes the structure, content and interesting words for writing the recommendation text; displaying the recommendation text template to the author, and receiving the content written by the author based on the recommendation text template to generate the recommendation text.

[0076] The categories of the target books include at least one of the following: classical literature, romance, urban, time travel, fantasy, history, etc. In addition, if the categories of the target books are not in the above categories, they can also be customized, such as Three-Body novels, etc. The similarity information of the works refers to the degree of correlation between the target book and the first book, such as the relationship between the two books being the upper and lower volumes, or the two books being stories of the same type, the same protagonist, and the same historical time period, etc.

[0077] It should be understood that when determining the recommended text template, other information may also be considered, and the recommended text template may be determined in combination with the aforementioned target book category, work similarity information, etc.

[0078] Optionally, in another possible implementation of the present embodiment, the above step 104 specifically includes: determining the content and interesting words of the recommended text based on the historical editing content of the copy, and the copy content whose conversion rate data exceeds a preset value; generating the recommended text template based on the categories of the first book and the target book, or the similarity information of the works, and the content of the recommended text and the arrangement and combination of the interesting words.

[0079] The historical editing content may be historical reader review content, and the text content with a conversion rate exceeding a preset value refers to the text content that has been historically statistically recommended to other readers as a text with high feedback. The work similarity information may include: the current first book and the target book have the same length, the same or similar book content, the same subject matter / type, etc.; the interesting words may be obtained based on the reader's historical reading data, and the above content may be arranged and combined to generate a recommendable text template.

[0080] See also Figure 5The process of generating a book recommendation text also includes generating the book recommendation text according to at least one recommended text template, wherein each recommended text template includes: a recommendation word editing area and a recommendation word strategy prompt content, wherein the recommendation word strategy is used to prompt the author to complete the editing operation of the recommendation word / recommendation text in the recommendation word editing area.

[0081] In addition, optionally, the above-mentioned determining the recommended text template based on the category of the first book and the target book, or the work similarity information, includes: searching for at least one text template that matches the category or the work similarity information based on the category of the first book or the work similarity information; and determining the recommended text template from the at least one text template based on the author's selection operation.

[0082] For example, in one example, the category of the first book is a historical theme type. Based on the category and the similarity information of the works, a text template matching the category is searched in at least one text template, wherein each book category corresponds to a text template. For example, the server recommends three text templates corresponding to three categories to the author client, namely, historical themes, fantasy themes, and cute baby themes. The text content corresponding to each theme is different. The author can choose one of the three text templates, such as selecting a text template of historical themes as the recommended text template, for example Figure 6 A recommended text template is selected by the author, and the editing operation of the recommended text content is completed based on the recommended text template.

[0083] Optionally, in another possible implementation of this embodiment, the relevant features of the first book include: the category of the first book and the status and content of the first book.

[0084] The category of the first book can refer to the description of the above embodiment, and will not be described in detail in this embodiment. The status of the first book includes two states: completed and serialized.

[0085] The above-mentioned determination of the target book in at least one second book based on the relevant features of the first book includes: obtaining the reader's historical reading data, determining at least one target-related feature based on the relevant features of the first book according to the historical reading data; searching for a second book that matches the at least one target-related feature in at least one second book, and determining it as the target book. The matching includes at least: the first book and the target book are of the same or similar category, the status of the first book is completed, the status of the second book is serialized, and the characters or plots of the second book are related to the book content of the first book.

[0086] For example, when it is determined based on the reader's historical reading data that the current reader has read science fiction and suspense books in the past, a search is performed based on the historical reading data to find a book that meets the target book criteria, and the book type is science fiction and suspense, and is serialized, and the characters or plots involve thrilling and suspense themes.

[0087] Optionally, in another embodiment, the above-mentioned step 104: determining a target book in at least one second book based on relevant characteristics of the first book, further includes: determining the target book based on relevant characteristics of the first book and a work recommendation score of each second book in the at least one second book, and the work recommendation score corresponding to the target book is greater than or equal to a threshold value.

