WO2019090741A1 - 推荐用户阅读喜好的书籍的方法及装置 - Google Patents

推荐用户阅读喜好的书籍的方法及装置 Download PDF

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Publication number
WO2019090741A1
WO2019090741A1 PCT/CN2017/110571 CN2017110571W WO2019090741A1 WO 2019090741 A1 WO2019090741 A1 WO 2019090741A1 CN 2017110571 W CN2017110571 W CN 2017110571W WO 2019090741 A1 WO2019090741 A1 WO 2019090741A1
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user
book
books
favorite
read
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PCT/CN2017/110571
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English (en)
French (fr)
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张泽斌
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深圳市华阅文化传媒有限公司
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Priority to PCT/CN2017/110571 priority Critical patent/WO2019090741A1/zh
Publication of WO2019090741A1 publication Critical patent/WO2019090741A1/zh

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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/33Querying
    • G06F16/335Filtering based on additional data, e.g. user or group profiles
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00Commerce
    • G06Q30/02Marketing; Price estimation or determination; Fundraising
    • G06Q30/0282Rating or review of business operators or products

Definitions

  • the present invention relates to a method for a user to select a book in the field of electronic books, and more particularly to a method and apparatus for recommending a user to read a favorite book.
  • a primary object of the present invention is to provide a method and apparatus for recommending a user to read a favorite book, and to send a list of books that the user may like to the user.
  • the present invention provides a method for recommending a user to read a favorite book, including the steps:
  • the obtaining the book information of the user's preference includes:
  • identity information of the user includes one or more of a gender, an age, a region, and a degree of education of the user;
  • the dimensions include: a book type, a special topic, and others;
  • the special topics include: Top Ten Leaderboards, Weekly Leaderboards, Monthly Leaderboards, and Author Leaderboards.
  • the obtaining the book information of the user's preference includes:
  • obtaining behavior information of the user where the behavior information includes a browsing database of the user, a number of clicks on the book, a reading time, a payment, and a search behavior;
  • the method includes:
  • a book belonging to the user's favorite type newly added to the server database is set as a book of the user's preference.
  • the method before sending the recommended book list to the user, the method includes:
  • the books on the book list are sorted in order of the number of users owned.
  • the present invention provides an apparatus for recommending a user to read a favorite book, including: an obtaining module, configured to acquire book information of a user's preference;
  • a list module configured to generate the at least one recommended book list according to different dimensions of the book information
  • a sending module send the recommended book list to a user.
  • the acquiring module includes:
  • an identity unit configured to acquire identity information of the user, where the identity information includes one or more of a gender, an age, a region, and a qualification of the user;
  • the same unit is used to obtain a book in the server database with other users of the same identity information, and the book is a book that the user likes.
  • the acquiring module further includes:
  • a behavior unit configured to acquire behavior information of the user, where the behavior information includes a browsing database of the user, a click count on the book, a reading time, a payment, and a search behavior;
  • a calculating unit configured to calculate, according to the behavior information of the user, the type of the favorite book of the user by using preset logic
  • a ranking unit configured to set a book in the server database whose book type is within a preset range is a book preferred by the user
  • a new book unit configured to set a book belonging to the user favorite type newly added to the server database as a user favorite book
  • an obtaining unit configured to acquire book information of the book that the user likes.
  • the device for recommending a user to read a favorite book further includes:
  • a sorting module configured to sort the books on the book list in order of the number of users owned.
  • the beneficial effects of the present invention are: according to the user's own identity and the reading record, identifying the book of interest to the user and transmitting it to the user's personal account, so that the user always has a sense of himself Interested in reading books.
  • FIG. 1 is a schematic diagram showing the steps of recommending a user to read a favorite book according to an embodiment of the present invention
  • FIG. 2 is a schematic diagram showing the steps of recommending a user to read a favorite book according to an embodiment of the present invention
  • FIG. 3 is a schematic diagram showing the steps of recommending a user to read a favorite book according to an embodiment of the present invention
  • FIG. 4 is a schematic diagram showing the steps of recommending a user to read a favorite book according to an embodiment of the present invention
  • FIG. 5 is a schematic structural diagram of a book for recommending a user to read a favorite according to an embodiment of the present invention
  • FIG. 6 is a schematic structural diagram of a book for recommending a user to read a favorite according to an embodiment of the present invention
  • FIG. 7 is a schematic structural diagram of a book for recommending a user to read a favorite according to an embodiment of the present invention.
  • FIG. 8 is a schematic structural diagram of a book for recommending a user to read a favorite according to an embodiment of the present invention.
  • a method for recommending a user to read a favorite book includes the following steps:
  • the book information refers to the name, content, number of words, type, author, protagonist, and some obvious tags of the book, which can reflect the information of the book, and also includes links in the server database.
  • “Journey to the West” is the name of the book; its content refers to the description of the specific plot, the number of words is about 820,000 words; the type is ancient novels; the author is Wu Chengen; the protagonist is Sun Wukong, Tang Yan, etc.; some obvious labels refer to such as "four One of the great masterpieces makes people think of the keywords of the book, and the obvious label can also be the protagonist name.
  • a book list is a list of books composed of multiple book names and links to the books.
  • the APP After installing a reading APP on a smart terminal such as a mobile phone, the APP obtains the book information of the user's preference and then sends the book list to the user.
  • the book information that the user likes is based on the user's personal information or other information such as the user's reading record to determine the user's book. For example, if the user is a male born in the 1980s, the user may like books written by the authors of the post-80s; the males born in the 1980s refer to personal information. For example, the user has read "Journey to the West” and "Romance of the Three Kingdoms" before, indicating that users like ancient classic novels.
  • the dimension described in S2 refers to the basis of classification by book type.
  • the book type refers to one dimension
  • the book author also refers to one dimension.
