CN106777360A - Content recommendation method and device - Google Patents
Content recommendation method and device Download PDFInfo
- Publication number
- CN106777360A CN106777360A CN201710040563.7A CN201710040563A CN106777360A CN 106777360 A CN106777360 A CN 106777360A CN 201710040563 A CN201710040563 A CN 201710040563A CN 106777360 A CN106777360 A CN 106777360A
- Authority
- CN
- China
- Prior art keywords
- content
- study
- recommendation
- homepage
- bag
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/953—Querying, e.g. by the use of web search engines
- G06F16/9535—Search customisation based on user profiles and personalisation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION 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
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0201—Market modelling; Market analysis; Collecting market data
- G06Q30/0202—Market predictions or forecasting for commercial activities
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Strategic Management (AREA)
- Development Economics (AREA)
- Databases & Information Systems (AREA)
- Finance (AREA)
- Theoretical Computer Science (AREA)
- Accounting & Taxation (AREA)
- Data Mining & Analysis (AREA)
- Physics & Mathematics (AREA)
- Entrepreneurship & Innovation (AREA)
- General Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- Game Theory and Decision Science (AREA)
- Economics (AREA)
- Marketing (AREA)
- General Business, Economics & Management (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The present invention is applied to field of terminal, there is provided a kind of content recommendation method and device.Methods described includes：User basic information is obtained, the study content matched with the user basic information is selected in the study content of homepage recommendation is designated, the study content of selection is recommended in homepage.User's request can effectively be adapted to by the above method, user time is saved.
Description
Technical field
The embodiment of the present invention belongs to field of terminal, more particularly to a kind of content recommendation method and device.
Background technology
At present, many application programs (Application, APP) all can be to user's content recommendation.
In the prior art, the content recommendation of most of APP is based on the selected themes of APP oneself, i.e. pushed away to all users
The content recommendation recommended all is identical.But because the user group of APP would generally be different, identical content recommendation does not have to user
Specific aim, so as to cause content recommendation to meet the demand of user, and expends the search time of user.
Therefore, it is necessary to a kind of new technical scheme is proposed, to solve above-mentioned technical problem.
The content of the invention
The embodiment of the invention provides a kind of content recommendation method and device, it is intended to which solving existing content recommendation does not have pin
Content recommendation is caused to be unsatisfactory for the problem of user's request property.
The embodiment of the present invention is achieved in that a kind of content recommendation method, and the content recommendation method includes：
Obtain user basic information；
The study content matched with the user basic information is selected in the study content of homepage recommendation is designated；
Recommend the study content of selection in homepage.
Further, select corresponding with the user basic information in the study content of homepage recommendation is designated described
Study content before, including：
Recommendation grade highest study content is selected from classified theme bag, and is designated homepage recommendation.
Further, recommendation grade highest study content is selected from classified theme bag described, and is designated
Before homepage is recommended, including：
Difference learns the numbers of visits of contents and/or obtains to praise number of times in statistics same subject bag；
The recommendation grade that number of times determines study content is praised according to the number of visits and/or obtain.
Further, after the study content for recommending selection in homepage, also include：
Detect whether to receive the browsing instructions for learning content；
When the browsing instructions of study content are received, the study content is shown；
Recommend other study contents with the study affiliated same subject bag of content.
Further, the recommendation and other study contents of the study affiliated same subject bag of content, specifically include：
Determine the number of the theme bag and the theme bag belonging to the study content；
When the number of the theme bag belonging to the study content is more than 1, user learning information is obtained；
Learn the theme bag belonging to content according to user learning information filtering, until the master belonging to the study content
The number for inscribing bag is equal to 1；
Recommend other study contents of the theme bag after filtering.
The another object of the embodiment of the present invention is to provide a kind of content recommendation device, and the content recommendation device includes：
Essential information acquiring unit, for obtaining user basic information；
Content selecting unit, for being selected and the user basic information in the study content of homepage recommendation is designated
The study content matched somebody with somebody；
First recommendation unit, the study content for recommending selection in homepage.
Further, the content recommendation device also includes：
Homepage recommends mark unit, for selecting recommendation grade highest study content from classified theme bag, and
It is designated homepage recommendation.
Further, the content recommendation device also includes：
Statistic unit, for counting checking number of visits and/or obtain and praising number of times for different study contents in same subject bag；
Recommendation grade determining unit, number of times determination study content is praised for checking number of visits according to and/or obtaining
Recommendation grade.
