CN106657581A - Electronic book reading plan recommendation system, method thereof, terminal and server - Google Patents
Electronic book reading plan recommendation system, method thereof, terminal and server Download PDFInfo
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- CN106657581A CN106657581A CN201610868738.9A CN201610868738A CN106657581A CN 106657581 A CN106657581 A CN 106657581A CN 201610868738 A CN201610868738 A CN 201610868738A CN 106657581 A CN106657581 A CN 106657581A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M1/00—Substation equipment, e.g. for use by subscribers
- H04M1/72—Mobile telephones; Cordless telephones, i.e. devices for establishing wireless links to base stations without route selection
- H04M1/724—User interfaces specially adapted for cordless or mobile telephones
- H04M1/72448—User interfaces specially adapted for cordless or mobile telephones with means for adapting the functionality of the device according to specific conditions
- H04M1/72451—User interfaces specially adapted for cordless or mobile telephones with means for adapting the functionality of the device according to specific conditions according to schedules, e.g. using calendar applications
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/50—Network services
- H04L67/55—Push-based network services
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Abstract
The invention discloses an electronic book reading plan recommendation system, a method thereof, a terminal and a server. The method comprises the steps of acquiring the personal information of a target user and the book name of an electronic book that is currently read by the target user; according to the personal information of the target user and the book name of the electronic book, constructing a similar user group, and acquiring the reading features other users in the similar user group; acquiring the reading features other users in the similar user group to generate a first recommended reading plan, and recommending a preliminary recommendation reading plan to the target user; acquiring the historical reading information of the target user in accessing and reading books, and conducting the statistics on the reading behavior features of the target user according to the historical reading information of the target user; according to the reading behavior features of the target user, adjusting the first recommended reading plan to generate a second recommended reading plan, and recommending the second recommended reading plan to the second user. According to the technical scheme of the invention, the user setting is not required, and all data are generated based on the basic information of users, the reading behavior information of users and the personalized information of users. Therefore, the individual requirements of users can be met.
Description
Technical field
The present invention relates to e-book reading technical field, more particularly to a kind of e-book reading proposed recommendations system and its
Method, terminal and service end.
Background technology
In traditional reading system, general reading aids arrange manually timed task by user, server background according to
The timed task at family sends prompting message, points out user next should perform the plan of arrangement.
It has the disadvantages that：Single function, can only play prompting function, and Jing often occurs the situation that repetition is reminded,
In the case where user completes to read, reminder message can be repeatedly sent.Reading can not be reasonably arranged to plan for user simultaneously.
The content of the invention
For the deficiencies in the prior art, the present invention propose a kind of e-book reading proposed recommendations system and method,
Terminal and service end, the present invention solves user in reading process, how effectively utilizes user's chip time, and improving user has
Effect is read, and service end intelligent scissor reading task is user's reasonable arrangement reading plan, while intelligence sends reminder message, is subtracted
The interference that few prompting message is produced to user, helps user to complete to read, experience whole reading process, understands that the reading of oneself is entered
Degree and reading rate.The happy reading of user, effective reading are helped, reading is finally completed.
To achieve these goals, technical solution of the present invention is as follows：
A kind of reading proposed recommendations method of e-book, it is characterised in that comprise the following steps：
The title of the e-book that the personal information and targeted customer for obtaining targeted customer is currently read；According to the personal information
Build fellow users group with the title, for collecting server in other related to the personal information of the targeted customer use
Family, and obtain the reading aspects of other users in fellow users group；
Obtain the reading aspects of other users in the fellow users group, generate the first recommended article plan, and will be described just
Step recommended article proposed recommendations are to the targeted customer；
The history reading information of targeted customer's read books is obtained, the targeted customer is obtained according to the history reading information
Reading behavior feature；
The first recommended article plan according to the reading behavior Character adjustment, generates the second recommended article plan, and by institute
Secondary recommended article proposed recommendations are stated to the targeted customer.