  • Dimensions include: book types, special topics, and others; among which book types include: history, science fiction, literature, romance, martial arts, and comprehension; special topics include: Top Ten Leaderboards, Weekly Leaderboards, Monthly Leaderboards, and Authors' Leaderboards. Others mean that merchants can define dimensions and so on according to their own needs.
  • the APP divides the books that the user likes according to the dimension, and each dimension generates a list of recommended books, and then sends the list of books corresponding to the dimensions to the user, so that the user can find the books that he wants to see, which book the user wants to see, click on the
  • the list of books that is, the link corresponding to the book, enters the interface for reading the book.
  • the user is sent to the user to register the account on the server. After the user logs into the personal account, the list of recommended books can be seen, and the list of recommended books is displayed on one of the pages of the APP through the server.
  • the user may slap the webpage of the smart terminal to log in to a website to read the list of recommended books.
  • the obtaining the book information of the user's preference includes:
  • Sl l obtaining identity information of the user, where the identity information includes one or more of a user's gender, age, region, and education;
  • the same gender, in the same city, the same academic qualifications, and the growth environment is similar, so the books that like to read are also very similar, so these books are the books that users like.
  • the user who reads the most books with the same user identity is recommended to the user. For example, a user A is 28 years old working in Shenzhen, is a bachelor's degree, and the same identity as the user A on the platform. There are 100 users, 30 of the 100 people read “Three-body”, 26 people read “Father Dad Poor", 20 people read “Zhu Xian”, and other books are less than 20 in 100 people. Reading, so the above three books default to the user A favorite reading books, send the list of these three books to the user.
  • the above steps of Sl l and S12 are applied to the new user who has just become the APP. Since the new user does not have the history of reading, the user is recommended to the new user by referring to the reading book of others.
  • the identity information of the user it may be the personal identity information filled in by the user registration, or the user may log in by binding other APPs, for example, the user registers the account of the reading APP with QQ, that is, the reading APP passes. Read the user's QQ information to obtain the user's identity information.
  • the method before sending the recommended book list to the user, the method includes:
  • the three books of "Three-body”, “Full Dad Poor Dad”, and “Zhu Xian” are recommended to the user, and the recommendation is made in this order, because "three-body” has 30 people and A user who reads the same identity, It is the largest reading group, indicating that this book is most liked by such a group, so the book is given the highest priority to A users, and the latter two books are also sorted one by one.
  • the obtaining the book information of the user's preference includes:
  • S13 Obtain behavior information of the user, where the behavior information includes a browsing database of the user, a click count of the book, a reading time, a payment, and a search behavior;
  • S14 calculating, according to the behavior information of the user, the type of the favorite book of the user by using preset logic;
  • S15 setting a book in the server database that the book type is ranked within a preset range is a book that users like;
  • the behavior information of the user refers to the operation information of the user on the APP interface, including the number of clicks on a book, the reading time, the reading fee paid, and the search for keywords in the book search.
  • the more behavior of the above behavior on a book or a certain type of book the more the user likes the book or the type of book. For example, A user clicked on historical novels 40 times in August, clicked on fantasy novels 32 times, and read historical novels in the middle of 20 hours. Reading the fantasy novels was 15 hours, and purchased 3 historical novels.
  • the list of recommended books is generated in the order of favorable ranking, so that the books most likely to be liked by the user are placed at the forefront, and the corresponding book information is also sent to the user, wherein the information of the books transmitted at least includes Book title and reading link.
  • the ranking may also be a ranking of user click-through rates within the server database, and thus may not be the six books listed above.
  • the book type can also be classified by the author. For example, the books that A users read in a certain period of time are Jiangnan (author's pen name), so the recommended books in Jiangnan are recommended books.
  • the method after calculating the type of the favorite book of the user, the method includes:
  • the server database is updated every day, the newly updated book is rarely clicked by the user, and may be recommended by the user but cannot be recommended to the user. Therefore, the step S16 is set, and the new type is set. Books added to the server database are also set with user-like books, which are pushed to the user on the APP interface.
  • the method for recommending a user to read a favorite book can identify a book of interest to the user according to the user's own identity and the reading record, and send it to the user's personal account, so that the user always Have books of your own interest to read.
  • the present invention provides an apparatus for recommending a user to read a favorite book, which is characterized by comprising:
  • the obtaining module 1 is configured to obtain book information of the user's preference
  • the list module 2 is configured to generate the at least one recommended book list according to different dimensions of the book information.
  • the sending module 4 sends the recommended book list to the user.
  • the book information refers to the name, content, number of words, type, author, protagonist, and some obvious tags of the book, which can reflect the information of the book, and also includes links in the server database.
  • “Journey to the West” is the name of the book; its content refers to the description of the specific plot, the number of words is about 820,000 words; the type is ancient novels; the author is Wu Chengen; the protagonist is Sun Wukong, Tang Yan, etc.; some obvious labels refer to such as "four One of the great masterpieces makes people think of the keywords of the book, and the obvious label can also be the protagonist name.
  • a book list is a list of books composed of multiple book names and links to the books.
  • the obtaining module 1 After installing a reading APP on a smart terminal such as a mobile phone, the obtaining module 1 acquires the book information of the user's preference and the sending module 4 transmits the book list to the user.
  • the book information that the user likes is based on the user's personal information or other information such as the user's reading record to determine the user's book. For example, if the user is a male born in the 1980s, the acquisition module 1 determines that the user may like the author's work after the 80s; the male born in the 1980s refers to personal information. For example, the user has read "Journey to the West" and "Romance of the Three Kingdoms" before, indicating that users like ancient classic novels. The above dimensions refer to the basis of classification by book type.
  • the book type refers to one dimension
  • the book author also refers to one dimension.