Further, the content recommendation device also includes：
Browsing instructions detection unit, for detecting whether receiving study content checks browsing instructions；
Study content display unit, for receiving when checking browsing instructions of content of study, shows in the study
Hold；
Second recommendation unit, for recommending other study contents with the study affiliated same subject bag of content.
Further, second recommendation unit is specifically included：
Theme bag number determining module, for determine it is described study content belonging to theme bag and the theme bag
Number；
Learning information acquisition module, for when the number of the theme bag belonging to the study content is more than 1, obtaining user
Learning information；
Theme packet filtering module, for learning the theme bag belonging to content according to user learning information filtering, until
The number of the theme bag belonging to the study content is equal to 1；
Recommending module, other study contents for recommending the theme bag after filtering.
In embodiments of the present invention, due to recommending study content in homepage, and the study content recommended is and the use
The study content of family essential information matching, hence in so that the study content recommended is more targeted, so as to effectively adapt to user need
Ask, save user time.
Brief description of the drawings
Fig. 1 is a kind of flow chart of content recommendation method that first embodiment of the invention is provided；
Fig. 2 is a kind of structure chart of content recommendation device that second embodiment of the invention is provided.
Specific embodiment
In order to make the purpose , technical scheme and advantage of the present invention be clearer, it is right below in conjunction with drawings and Examples
The present invention is further elaborated.It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, and
It is not used in the restriction present invention.
It should be appreciated that when using in this specification and in the appended claims, term " including " indicate described spy
Levy, entirety, step, operation, the presence of element and/or component, but be not precluded from one or more of the other feature, entirety, step,
The presence or addition of operation, element, component and/or its set.
It is also understood that the term used in this description of the invention is merely for the sake of the mesh for describing specific embodiment
And be not intended to limit the present invention.As used in description of the invention and appended claims, unless on
Other situations are hereafter clearly indicated, otherwise " one " of singulative, " one " and " being somebody's turn to do " is intended to include plural form.
It will be further appreciated that, the term "and/or" used in description of the invention and appended claims is
Refer to any combinations of one or more in the associated item listed and be possible to combination, and including these combinations.
In the embodiment of the present invention, user basic information is obtained, selection and institute in the study content of homepage recommendation is designated
The study content of user basic information matching is stated, the study content of selection is recommended in homepage.
In order to illustrate technical solutions according to the invention, illustrated below by specific embodiment.
Embodiment one：
Fig. 1 shows a kind of flow chart of content recommendation method that first embodiment of the invention is provided, and details are as follows：
Step S11, obtains user basic information.
Specifically, need to fill in user profile during user's registration APP, the user profile includes user basic information and use
Family learning information.The identity information of the user basic information including user, such as user name, age and is reading grade etc..Institute
State user learning information and version, Publication Year and the publisher of teaching material etc. are learned including user.After User logs in APP, move
Dynamic equipment can obtain user basic information and user learning information.
Alternatively, before the step S11, including：
Whether A1, detection user have logged in.
If A2, detecting user and being not logged in, in preset content and/or Hot Contents that homepage displaying is recommended.Wherein, institute
It can be the study content that backstage is recommended, the study content that for example master recommends to state preset content；The Hot Contents can be
Current hot content, can be the most content of number of visits, can be the most content of like time, can also be with currently
The content of red-letter day correlation.
Step S12, selects the study matched with the user basic information in the study content of homepage recommendation is designated
Content.
Alternatively, in order to recommend appropriate content in time to user, before the step S12, including：
B3, the selection recommendation grade highest study content from classified theme bag, and it is designated homepage recommendation.Specifically
Ground, the study content presses subject classification, and is stored in theme bag, for example, press reading grade's classification, by study account classification, institute
Stating study content can be while belongs to multiple themes.Recommendation grade highest is selected to learn content respectively from each theme bag.
Alternatively, in order to select recommendation grade highest study content from numerous contents, before the B3,
Including：
Difference learns the numbers of visits of contents and/or obtains to praise number of times in B1, statistics same subject bag.Specifically, count same
Difference learns the numbers of visits of contents or obtains to praise number of times in one theme bag, or, while different study in counting same subject bag
The number of visits of content and obtain and praise number of times.