Preferably, the first recommended article proposed recommendations information includes：Start reading time, reading time length, with
And reading time interval, it is described generation the first recommended article plan the step of be：
Rule is split according to default e-book, the e-book is split into some fragments, and by reading order, to described
Section is numbered；
The understanding difficulty or ease coefficient and excellent degree coefficient of the e-book fragment that the fellow users group uploads are counted, and is combined
The reading aspects of the fellow users group, are that user generates daily reading task, and are distributed in each reading task different
The contents fragment of quantity, and understanding that difficulty or ease coefficient is big or the big content segments of excellent degree coefficient lengthen reading time or reduction
Reading task.
Preferably, the first recommended article plan is according to the reading behavior Character adjustment：
According to the reading behavior feature of the targeted customer, by first recommended article recommend in the works when starting to read
Between, reading time length and reading time interval be adjusted.
Preferably, also include：
Judge whether the current e-book read is read last chapters and sections, be, then read according to the history of the targeted customer
Information Statistics go out targeted customer's books type interested and the digest content of wherein one books are labeled as into reading message to carry
Awake content；
Otherwise the digest of the following sections of the current e-book read is labeled as reading prompting message content；
Preferably, also include：
According to the reading behavior feature of the targeted customer, will read message before targeted customer's common beginning reading time and carry
Awake content is sent to targeted customer；
Judge whether targeted customer completes reading task, be, then do not retransmit reading reminder message content；
Otherwise, judge whether targeted customer starts reading task, be, then do not retransmit reading reminder message content；
Otherwise, prompting message content will be read in the range of targeted customer's reading time or afterwards and is sent to targeted customer.
Preferably, also include：
After targeted customer reads, the reading information of targeted customer is counted, including：Number of words, the reading for read duration, reading
Complete number of pages and the chapters and sections number for reading, and statistical information is added in the current reading progress of targeted customer；
Current reading progress ranking of the targeted customer in fellow users group is calculated, for providing across comparison.
Preferably, also include：
The current reading progress of targeted customer and the second recommended article plan are contrasted；
Judge that current progress of reading, whether more than the second recommended article plan, is then to send reward reminder message to targeted customer；
Whether current progress of reading otherwise is judged equal to the second recommended article plan, be then to send to targeted customer and encourage to remind
Message, otherwise sends excitation reminder message to targeted customer.
Preferably, also include：
There is provided targeted customer can change daily minimum reading time, meter that recommended article is recommended in the works according to own actual situation
Draw and read total number of days, with the operation for increasing, deleting free time.
Preferably, described transmission is read reminder message content and includes note prompting, voice reminder, carries inside client application
Awake three kinds of modes.
The reading proposed recommendations system of a kind of e-book, it is characterised in that include with lower module：
Preliminary reading information module is obtained, the electronics that the personal information and targeted customer for obtaining targeted customer is currently read
The title of book；
Similar reading information module is obtained, for building fellow users group with the title according to the personal information, for converging
The other users related to the personal information of the targeted customer in collection server, and obtain other users in fellow users group
Reading aspects；
First recommending module, for obtaining the fellow users group in other users reading aspects, generate the first recommended article
Plan, and by described preliminary recommended article proposed recommendations to the targeted customer；
Reading aspects module is obtained, for obtaining the history reading information that targeted customer accesses reading website, according to the history
Reading information obtains the reading behavior feature of the targeted customer；
Second recommending module, for the first recommended article plan according to the reading behavior Character adjustment, generates second and pushes away
Reading plan is recommended, and by the secondary recommended article proposed recommendations to the targeted customer.
The terminal of the reading proposed recommendations system of a kind of e-book, it is characterised in that the terminal includes：
Information module is uploaded, for user by network upload user essential information to server；
Prompting module is sent, for after network and message transfer, client to receive prompting message, suitable push is selected
Time, message content and push mode are sent to user and read reminder message.
