CN108960961B - Book recommendation method and book recommendation system - Google Patents
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Abstract
The application discloses a book recommendation method and a book recommendation system, wherein the method comprises the following steps: obtaining scores of titles recommended for users; and recommending book information for the user according to the score, wherein the score can reflect short boards in the aspect of knowledge of the user or can reflect the direction of the knowledge which needs to be supplemented by the user, so that when recommending the book information for the user according to the score, the matching rate of the recommended book information and the requirement of the user is relatively high, and the matching rate of the purchased book and the requirement of the user is relatively high after the user purchases the book according to the recommended book information.
Description
Technical Field
The application relates to the field of computers, in particular to a book recommendation method and a book recommendation system.
Background
With the continuous development of the internet technology, the concept of knowledge payment is continuously in depth, a user can purchase books on a shopping platform to enrich the user, but the user may not know the user enough or only purchases the books according to the propaganda content of the books on the shopping platform, so that the matching degree of the purchased books and the self needs is relatively low.
Disclosure of Invention
The main object of the present application is to provide a book recommendation method and a book recommendation system, so that the matching degree between the book purchased by the user and the needs of the user is relatively high.
In order to achieve the above object, the present application provides a book recommendation method, including:
obtaining scores of titles recommended for users;
and recommending book information for the user according to the score.
Optionally, the obtaining the score of the title recommended for the user includes:
obtaining an interest identifier selected by the user;
sending the question corresponding to the interest identification to the user;
comparing the answer provided by the user for the question with a target answer to obtain a comparison result;
and determining the score of the title recommended for the user according to the comparison result.
Optionally, the sending the topic corresponding to the interest identifier to the user includes:
determining at least one target option corresponding to the interest identifier;
according to a preset distribution rule, performing division operation on a preset threshold and the number of the target options to determine the number of questions corresponding to each target option;
and selecting the topics with the number corresponding to each target option from the topics corresponding to each target option according to the number of the topics corresponding to each target option so as to send the topics with the number corresponding to each target option to the user.
Optionally, the interest identification comprises a person identification.
Optionally, the determining, according to the comparison result, a score of a title recommended for the user includes:
determining a comparison result of the questions corresponding to each target option;
and determining the score of the question corresponding to each target option according to the comparison result of the question corresponding to each target option and the score distributed to the question corresponding to each target option.
Optionally, recommending book information for the user according to the score includes:
adding the scores of the questions corresponding to the target options to obtain the scores corresponding to the target options;
determining a target option with the lowest score;
and recommending the book information of the specified number corresponding to the target option with the minimum score to the user according to a preset recommendation rule.
In order to achieve the above object, the present application provides a book recommendation system, including:
the system comprises an acquisition unit, a processing unit and a display unit, wherein the acquisition unit is used for acquiring scores of titles recommended for users;
and the recommending unit is used for recommending the book information for the user according to the score.
Optionally, when the obtaining unit is configured to obtain a score of a title recommended for a user, the obtaining unit is specifically configured to:
obtaining an interest identifier selected by the user;
sending the question corresponding to the interest identification to the user;
comparing the answer provided by the user for the question with a target answer to obtain a comparison result;
and determining the score of the title recommended for the user according to the comparison result.
Optionally, when the obtaining unit is configured to send the topic corresponding to the interest identifier to the user, the obtaining unit is specifically configured to:
determining at least one target option corresponding to the interest identifier;
according to a preset distribution rule, performing division operation on a preset threshold and the number of the target options to determine the number of questions corresponding to each target option;
and selecting the topics with the number corresponding to each target option from the topics corresponding to each target option according to the number of the topics corresponding to each target option so as to send the topics with the number corresponding to each target option to the user.
The interest identification comprises a person identification.
Optionally, when the obtaining unit is configured to determine, according to the comparison result, a score of a title recommended for the user, the obtaining unit is specifically configured to:
determining a comparison result of the questions corresponding to each target option;
and determining the score of the question corresponding to each target option according to the comparison result of the question corresponding to each target option and the score distributed to the question corresponding to each target option.