[0088] Among them, the work recommendation score can be determined based on comprehensive factors such as the reader's popularity of the work, the content of the work, and the correlation with a certain old book. The specific score can be judged by the system. For example, the "3-day reader retention rate" of a new book can be monitored and calculated. If the "3-day reader retention rate" is high, the corresponding work recommendation score will also be higher when scoring, thereby obtaining more traffic.

[0089] Furthermore, the so-called 3-day reader retention rate can be reflected as the 3-day reader retention of a new book in a group of readers. The higher the 3-day reader retention rate, the better the overall quality of readers reading the book, and the higher the work recommendation score will be. The platform will give priority to pushing such books and increase the exposure of the book.

[0090] It should be understood that the above-mentioned "3-day reader retention rate" is only one criterion for judging the work recommendation score, and other standards can also be used for comprehensive scoring. This embodiment does not limit the various standards for judging the work recommendation score.

[0091] In addition, the threshold value can be understood as an average score or a minimum score for push. For example, the threshold value can be 60 points, and the full score is set to 100 points. In this example, the work recommendation score corresponding to each book in the new book list can be obtained by evaluating all the information of each new book collected by the terminal device. For example, after scoring, the candidate second book list contains 3 books. After review and scoring, the corresponding work recommendation scores are 20 points, 50 points and 80 points respectively. Then, the book with a work recommendation score of 80 points is determined as the target book.

[0092] In this embodiment, by calculating the work recommendation score of each second book, the second book with a higher work recommendation score is selected as the target book and pushed to the readers, thereby increasing the exposure rate of the target book, giving more readers the opportunity to read the book and ensuring the number of readers.

[0093] In addition, the method provided in this embodiment can improve the recommendation rate of books, and through the association between the original book and the target book, it also improves the reader's retention rate on the target book, thereby significantly helping the target book to improve retention data and bringing more readers to the original author.

[0094] Optionally, in any of the above possible embodiments, step 104 further includes: generating the book recommendation text containing the recommendation text and the relevant information of the target book based on the recommendation text, the relevant information of the target book, and based on the insertion operation of the author at the relevant position of the first book.

[0095] The relevant position of the first book includes the end of the first book or the end of the final chapter.

[0096] Optionally, the book recommendation text also includes a hyperlink to the target book; after the above step 105, in which the book recommendation text is pushed to the reader, the method further includes: receiving an operation of the reader clicking on the hyperlink, and jumping to the reading page of the target book in response to the operation.

[0097] Specifically, one implementation method is as follows: Figure 3 As shown, at the end of the old book, a book recommendation text "Author's words" and a hyperlink are embedded. For example, a hyperlink address is set on the title of the book recommendation text, and the hyperlink address is used to associate with the reading page of the new book. When a reader clicks on the hyperlink, such as when the reader clicks on the title "XXX Book", the book recommendation text (i.e., the book card) corresponding to the new book is lit up to prompt the reader to enter the book reader for reading. The page mask outside the book recommendation text is gray. If a user clicks on the gray mask, the current data card is closed.

[0098] Optionally, the method also includes: if it is impossible to jump to the new book reading interface due to network reasons, such as a network error, that is, the book reader cannot be linked with one click, the system prompts the reader through a toast that there is a network error and to try again later.

[0099] The method provided in this embodiment sets the link address of the target book in the book recommendation card, so that after the reader clicks the link address, he can directly jump to the target book reader, so that the reader can quickly transition to reading the target book, improving the reader's reading experience.

[0100] Based on the book push method provided in the above embodiment, in this embodiment, a method for generating a book push text is also provided. The method is used to generate the above book push text. Specifically, the method can be applied to a terminal device, such as a mobile phone terminal. Figure 7 As shown, the method for generating book recommendation text includes the following steps:

[0101] Step 201: receiving a book recommendation text, wherein the book recommendation text includes a recommendation text and relevant information of a target book, wherein the target book and the first book are written by the same author.

[0102] The book recommendation text includes but is not limited to book recommendation cards, book recommendation labels, book recommendation advertisements, etc. The recommendation text and related information of the target book include but are not limited to book categories, contents, comments and other information, which are not limited in this embodiment.