The service end of the reading proposed recommendations system of a kind of e-book, it is characterised in that the service end includes：
Log collection module, for server the daily reading behavior daily record of user is collected, by the incoming big data analysis of daily record data
Server, the daily reading behavior daily record of analysis user；
Data analysis module：For analyzing user behavior data, the reading aspects of user are counted；
Read plan generation module：For arranging reading task, the plan of reading is generated, while being responsible for self adjustment of user's plan
With it is perfect；
Progress ranking module, for contrasting reading progress ranking and the reading plan of user, tracking user reads progress；
Prompting message module, for scheduling message Push Service on demand, to user reminder message is sent.
Beneficial effects of the present invention：
Arrange without the need for user.On the premise of relevant information is not provided with, service end backstage can automatically collect user's reading to user
Behavioural information, is that user generates reading plan after analysis.
All data are all based on the essential information of user, user's reading behavior information and customized information.Data analysis mould
Block can process the reading behavior daily record on user's same day, record the daily reading behavior of user.By contrasting the nearest time（Such as 60
My god）Reading behavior, count the reading aspects of user, including reading rate from reading behavior, reading time breaks（During fragment
Between）Deng rationally using chip time, being characterized as that each being customized of user is serviced according to occupation, hobby, custom etc..Together
When reading aspects can follow the change of user's reading habit and change, cater to users ' individualized requirement.
Description of the drawings
Fig. 1 be the present invention realize whole process Organization Chart；
Fig. 2 be the present invention realize logical process flow chart；
Fig. 3 is that the personal details page of the present invention arranges surface chart；
Fig. 4 is user's read interface figure of the present invention；
Fig. 5 is that the present invention provides reading aids control interfaces figure；
Fig. 6 is the reading aids surface chart of the present invention；
Fig. 7 is the daily reading time surface chart that user of the present invention changes system recommendation；
Fig. 8 is total reading time surface chart that user of the present invention changes system recommendation；
Fig. 9 is that user of the present invention checks current books reading information schematic diagram；
Figure 10 is that user of the present invention selects to read details date schematic diagram；
Figure 11 is the concrete reading information figure that user of the present invention checks exact date；
Figure 12 is the displaying figure of reminder message of the present invention；
Figure 13 is that the present invention has reminder message to enter read interface schematic diagram；
Figure 14 is to remind user to complete reading plan message interface schematic diagram in user's reading process of the present invention；
Figure 15 is key step flow chart of the present invention.
Specific embodiment
With reference to the accompanying drawings and examples, the present invention is expanded on further.
Embodiment one：
The configuration operation entry of traditional reading proposed recommendations hides relatively deep, configuration trouble.If user needs prompting function, just
Must be by client (such as：Mobile phone A PP) arranging manually.Remind to push and arrange single, certain several time point can only be fixed on.
Alerting pattern and reminded contents are single, and message informing can only be carried out inside client end AP P, in the case where network is not smooth, use
Family can not receive effectively prompting, and reminder message content is simply single, it is impossible to well excitation user is played to user and read
The effect of reading；Lack one read contrast and feed back present mode, user can not intuitively find out the reading progress of oneself and
Read plan.Lack user behavior analysis, it is impossible to track the reading conditions of user.Such as：Reading progress, reading time, reads daily
The features such as read time section, reading rate, books type hobby.
The present invention provides reading proposed recommendations system and method, terminal and the service end of e-book, comprises the following steps：
S101, the book of the e-book that the personal information and targeted customer that acquisition target is sent by intelligent terminal is currently read
Name；
User arranges personal information after the completion of registration by personal details page, including：Date of birth, sex, occupation, love
The essential information such as good.After user has filled in personal information, server background collects these user basic informations, as
The Back ground Information of later stage counting user data.It is different to the degree of understanding of things with the user of sex for all ages and classes, read
Assistant can win elite digest content from books and send reminder message to user using different mode and sentence, so as to more
It is close to the users.