B2, the recommendation grade that number of times determines study content is praised according to the number of visits and/or obtain.Specifically, when only uniting
During the number of visits of the different study contents in meter same subject bag, by the different study contents in same subject bag by browsing time
Number sequence, number of visits is more, and recommendation grade is higher.Similarly, obtaining when the different study contents in only statistics same subject bag
When praising number of times, obtain and praise that number of times is more, recommendation grade is higher.Difference in same subject bag is counted simultaneously learns browsing for content
Number of times and obtain when praising number of times, if number of visits is identical, obtains and praise that number of times is more, recommendation grade is higher；If conversely, obtain praising number of times phase
Together, then number of visits is more, and recommendation grade is higher.It is of course also possible to the different weights of number of times imparting are praised with obtaining to number of visits,
So, when the different study contents in counting same subject bag simultaneously numbers of visits and obtain praise number of times when, calculate browse respectively
The product X of the corresponding weights of number of times, calculating obtains the product Y for praising the corresponding weights of number of times, then calculates product X and product
Y's and (X+Y), (X+Y) value is bigger, and recommendation grade is higher.
Alternatively, for quick obtaining and show that recommendation grade highest learns content, the step S12 also includes：
C1, to be designated homepage recommendation study content addition homepage displaying attribute after be stored in homepage recommend storehouse.Will mark
For the study content that homepage is recommended is packed, addition agrees with theme or the homepage in red-letter day displaying attribute, wherein, the homepage exhibition
Show that attribute is included but is not limited to recommend title and recommends front cover.
C2, the study content that selection is matched with user basic information from homepage recommendation storehouse.That is, it is designated having
Homepage recommend study content and with the addition of homepage displaying attribute homepage recommend storehouse in directly choose and user basic information
The study content matched somebody with somebody, for example, chosen in homepage recommends storehouse reading the study content that grade matches with user.
Step S13, recommends the study content of selection in homepage.
Alternatively, in order to the more appropriate contents of active push are to user, after the step S13, including：
D1, the browsing instructions for detecting whether to receive study content.
D2, when the browsing instructions of study content are received, show the study content.
Other study contents of D3, recommendation and the study affiliated same subject bag of content.
Because user generally learns just for same knowledge point in a period of time, and in the study of same subject bag
Hold and be usually same or analogous knowledge point, therefore, after user browses certain study content, actively recommend and the study
Other study contents of the affiliated same subject bag of content, can reduce the operation that user searches again for, and improve learning efficiency.
Alternatively, same study content may simultaneously belong to multiple theme bags, therefore, the D3 is specifically included：
D31, the number for determining the theme bag learnt belonging to content and the theme bag.
D32, it is described study content belonging to theme bag number be more than 1 when, obtain user learning information.Wherein, institute
State user learning information and version, Publication Year and the publisher of teaching material etc. are learned including user.
D33, the theme bag according to user learning information filtering belonging to study content, until belonging to the study content
Theme bag number be equal to 1.
D34, other study contents for recommending the theme bag after filtering.
Specifically, when the number of the theme bag belonging to the study content is more than 1, teaching material is learned according to the user
Version, Publication Year and publisher etc. carry out matching filtering.For example, when the study content belongs to multiple theme bags,
Matched according to the version that user learns teaching material, the theme bag of the version match of teaching material is learned in selection with user, so as to enter one
Step has filtered theme bag, improves the accuracy and validity of recommendation.Certainly, if an information according to user learning information
After (such as the version of teaching material that user learns) filtering theme bag, the number of the theme bag after filtering continues according to user still greater than 1, then
The other information of learning information continues to filter, as the Publication Year of the version according to teaching material that user learns is filtered, herein not
Repeat again.
Alternatively, when the study content belongs to multiple theme bags, the study commending contents grade can be selected most
In current topic bag belonging to height other study contents, it is also possible to select it is described study content belonging to multiple theme bags in,
In each theme bag except it is described study content in addition to, recommendation grade highest other study contents.
In first embodiment of the invention, by obtaining user basic information, in the study content of homepage recommendation is designated
The study content that selection is matched with the user basic information, recommends the study content of selection in homepage, and institute is checked in user
Recommend other study contents of the study affiliated theme of content during the study content for stating homepage selection, when the study content is same
When belonging to multiple theme bags, according to user learning information filtering theme bag, and recommend in the theme bag after filtering other learn
Practise, effectively adapt to user's request, save user time.
