CN107122397A - Content recommendation method and device - Google Patents
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- CN107122397A CN107122397A CN201710154429.XA CN201710154429A CN107122397A CN 107122397 A CN107122397 A CN 107122397A CN 201710154429 A CN201710154429 A CN 201710154429A CN 107122397 A CN107122397 A CN 107122397A
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- 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
Abstract
The present invention provides a kind of content recommendation method and device, and this method includes：Receive the classifying content recommendation information generated according to user's search behavior；The classifying content recommendation information includes at least one classifying content；The classifying content is subscribed to for active user.The present invention is by subscribing to the classifying content recommended according to user's search behavior, the information content for alloing product actively constantly to recommend to be recommended according to the optimization of user's search behavior to user in subscriptions page, improve and recommend to have ensured the frequency recommended while accuracy rate, so as to greatly improve the information dispensed amount of product.
Description
Technical field
The application is related to search technique field, and in particular to a kind of content recommendation method and device.
Background technology
The searching service and information business in search product are typically isolated completely at present, and searching service is independent use
Householder moves behavior pattern, and information business is independent product active behavior pattern, and both are separate.
The recommendation of information content only relies upon the interest proposed algorithm on backstage, and the foundation of user preference takes long enough,
Content recommendation is inaccurate, the related information of the user for not utilizing searching service to be obtained.And due to point of existing information
It, according to information content classified types, is the method that all users are adapted to same mode classification that class mode, which is, divides particle
It is very thick, it is impossible to the demand of accurate covering individual subscriber, it is difficult to lift acceptance of the user to content.
For above mentioned problem, a kind of thinking of solution is that display is pushed away according to this search while search result is shown
The information content recommended, but the defect of such solution is to be only capable of to recommend user when user is often once searched for
Information content, and in search result shows the page, user is significantly higher than to the attention rate of search result in recommending
The attention rate of appearance, therefore lifting of such solution to Products Information dispensed amount is very limited, it is impossible to make full use of search industry
The related information of the obtained user of business.
The content of the invention
In view of drawbacks described above of the prior art or deficiency, expect to provide a kind of user for making full use of searching service to obtain
The degree of accuracy that individualized content is recommended in related information lifting information business, is pushed away with lifting the content of information dispensed amount of product
Recommend method and device.
In a first aspect, the present invention provides a kind of content recommendation method, this method includes：
Receive the classifying content recommendation information generated according to user's search behavior；The classifying content recommendation information is included at least
One classifying content；
The classifying content is subscribed to for active user.
Second aspect, the present invention provides a kind of content recommendation device, and the device includes：
Search unit, is configured to scan for, so that service end obtains the search behavior of active user；
Feedback information receiving unit is searched for, is configured to receive the classifying content that service end is generated according to user's search behavior
Recommendation information；The classifying content recommendation information includes at least one classifying content；
Commending contents unit, is configured to subscribe to the classifying content for active user；
Content display unit, the related content for the classifying content being configured to ordered by obtaining and display.
The third aspect, the present invention also provides a kind of equipment, including one or more processors and memory, wherein memory
Comprising the instruction that can be performed by the one or more processors to cause the one or more processors to perform according to of the invention each
The content recommendation method that embodiment is provided.
Fourth aspect, the present invention also provides a kind of computer-readable recording medium for the computer program that is stored with, the calculating
Machine program makes computer perform the content recommendation method provided according to various embodiments of the present invention.
The content recommendation method and device that many embodiments of the present invention are provided are pushed away by subscribing to according to user's search behavior
The classifying content recommended so that product actively constantly can be recommended to be optimized according to user's search behavior in subscriptions page to user to be pushed away
The information content recommended, improves and recommends to have ensured the frequency recommended (far above what is shown in result of page searching while accuracy rate
Frequency), so as to greatly improve the information dispensed amount of product；
The content recommendation method and device that some embodiments of the invention are provided further provide two kinds of subscribing modes：It is a kind of
The recommendation subscription component for recommending to subscribe to institute's content recommendation classification is shown in result of page searching, is that user remains right to choose
User can also be made voluntarily to subscribe to its interested but background analysis algorithm simultaneously and may think that priority not high content relatively point
Class；It is another directly to subscribe to background analysis algorithm for user and give priority to the higher classifying content of level, reduce user's subscription
It is manually operated；
The content recommendation method and device that some embodiments of the invention are provided are further by recommending according to all kinds of different use
The classifying content that family search behavior is obtained, covers all around the classifying content that user may be interested；
Some embodiments of the invention provide content recommendation method and device further by by user to classifying content
Edit action is sent to service end for optimization user's portrait, further improves the accuracy to user's Generalization bounds；
The content recommendation method and device that some embodiments of the invention are provided in product homepage with label further by being made
The content recommended is shown by the switching unit of all the elements, the frequency of recommendation is further increased, and the information of product is divided
Hair amount；
The content recommendation method and device that some embodiments of the invention are provided are further by polymerize the modularization of card
Component assembly recommends the content of the diversification classification of same classifying content, further improves the frequency of recommendation, and product
Information dispensed amount.