[0103] In addition, the book recommendation text includes: author identity information, the title of the target book and the recommendation. Furthermore, the author identity information can be the author's pen name, user name, ID number and other information used to identify the user. The title of the target book can be in the form of text, numbers, characters and other expressions. The recommendation can be written based on the content of the target book and the reader's preferences to attract readers. In addition, the book recommendation card can also include other content, such as the author's headshot, logo and so on.

[0104] Step 202: Obtain the relevant position of the first book in the editable area of ​​the display interface.

[0105] The relevant position of the first book includes the last chapter or the end of the first book, and step 202 specifically includes: inserting the book recommendation text at the last chapter or the end of the first book.

[0106] Step 203, receiving the author's editing operation, and inserting the book recommendation text into the relevant position of the first book.

[0107] For example, in the aforementioned Figure 5 After the author edits the recommendation / recommendation text, he / she shall submit the application for review. After the review is passed, the recommendation text will be automatically inserted into the last chapter or end of the current first book. Figure 4 As shown in the example, a book recommendation text "Author's Comments" is generated and inserted into the last page, for example, after the comment area on the last page of the current book. The comment area is used for readers to write down their impressions and comments after reading the current book.

[0108] In step 203 of the present embodiment, before inserting the book recommendation text, the method further includes: displaying a recommendation text template on a display interface, the recommendation text template including relevant information of the first book, relevant information of the second book and the recommendation text content; generating a book recommendation text according to the recommendation text content, relevant information of the first book and / or relevant information of the second book.

[0109] The relevant information of the first book and / or the target book includes: the title of the first book and / or the target book, the book type, book reviews or related post content, etc.; the recommended text content can be determined based on the categories of the first book and the target book, or the work similarity information, etc.

[0110] When editing the recommendation text template, the author can click the "View High-Quality Cases" option on the display interface, such as Figure 5 As shown, a recommendation template is selected from the high-quality cases stored in the database for the author to use when writing the recommendation.

[0111] Furthermore, in a specific embodiment, the displaying of recommended text templates on the display interface includes: obtaining at least one candidate text template that matches the relevant information of the first book, the relevant information of the first book including the category and work similarity information of the first book; receiving a selection operation of the author among the at least one candidate text template, and in response to the selection operation, determining one of the selected ones as the recommended text template.

[0112] For example, the category of the first book is science fiction, and the work similarity information includes themes related to The Three-Body Problem. Based on the category information of the science fiction category and the work similarity, a text template belonging to the science fiction category and with a high similarity is searched in at least one text template as a candidate text template, and provided to the author for selection. When the author selects one of the text templates, the selected template is determined as the recommended text template ultimately used to generate the recommended text, so that the author can edit the recommendation.

[0113] Optionally, the above-mentioned generating a book recommendation text based on the content of the recommendation text, relevant information of the first book and / or relevant information of the second book includes: determining the content of the recommendation text based on the content, comments or related post content of the first book, and / or, based on the content of the target book and related comments after readers' trial reading; generating a book recommendation text based on the content of the recommendation text, relevant information of the first book and / or relevant information of the second book.

[0114] Specifically, the process of generating the book recommendation text according to the content of the recommendation text, the relevant information of the first book and / or the relevant information of the second book is described in detail in the aforementioned embodiment, and will not be repeated here in this embodiment.

[0115] The method provided in this embodiment, on the author-side client, receives a book recommendation text including a recommendation text and relevant information of the target book, and inserts the book recommendation text into a relevant position of the first book, thereby pushing the target new book to the reader. Since the recommendation text in the book recommendation text is determined based on the content of the first book, comments or related post content, and / or the content of the target book, relevant comments after the reader's trial reading, etc., the target book pushed to the current reader is more accurate, thereby improving the quality of new book traffic.

[0116] Optionally, in this embodiment, the book recommendation text also includes a link address of the target book; for example, the title of the target book is used as the link address and embedded in the book recommendation card. When a reader clicks on the link address, the reader is redirected to the reading interface of the target book in response to the operation, so that the reader can quickly transition to reading the new book, thereby improving the reader's reading experience.