It should be understood that in embodiments of the present invention, the size of the sequence number of above-mentioned each process is not meant to the elder generation of execution sequence
Afterwards, the execution sequence of each process should be with its function and internal logic determination, the implementation process structure without tackling the embodiment of the present invention
Into any restriction.
Embodiment two：
Fig. 2 shows a kind of structure chart of content recommendation device that second embodiment of the invention is provided, and the device can be used for
In intelligent terminal.The intelligent terminal can include the user communicated with one or more core nets through wireless access network RAN
Equipment, the user equipment can be mobile phone (or being " honeycomb " phone), the computer with mobile device etc., for example,
User equipment can also be portable, pocket, hand-held, built-in computer or vehicle-mounted mobile device, they and nothing
Line access exchanges voice and/or data.Again for example, the mobile device can include smart mobile phone, panel computer, individual digital
Assistant PDA, point-of-sale terminal POS or vehicle-mounted computer etc..For convenience of description, illustrate only the portion related to the embodiment of the present invention
Point.
The content recommendation device includes：Essential information acquiring unit 21, content selection list 22, the first recommendation unit 23, its
In：
Essential information acquiring unit 21, for obtaining user basic information.
Specifically, need to fill in user profile during user's registration APP, the user profile includes user basic information and use
Family learning information.The identity information of the user basic information including user, such as user name, age and is reading grade etc..Institute
State user learning information and version, Publication Year and the publisher of teaching material etc. are learned including user.After User logs in APP, move
Dynamic equipment can obtain user basic information and user learning information.
Alternatively, the content recommendation device includes：
Detection unit is logged in, for detecting whether user has logged in.
Preset content recommendation unit, if being not logged in for detecting user, homepage displaying recommend preset content and/
Or Hot Contents.
Wherein, the preset content can be the study content that backstage is recommended, the study content that for example master recommends；It is described
Hot Contents can be current hot content, can be the most content of number of visits, can be the most content of like time,
Can also be the content related to current red-letter day.
Content selecting unit 22, for being selected and the user basic information in the study content of homepage recommendation is designated
The study content of matching.
Alternatively, in order to recommend appropriate content in time to user, the content recommendation device includes：
Homepage recommends mark unit, for selecting recommendation grade highest study content from classified theme bag, and
It is designated homepage recommendation.Specifically, the study content presses subject classification, and is stored in theme bag, for example, press reading year fraction
Class, by study account classification, the study content can simultaneously belong to multiple themes.Selection is recommended respectively from each theme bag
Grade highest learns content.
Alternatively, in order to select recommendation grade highest study content, the commending contents from numerous contents
Device also includes：
Statistic unit, for counting checking number of visits and/or obtain and praising number of times for different study contents in same subject bag.
Specifically, difference learns the numbers of visits of contents or obtains to praise number of times in statistics same subject bag, or, while counting same subject
Difference learns the numbers of visits of contents and obtains to praise number of times in bag.
Recommendation grade determining unit, number of times determination study content is praised for checking number of visits according to and/or obtaining
Recommendation grade.Specifically, when the number of visits of the different study contents in only statistics same subject bag, by same subject bag
Different study contents sorted by number of visits, number of visits is more, and recommendation grade is higher.Similarly, when only counting same subject
When the obtaining of different study contents in bag praises number of times, obtain and praise that number of times is more, recommendation grade is higher.When while counting same subject bag
In different study contents numbers of visits and obtain when praising number of times, if number of visits is identical, obtain that to praise number of times more, recommend etc.
Level is higher；If conversely, obtain praise number of times it is identical when, number of visits is more, and recommendation grade is higher.It is of course also possible to give browse secondary
Number praises the different weights of number of times impartings with obtaining, and so, different study contents in same subject bag is counted simultaneously browse secondary
Number and obtain when praising number of times, the product X of the corresponding weights of number of visits is calculated respectively, calculating is obtained praises the corresponding power of number of times
The product Y of value, then calculate product X and product Y's and (X+Y), (X+Y) value is bigger, and recommendation grade is higher.
Alternatively, for quick obtaining and show that recommendation grade highest learns content, the content recommendation device also wraps
Include：
Homepage recommend stock enter unit, for be designated homepage recommendation study content addition homepage displaying attribute after deposit
Enter homepage and recommend storehouse.The study content that homepage recommendation will be designated is packed, and addition agrees with theme or the displaying of the homepage in red-letter day
Attribute, wherein, the homepage displaying attribute is included but is not limited to recommend title and recommends front cover.