Brief description of the drawings
By reading the detailed description made to non-limiting example made with reference to the following drawings, the application's is other
Feature, objects and advantages will become more apparent upon：
The flow chart for the content recommendation method that Fig. 1 provides for one embodiment of the invention.
Fig. 2 is a kind of flow chart of preferred embodiment of method shown in Fig. 1.
Fig. 3 is a kind of flow chart of preferred embodiment of method shown in Fig. 1.
Fig. 4 is the block schematic illustration of product homepage in the preferred embodiment of method shown in Fig. 2 or Fig. 3.
Fig. 5 is a kind of flow chart of preferred embodiment of method shown in Fig. 1.
Fig. 6 is a kind of flow chart of preferred embodiment of method shown in Fig. 1.
The structural representation for the content recommendation device that Fig. 7 provides for one embodiment of the invention.
A kind of structural representation for equipment that Fig. 8 provides for one embodiment of the invention.
Embodiment
The application is described in further detail with reference to the accompanying drawings and examples.It is understood that this place is retouched
The specific embodiment stated is used only for explaining related invention, rather than the restriction to the invention.It also should be noted that, in order to
It is easy to illustrate only the part related to invention in description, accompanying drawing.
It should be noted that in the case where not conflicting, the feature in embodiment and embodiment in the application can phase
Mutually combination.Describe the application in detail below with reference to the accompanying drawings and in conjunction with the embodiments.
The flow chart for the content recommendation method that Fig. 1 provides for one embodiment of the invention.
As shown in figure 1, in the present embodiment, the content recommendation method that the present invention is provided includes：
S10：Receive the classifying content recommendation information generated according to user's search behavior.Wherein, the classifying content recommendation
Breath includes at least one classifying content.
S30：The classifying content is subscribed to for active user.
In step slo, user's search behavior can be following arbitrary one or more：This search of active user
Behavior；The historical search behavior of active user；The search behavior of each user under the classification of active user's owning user, for example, in it is old
Search behavior of year user etc.；Possesses the search behavior of each user of same attribute with active user, for example, interested in military affairs
The search behavior of user etc.；The popular search behavior of all users of present period.In more embodiments, it can also be configured to
The different types of user's search behavior screened according to different demands.
Classifying content recommendation information can only include a recommended priority highest classifying content, can also include multinomial
Classifying content, particular number can be configured according to the actual requirements.The species of classifying content is related to above-mentioned user's search behavior.
For example, when user's search behavior includes this search behavior of active user, and all users of present period popular search
During behavior, " Hu Ge " searched for according to active user may then recommend related to " Hu Ge " and current hot topic to active user
" thinkling sound Ya lists " be used as a classifying content.
In step s 30, a variety of subscribing manners can be configured according to the actual requirements to acquired in step S10
Classifying content is subscribed to, or selectivity is subscribed to.A kind of quilt for selecting to subscribe to by active user is specifically introduced below with reference to Fig. 2
Dynamic subscribing mode, and a kind of active subscribing mode directly subscribed to for active user is specifically introduced with reference to Fig. 3, implement more
In example, the subscribing mode of more different modes can be also configured according to different demands, identical technique effect can be achieved.
Above-described embodiment is by subscribing to the classifying content recommended according to user's search behavior so that product can actively be held
Continuously recommend to optimize according to user's search behavior the information content recommended to user in subscriptions page, improve and recommend the same of accuracy rate
When ensured the frequency (far above the frequency that show in result of page searching) recommended so that the information for greatly improving product is divided
Hair amount.
Fig. 2 is a kind of flow chart of preferred embodiment of method shown in Fig. 1.
As shown in Fig. 2 in a preferred embodiment, step S30 includes：
S301：The recommendation subscription component for recommending subscribed content classification is shown in result of page searching；
S302：In response to clicking on the recommendation subscription component, the classification that corresponding content classification is added in subscriptions page is subscribed to
Component；
S305：In response to clicking on or sliding into the classification subscription component, related content and the display of the classifying content are obtained.