[0117] The embodiment of the present invention also discloses a book pushing device, which is used to achieve the above Figure 2 Specifically, as shown in the book push method Figure 8 As shown, the device includes: an acquisition unit 810, a determination unit 820, a processing unit 830, a generation unit 840 and a push unit 850. In addition, the device may also include other units and modules, such as a storage unit and the like.

[0118] The acquisition unit 810 is used to acquire a first book, where the first book is the book currently being read by the reader.

[0119] The determination unit 820 is configured to determine a target book from at least one second book according to the relevant features of the first book, wherein the second book and the first book are both written by the same author.

[0120] The processing unit 830 is configured to determine a recommended text according to the content of the target book and / or the first book.

[0121] The generating unit 840 is used to generate a book recommendation text of the target book according to the recommendation text and the relevant information of the target book.

[0122] The push unit 850 is used to push the recommended book text to the reader.

[0123] Optionally, in a specific implementation, the processing unit 830 is specifically used to obtain the key text of the first book and / or the key text of the target book; and determine the recommended text based on the key text of the first book and / or the key text of the target book.

[0124] Optionally, in another specific implementation, the acquisition unit 810 is further used to extract the content, comments or related post content of the first book to obtain the key text of the first book, and / or to obtain the key text of the target book based on the content of the target book and related comments after readers' trial reading.

[0125] Optionally, in another specific implementation, the processing unit 830 is specifically used to determine a recommendation text template based on the category or work similarity information between the first book and the target book, wherein the recommendation text template includes the structure, content and interesting words for writing the recommendation text.

[0126] In addition, the above device further comprises a display unit and a receiving unit. The display unit is used to display the recommended text template to the author, and the receiving unit is used to receive the content written by the author based on the recommended text template, and generate the recommended text through the generating unit 840.

[0127] Optionally, in another specific embodiment, the processing unit 830 is further used to determine the content and interesting words of the recommended text based on the historical editing content of the copy, and the copy content whose conversion rate data exceeds a preset value; and generate the recommended text template based on the category of the first book and the target book, or the similarity information of the works, and the content of the recommended text and the arrangement and combination of the interesting words.

[0128] Optionally, in another specific implementation, the processing unit 830 is further used to search for at least one text template that matches the category or the work similarity information of the first book based on the category or the work similarity information; and determine the recommended text template in the at least one text template based on the author's selection operation.

[0129] Optionally, in another specific implementation, the relevant characteristics of the first book include: at least one of: the category of the first book, information applicable to readers, and the status and content of the first book.

[0130] The determination unit 820 is further configured to obtain the reader's historical reading data, determine at least one target-related feature based on the relevant features of the first book in the historical reading data, and search for a second book matching the at least one target-related feature in at least one second book, and determine the second book as the target book.

[0131] The matching includes at least: the first book and the target book are of the same or similar category, the first book is about to be completed or has been completed, the second book is in serial status, and the characters or plots of the second book are related to the content of the first book.

[0132] Optionally, in another specific implementation, the determination unit 820 is further used to determine the target book based on relevant features of the first book and the work recommendation score of each second book in the at least one second book, and the work recommendation score corresponding to the target book is greater than or equal to a threshold value.

[0133] Optionally, in another specific embodiment, the processing unit 830 is further used to generate the book recommendation text containing the recommendation text and the relevant information of the target book based on the recommendation text, the relevant information of the target book, and the insertion operation of the author at the relevant position of the first book.

[0134] The relevant position of the first book includes: the end of the first book or the end of the final chapter.

[0135] In addition, optionally, the book recommendation text also includes a hyperlink to the target book; the receiving unit is further used to receive the reader's operation of clicking on the hyperlink, and the processing unit 830 is further used to jump to the reading page of the target book in response to the operation.

[0136] The book push device provided in this embodiment establishes an association with a target book based on relevant features of a first book currently being read by a reader, and generates a book push text containing a recommendation text based on the contents of the first book and the target book. Since the target book recommended in the book push text is relevant to the first book, the pushed target book is more targeted, thereby improving the success rate of book push and ensuring that the number of readers of the pushed book does not decrease.