Second content selecting unit, in the study that the homepage recommends that selection is matched with user basic information in storehouse
Hold.That is, recommend directly to be selected in storehouse in the homepage for having the study content for being designated homepage recommendation and with the addition of homepage displaying attribute
The study content matched with user basic information is taken, for example, chosen in homepage recommends storehouse reading grade matches with user
Practise content.
First recommendation unit 23, the study content for recommending selection in homepage.
Alternatively, in order to the more appropriate contents of active push are to user, the content recommendation device, including：
Browsing instructions detection unit, for detecting whether receiving study content checks browsing instructions；
Study content display unit, for receiving when checking browsing instructions of content of study, shows in the study
Hold；
Second recommendation unit, for recommending other study contents with the study affiliated same subject bag of content.
Because user generally learns just for same knowledge point in a period of time, and in the study of same subject bag
Hold and be usually same or analogous knowledge point, therefore, after user browses certain study content, actively recommend and the study
Other study contents of the affiliated same subject bag of content, can reduce the operation that user searches again for, and improve learning efficiency.
Alternatively, same study content may simultaneously belong to multiple theme bags, therefore, second recommendation unit is specific
Including：
Theme bag number determining module, for determine it is described study content belonging to theme bag and the theme bag
Number；
Learning information acquisition module, for when the number of the theme bag belonging to the study content is more than 1, obtaining user
Learning information；
Theme packet filtering module, for learning the theme bag belonging to content according to user learning information filtering, until
The number of the theme bag belonging to the study content is equal to 1；
Recommending module, other study contents for recommending the theme bag after filtering.
Specifically, when the number of the theme bag belonging to the study content is more than 1, teaching material is learned according to the user
Version, Publication Year and publisher etc. carry out matching filtering.For example, when the study content belongs to multiple theme bags,
Matched according to the version that user learns teaching material, the theme bag of the version match of teaching material is learned in selection with user, so as to enter one
Step has filtered theme bag, improves the accuracy and validity of recommendation.Certainly, if an information according to user learning information
After (such as the version of teaching material that user learns) filtering theme bag, the number of the theme bag after filtering continues according to user still greater than 1, then
The other information of learning information continues to filter, as the Publication Year of the version according to teaching material that user learns is filtered, herein not
Repeat again.
Alternatively, when the study content belongs to multiple theme bags, the study commending contents grade can be selected most
In current topic bag belonging to height other study contents, it is also possible to select it is described study content belonging to multiple theme bags in,
In each theme bag except it is described study content in addition to, recommendation grade highest other study contents.
In second embodiment of the invention, by obtaining user basic information, in the study content of homepage recommendation is designated
The study content that selection is matched with the user basic information, recommends the study content of selection in homepage, and institute is checked in user
Recommend other study contents of the study affiliated theme of content during the study content for stating homepage selection, when the study content is same
When belonging to multiple theme bags, according to user learning information filtering theme bag, and recommend in the theme bag after filtering other learn
Practise, effectively adapt to user's request, save user time.
Those of ordinary skill in the art are it is to be appreciated that the list of each example described with reference to the embodiments described herein
Unit and algorithm steps, can be realized with the combination of electronic hardware or computer software and electronic hardware.These functions are actually
Performed with hardware or software mode, depending on the application-specific and design constraint of technical scheme.Professional and technical personnel
Described function, but this realization can be realized it is not considered that exceeding using distinct methods to each specific application
The scope of the present invention.
It is apparent to those skilled in the art that, for convenience and simplicity of description, the system of foregoing description,
The specific work process of device and unit, may be referred to the corresponding process in preceding method embodiment, will not be repeated here.
In several embodiments provided herein, it should be understood that disclosed system, apparatus and method, can be with
Realize by another way.For example, device embodiment described above is only schematical, for example, the unit
Divide, only a kind of division of logic function there can be other dividing mode when actually realizing, for example multiple units or component
Can combine or be desirably integrated into another system, or some features can be ignored, or do not perform.It is another, it is shown or
The coupling each other for discussing or direct-coupling or communication connection can be the indirect couplings of device or unit by some interfaces
Close or communicate to connect, can be electrical, mechanical or other forms.
The unit that is illustrated as separating component can be or may not be it is physically separate, it is aobvious as unit
The part for showing can be or may not be physical location, you can with positioned at a place, or can also be distributed to multiple
On NE.Some or all of unit therein can be according to the actual needs selected to realize the mesh of this embodiment scheme
's.