Specifically, in the present embodiment, recommend subscription component to subscribe to button, subscriptions page is product homepage, and classification is ordered
Component is read for label (tag), according to the actual requirements subscription component can will be recommended to be configured to other this areas in more embodiments
Conventional interactive component, diverse location or the page in path in product are configured to by subscriptions page, and, by subscription component of classifying
It is configured to other selective changeover modules commonly used in the art.
In above-mentioned passive subscribing mode, the classifying content recommendation information that abovementioned steps S10 is received generally includes multinomial
Classifying content (can also only include a classifying content), so as to show the multinomial classifying content recommended in step S301
Button is subscribed to so that user selects, the probability that user subscribes to is improved.
For example, in step S301, showing that " finance ", " house property ", " vapour are subscribed in recommendation respectively in result of page searching
The subscription button of car "；
In step S302, when user clicks on any subscription button, such as classifying content is the subscription button of " automobile ", is rung
The label of " automobile " should be added in homepage in the clicking operation；
In step S305, when user clicks on or slid into " automobile " label in homepage, in response to the click or slip
Operation, obtains the related content of " automobile " classification, and is shown in content display frame.
A kind of passive subscribing mode is above mentioned embodiment provided, shows that recommendation subscription is recommended in result of page searching interior
Hold classification recommendation subscription component, be can also be made while user remains right to choose user voluntarily subscribe to its it is interested but after
Platform parser may think that priority not high classifying content relatively.
Above-described embodiment also further passes through the classifying content for recommending to obtain according to all kinds of different user search behaviors, Quan Fang
The possible classifying content interested of position covering user.
Fig. 3 is the flow chart of another preferred embodiment of method shown in Fig. 1.
As shown in figure 3, in another preferred embodiment, step S30 includes：
S304：The classification subscription component of the classifying content is added in subscriptions page；
S305：In response to clicking on or sliding into the classification subscription component, related content and the display of the classifying content are obtained.
In the present embodiment, subscriptions page is similarly product homepage, and classification subscription component is similarly label (tag), more
Different configurations can be used in many embodiments according to the actual requirements.
In above-mentioned active subscribing mode, the classifying content recommendation information that abovementioned steps S10 is received generally includes less
The classifying content (such as 1-2, but can also be configured the classifying content of more item numbers according to the actual requirements) of item number, so as to avoid
Actively for active user's subscription quantity is excessive, recommending classification, not enough accurately classifying content reduces user's body in step S304
Test.
For example, only including " finance " classifying content in the classifying content recommendation information that step S10 is received, in step
In rapid S304, " finance " label is directly added in homepage for active user, in step S305, when user clicks in homepage
Or when sliding into " finance " label, in response to the click or slide, the related content of " finance " classification is obtained, and in content
Shown in display frame.
A kind of active subscribing mode is above mentioned embodiment provided, directly subscribing to background analysis algorithm for user gives priority to level
Higher classifying content, reduces the manually operated of user's subscription.
Fig. 4 is the block schematic illustration of product homepage in the preferred embodiment of method shown in Fig. 2 or Fig. 3.
As shown in figure 4, in the present embodiment, only including search column, tag along sort column as the product homepage of subscriptions page
With content display field.All the elements shown by content display field are used as the switching of classification using each label in tag along sort column
Display unit.
Search column enters confession user as function of search and scanned for, and tag along sort column shows for switch contents display field
The classifying content shown.In response to the click tag operational or slide of active user, above-mentioned steps S305 is performed, you can display
The content recommended according to user's search behavior.
Skilled person will appreciate that framework shown in dawn Fig. 4 is merely illustrative framework, can be according to reality in more embodiments
Border demand configuration different shape, the framework of layout, as long as the function of each component is constant in framework can be achieved identical technology effect
Really.
Fig. 5 is a kind of flow chart of preferred embodiment of method shown in Fig. 1.
As shown in figure 5, in a preferred embodiment, also including before step S30：
S20：Screened according to pre-configured strategy in each classifying content that the classifying content recommendation information includes.
Specifically, the pre-configured strategy can be configured selectively according to the actual requirements, for example, remove and actively added with user
The classifying content identical classifying content of label, or, the quantity for the classifying content subscribed at present according to active user are screened in step
The quantity for the classifying content subscribed in rapid S30 for active user.