S102, obtains the title information of the e-book that targeted customer is currently reading, according to the personal information and institute
State title and build fellow users group, for collecting server in other users related to the personal information of the targeted customer,
And obtain the reading aspects of other users in fellow users group；
S103, obtains the reading aspects of other users in the fellow users group, generates the first recommended article plan, and will be described
Preliminary recommended article proposed recommendations to the targeted customer；
Server background is sorted out user by contrast targeted customer and the basic document of other readings fan, is built
Fellow users group.Fellow users group is other users related to the personal information of the targeted customer in server.By right
Attribute is read in the user for counting of other users reading behavior, is that targeted customer generates different reading plans, help use
Family reasonable arrangement reading task.
User can also according to their needs change the daily reading time of system recommendation and number of days is read in plan, and can
To be increased according to own actual situation and delete free time.
System generate the first recommended article plan the step of be：E-book length is parsed, with section, page, number of words etc.
EBook content is divided into N number of contents fragment for unit, and according to content order, number consecutively.With reference to the reading aspects of user
With fellow users reading behavior information, books understand that degree-of-difficulty factor size, excellent degree coefficient magnitude etc., from multiple dimensions, are user
The daily reading task of distribution, generates recommended article plan.The fragment of fellow users group's reading time length is labeled as to understand difficult
Degree coefficient is big, and the fragment included often is labeled as the big fragment of excellent coefficient.
The reading progress of tracking user simultaneously contrasts reading plan, when user is not timely completed reading task, sends out to user
Prompting is sent to read message.Progress is read by tracking user, plan is read in contrast, when user deviates and reads plan, server
Prompting message can be sent to user, help reminds user to complete reading plan, encourages user to carry out effective reading.
S104, obtains the history reading information that targeted customer accesses reading website, is obtained according to the history reading information
The reading behavior feature of the targeted customer；
The history reading information of the daily read books of targeted customer is collected, the reading behavior daily record is analyzed, mesh is counted and analyze
The reading aspects of mark user, according to statistics the plan of reading is further improved, and the second recommendation for being generated as user's customization is read
Read plan；
After targeted customer reads a period of time, server can record the reading behavior of user, and analyze the reading row of user
For such as：Reading time, reading rate, reading time section etc., and while the spy such as books type, chip time that user is read
Levy and record.The reading plan for recommending user is adjusted according to these information, further improves the plan of reading.
Server background is by the books type read at ordinary times to targeted customer, books elite content and includes digest content
Statistics, the books elite contents fragment that user is not read as reminder message content a part, for reminding and guiding
User completes to read.
S105, the first recommended article plan according to the reading behavior Character adjustment generates the second recommended article meter
Draw, and by the secondary recommended article proposed recommendations to the targeted customer.
After the Back ground Information to user and reading behavior analysis, the reading time of origin of user, server are counted
User is common read time of origin inwardly or read the transmission time before rear line send and read reminder message；
After backstage is analyzed the Back ground Information and behavioural habits of user, such as：It is common by backstage statistical analysis user
Reading time occurs at noon 12：30-13：Between 30, then server background will at noon 12：20（Or 12：30、13：
00、13：30,13：In the range of 40 grade approximate times）The reading reminder message for having set reminder message content is sent to user.
And server statistics analyze it is in need to user send reminder message prompting user complete read when, note can be passed through
The various ways such as prompting, voice reminder or client application inside story notice are reminded.
According to the reading progress and the comparing result of reading plan of user, to user different prompting messages are sent.
In reading aids, the daily number of pages model for reading planned time and reading plan target of user can be shown
Enclose, in the case where user reaches reading time or reads task number of pages, user just completes the reading task on the same day.
In user's reading process, server background is monitored by the reading conditions to user, and readding user
Reading progress and reading plan are contrasted, then according to different comparing results to user send have remind, encourage, excitation,
The reminder messages of different nature such as reward, to encourage user to complete to read.Such as：After user's long-time is read, server background meeting
Rest reminding is sent to user；When the reading progress of user is faster than reading plan, server background can send reward and carry to user
Wake up, encourage user to continue conscientious effective reading；In the case where user does not complete same day reading plan, and with reference to user itself
Situation issues the user with excitation and reminds, and reminds user to hit the target content, carries out conscientious, wide and efficient reading.