In addition, during each functional unit in each embodiment of the invention can be integrated in a processing unit, it is also possible to
It is that unit is individually physically present, it is also possible to which two or more units are integrated in a unit.
If the function is to realize in the form of SFU software functional unit and as independent production marketing or when using, can be with
Storage is in a computer read/write memory medium.Based on such understanding, technical scheme is substantially in other words
The part contributed to prior art or the part of the technical scheme can be embodied in the form of software product, the meter
Calculation machine software product is stored in a storage medium, including some instructions are used to so that a computer equipment (can be individual
People's computer, server, or network equipment etc.) perform all or part of step of each embodiment methods described of the invention.
And foregoing storage medium includes：USB flash disk, mobile hard disk, read-only storage (ROM, Read-Only Memory), arbitrary access are deposited
Reservoir (RAM, Random Access Memory), magnetic disc or CD etc. are various can be with the medium of store program codes.
The above, specific embodiment only of the invention, but protection scope of the present invention is not limited thereto, and it is any
Those familiar with the art the invention discloses technical scope in, change or replacement can be readily occurred in, should all contain
Cover within protection scope of the present invention.Therefore, protection scope of the present invention described should be defined by scope of the claims.
Claims (10)
1. a kind of content recommendation method, it is characterised in that the content recommendation method includes：
Obtain user basic information；
The study content matched with the user basic information is selected in the study content of homepage recommendation is designated；
Recommend the study content of selection in homepage.
2. content recommendation method according to claim 1, it is characterised in that be designated the study of homepage recommendation described
Before study content corresponding with the user basic information is selected in content, including：
Recommendation grade highest study content is selected from classified theme bag, and is designated homepage recommendation.
3. content recommendation method according to claim 2, it is characterised in that selected from classified theme bag described
Recommendation grade highest learn content, and be designated homepage recommend before, including：
Difference learns the numbers of visits of contents and/or obtains to praise number of times in statistics same subject bag；
The recommendation grade that number of times determines study content is praised according to the number of visits and/or obtain.
4. content recommendation method according to claim 2, it is characterised in that in the study for recommending selection in homepage
After content, also include：
Detect whether to receive the browsing instructions for learning content；
When the browsing instructions of study content are received, the study content is shown；
Recommend other study contents with the study affiliated same subject bag of content.
5. content recommendation method according to claim 4, it is characterised in that the recommendation is same with belonging to the study content
Other study contents of one theme bag, specifically include：
Determine the number of the theme bag and the theme bag belonging to the study content；
When the number of the theme bag belonging to the study content is more than 1, user learning information is obtained；
Learn the theme bag belonging to content according to user learning information filtering, until the theme bag belonging to the study content
Number be equal to 1；
Recommend other study contents of the theme bag after filtering.
6. a kind of content recommendation device, it is characterised in that the content recommendation device includes：
Essential information acquiring unit, for obtaining user basic information；
Content selecting unit, for selecting what is matched with the user basic information in the study content of homepage recommendation is designated
Study content；
First recommendation unit, the study content for recommending selection in homepage.
7. content recommendation device according to claim 6, it is characterised in that the content recommendation device also includes：
Homepage recommends mark unit, for selecting recommendation grade highest study content from classified theme bag, and identifies
For homepage is recommended.
8. content recommendation device according to claim 7, it is characterised in that the content recommendation device also includes：
Statistic unit, for counting checking number of visits and/or obtain and praising number of times for different study contents in same subject bag；
Recommendation grade determining unit, the recommendation that number of times determines study content is praised for checking number of visits according to and/or obtaining
Grade.
9. content recommendation device according to claim 7, it is characterised in that the content recommendation device also includes：
Browsing instructions detection unit, for detecting whether receiving study content checks browsing instructions；
Study content display unit, for receiving when checking browsing instructions of content of study, shows the study content；
Second recommendation unit, for recommending other study contents with the study affiliated same subject bag of content.