Optionally, when the recommending unit is configured to recommend the book information to the user according to the score, the recommending unit includes:
adding the scores of the questions corresponding to the target options to obtain the scores corresponding to the target options;
determining a target option with the lowest score;
and recommending the book information of the specified number corresponding to the target option with the minimum score to the user according to a preset recommendation rule.
The technical scheme provided by the embodiment of the application can have the following beneficial effects:
in the method, the book information is recommended for the user according to the score of the title recommended for the user, and the score can reflect short boards in the knowledge aspect of the user or reflect the direction of the knowledge required to be supplemented by the user, so that when the book information is recommended for the user according to the score, the matching rate of the recommended book information and the requirement of the user is relatively high, and the matching rate of the purchased book and the requirement of the user is relatively high after the user purchases the book according to the recommended book information.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, serve to provide a further understanding of the application and to enable other features, objects, and advantages of the application to be more apparent. The drawings and their description illustrate the embodiments of the invention and do not limit it. In the drawings:
fig. 1 is a schematic flowchart of a book recommendation method provided in the present application;
fig. 2 is a schematic flowchart of another book recommendation method provided in the present application;
fig. 3 is a schematic flowchart of another book recommendation method provided in the present application;
FIG. 4 is a schematic flow chart of another data recommendation method provided herein;
fig. 5 is a schematic flowchart of another book recommendation method provided in the present application;
fig. 6 is a schematic mechanism diagram of a book recommendation system provided in the present application.
Detailed Description
In order to make the technical solutions better understood by those skilled in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only partial embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that the terms "first," "second," and the like in the description and claims of this application and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It should be understood that the data so used may be interchanged under appropriate circumstances such that embodiments of the application described herein may be used. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
In this application, the terms "upper", "lower", "left", "right", "front", "rear", "top", "bottom", "inner", "outer", "middle", "vertical", "horizontal", "lateral", "longitudinal", and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings. These terms are used primarily to better describe the present application and its embodiments, and are not used to limit the indicated devices, elements or components to a particular orientation or to be constructed and operated in a particular orientation.
Moreover, some of the above terms may be used to indicate other meanings besides the orientation or positional relationship, for example, the term "on" may also be used to indicate some kind of attachment or connection relationship in some cases. The specific meaning of these terms in this application will be understood by those of ordinary skill in the art as appropriate.
Furthermore, the terms "mounted," "disposed," "provided," "connected," and "sleeved" are to be construed broadly. For example, it may be a fixed connection, a removable connection, or a unitary construction; can be a mechanical connection, or an electrical connection; may be directly connected, or indirectly connected through intervening media, or may be in internal communication between two devices, elements or components. The specific meaning of the above terms in the present application can be understood by those of ordinary skill in the art as appropriate.
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.
Fig. 1 is a schematic flowchart of a book recommendation method provided in the present application, and as shown in fig. 1, the method includes the following steps:
101. and acquiring the score of the title recommended for the user.
Specifically, when a user purchases a book on a book recommendation system (e.g., a shopping platform for books), the book recommendation system recommends a certain number of titles to the user in order to know the knowledge requirement of the user or to know the short knowledge board of the user, and the specific titles may be set according to actual needs, for example: whether financial topics or historical topics are recommended to the user, the depth related to the topics and the like can be recommended according to feedback information of the user or according to interests, and the specific mode of recommending the topics is not specifically limited herein.
102. And recommending book information for the user according to the score.
Specifically, when recommending book information for a user, the book information is recommended according to the score of the title recommended for the user, and the score can reflect the short board in the aspect of knowledge of the user or reflect the direction of the knowledge that the user needs to supplement, so that when recommending book information for the user according to the score, the matching rate of the recommended book information and the requirement of the user is relatively high, and the matching rate of the book purchased by the user and the requirement of the user is relatively high after purchasing the book according to the recommended book information.
For example, after obtaining the score, the score segment where the score is located may be determined, then the book information configured for the score segment in advance is obtained, and then the obtained book information is recommended to the user, it should be noted that the above is only an example of recommending book information provided by the present application, and the implementation manner of the present application is not limited.