Advantage of the present invention
User can be without the need for arranging.On the premise of relevant information is not provided with, service end backstage can automatically collect information to user, lead to
It is that user generates reading plan after crossing analysis；
All data are all based on the essential information of user, user behavior information and customized information.Rationally utilize chip time, root
Each being customized of user service is characterized as according to occupation, hobby, custom etc.；
Reading plan is automatically generated, helps user to complete to read.The reading plan for customizing is generated for user, user can enter
Row is contrasted self；
In reading process, across comparison is provided the user, calculate active user in all rankings ibidemed and read user.Readding
After running through, summarize user and read overall process；
For different reading progress situations, to user different types of reminder message is sent.Prize is sent to reading positive user
Information is encouraged, encouragement information is sent to domestic consumer, the user to infrequently reading sends excitation information, excitation user's culture is read
Hobby；
Intelligence sends reminds.Such as：When user completed reading plan the same day, when user interrupts suddenly reading, service
Device backstage does not send prompting message, it is to avoid bother the current thing of user, interrupts the work at present of user, sends to user in the later stage
Remind, point out user to read；
Various alerting patterns.The function of avoiding reading aids is subject to the circumscribed restriction of network.
Message content is simplified substantial.With reference to the reading conditions of user, send to user and there is prompting, encouragement, excitation, reward
The content of property.Such as：The contents such as the elite digest of read books following sections, well-known saying of pursuing a goal with determination.
Embodiment two：
E-book reading commending system of the present invention provides a kind of intelligent generation and reads plan, sends message recommendation prompting
Method.Without the need for manual configuration, background server to user journal data and user basic information by carrying out point automatically for user
Analysis is processed, rationally using chip time, split reading task, be that user generates suitable reading plan and selects to close for user
Suitable alerting pattern and reminded contents.
Because user is a regular process in reading process, such as：
1) essential informations such as hobby, occupation according to oneself search oneself books interested；
2) reading time is fixed, fragmentation, and not every user can daily arrange a long period to go efficiently
Conscientious reading；
3) reading rate, the cyclically-varying of reading time length.
For these features, reading aids can effectively help user to make full use of chip time, be analyzed by back-end data,
Rationally segmentation reading task, is that user generates a suitable reading plan.And by user behavior analysis, not timing to
Family sends to read and reminds, and encourages user to read.If server background detected user when fulfiling reading ahead of schedule on the same day, meeting
No longer remind, reduce unnecessary reminder message interference.
For all ages and classes and sex crowd to the degree of understanding of things without service end backstage is by collecting user's
Essential information, such as：The essential informations such as age, sex, hobby, occupation.Then according to these information, using different prompting sides
Formula and reminded contents send reminder message to user.And win from books in the elite of the following sections that user does not read perhaps
Digest content, so as to more be close to the users, reading is guided to user as reminder message content.
Server background can be analyzed always to the daily reading behavior of each user, track the reading progress of user,
So as to issue the user with the reading prompting message of different phase, user's recommended article plan is improved, differently help user
Wide and efficient reading, encourages, encourages user to complete reading task.
User basic information method is obtained in system is：User enters user basic information and arranges the page, can be in the page
The essential information of oneself is set in face.User basic information is obtained in the information that server background is filled in from user.
Statistical analysis user behavior method in service end backstage is：User is carried out after daily reading, and server background can be remembered
Feature and the attributes such as reading behavior, the read books type at family, chip time are employed, and analyze user's daily reading time,
Reading rate, reading time section and reading habit.
System alert time generation method is：Server background counts user by reading the analysis planned to user
Reading habit.According to the daily concentration reading time of user, the time point that message is pushed is determined.