[0137] Based on the method for generating a book recommendation text described in the above embodiment, this embodiment also provides a device for generating a book recommendation text. Fig. 9 As shown, the device includes: a receiving unit 910, an acquiring unit 920 and an inserting unit 930. In addition, the device may also include other units and modules, such as a storage unit and the like.

[0138] The receiving unit 910 is used to receive a book recommendation text, wherein the book recommendation text includes a recommendation text and relevant information of a target book, and the target book and the first book are written by the same author.

[0139] The acquisition unit 920 is used to acquire the relevant position of the first book in the editable area of ​​the display interface.

[0140] The inserting unit 930 is used to insert the book recommendation text into the relevant position of the first book based on the author's editing operation.

[0141] Optionally, in a specific implementation, the above-mentioned device further includes a display unit and a generation unit.

[0142] The display unit is used to display a recommendation text template on a display interface, wherein the recommendation text template includes relevant information of the first book, relevant information of the second book and the recommendation text content.

[0143] The generating unit is used to generate a book recommendation text according to the content of the recommendation text, the relevant information of the first book and / or the relevant information of the second book.

[0144] Optionally, in another specific implementation, the acquisition unit 920 is further used to acquire at least one candidate text template that matches the relevant information of the first book, and the relevant information of the first book includes the category of the first book and the similarity information of the works.

[0145] The receiving unit 910 is further configured to receive a selection operation of the author from among the at least one candidate text template. In response to the selection operation, the generating unit determines one of the selected ones as the recommended text template.

[0146] Optionally, in another specific embodiment, the generating unit is further used to determine the content of the recommended text based on the content, comments or related post content of the first book, and / or the content of the target book and related comments after readers' trial reading; and to generate a book recommendation text based on the content of the recommended text, relevant information of the first book and / or relevant information of the second book.

[0147] Optionally, in another specific implementation, the inserting unit 930 is further configured to insert the book recommendation text at the last chapter or the end of the first book.

[0148] In addition, it should be noted that the device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present embodiment. In addition, in the accompanying drawings of the device embodiments provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, which may be specifically implemented as one or more communication buses or signal lines.

[0149] In addition, an embodiment of the present invention further provides an electronic device, such as Fig.10As shown, the electronic device may include a processor 110 and a memory 120, wherein the processor 110 and the memory 120 may be connected via a bus or in other ways. Fig.10 In the example, the connection through a bus is taken. In addition, the electronic device further includes at least one interface 130, and the at least one interface 130 may be a communication interface or other interface, which is not limited in this embodiment.

[0150] The processor 110 may be a central processing unit (CPU). The processor 110 may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or a combination of the above chips.

[0151] The memory 120, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs, non-transitory computer executable programs and modules, such as program instructions / modules corresponding to the book push method and the book push text generation method in the embodiments of the present invention. The processor 110 executes various functional applications and data processing of the processor by running the non-transitory software programs, instructions and modules stored in the memory 120, that is, the book push method and the book push text generation method in the above method embodiments are implemented.

[0152] The memory 120 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and applications required for at least one function; the data storage area may store data created by the processor 110, etc. In addition, the memory 120 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some embodiments, the memory 120 may optionally include a memory remotely arranged relative to the processor 110, and these remote memories may be connected to the processor 110 via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0153] In addition, at least one interface 130 is used for communication between the electronic device and external devices, such as communication with a server, etc. Optionally, at least one interface 130 can also be used to connect external input and output devices, such as a keyboard, a display screen, etc.

[0154] The one or more modules are stored in the memory 120 and when executed by the processor 110, perform the following steps: Figure 2 The book push method described above, and the execution of Figure 7 The method for generating book recommendation text is shown.

[0155] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by hardware related to computer program instructions, and the computer program instructions can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, the storage medium can be a disk, an optical disk, a read-only memory (ROM), a random access memory (RAM), a flash memory, a hard disk (HDD) or a solid-state drive (SSD), etc.; the storage medium can also include a combination of the above-mentioned types of memory.