In a possible embodiment, fig. 2 is a schematic flow chart of another book recommendation method provided in the present application, and as shown in fig. 2, when step 101 is executed, the method specifically includes the following steps:
201. and acquiring the interest identification selected by the user.
Specifically, the book recommendation system may recommend an interest identifier for the user, and the user may select a corresponding interest identifier according to a requirement of the user, so that the book recommendation system obtains the interest identifier selected by the user.
For example, the interest identifier may be an avatar identifier of a character with social influence, and different characters may correspond to different fields, for example, the interest identifier may include an avatar identifier of cloudson, an avatar identifier of yi zhongtian, an avatar identifier of bafite, and the like, where cloudson represents an internet field, yi zhongtian represents a historical field, and bafite represents a financial field, and the user may select a corresponding avatar identifier according to the field of interest, and on the basis of the above example, a field may be further subdivided, taking the historical field as an example, the field may further include an avatar identifier of chongye (which is well known from historical knowledge of the qing dynasty), an avatar identifier of yi zhongtian (which is well known from historical knowledge of the three nations), an avatar identifier of yuanhefying (which is well known from historical knowledge of the song dynasty), on the basis of the above example, the segmentation can be performed again according to a certain historical character or a certain historical event known by a certain character with social influence, and details are not repeated herein.
On the basis of the example, the book recommendation system can recommend a plurality of avatar identifications for the user, the user can select corresponding avatar identifications according to the self requirements, and by taking the history field as an example, if the user wants to roughly know the history, the avatar identification which is easy to be in the history field can be selected; if the user wants to know the three-country times, the head portrait identifier of the yi zhong tian corresponding to the three-country times in the history periods in the history field can be selected; if the user wants to know about a historical person or a historical event, an avatar identification that is well known to the historical person or the historical event may be selected.
It should be noted that the above description is only given as an exemplary description, and is not intended to specifically limit the present application, and the purpose of the present application is to enable an interest identifier to represent a certain field, or represent each sub-field in a certain field, or represent different branches in a certain sub-field, so that a user selects a corresponding interest identifier according to his/her own needs, so that a book recommendation system recommends book information with a high matching rate to the user, and a specific style of the interest identifier, and a field corresponding to the interest identifier, or a sub-field in a certain field, or a branch in a certain sub-field may be set according to actual needs, which is not specifically limited herein.
202. And sending the topic corresponding to the interest identification to the user.
Specifically, after an interest identifier selected by a user is determined, topics are selected from topics preset for the interest identifier and sent to the user, where the number of topics preset for the interest identifier and the specific topics are not specifically limited herein, and the specific number of selected topics may be set according to actual needs, and is not specifically limited herein.
203. And comparing the answer provided by the user for the question with the target answer to obtain a comparison result.
Specifically, after obtaining the topic recommended for the user, the user may select an answer according to the requirement of the topic, for example, the topic may be a judgment topic, and the user may make an incorrect judgment on the topic, or the topic may be a selection topic, and the user may select a candidate answer for the topic.
After the user selects an answer, the book recommendation system needs to judge whether the answer selected by the user for a certain topic is correct or not, the judgment mode can set a target answer for the topic in advance, after the answer selected by the user for the topic is obtained, the target answer set for the topic can be used for comparing with the answer selected by the user for the topic, if the answer selected by the user for the topic is consistent, the answer selected by the user for the topic is determined to be correct, and if the answer selected by the user for the topic is not consistent, the answer selected by the user for the topic is determined to be wrong.
204. And determining the score of the title recommended for the user according to the comparison result.
For example, if the score of the topic is 5, taking the judgment of the topic as an example, when the answer of the user is correct, the score of the user on the topic is determined to be 5, when the answer of the user is wrong, the score of the user on the topic is determined to be 0, taking the selection of the topic as an example, when the answer of the user is correct, the score of the user on the topic is determined to be 5, when the answer of the user is wrong, the score of the user on the topic is determined to be 0, or the score of the user on the topic can be determined according to the proximity degree of the answer selected by the user and the target answer, or the score can be pre-assigned to each answer of the topic, after the answer of the topic is selected by the user, which answer is selected by the user is determined, and then the score corresponding to the answer is determined to be the score of the topic, which should be mentioned above only by way of example, the specific score assigned to a topic and the scoring manner and criteria of a certain topic may be set according to actual needs, and are not specifically limited herein.