10. content recommendation device according to claim 9, it is characterised in that second recommendation unit is specifically included：
Theme bag number determining module, the number for determining theme bag and the theme bag belonging to the study content；
Learning information acquisition module, for when the number of the theme bag belonging to the study content is more than 1, obtaining user learning
Information；
Theme packet filtering module, for learning the theme bag belonging to content according to user learning information filtering, until described
The number of the theme bag belonging to study content is equal to 1；
Recommending module, other study contents for recommending the theme bag after filtering.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710040563.7A CN106777360A (en) | 2017-01-18 | 2017-01-18 | Content recommendation method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710040563.7A CN106777360A (en) | 2017-01-18 | 2017-01-18 | Content recommendation method and device |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN106777360A true CN106777360A (en) | 2017-05-31 |
Family
ID=58944319
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710040563.7A Pending CN106777360A (en) | 2017-01-18 | 2017-01-18 | Content recommendation method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106777360A (en) |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107222584A (en) * | 2017-08-09 | 2017-09-29 | 广东小天才科技有限公司 | The recommendation method and server of a kind of children education application |
| CN108600337A (en) * | 2018-03-30 | 2018-09-28 | 上海乂学教育科技有限公司 | A kind of best learning Content automatic push method |
| CN109003478A (en) * | 2018-08-07 | 2018-12-14 | 广东小天才科技有限公司 | A kind of learning interaction method and facility for study |
| CN109033418A (en) * | 2018-08-07 | 2018-12-18 | 广东小天才科技有限公司 | A kind of the intelligent recommendation method and facility for study of learning Content |
| CN109166062A (en) * | 2018-08-07 | 2019-01-08 | 苏州承儒信息科技有限公司 | A kind of educational institution's recommended method and its system based on big data |
| CN109190018A (en) * | 2018-08-07 | 2019-01-11 | 苏州承儒信息科技有限公司 | Local educational institution's intelligent recommendation method and its system based on user's similarity |
| CN109344335A (en) * | 2018-12-20 | 2019-02-15 | 广东小天才科技有限公司 | A kind of content recommendation method and electronic equipment |
| CN109410675A (en) * | 2018-12-12 | 2019-03-01 | 广东小天才科技有限公司 | A kind of exercise recommended method and private tutor's equipment based on student's portrait |
| CN109712040A (en) * | 2018-11-29 | 2019-05-03 | 国政通科技有限公司 | A kind of learning system and its processing method |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103514162A (en) * | 2012-06-15 | 2014-01-15 | 上海蓝卓教育信息科技有限公司 | Intelligent courseware recommending system |
| CN104216883A (en) * | 2013-05-29 | 2014-12-17 | 酷盛(天津）科技有限公司 | Video recommendation reason generating system and method |
| CN104899195A (en) * | 2014-01-26 | 2015-09-09 | 武汉联影医疗科技有限公司 | Customized educational resource recommending method and apparatus |
| CN104915740A (en) * | 2014-03-11 | 2015-09-16 | 王波 | Network teaching platform composed of group membership |
| CN105630878A (en) * | 2015-12-17 | 2016-06-01 | 小米科技有限责任公司 | Method and apparatus for displaying application service information |
| CN105843858A (en) * | 2016-03-17 | 2016-08-10 | 广东小天才科技有限公司 | Recommendation method and device of learning resources |
| CN106060665A (en) * | 2016-07-18 | 2016-10-26 | 青岛海信传媒网络技术有限公司 | Television content recommending method, device and page server |
| CN106097202A (en) * | 2016-06-21 | 2016-11-09 | 广州伟度计算机科技有限公司 | A kind of intelligent terminal APP for family-school interaction realizes system and implementation method |
| CN106157203A (en) * | 2016-06-16 | 2016-11-23 | 北京数智源科技股份有限公司 | Micro-teaching platform |
-
2017
- 2017-01-18 CN CN201710040563.7A patent/CN106777360A/en active Pending
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103514162A (en) * | 2012-06-15 | 2014-01-15 | 上海蓝卓教育信息科技有限公司 | Intelligent courseware recommending system |
| CN104216883A (en) * | 2013-05-29 | 2014-12-17 | 酷盛(天津）科技有限公司 | Video recommendation reason generating system and method |
| CN104899195A (en) * | 2014-01-26 | 2015-09-09 | 武汉联影医疗科技有限公司 | Customized educational resource recommending method and apparatus |
| CN104915740A (en) * | 2014-03-11 | 2015-09-16 | 王波 | Network teaching platform composed of group membership |
| CN105630878A (en) * | 2015-12-17 | 2016-06-01 | 小米科技有限责任公司 | Method and apparatus for displaying application service information |