  • Dimensions include: book types, special topics, others; among which book types include: history, science fiction, text Learning, romance, martial arts, comprehension; special topics include: Top Ten Rankings, Weekly Leaderboards, Monthly Leaderboards, Author Rankings. Others mean that merchants can define dimensions and so on according to their own needs.
  • the list module 2 divides the books that the user likes according to the dimension, and each dimension correspondingly generates a list of recommended books, and then the sending module 4 sends the list of books corresponding to the dimensions to the user, so that the user can find the books that he wants to see, and the user wants to see which books.
  • the sending module 4 sends the account to the user to be registered on the server. After the user logs in to the personal account, the list of recommended books can be seen, and the list of recommended books is displayed on one of the pages of the APP by the server.
  • the webpage of the user's smart terminal may be logged into a website of a certain reading to see a list of recommended books.
  • the acquiring module 1 includes:
  • the identity unit 11 is configured to acquire identity information of the user, where the identity information includes the gender of the user, and the age
  • the same unit 12 is used to obtain a book in the server database with other users of the same identity information, and the book is a book that the user likes.
  • the identity unit 11 obtains the identity information of all users of the entire server and the reading record, and then the same unit 12 looks at the books that the same person as the user looks at according to the identity information input by the user, because the user and the identity of these other users are In the same way, the same age, gender, and the same city, the same academic qualifications, and the growth environment is similar, so the books that like to read are also similar, so these books are users' favorite books.
  • the same unit 12 recommends the user who reads the most books with the same user identity as the user, for example, a user A male working in Shenzhen at the age of 28, is a bachelor degree, and the identity unit 11 confirms the There are 100 users on the platform who have the same identity as User A.
  • the sending module 4 sends the list of the three books to the user.
  • the use of the identity unit 11 and the same unit 12 described above is suitable for a new user who has just become the APP. Since the new user does not have a history of reading, the acquisition module 1 refers to the reading book of others to recommend to the new user.
  • the identity unit 11 may obtain the identity information of the user, may be the personal identity information filled in by the user, or may be logged in by the user by binding other APPs, for example, the user registers the account of the reading APP with QQ, ie, The reading APP obtains the identity information of the user by reading the QQ information of the user.
  • the acquiring module 1 further includes:
  • the behavior unit 13 is configured to acquire behavior information of the user, where the behavior information includes a browsing server database of the user, a click count on the book, a reading time, a payment, and a search behavior;
  • the calculating unit 14 is configured to calculate, according to the behavior information of the user, the type of the favorite book of the user by using preset logic;
  • a ranking unit 15 configured to set a book in the server database whose book type is within a preset range is a book preferred by the user;
  • a new book unit 16 configured to set a book of a type belonging to the user preference newly added to the server database as a book preferred by the user;
  • the obtaining unit 17 is configured to acquire book information of the book that the user likes.
  • the behavior information of the user refers to the operation information of the user on the APP interface, including the number of clicks on a book, the reading time, the reading fee paid, and the search for keywords in the book search.
  • the more behavior of the above behavior on a book or a certain type of book the more the user likes the book or the type of book.
  • the behavior unit 13 obtained the A user clicked on the historical novel 40 times in August, clicked the fantasy novel 32 times, and the reading history novel was 20 hours, and the reading fantasy novel was 15 hours, and purchased 3 This historical novel consumes 30 yuan, and purchases 3 fictional novels for 28 yuan.
  • the behavior unit 13 obtains the behavior of the A user, it sends it to the computing unit 14, and then the computing unit 14 calculates that the book that the user likes is a history type and a fantasy type, and then the ranking unit 15 searches the server database for each of the two types of books.
  • the first three books are the top three in the history category: "Hanxiang”, “With warehouse to Daming”, “Mythical version of the Three Kingdoms”, and the top three “Fantasy”, “Dust”, Tiandao Library, and then the acquisition unit 17 obtains the book information of the books (the book information to Excluding the names of these books and the corresponding link addresses), a total of 6 books are sent to the A user. If the A user wants to read the book, he can directly click the link corresponding to the book information to enter the reading interface. After the sending module 4 transmits the recommended book list, the ranking unit 15 generates a list of recommended books in the order of favorable ranking, so that the books most likely to be liked by the user are placed at the forefront.
  • the ranking of ranking unit 15 may also be a ranking of user click-through rates within the server database, and thus may not be the six books listed above.
  • the calculation unit 14 can also be classified by the author in calculating the book type. For example, the books that the A user sees in a certain period of time are all Jiangnan (author's pen name), so Jiangnan is recommended in the recommended time. Books of the work.
  • the server database is updated every day, the newly updated book is rarely clicked by the user, and may be recommended by the user but cannot be recommended to the user. Therefore, the new book unit 16 is set, and the new type of the database is added to the server database. Books with user preferences are also set and pushed to the user on the A PP interface.
  • the device for recommending a user to read a favorite book further includes:
  • the sorting module 3 is configured to sort the books on the book list in order of the number of users owned.
  • a user A is 28 years old working in Shenzhen, and has a bachelor's degree.
  • the three books of "Three-body”, “Father Dad Poor” and “Zhu Xian” are recommended to the user, and the sorting module 3 is recommended in this order, because the "three-body” has 30 people and the same identity of the A user. People reading, is the largest reading group, indicating that this book is most liked by such a group, so the book is most recommended to A users, and the latter two books are also sorted.
  • the device for recommending a user to read a favorite book can identify a book of interest to the user according to the user's own identity and the reading record, and send it to the user's personal account, so that the user always Have books of your own interest to read.