In a possible embodiment, fig. 3 is a schematic flow chart of another book recommendation method provided in the present application, and as shown in fig. 3, when step 202 is executed, the following steps may be performed:
301. and determining at least one target option corresponding to the interest identifier.
Specifically, different interest identifiers may correspond to different numbers and different types of target options, or may also correspond to the same number and the same type of target options, where the target options may enable capability dimensions, such as logic capability, communication capability, understanding capability, analysis capability, and the like, and the capability dimensions may be configured for the interest identifiers according to characteristics of the different interest identifiers.
It should be noted that the number and the type of the target options corresponding to the interest identifier may be set according to actual needs, and are not specifically limited herein.
302. And according to a preset distribution rule, performing division operation on a preset threshold and the number of the target options to determine the number of the questions corresponding to each target option.
For example, a preset threshold is preset for an interest identifier, and after a target option corresponding to a certain interest identifier is determined, dividing the preset threshold value and the number of the target options to determine the number of the topics corresponding to each target option under the interest identifier, for example, the target options corresponding to a certain interest identifier include a first target option, a second target option and a third target option, the preset threshold corresponding to the interest identifier is 25, after the number of titles of each target option is determined according to the method, the number of topics corresponding to the first target option may be 8, the number of topics corresponding to the second target option may be 8, the number of topics corresponding to the third target option may be 9, if the preset threshold corresponding to the interest identifier is 24, the first target option, the second target option, and the third target option may respectively correspond to 8 topics.
It should be noted that the foregoing is only an exemplary implementation manner provided by the present application, and is not limited to the present application, and the specific implementation of the preset allocation rule may be set according to actual needs, and is not limited to the specific implementation.
It should be noted again that the preset threshold values corresponding to different interest identifiers may be different or may also be the same, and the preset threshold values corresponding to the interest identifiers may be set according to actual needs, which is not specifically limited herein.
303. And selecting the topics with the number corresponding to each target option from the topics corresponding to each target option according to the number of the topics corresponding to each target option so as to send the topics with the number corresponding to each target option to the user.
For example, a certain number of titles are configured for each target option in advance, for example, 20 titles are configured for a first target option in advance, 30 titles are configured for a second target option in advance, 20 titles are configured for a third option in advance, and after the number of titles corresponding to each target option is determined, a corresponding number of titles are selected from the titles configured for each target option in advance, such as: when the number of topics corresponding to the first target option is 8, the number of topics corresponding to the second target option is 8, and the number of topics corresponding to the third target option is 9, 8 topics are selected from 20 topics configured for the first target option in advance, 8 topics are selected from 30 topics configured for the second target option in advance, and 9 topics are selected from 20 topics configured for the third option in advance.
In one possible embodiment, the interest identifiers shown in FIG. 2 or FIG. 3 may be people identifiers.
Specifically, the person identifier may include: the specific recommendation method of the book information includes detailed description, and details are not repeated here.
In a possible embodiment, fig. 4 is a flowchart illustrating another data recommendation method provided in the present application, and as shown in fig. 4, when step 204 is executed, the following steps may be performed:
401. and determining the comparison result of the titles corresponding to the target options.
402. And determining the score of the question corresponding to each target option according to the comparison result of the question corresponding to each target option and the score distributed to the question corresponding to each target option.
For example, if the target options include a first target option and a second target option, where the titles corresponding to the first target option include a first title and a second title, and the titles corresponding to the second target option include a third title, a fourth title and a fifth title, after obtaining answers provided by the user for the first title to the fifth title, determining answers corresponding to the first title and the second title, determining answers corresponding to the third title to the fifth title, then determining scores corresponding to the first title and the second title under the first target option, and determining scores corresponding to the third title to the fifth title under the second target option, so as to determine the score condition corresponding to each target option.
The assignment of the score and the mode of the topic and the scoring mode of the topic are described in detail above, and are not limited to the details.