| CN105843858A (en) * | 2016-03-17 | 2016-08-10 | 广东小天才科技有限公司 | Recommendation method and device of learning resources |
| CN106157203A (en) * | 2016-06-16 | 2016-11-23 | 北京数智源科技股份有限公司 | Micro-teaching platform |
| CN106097202A (en) * | 2016-06-21 | 2016-11-09 | 广州伟度计算机科技有限公司 | A kind of intelligent terminal APP for family-school interaction realizes system and implementation method |
| CN106060665A (en) * | 2016-07-18 | 2016-10-26 | 青岛海信传媒网络技术有限公司 | Television content recommending method, device and page server |
Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107222584A (en) * | 2017-08-09 | 2017-09-29 | 广东小天才科技有限公司 | The recommendation method and server of a kind of children education application |
| CN108600337A (en) * | 2018-03-30 | 2018-09-28 | 上海乂学教育科技有限公司 | A kind of best learning Content automatic push method |
| CN109003478A (en) * | 2018-08-07 | 2018-12-14 | 广东小天才科技有限公司 | A kind of learning interaction method and facility for study |
| CN109033418A (en) * | 2018-08-07 | 2018-12-18 | 广东小天才科技有限公司 | A kind of the intelligent recommendation method and facility for study of learning Content |
| CN109166062A (en) * | 2018-08-07 | 2019-01-08 | 苏州承儒信息科技有限公司 | A kind of educational institution's recommended method and its system based on big data |
| CN109190018A (en) * | 2018-08-07 | 2019-01-11 | 苏州承儒信息科技有限公司 | Local educational institution's intelligent recommendation method and its system based on user's similarity |
| CN109712040A (en) * | 2018-11-29 | 2019-05-03 | 国政通科技有限公司 | A kind of learning system and its processing method |
| CN109410675A (en) * | 2018-12-12 | 2019-03-01 | 广东小天才科技有限公司 | A kind of exercise recommended method and private tutor's equipment based on student's portrait |
| CN109410675B (en) * | 2018-12-12 | 2021-03-12 | 广东小天才科技有限公司 | Exercise recommendation method based on student portrait and family education equipment |
| CN109344335A (en) * | 2018-12-20 | 2019-02-15 | 广东小天才科技有限公司 | A kind of content recommendation method and electronic equipment |
| CN109344335B (en) * | 2018-12-20 | 2020-12-25 | 广东小天才科技有限公司 | Content recommendation method and electronic equipment |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106777360A (en) | Content recommendation method and device | |
| CN103412882B (en) | A kind of method and device identifying that consumption is intended to | |
| CN103902538B (en) | Information recommending apparatus and method based on decision tree | |
| CN104102648A (en) | User behavior data based interest recommending method and device | |
| CN103942712A (en) | Product similarity based e-commerce recommendation system and method thereof | |
| CN109471657A (en) | Gray scale dissemination method, device, computer equipment and computer storage medium | |
| CN107862566A (en) | A kind of Method of Commodity Recommendation and system | |
| CN107632984A (en) | A kind of cluster data table shows methods, devices and systems | |
| CN105138690B (en) | The method and apparatus for determining keyword | |
| CN110390584A (en) | A kind of recognition methods of abnormal user, identification device and readable storage medium storing program for executing | |
| CN108388630A (en) | A kind of shopping information method for pushing, device and electronic equipment | |
| CN103365904A (en) | Advertising information searching method and system | |
| CN108009216A (en) | The processing method of destination object, device and system, storage medium, processor | |
| CN107092609A (en) | A kind of information-pushing method and device | |
| CN109977177A (en) | Generate the method and device of user's portrait | |
| CN107483381A (en) | The monitoring method and device of interlock account | |
| CN106919588A (en) | A kind of application program search system and method | |
| CN108153781A (en) | The method and apparatus for extracting the keyword of business scope | |
| WO2013173194A1 (en) | A user recommendation method and device | |
| CN109446402A (en) | A kind of searching method and device | |
| CN106204163B (en) | Method and device for determining user attribute characteristics | |
| CN107066293A (en) | Memory space management and device | |
| CN106873856A (en) | Application icon sorting technique and device | |
| CN105321095A (en) | Consumption service system and method for integrating iBeacon indoor positioning technology and information logistics cloud platform through telecommunication | |
| CN106952111A (en) | Personalized recommendation method and device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20170531 |
|
| RJ01 | Rejection of invention patent application after publication |