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Abstract

本发明属于电子书领域,提供了一种推荐用户阅读喜好的书籍的方法及装置,其中方法包括:获取用户喜好的书籍信息;将所述书籍信息按照不同的维度生成至少一个推荐书籍名单;将推荐书籍名单发送给用户。本发明的推荐用户阅读喜好的书籍的方法及装置可以识别用户感兴趣的书籍,并发送给用户,使用户始终有感兴趣的书籍阅读。

Description

推荐用户阅读喜好的书籍的方法及装置 技术领域
[0001] 本发明涉及到电子书领域用户选择读书的方法, 特别是涉及到一种推荐用户阅 读喜好的书籍的方法及装置。
背景技术
[0002] 随着智能手机的普及, 现有很多人都喜欢读电子书, 方便随吋阅读。 下载一个
APP后, 访问 APP的服务器的数据库, 获取很多书籍资源。
[0003] 现在的阅读 APP, 都会推荐一些比较畅销的书或好评率较高的书在主界面, 供 用户选择阅读。 但是畅销的书或者好评率较高的书不一定是用户比较喜欢的。 技术问题
[0004] 本发明的主要目的为提供一种推荐用户阅读喜好的书籍的方法及装置, 将用户 可能喜欢的书籍名单发送给用户。
问题的解决方案
技术解决方案
[0005] 本发明提出一种推荐用户阅读喜好的书籍的方法, 包括步骤:
[0006] 获取用户喜好的书籍信息;
[0007] 将所述书籍信息按照不同的维度生成至少一个推荐书籍名单;
[0008] 将所述推荐书籍名单发送给用户。
[0009] 进一步地, 所述获取用户喜好的书籍信息包括:
[0010] 获取用户的身份信息, 所述身份信息包括用户的性别、 年齢、 所在地区、 学历 的一种或多种;
[0011] 获取服务器数据库里与其他相同身份信息用户的书籍, 该书籍为用户喜好的书 禾曰。
[0012] 进一步地, 所述维度包括: 书籍类型、 特殊专题、 其他;
[0013] 其中所述书籍类型包括: 历史、 科幻、 文学、 言情、 武侠、 修真;
[0014] 所述特殊专题包括: 十大排行榜、 周排行榜、 月排行榜、 作者排行榜。 [0015] 进一步地, 所述获取用户喜好的书籍信息包括:
[0016] 获取用户的行为信息, 所述行为信息包括用户的浏览服务器数据库吋对书籍的 点击次数、 阅读吋间、 付费、 搜索行为;
[0017] 根据用户的行为信息, 运用预设的逻辑计算出用户喜爱的书籍的类型;
[0018] 设置服务器数据库里的所述书籍类型排名在预设范围内的书籍为所述用户喜好 的书籍;
[0019] 获取所述用户喜好的书籍的书籍信息。
[0020] 进一步地, 所述计算出用户喜爱的书籍的类型之后包括:
[0021] 将新加入服务器数据库的属于所述用户喜好的类型的书籍设置为用户喜好的书 禾曰。
[0022] 进一步地, 将所述推荐书籍名单发送给用户前包括:
[0023] 将书籍名单上的书籍按照拥有的用户数量从多到少的顺序进行排序。
[0024] 本发明提出一种推荐用户阅读喜好的书籍的装置, 包括: 获取模块, 用于获取 用户喜好的书籍信息;
[0025] 名单模块, 用于将所述书籍信息按照不同的维度生成至少一个推荐书籍名单; [0026] 发送模块, 将所述推荐书籍名单发送给用户。
[0027] 进一步地, 所述获取模块包括:
[0028] 身份单元, 用于获取用户的身份信息, 所述身份信息包括用户的性别、 年齢、 所在地区、 学历的一种或多种;
[0029] 相同单元, 用于获取服务器数据库里与其他相同身份信息用户的书籍, 该书籍 为用户喜好的书籍。
[0030] 进一步地, 所述获取模块还包括:
[0031] 行为单元, 用于获取用户的行为信息, 所述行为信息包括用户的浏览服务器数 据库吋对书籍的点击次数、 阅读吋间、 付费、 搜索行为;
[0032] 计算单元, 用于根据用户的行为信息, 运用预设的逻辑计算出用户喜爱的书籍 的类型;
[0033] 排名单元, 用于设置服务器数据库里的所述书籍类型排名在预设范围内的书籍 为所述用户喜好的书籍; [0034] 新书单元, 用于将新加入服务器数据库的属于所述用户喜好的类型的书籍设置 为用户喜好的书籍;
[0035] 获取单元, 用于获取所述用户喜好的书籍的书籍信息。
[0036] 进一步地, 所述推荐用户阅读喜好的书籍的装置还包括:
[0037] 排序模块, 用于将书籍名单上的书籍按照拥有的用户数量从多到少的顺序进行 排序。
发明的有益效果
有益效果
[0038] 与现有技术相比, 本发明的有益效果是: 根据用户的自身身份以及阅读记录, 识别用户感兴趣的书籍, 并将其发送到用户的个人账户上, 使用户始终有自己 感兴趣的书籍阅读。
对附图的简要说明
附图说明
[0039] 图 1是本发明一实施例的推荐用户阅读喜好的书籍的步骤示意图;
[0040] 图 2是本发明一实施例的推荐用户阅读喜好的书籍的步骤示意图;
[0041] 图 3是本发明一实施例的推荐用户阅读喜好的书籍的步骤示意图;
[0042] 图 4是本发明一实施例的推荐用户阅读喜好的书籍的步骤示意图;
[0043] 图 5是本发明一实施例的推荐用户阅读喜好的书籍的结构示意图;
[0044] 图 6是本发明一实施例的推荐用户阅读喜好的书籍的结构示意图;