System generates reading method of planning：Server is parsed to the length of every e-book, while counting use
Family behavioural information, coordinates the free time of user, is divided the content into units of section, page, number of words from 0 to N number of stage.With reference to use
Family reading aspects（Such as：Reading rate, reads book-type）It is that every user recommends to generate a independent reading plan.So
Afterwards progress is read by tracking user, plan is read in contrast.When plan is read in the deviation of user, server background to user sends out
Send prompting message.Help user to complete reading plan, encourage user to carry out effective reading.
System sends based reminding method：Analyze in server statistics and send reminder message prompting use to user in need
When family completes to read, can be by various ways such as note prompting, voice reminder and client application inside story notices.
Reading aids method to set up is：Before user reads complete to return main interface first, reading aids interfaces is ejected.Or
Person user in the toolbar for reading main interface clicks on reading aids button, into reading aids interface.
System response user clicks on message approach and is：
1. when PUSH message is to read reminder message, after clicking on reminder message, read interface is directly entered；
2. when PUSH message completes excitation, the reward message read for user, user can click on continuation reading and stay in reading
Interface, or other buttons are clicked on into other interfaces.
Reading task rendering method is：In reading aids, the daily reading planned time of user and reading can be shown
Plan target range of pages.In the case where user completes the reading time of task or completes task number of pages, user just completes
The reading task on the same day.
System sends type of reminders：Server background by contrasting to reading progress and reading plan, according to not
Same comparing result sends different reminder messages.Such as：After user's long-time is read, reading aids to user sends rest system
System；When the reading progress of user is faster than reading plan, server background sends reward and is reminded to user, encourages user to continue
Conscientious effective reading；In the case where user does not complete same day reading plan, prompting is issued the user with, remind user to complete meter
Draw content etc..With reference to many-sided excitation user such as user's own situation and current reading progress is conscientious, effective reading, raising is read
Reading level, makes user that enjoyment is obtained from reading.
Embodiment three：
As shown in figure 3, user is after the completion of registration, personal essential information is arranged by personal details page, wherein in 301 regions
The Back ground Informations such as date of birth, sex, occupation, the hobby of user are filled in, 302 regions is clicked on and is preserved.
After user fills in and completes essential information, server background can collect user basic information, use as later stage statistics
The basic data of user data.
As shown in figure 4, user clicks on the central area of read interface 401, toolbar is ejected.
As shown in figure 5, user clicks on 502 region reading aids controls, or after user reads the books for the first time, point
Hit the return push-button in 501 regions, automatic spring reading aids interface.
As shown in fig. 6, server background is by contrast active user and other users data etc. big data analysis, it is user
Generate recommended article plan.In Fig. 6：602 regions are the daily reading planned time that system is recommended to user, and 603 regions are
System to completing of recommending of user reads total number of days.In figure 6 user can delete, increase by clicking on 604,605 buttons
Plus the free time that can be read daily, after modification after the completion of click on 606 regions preserve reading plan.Simultaneously user can be 601
Reading aids function is enabled or closed in region, 602 regions is clicked on, into Fig. 7 interfaces.
As shown in fig. 7, user can change the daily plan reading time of system recommendation.
603 regions are clicked on, into Fig. 8 interfaces.
As shown in figure 8, number of days is read in the plan that user can change system recommendation.
After user's reading for a period of time, the daily reading behavior daily record of user is collected, user is daily reads for analysis
Reading behavior, server will further improve the plan of reading according to analysis result, ultimately produce the intelligence customization without the need for user intervention
Change the plan of reading.
607 regions are clicked in figure 6, are entered access customer and are read progress interface.
As shown in figure 9, having shown user's reading conditions in figure, entirely reading for user is therefrom we can see that
Journey, excitation user reads：
A. user started to read the books on 6.30th；
B. user has 7.7 and forgets to read；
C.7.8-7.14 the reading plan target on the same day is not completed
D.7.15-7.25 have overfulfiled reading plan
E. complete to read 7.26
In fig .9, the date locating rod in 901 regions is dragged, date selection interface occurs.