In a possible embodiment, fig. 5 is a flowchart illustrating another book recommendation method provided in the present application, and as shown in fig. 5, when step 101 is executed, the method may be implemented by:
501. and performing addition operation on the scores of the questions corresponding to the target options to obtain the scores corresponding to the target options.
502. The least scoring target option is determined.
503. And recommending the book information of the specified number corresponding to the target option with the minimum score to the user according to a preset recommendation rule.
Specifically, after determining the title corresponding to each target option and the score of the title, the total score of each target option may be determined, and the target option with the lowest score may indicate a direction in which the user needs to supplement knowledge or a short board capable of indicating knowledge of the user, so that book information under the target option with the lowest score may be recommended to the user, and the book information may be recommended according to a preset specified number when recommending books, wherein when recommending a specified number of books to the user, the book information may be recommended according to a preset recommendation rule, for example, the target option with the lowest score is a first target option, and the data information configured for the first target option in advance includes 20 books, and if the specified number is 10 books, then 10 books may be randomly selected from the 20 books and recommended to the user, or books with sales ranked in top 10 may be recommended to the user according to sales of the 20 books, the above is only an exemplary preset recommendation rule, and certainly, recommendation rules of other recommendation manners may also be included, and a specific recommendation rule may be set according to an actual situation, which is not specifically limited herein.
Fig. 6 is a schematic mechanism diagram of a book recommendation system provided in the present application, and as shown in fig. 6, the book recommendation system includes:
an obtaining unit 61, configured to obtain a score of a title recommended for a user;
and the recommending unit 62 is configured to recommend the book information to the user according to the score.
In a possible embodiment, when the obtaining unit 61 is configured to obtain the score of the title recommended for the user, specifically:
obtaining an interest identifier selected by the user;
sending the question corresponding to the interest identification to the user;
comparing the answer provided by the user for the question with a target answer to obtain a comparison result;
and determining the score of the title recommended for the user according to the comparison result.
In a possible embodiment, when the obtaining unit 61 is configured to send the topic corresponding to the interest identifier to the user, it is specifically configured to:
determining at least one target option corresponding to the interest identifier;
according to a preset distribution rule, performing division operation on a preset threshold and the number of the target options to determine the number of questions corresponding to each target option;
and selecting the topics with the number corresponding to each target option from the topics corresponding to each target option according to the number of the topics corresponding to each target option so as to send the topics with the number corresponding to each target option to the user.
In one possible embodiment, the interest identification includes a person identification.
In a possible embodiment, when the obtaining unit 61 is configured to determine, according to the comparison result, a score of a topic recommended for the user, specifically:
determining a comparison result of the questions corresponding to each target option;
and determining the score of the question corresponding to each target option according to the comparison result of the question corresponding to each target option and the score distributed to the question corresponding to each target option.
In a possible embodiment, when the recommending unit 62 is configured to recommend book information for the user according to the score, the recommending unit includes:
adding the scores of the questions corresponding to the target options to obtain the scores corresponding to the target options;
determining a target option with the lowest score;
and recommending the book information of the specified number corresponding to the target option with the minimum score to the user according to a preset recommendation rule.
With regard to the system in the above-described embodiment, the specific manner in which each unit performs the operation has been described in detail in the embodiment related to the method, and will not be elaborated here.
In the method, the book information is recommended for the user according to the score of the title recommended for the user, and the score can reflect short boards in the knowledge aspect of the user or reflect the direction of the knowledge required to be supplemented by the user, so that when the book information is recommended for the user according to the score, the matching rate of the recommended book information and the requirement of the user is relatively high, and the matching rate of the purchased book and the requirement of the user is relatively high after the user purchases the book according to the recommended book information.