[0045] 图 7是本发明一实施例的推荐用户阅读喜好的书籍的结构示意图;
[0046] 图 8是本发明一实施例的推荐用户阅读喜好的书籍的结构示意图。
[0047]
[0048] 本发明目的的实现、 功能特点及优点将结合实施例, 参照附图做进一步说明。
实施该发明的最佳实施例
本发明的最佳实施方式
[0049] 应当理解, 此处所描述的具体实施例仅仅用以解释本发明, 并不用于限定本发 明。 [0050] 参照图 1, 提出本发明的一实施例的推荐用户阅读喜好的书籍的方法, 包括步 骤:
[0051] Sl、 获取用户喜好的书籍信息;
[0052] S2、 将所述书籍信息按照不同的维度生成至少一个推荐书籍名单;
[0053] S4、 将所述推荐书籍名单发送给用户。
[0054] 本实施例中, 书籍信息是指书籍的名字、 内容、 字数、 类型、 作者、 主角以及 一些明显标签等能体现书籍的信息, 还包括在服务器数据库里的链接。 例如 《 西游记》 是书籍的名字; 其内容是指具体的情节等描述, 字数约 82万字; 类型 是古代长篇小说; 作者是吴承恩; 主角是孙悟空、 唐僧等; 一些明显标签是指 如"四大名著之一 "使人们说起来就能联想到该书籍的关键词, 明显标签也可以是 主角名字等。 书籍名单是指多个书籍名字组成的书籍名单以及该书籍对应的链 接。 在智能终端例如手机上安装一款读书的 APP后, APP来获取用户喜好的书籍 信息然后将书籍名单发送给用户。 用户喜好的书籍信息是根据用户的个人信息 或者是用户的阅读记录等其他信息判断出用户的书籍。 例如用户是 80年代出生 的男性, 则用户可能喜欢 80后作者著作的书籍; 其中 80年代出生的男性就是指 个人信息。 又例如用户之前有阅读过 《西游记》 、 《三国演义》 , 则说明用户 喜欢古代经典小说。 S2所述的维度, 是指按书籍类型分类的依据, 例如书籍类 型就是指一个维度, 书籍作者也是指一个维度。 维度包括: 书籍类型、 特殊专 题、 其他; 其中书籍类型包括: 历史、 科幻、 文学、 言情、 武侠、 修真; 特殊 专题包括: 十大排行榜、 周排行榜、 月排行榜、 作者排行榜。 其他是指商家可 以根据自身的需求来定义维度等。 APP将用户喜欢的书籍按照维度进行划分, 每 个维度对应生成一个推荐书籍名单, 然后将维度对应的书籍名单发送给用户, 方便用户査找想看的书籍, 用户想看哪本书吋, 点击该书籍名单, 即点击了该 书籍对应的链接, 则进入到阅读该书籍的界面。 具体的, 发送给用户是发送给 用户该服务器上注册的账户, 用户登户个人账户后即可以看到推荐书籍名单, 通过服务器将推荐书籍名单显示在 APP的其中一个页面上。 在其他实施例场合中 , 也可以是用户打幵智能终端的网页登录某一读书的网站来看到推荐书籍名单 [0055] 参照图 2, 本实施例中, 所述获取用户喜好的书籍信息包括:
[0056] Sl l、 获取用户的身份信息, 所述身份信息包括用户的性别、 年齢、 所在地区 、 学历的一种或多种;
[0057] S12、 获取服务器数据库里与其他相同身份信息用户的书籍, 该书籍为用户喜 好的书籍。
[0058] 本实施例中, 虽然说不同的人喜欢阅读不同类型的书籍, 但是同一种类型的人 喜欢阅读的书籍类型有很多都是类似的。 例如 30-40岁以上的中高层学历人士喜 欢阅读商务、 成功类型的书籍, 国内一线城市的人相较小城市的人生活比较小 资, 很多阅读的书籍都偏向小清新, 普遍男性喜欢看武侠、 历史类的书籍, 女 性喜欢看言情、 生活类的书籍。 APP获取整个服务器的全部用户的身份信息以及 阅读记录, 然后根据用户输入的身份信息, 看与用户身份一样的人都看的是哪 些书籍, 因为用户与这些其他用户的身份都一样, 年齢相仿、 性别一样、 处于 同样的城市, 获得的学历也一样, 从而成长的环境也都类似, 因此喜欢阅读的 书籍也都很多相似, 因而这些书籍就是用户喜好的书籍。 在一具体实施例中, 将与用户身份一样的其他用户阅读书籍最多的三本推荐给用户, 例如, 某一用 户 A男 28岁在深圳工作, 是本科学历, 该平台上与用户 A相同身份的用户有 100人 , 这 100人中有 30人阅读 《三体》 , 26人阅读 《富爸爸穷爸爸》 , 20人阅读 《诛 仙》 , 其他的书籍在这 100人中均是少于 20人阅读, 因此将上述三本书默认为用 户 A喜好阅读的书籍, 将这三本书的名单发送给用户 。 上述 Sl l、 S12的步骤适 用于刚成为该 APP的新用户, 因新用户没有阅读历史记录, 因而参考他人的阅读 书籍, 来推荐给新用户。 另外, 在获取用户的身份信息吋, 可以是用户注册吋 填写的个人身份信息, 也可以是用户通过绑定其他 APP来登陆的, 例如用户用 Q Q来注册该阅读 APP的账户, 即阅读 APP通过读取该用户的 QQ信息来获取用户的 身份信息。
[0059] 参照图 4, 本实施例中, 将所述推荐书籍名单发送给用户前包括:
[0060] S3、 将推荐书籍名单上的书籍按照拥有的用户数量从多到少的顺序进行排序。