As shown in Figure 10, after the specific date is selected, the reading conditions on user's same day are shown.
As shown in figure 11, user checks the plan target of 2016-07-11, completes the feelings in detail such as task, overall ranking situation
Condition, clicks on 1101 region confirming buttons, returns initial interface（Fig. 9）.In initial interface Fig. 9, locating rod in the date on the same day or
The Close Date is read, and does not show the reading statistical information on the same day.
After backstage is analyzed the Back ground Information and behavioural habits of user, such as：It is logical by backstage statistical analysis user
Normal reading time occurs at noon 12：30-13：Between 30, then server background will at noon 13：00 to user sends
Read reminder message.
As shown in figure 12, a kind of exhibition method of reminder message is illustrated, after clicking on 1201 regions, user will be directed into
Read interface, as shown in figure 13.
Additionally, for the heterogeneous networks situation of user, in addition to the message informing in application is pushed to user, we may be used also
To send reminding short message, remind the various ways such as voice to user, the push for reducing message informing is disturbed by environmental factor.
For reminder message content, in background server by books, and the analysis of user's read books data, statistics
Go out digest content and books elite content.During prompting message is sent to user, with reference to the reading conditions of user, Xiang Yong
Family sends the reminder message with properties such as prompting, encouragement, excitation, rewards.Encourage, excitation user completes to read.
When user completes the reading task on the same day, background service sends task completion message and reminds to user, and gives
The user reward of a bit（Such as：Integration etc.）.
As shown in figure 14：User clicks on 1401 regions and continues to read, and interface returns read interface；User clicks on 1402 regions
After the meeting, interface jumps to the other guide interface of APP for rest one.
Above-described is only the preferred embodiment of the present invention, the invention is not restricted to above example.It is appreciated that this
Art personnel directly derive without departing from the basic idea of the present invention or associate other improve and change
It is considered as being included within protection scope of the present invention.
Claims (12)
1. a kind of reading proposed recommendations method of e-book, it is characterised in that comprise the following steps：
The title of the e-book that the personal information and targeted customer for obtaining targeted customer is currently read；
Fellow users group is built according to the personal information and the title, for collecting server in the targeted customer's
The related other users of personal information, and obtain the reading aspects of other users in fellow users group；
Obtain the reading aspects of other users in the fellow users group, generate the first recommended article plan, and will be described just
Step recommended article proposed recommendations are to the targeted customer；
The history reading information that targeted customer accesses read books is obtained, the target is obtained according to the history reading information
The reading behavior feature of user；
The first recommended article plan according to the reading behavior Character adjustment, generates the second recommended article plan, and by institute
Secondary recommended article proposed recommendations are stated to the targeted customer.
2. it is according to claim 1 to read proposed recommendations method, it is characterised in that the first recommended article proposed recommendations
Information includes：Start reading time, reading time length and reading time interval, the first recommended article plan of the generation
The step of be：
Rule is split according to default e-book, the e-book is split into some fragments, and by reading order, to described
Section is numbered；
The understanding difficulty or ease coefficient and excellent degree coefficient of the e-book fragment that the fellow users group uploads are counted, and is combined
The reading aspects of the fellow users group, are that user generates daily reading task, and are distributed in each reading task different
The contents fragment of quantity, is understanding that difficulty or ease coefficient is big or the big content segments of excellent degree coefficient lengthen reading time or reduction is read
Reading task.
3. it is according to claim 1 and 2 to read proposed recommendations method, it is characterised in that according to the reading behavior feature
Adjusting the first recommended article plan is：
According to the reading behavior feature of the targeted customer, by first recommended article recommend in the works when starting to read
Between, reading time length and reading time interval be adjusted.