[0156] Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A method for pushing books. It is characterized in that The method comprises: Obtain a first book, where the first book is the book currently being read by the reader; Determine a target book from at least one second book according to the relevant features of the first book, wherein the second book and the first book are both written by the same author, and the second book is a serialized book; Determining a recommended text according to the content of the target book and / or the first book; Generate a book recommendation text for the target book based on the recommendation text and relevant information of the target book; Pushing the recommended book text to the reader; Wherein, determining the recommended text according to the content of the target book and / or the first book includes: Determine a recommended text template according to the similarity information between the first book and the target book, wherein the recommended text template includes the structure, content and interesting words of the recommended text, and the content and interesting words of the recommended text are determined according to the historical editing content of the copy and the copy content whose conversion rate data exceeds a preset value; The recommendation text template is displayed to the author, and the content written by the author based on the recommendation text template is received to generate the recommendation text.

2. The method according to claim 1, It is characterized in that The step of determining the recommended text according to the content of the target book and / or the first book includes: Acquire the key text of the first book and / or the key text of the target book; The recommended text is determined according to the key text of the first book and / or the key text of the target book.

3. The method according to claim 2, It is characterized in that The obtaining of the key text of the first book and / or the key text of the second book includes: Extract the content, comments or related post content of the first book to obtain the key text of the first book, and / or obtain the key text of the target book based on the content of the target book and related comments after readers' trial reading.

4. The method according to claim 1, It is characterized in that Determining a recommended text template according to the work similarity information between the first book and the target book includes: Determine the content and interesting words of the recommended text according to the historical editing content of the copy and the copy content whose conversion rate data exceeds a preset value; The recommendation text template is generated according to the work similarity information between the first book and the target book, as well as the content of the recommendation text and the arrangement and combination of the interesting words.

5. The method according to claim 1, It is characterized in that The step of determining a recommended text template according to the work similarity information between the first book and the target book includes: According to the work similarity information of the target book, searching for at least one text template that matches the work similarity information of the target book; Based on the selection operation of the author, the recommended text template is determined in the at least one text template.

6. The method according to any one of claims 1 to 5, It is characterized in that The related features of the first book include: at least one of the category of the first book, the status and content of the first book; Determining a target book from at least one second book according to the relevant features of the first book includes: Acquire the reader's historical reading data, and determine at least one target-related feature according to the relevant features of the historical reading data in the first book; Searching for a second book matching the at least one target-related feature in at least one second book, and determining the second book as the target book; The matching includes at least: the first book and the target book are of the same or similar category, the first book is about to be completed or has been completed, the second book is in serial status, and the characters or plots of the second book are related to the content of the first book.

7. The method according to claim 6, It is characterized in that Determining a target book from at least one second book according to the relevant features of the first book also includes: The target book is determined according to the relevant features of the first book and the work recommendation score of each second book in the at least one second book, and the work recommendation score corresponding to the target book is greater than or equal to a threshold value.

8. The method according to any one of claims 1 to 5, It is characterized in that Generating a recommendation text for the target book according to the recommendation text and the relevant information of the target book, including: The book recommendation text including the recommendation text and the relevant information of the target book is generated according to the recommendation text, the relevant information of the target book, and based on the insertion operation of the author at the relevant position of the first book.

9. The method according to claim 8, It is characterized in that The relevant position of the first book includes: the end of the first book or the end of the final chapter.

10. The method according to claim 9, It is characterized in that The book recommendation text also includes a hyperlink to the target book; After pushing the recommended book text to the reader, the method further includes: An operation of the reader clicking on the hyperlink is received, and in response to the operation, the reader jumps to a reading page of the target book.