[0061] 本实施例中, 将 《三体》 、 《富爸爸穷爸爸》 、 《诛仙》 这三本书推荐给用户 吋, 按照这一顺序来进行推荐, 因 《三体》 有 30人和 A用户相同身份的人阅读, 是最大的阅读群体, 说明这本书最受这样的群体喜欢, 因而将这本书最优先推 荐给 A用户, 同样将后两本书依次排序。
[0062] 参照图 3, 本实施例中, 所述获取用户喜好的书籍信息包括:
[0063] S13、 获取用户的行为信息, 所述行为信息包括用户的浏览服务器数据库吋对 书籍的点击次数、 阅读吋间、 付费、 搜索行为;
[0064] S14、 根据用户的行为信息, 运用预设的逻辑计算出用户喜爱的书籍的类型; [0065] S15、 设置服务器数据库里的所述书籍类型排名在预设范围内的书籍为所述用 户喜好的书籍;
[0066] S17、 获取所述用户喜好的书籍的书籍信息。
[0067] 本实施例中, 用户的行为信息是指用户在 APP界面的操作信息, 包括对某本书 的点击次数、 阅读吋间、 支付的阅读费用、 寻找书吋搜索的关键字等行为, 上 述行为对某本书籍或某类书籍产生的行为越多, 说明用户对这本书籍或这类书 籍越是喜好。 例如, A用户在 8月份点击了历史小说 40次, 点击玄幻小说 32次, 阅读历史小说吋间上是 20小吋, 阅读玄幻小说吋间上是 15小吋, 共购买了 3本历 史小说消费 30元, 共购买 3本玄幻小说消费 28元, 期间多次在该 APP内搜索 "历史 "、 "华夏"、 "古代"、 "玄幻"、 "修真 "等相关的书籍, APP获取到 A用户的行为后 , 计算出用户喜欢的书籍是历史类型和玄幻类型, 然后在服务器数据库内搜索 这两类书籍各自好评排名前 3的书, 分别是在历史类型排名前 3的 《汉乡》 、 《 带着仓库到大明》 、 《神话版三国》 以及玄幻类型排名前 3的 《圣墟》 、 《尘骨 》 、 《天道图书馆》 , 一共 6本书籍发送给 A用户, 。 在发送推荐书籍名单吋, 按照好评排名的顺序生成推荐书籍名单, 使最有可能受用户喜欢的书籍放在最 前面, 同吋也将对应的书籍信息发送给用户, 其中发送的书籍信息至少包括书 名和阅读链接。 在另一具体实施例中, 排名也可以是服务器数据库内用户点击 率的排名, 从而可能就不是上述的 6本书籍。 另外, 书籍类型也可以是以作者分 类的, 例如 A用户在某个段吋间看的书都是江南 (作者笔名) 著作的, 因而在推 荐的吋候推荐的都是江南著作的书籍。
[0068] 本实施例中, 所述计算出用户喜爱的书籍的类型之后包括:
[0069] S16、 将新加入服务器数据库的属于所述用户喜好的类型的书籍设置为用户喜 好的书籍。
[0070] 本实施例中, 由于服务器数据库每天是更新的, 因而刚更新的书籍是很少有用 户点击, 有可能是用户喜欢的而无法推荐给用户, 因而设置 S16步骤, 将该类型 的新加入服务器数据库的书籍也设置有用户喜好的书籍, 在 APP界面推送给用户
[0071] 综上所述, 本发明的推荐用户阅读喜好的书籍的方法可以根据用户的自身身份 以及阅读记录, 识别用户感兴趣的书籍, 并将其发送到用户的个人账户上, 使 用户始终有自己感兴趣的书籍阅读。
[0072] 参照图 5, 本发明提供一种推荐用户阅读喜好的书籍的装置, 其特征在于, 包 括:
[0073] 获取模块 1, 用于获取用户喜好的书籍信息;
[0074] 名单模块 2, 用于将所述书籍信息按照不同的维度生成至少一个推荐书籍名单 [0075] 发送模块 4, 将所述推荐书籍名单发送给用户。
[0076] 本实施例中, 书籍信息是指书籍的名字、 内容、 字数、 类型、 作者、 主角以及 一些明显标签等能体现书籍的信息, 还包括在服务器数据库里的链接。 例如 《 西游记》 是书籍的名字; 其内容是指具体的情节等描述, 字数约 82万字; 类型 是古代长篇小说; 作者是吴承恩; 主角是孙悟空、 唐僧等; 一些明显标签是指 如"四大名著之一 "使人们说起来就能联想到该书籍的关键词, 明显标签也可以是 主角名字等。 书籍名单是指多个书籍名字组成的书籍名单以及该书籍对应的链 接。 在智能终端例如手机上安装一款读书的 APP后, 获取模块 1获取用户喜好的 书籍信息然后发送模块 4将书籍名单发送给用户。 用户喜好的书籍信息是根据用 户的个人信息或者是用户的阅读记录等其他信息判断出用户的书籍。 例如用户 是 80年代出生的男性, 则获取模块 1判断用户可能喜欢 80后作者著作的书籍; 其 中 80年代出生的男性就是指个人信息。 又例如用户之前有阅读过 《西游记》 、 《三国演义》 , 则说明用户喜欢古代经典小说。 其中上述的维度, 是指按书籍 类型分类的依据, 例如书籍类型就是指一个维度, 书籍作者也是指一个维度。 维度包括: 书籍类型、 特殊专题、 其他; 其中书籍类型包括: 历史、 科幻、 文 学、 言情、 武侠、 修真; 特殊专题包括: 十大排行榜、 周排行榜、 月排行榜、 作者排行榜。 其他是指商家可以根据自身的需求来定义维度等。 名单模块 2将用 户喜欢的书籍按照维度进行划分, 每个维度对应生成一个推荐书籍名单, 然后 发送模块 4将维度对应的书籍名单发送给用户, 方便用户査找想看的书籍, 用户 想看哪本书吋, 点击该书籍名单, 即点击了该书籍对应的链接, 则进入到阅读 该书籍的界面。 具体的, 发送模块 4发送给用户是发送给用户该服务器上注册的 账户, 用户登户个人账户后即可以看到推荐书籍名单, 通过服务器将推荐书籍 名单显示在 APP的其中一个页面上。 在其他实施例场合中, 也可以是用户打幵智 能终端的网页登录某一读书的网站来看到推荐书籍名单。