The above description is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (6)
1. A book recommendation method, the method comprising:
obtaining a score of a title recommended for a user, comprising: obtaining the interest identification selected by the user: the book recommendation system recommends interest identification for the user, and the user selects corresponding interest identification according to the requirement of the user so that the book recommendation system obtains the interest identification selected by the user; sending the topic corresponding to the interest identifier to the user, including: determining at least one target option corresponding to the interest identifier; determining the number of questions corresponding to each target option;
selecting the questions with the number corresponding to each target option from the question library corresponding to each target option according to the number of the questions corresponding to each target option so as to send the questions with the number corresponding to each target option to the user;
comparing the answer provided by the user for the question with a target answer to obtain a comparison result; determining the score of the title recommended for the user according to the comparison result;
recommending book information for the user according to the score, wherein the recommending comprises the following steps:
adding the scores of the questions corresponding to the target options to obtain the scores corresponding to the target options;
determining a target option with the lowest score;
recommending the book information with the specified number corresponding to the target option with the minimum score to the user.
2. The method of claim 1, wherein the interest identification comprises a person identification.
3. The method of claim 1, wherein determining a score for a topic recommended for the user based on the comparison comprises:
determining a comparison result of the questions corresponding to each target option;
and determining the score of the question corresponding to each target option according to the comparison result of the question corresponding to each target option and the score distributed to the question corresponding to each target option.
4. A book recommendation system, comprising:
an acquisition unit configured to acquire a score of a title recommended for a user, the acquisition unit including: obtaining the interest identification selected by the user: the book recommendation system recommends interest identification for the user, and the user selects corresponding interest identification according to the requirement of the user so that the book recommendation system obtains the interest identification selected by the user; sending the topic corresponding to the interest identifier to the user, including: determining at least one target option corresponding to the interest identifier; determining the number of questions corresponding to each target option;
selecting the questions with the number corresponding to each target option from the question library corresponding to each target option according to the number of the questions corresponding to each target option so as to send the questions with the number corresponding to each target option to the user;
comparing the answer provided by the user for the question with a target answer to obtain a comparison result; determining the score of the title recommended for the user according to the comparison result;
the recommending unit is used for recommending book information for the user according to the score, and comprises the following steps:
adding the scores of the questions corresponding to the target options to obtain the scores corresponding to the target options;
determining a target option with the lowest score;
recommending the book information with the specified number corresponding to the target option with the minimum score to the user.
5. The book recommendation system of claim 4, wherein the interest identification comprises a person identification.
6. The book recommendation system according to claim 4, wherein when the obtaining unit is configured to determine, according to the comparison result, the score of the title recommended for the user, specifically:
determining a comparison result of the questions corresponding to each target option;
and determining the score of the question corresponding to each target option according to the comparison result of the question corresponding to each target option and the score distributed to the question corresponding to each target option.
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| CN201810558631.3A CN108960961B (en) | 2018-06-01 | 2018-06-01 | Book recommendation method and book recommendation system |
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| CN201810558631.3A CN108960961B (en) | 2018-06-01 | 2018-06-01 | Book recommendation method and book recommendation system |
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| CN112150713A (en) * | 2020-08-28 | 2020-12-29 | 黄石微美生活网络科技有限公司 | Book borrowing method and background server |
| CN113987353B (en) * | 2021-10-29 | 2022-08-09 | 掌阅科技股份有限公司 | Book recommendation method, computing device and storage medium |
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| CN107766547A (en) * | 2017-10-31 | 2018-03-06 | 掌阅科技股份有限公司 | E-book recommends method, electronic equipment and computer-readable storage medium |
| CN108090855A (en) * | 2017-12-20 | 2018-05-29 | 维沃移动通信有限公司 | Method and mobile terminal are recommended in a kind of study plan |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20170169498A1 (en) * | 2015-12-15 | 2017-06-15 | International Business Machines Corporation | Identifying recommended electronic books with detailed comparisons |
| CN105787839A (en) * | 2016-03-23 | 2016-07-20 | 成都准星云学科技有限公司 | Method and device for pushing learning resources |
| CN107343053A (en) * | 2017-08-01 | 2017-11-10 | 骆德轩 | A kind of content recommendation method |
| CN107766547A (en) * | 2017-10-31 | 2018-03-06 | 掌阅科技股份有限公司 | E-book recommends method, electronic equipment and computer-readable storage medium |
| CN108090855A (en) * | 2017-12-20 | 2018-05-29 | 维沃移动通信有限公司 | Method and mobile terminal are recommended in a kind of study plan |
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