4. it is according to claim 1 to read proposed recommendations method, it is characterised in that also to include：
Judge whether the current e-book read is read last chapters and sections, be, then read according to the history of the targeted customer
Information Statistics go out targeted customer's books type interested and the digest content of wherein one books are labeled as into reading message to carry
Awake content；
Otherwise the digest of the following sections of the current e-book read is labeled as reading prompting message content.
5. it is according to claim 1 to read proposed recommendations method, it is characterised in that also to include：
According to the reading behavior feature of the targeted customer, will read message before targeted customer's common beginning reading time and carry
Awake content is sent to targeted customer；
Judge whether targeted customer completes reading task, be, then do not retransmit reading reminder message content；
Otherwise, judge whether targeted customer starts reading task, be, then do not retransmit reading reminder message content；
Otherwise, prompting message content will be read in the range of targeted customer's reading time or afterwards and is sent to targeted customer.
6. it is according to claim 1 to read proposed recommendations method, it is characterised in that characterized in that, also including：
After targeted customer reads, the reading information of targeted customer is counted, including：Number of words, the reading for read duration, reading
Complete number of pages and the chapters and sections number for reading, and statistical information is added in the current reading progress of targeted customer；
Current reading progress ranking of the targeted customer in fellow users group is calculated, for providing across comparison.
7. it is according to claim 1 to read proposed recommendations method, it is characterised in that also to include：
The current reading progress of targeted customer and the second recommended article plan are contrasted；
Judge that current progress of reading, whether more than the second recommended article plan, is then to send reward reminder message to targeted customer；
Whether current progress of reading otherwise is judged equal to the second recommended article plan, be then to send to targeted customer and encourage to remind
Message, otherwise sends excitation reminder message to targeted customer.
8. it is according to claim 1 to read proposed recommendations method, it is characterised in that also to include：
There is provided targeted customer can change daily minimum reading time, meter that recommended article is recommended in the works according to own actual situation
Draw and read total number of days, with the operation for increasing, deleting free time.
9. it is according to claim 1 to read proposed recommendations method, it is characterised in that reminder message content is read in the transmission
Three kinds of modes are reminded including note prompting, voice reminder, client application inside.
10. the reading proposed recommendations system of a kind of e-book, it is characterised in that include with lower module：
Preliminary reading information module is obtained, the electronics that the personal information and targeted customer for obtaining targeted customer is currently read
The title of book；
Similar reading information module is obtained, for building fellow users group with the title according to the personal information, for converging
The other users related to the personal information of the targeted customer in collection server, and obtain other users in fellow users group
Reading aspects；
First recommending module, for obtaining the fellow users group in other users reading aspects, generate the first recommended article
Plan, and by described preliminary recommended article proposed recommendations to the targeted customer；
Reading aspects module is obtained, for obtaining the history reading information of targeted customer's read books, is read according to the history
The reading behavior feature of targeted customer described in acquisition of information；
Second recommending module, for the first recommended article plan according to the reading behavior Character adjustment, generates second and pushes away
Reading plan is recommended, and by the secondary recommended article proposed recommendations to the targeted customer.
The terminal of the reading proposed recommendations system of 11. a kind of e-book, it is characterised in that the terminal includes：
Information module is uploaded, for user by network upload user essential information to server；
Prompting module is sent, for after network and message transfer, client to receive prompting message, suitable push is selected
Time, message content and push mode are sent to user and read reminder message.
The service end of the reading proposed recommendations system of 12. a kind of e-book, it is characterised in that the service end includes：
Log collection module, for server the daily reading behavior daily record of user is collected, by the incoming big data analysis of daily record data
Server, the daily reading behavior daily record of analysis user；
Data analysis module：For analyzing user behavior data, the reading aspects of user are counted；
Read plan generation module：For arranging reading task, the plan of reading is generated, while being responsible for self adjustment of user's plan
With perfect, the reading plan of generation second；
Progress ranking module, for contrasting reading progress ranking and the reading plan of user, tracking user reads progress；
Prompting message module, for scheduling message Push Service on demand, to user reminder message is sent.
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