[0077] 参照图 6, 本实施例中, 所述获取模块 1包括:
[0078] 身份单元 11, 用于获取用户的身份信息, 所述身份信息包括用户的性别、 年齢
、 所在地区、 学历的一种或多种;
[0079] 相同单元 12, 用于获取服务器数据库里与其他相同身份信息用户的书籍, 该书 籍为用户喜好的书籍。
[0080] 本实施例中, 虽然说不同的人喜欢阅读不同类型的书籍, 但是同一种类型的人 喜欢阅读的书籍类型有很多都是类似的。 例如 30-40岁以上的中高层学历人士喜 欢阅读商务、 成功类型的书籍, 国内一线城市的人相较小城市的人生活比较小 资, 很多阅读的书籍都偏向小清新, 普遍男性喜欢看武侠、 历史类的书籍, 女 性喜欢看言情、 生活类的书籍。 身份单元 11获取整个服务器的全部用户的身份 信息以及阅读记录, 然后相同单元 12根据用户输入的身份信息, 看与用户身份 一样的人都看的是哪些书籍, 因为用户与这些其他用户的身份都一样, 年齢相 仿、 性别一样、 处于同样的城市, 获得的学历也一样, 从而成长的环境也都类 似, 因此喜欢阅读的书籍也都很多相似, 因而这些书籍就是用户喜好的书籍。 在一具体实施例中, 相同单元 12将与用户身份一样的其他用户阅读书籍最多的 三本推荐给用户, 例如, 某一用户 A男 28岁在深圳工作, 是本科学历, 身份单元 11确认该平台上与用户 A相同身份的用户有 100人, 这 100人中有 30人阅读 《三体 》 , 26人阅读 《富爸爸穷爸爸》 , 20人阅读 《诛仙》 , 其他的书籍在这 100人中 均是少于 20人阅读, 因此相同单元 12将上述三本书默认为用户 A喜好阅读的书籍 , 然后发送模块 4将这三本书的名单发送给用户 。 上述身份单元 11和相同单元 1 2的使用适用于刚成为该 APP的新用户, 因新用户没有阅读历史记录, 因而获取 模块 1参考他人的阅读书籍, 来推荐给新用户。 另外, 身份单元 11在获取用户的 身份信息吋, 可以是用户注册吋填写的个人身份信息, 也可以是用户通过绑定 其他 APP来登陆的, 例如用户用 QQ来注册该阅读 APP的账户, 即阅读 APP通过读 取该用户的 QQ信息来获取用户的身份信息。
[0081] 参照图 7, 本实施例中, 所述获取模块 1还包括:
[0082] 行为单元 13, 用于获取用户的行为信息, 所述行为信息包括用户的浏览服务器 数据库吋对书籍的点击次数、 阅读吋间、 付费、 搜索行为;
[0083] 计算单元 14, 用于根据用户的行为信息, 运用预设的逻辑计算出用户喜爱的书 籍的类型;
[0084] 排名单元 15, 用于设置服务器数据库里的所述书籍类型排名在预设范围内的书 籍为所述用户喜好的书籍;
[0085] 新书单元 16, 用于将新加入服务器数据库的属于所述用户喜好的类型的书籍设 置为用户喜好的书籍;
[0086] 获取单元 17, 用于获取所述用户喜好的书籍的书籍信息。
[0087] 本实施例中, 用户的行为信息是指用户在 APP界面的操作信息, 包括对某本书 的点击次数、 阅读吋间、 支付的阅读费用、 寻找书吋搜索的关键字等行为, 上 述行为对某本书籍或某类书籍产生的行为越多, 说明用户对这本书籍或这类书 籍越是喜好。 例如, 行为单元 13获得 A用户在 8月份点击了历史小说 40次, 点击 玄幻小说 32次, 阅读历史小说吋间上是 20小吋, 阅读玄幻小说吋间上是 15小吋 , 共购买了 3本历史小说消费 30元, 共购买 3本玄幻小说消费 28元, 期间多次在 该 APP内搜索 "历史"、 "华夏"、 "古代"、 "玄幻,,、 "修真 "等相关的书籍, 行为单 元 13获取到 A用户的行为后, 发送给计算单元 14, 然后计算单元 14计算出用户喜 欢的书籍是历史类型和玄幻类型, 然后排名单元 15在服务器数据库内搜索这两 类书籍各自好评排名前 3的书, 分别是在历史类型排名前 3的 《汉乡》 、 《带着 仓库到大明》 、 《神话版三国》 以及玄幻类型排名前 3的 《圣墟》 、 《尘骨》 、 《天道图书馆》 , 然后获取单元 17获取这几本书籍的书籍信息 (该书籍信息至 少包括这几本书的名字和对应的链接地址) , 一共 6本书籍发送给 A用户, A用户 想看哪本书, 则可以直接点击该书籍信息对应的链接进入阅读界面。 在发送模 块 4发送推荐书籍名单吋, 排名单元 15按照好评排名的顺序生成推荐书籍名单, 使最有可能受用户喜欢的书籍放在最前面。 在另一具体实施例中, 排名单元 15 的排名也可以是服务器数据库内用户点击率的排名, 从而可能就不是上述的 6本 书籍。 另外, 计算单元 14在计算书籍类型也可以是以作者分类的, 例如 A用户在 某个段吋间看的书都是江南 (作者笔名) 著作的, 因而在推荐的吋候推荐的都 是江南著作的书籍。 另外, 由于服务器数据库每天是更新的, 因而刚更新的书 籍是很少有用户点击, 有可能是用户喜欢的而无法推荐给用户, 因而设置新书 单元 16, 将该类型的新加入服务器数据库的书籍也设置有用户喜好的书籍, 在 A PP界面推送给用户。