11. A method for generating book recommendation text, It is characterized in that The method comprises: Receive a book recommendation text, the book recommendation text including the recommendation text and relevant information of a target book, the target book and a first book are written by the same author, the target book is determined from at least one second book based on relevant features of the first book, the second book is a serialized book, the recommendation text template is determined based on work similarity information between the first book and the target book, the recommendation text template includes the structure, content and interesting words of writing the recommendation text, the content and interesting words of the recommendation text are determined based on historical editing content of the copy, and the copy content with conversion rate data exceeding a preset value; Obtaining a relevant position of the first book in an editable area of ​​the display interface; receiving the author's editing operation, and inserting the book recommendation text into the relevant position of the first book; Before inserting the book recommendation text at the relevant position of the first book, the method further includes: Displaying a recommendation text template on a display interface, wherein the recommendation text template includes relevant information of the first book, relevant information of the second book, and recommendation text content; A book recommendation text is generated according to the recommendation text content, relevant information of the first book and / or relevant information of the second book.

12. The method according to claim 11, It is characterized in that Display recommended text templates on the display interface, including: Acquire at least one candidate text template that matches the relevant information of the first book, where the relevant information of the first book includes the category of the first book and the similarity information of the works of the target book; A selection operation of the author among the at least one candidate text template is received, and in response to the selection operation, one of the selected text templates is determined to be the recommended text template.

13. The method according to claim 12, It is characterized in that Generating a book recommendation text according to the content of the recommendation text, the relevant information of the first book and / or the relevant information of the second book includes: Determine the content of the recommended text according to the content, comments or related posts of the first book, and / or according to the content of the target book and related comments of readers after trial reading; A book recommendation text is generated according to the recommendation text content, relevant information of the first book and / or relevant information of the second book.

14. The method according to any one of claims 11 to 13, It is characterized in that Inserting the book recommendation text at a relevant position of the first book includes: The book recommendation text is inserted at the last chapter or the end of the first book.

15. A book pushing device, It is characterized in that The device comprises: An acquiring unit, configured to acquire a first book, wherein the first book is a book currently being read by the reader; a determination unit, configured to determine a target book from at least one second book according to the relevant features of the first book, wherein the second book and the first book are both written by the same author, and the second book is a serialized book; A processing unit, configured to determine a recommended text according to the content of the target book and / or the first book; A generating unit, configured to generate a book recommendation text of the target book according to the recommendation text and relevant information of the target book; A push unit, used for pushing the recommended book text to the reader; The processing unit is specifically used to determine a recommended text template according to the similarity information between the first book and the target book, wherein the recommended text template includes the structure, content and interesting words of the recommended text, and the content and interesting words of the recommended text are determined according to the historical editing content of the copy and the copy content whose conversion rate data exceeds a preset value; A display unit, used for displaying the recommended text template to the author; The receiving unit is used to receive the content written by the author based on the recommendation text template, and to generate the recommendation text through the generating unit.

16. A device for generating a book recommendation text, It is characterized in that The device comprises: A receiving unit is used to receive a book recommendation text, wherein the book recommendation text includes relevant information of the recommendation text and a target book, the target book and the first book are written by the same author, the target book is determined from at least one second book based on relevant features of the first book, the second book is a serialized book, the recommendation text template is determined based on work similarity information between the first book and the target book, the recommendation text template includes a structure, content and interesting words for writing the recommendation text, and the content and interesting words of the recommendation text are determined based on historical editing content of the copy, and the copy content whose conversion rate data exceeds a preset value; An acquisition unit, configured to acquire a relevant position of the first book on an editable area of ​​a display interface; An inserting unit, used for inserting the book recommendation text at a relevant position of the first book based on the author's editing operation; A display unit, configured to display a recommendation text template on a display interface, wherein the recommendation text template includes relevant information of the first book, relevant information of the second book, and recommendation text content; A generating unit is used to generate a book recommendation text according to the content of the recommendation text, relevant information of the first book and / or relevant information of the second book.

17. An electronic device comprising a memory and a processor, It is characterized in that The memory stores computer program instructions; When the processor executes the computer program instructions, the method according to any one of claims 1 to 10 or any one of claims 11 to 14 is implemented.

18. A computer-readable storage medium, It is characterized in that The computer readable storage medium stores a computer program; When the computer program is executed by a computer, the method according to any one of claims 1 to 10 or any one of claims 11 to 14 is implemented.

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