[0088] 参照图 8, 本实施例中, 所述推荐用户阅读喜好的书籍的装置还包括:
[0089] 排序模块 3, 用于将书籍名单上的书籍按照拥有的用户数量从多到少的顺序进 行排序。
[0090] 本实施例中, 某一用户 A男 28岁在深圳工作, 是本科学历, 该平台上与用户 A 相同身份的用户有 100人, 这 100人中有 30人阅读 《三体》 , 26人阅读 《富爸爸 穷爸爸》 , 20人阅读 《诛仙》 , 其他的书籍在这 100人中均是少于 20人阅读, 因 此将上述三本书默认为用户 A喜好阅读的书籍, 将这三本书的名单发送给用户 A 。 将 《三体》 、 《富爸爸穷爸爸》 、 《诛仙》 这三本书推荐给用户吋, 排序模 块 3按照这一顺序来进行推荐, 因 《三体》 有 30人和 A用户相同身份的人阅读, 是最大的阅读群体, 说明这本书最受这样的群体喜欢, 因而将这本书最优先推 荐给 A用户, 同样将后两本书依次排序。
[0091] 综上所述, 本发明的推荐用户阅读喜好的书籍的装置可以根据用户的自身身份 以及阅读记录, 识别用户感兴趣的书籍, 并将其发送到用户的个人账户上, 使 用户始终有自己感兴趣的书籍阅读。
[0092] 以上所述仅为本发明的优选实施例, 并非因此限制本发明的专利范围, 凡是利 用本发明说明书及附图内容所作的等效结构或等效流程变换, 或直接或间接运 用在其他相关的技术领域, 均同理包括在本发明的专利保护范围内。
[£600]
II
TZ.S0ll/Z.l0ZN3/X3d ΐ^Ζ.060/6ΪΟΖ OAV

Claims

权利要求书
一种推荐用户阅读喜好的书籍的方法, 其特征在于, 包括步骤: 获取用户喜好的书籍信息;
将所述书籍信息按照不同的维度生成至少一个推荐书籍名单; 将所述推荐书籍名单发送给用户。
如权利要求 1所述的推荐用户阅读喜好的书籍的方法, 其特征在于, 所述获取用户喜好的书籍信息包括:
获取用户的身份信息, 所述身份信息包括用户的性别、 年齢、 所在地 区、 学历的一种或多种;
获取服务器数据库里与其他相同身份信息用户的书籍, 该书籍为用户 喜好的书籍。
如权利要求 1所述的推荐用户阅读喜好的书籍的方法, 其特征在于, 所述维度包括: 书籍类型、 特殊专题、 其他;
其中所述书籍类型包括: 历史、 科幻、 文学、 言情、 武侠、 修真; 所述特殊专题包括: 十大排行榜、 周排行榜、 月排行榜、 作者排行榜 如权利要求 3所述的推荐用户阅读喜好的书籍的方法, 其特征在于, 所述获取用户喜好的书籍信息包括:
获取用户的行为信息, 所述行为信息包括用户的浏览服务器数据库吋 对书籍的点击次数、 阅读吋间、 付费、 搜索行为;
根据用户的行为信息, 运用预设的逻辑计算出用户喜爱的书籍的类型
设置服务器数据库里的所述书籍类型排名在预设范围内的书籍为所述 用户喜好的书籍;
获取所述用户喜好的书籍的书籍信息。
如权利要求 4所述的推荐用户阅读喜好的书籍的方法, 其特征在于, 所述计算出用户喜爱的书籍的类型之后包括:
将新加入服务器数据库的属于所述用户喜好的类型的书籍设置为用户 喜好的书籍。
如权利要求 1所述的推荐用户阅读喜好的书籍的方法, 其特征在于, 将所述推荐书籍名单发送给用户前包括:
将书籍名单上的书籍按照拥有的用户数量从多到少的顺序进行排序。 一种推荐用户阅读喜好的书籍的装置, 其特征在于, 包括: 获取模块, 用于获取用户喜好的书籍信息;
名单模块, 用于将所述书籍信息按照不同的维度生成至少一个推荐书 籍名单;
发送模块, 将所述推荐书籍名单发送给用户。
如权利要求 7所述的推荐用户阅读喜好的书籍的装置, 其特征在于, 所述获取模块包括:
身份单元, 用于获取用户的身份信息, 所述身份信息包括用户的性别 、 年齢、 所在地区、 学历的一种或多种;
相同单元, 用于获取服务器数据库里与其他相同身份信息用户的书籍 , 该书籍为用户喜好的书籍。
如权利要求 7所述的推荐用户阅读喜好的书籍的装置, 其特征在于, 所述获取模块还包括:
行为单元, 用于获取用户的行为信息, 所述行为信息包括用户的浏览 服务器数据库吋对书籍的点击次数、 阅读吋间、 付费、 搜索行为; 计算单元, 用于根据用户的行为信息, 运用预设的逻辑计算出用户喜 爱的书籍的类型;
排名单元, 用于设置服务器数据库里的所述书籍类型排名在预设范围 内的书籍为所述用户喜好的书籍;
新书单元, 用于将新加入服务器数据库的属于所述用户喜好的类型的 书籍设置为用户喜好的书籍。
如权利要求 9所述的推荐用户阅读喜好的书籍的装置, 其特征在于, 所述获取模块还包括:
获取单元, 用于获取所述用户喜好的书籍的书籍信息。 [权利要求 11] 如权利要求 7所述的推荐用户阅读喜好的书籍的装置, 其特征在于, 还包括:
排序模块, 用于将书籍名单上的书籍按照拥有的用户数量从多到少的 顺序进行排序。
PCT/CN2017/110571 2017-11-10 2017-11-10 推荐用户阅读喜好的书籍的方法及装置 WO2019090741A1 (zh)

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