For example, the classifying content recommendation information that step S10 is received includes three classifying contents, active user subscribes at present
Classifying content quantity be no more than 3 when, do not screen；The quantity for the classifying content that active user subscribes at present is 4-6
When, filter out higher two of recommended priority；When the quantity for the classifying content that active user subscribes at present is more than 6, screening
Go out recommended priority highest one, etc..
Above-mentioned strategy can configure not of the same race according to the actual requirements only as exemplary screening strategy in more embodiments
Class, the strategy screened according to different type attribute, can be achieved identical technique effect.
Above-described embodiment is further recommended by the switching unit display in product homepage using label as all the elements
Content, further increase the frequency of recommendation, and product information dispensed amount.
Fig. 6 is a kind of flow chart of preferred embodiment of method shown in Fig. 1.
As shown in fig. 6, in a preferred embodiment, further comprising after step S30：
S40：Active user is recorded to the edit operation of the classification subscription component and is sent to service end, for optimization user
Portrait and the related operation operation of progress.
Specifically, active user can enter to each label in tag along sort column shown in Fig. 4 (or other types of framework)
The different edit operations such as row rearrangement, deletion, addition, the edit operation is sent to service end, is available for service end to pass through each
Class algorithm further optimizes user's portrait of active user, so that recommend more accurately classifying content for active user, and
Progress is other to be operated to user's related all kinds of operations interested.
Above-described embodiment is further by the way that user is sent to service end to the edit action of classifying content so that optimization is used
Family is drawn a portrait, and further improves the accuracy to user's Generalization bounds.
In a preferred embodiment, in above-mentioned steps S305, obtain the related content of the classifying content and show specific bag
Include：The content portals of related some classifications of the classifying content are obtained, and are aggregated in display in same polymerizing component.
Specifically, content display field as shown in Figure 4, is not suitable for a variety of different classes of contents of display, and show
The content quantity shown is limited, and user, which needs to slide, shows that list progressively obtains more contents.
In the present embodiment, polymerizing component is polymerization card, and above-mentioned some classifications include following at least two classifications：Hundred
Section, video, novel, mhkc, keyword, so as to by content portals of all categories be integrated in most easily position for user
Access.
In more embodiments, different types of polymerizing component, and integrated difference wherein can be configured according to the actual requirements
The classification of species is used as content portals.
Above-described embodiment to polymerize the modular assembly of card further by polymerizeing the polynary of the same classifying content of recommendation
Change the content of classification, further improve the frequency of recommendation, and product information dispensed amount.
The structural representation for the content recommendation device that Fig. 7 provides for one embodiment of the invention.Commending contents dress shown in Fig. 7
The either method performed shown in Fig. 1-6 can be corresponded to by putting.
As shown in fig. 7, in the present embodiment, a kind of content recommendation device 10 that the present invention is provided include search unit 11,
Search for feedback information receiving unit 13, commending contents unit 15 and content display unit 17.
Search unit 11 is configured to scan for, so that service end 20 obtains the search behavior of active user.Service end
20 collect the search behavior of some users, and the user that can obtain the variant species described in method shown in above-mentioned Fig. 1 searches
Suo Hangwei.
Search feedback information receiving unit 13 is configured to receive the content that service end 20 is generated according to user's search behavior
Classification recommendation information.The classifying content recommendation information includes at least one classifying content.
Commending contents unit 15 is configured to subscribe to the classifying content for active user.
Content display unit 17 is configured to the related content of the classifying content ordered by acquisition and display.
In a preferred embodiment, commending contents unit 15 is further configured to show recommendation in result of page searching
Subscribe to the recommendation subscription component of the classifying content；And, in response to clicking on the recommendation subscription component, the addition pair in subscriptions page
Answer the classification subscription component of classifying content.
Content display unit 17 is further configured to, in response to clicking on or sliding into the classification subscription component, obtain this interior
Hold related content and the display of classification.
Commending contents unit 15 and the passive subscribing mode performed by content display unit 17 are referred in the present embodiment
The method shown in Fig. 2 is stated, here is omitted.
In a preferred embodiment, commending contents unit 15 is further configured to add the content point in subscriptions page
The classification subscription component of class.
Content display unit 17 is further configured to, in response to clicking on or sliding into the classification subscription component, obtain this interior
Hold related content and the display of classification.
Commending contents unit 15 and the active subscribing mode performed by content display unit 17 are referred in the present embodiment
The method shown in Fig. 3 is stated, here is omitted.
In a preferred embodiment, commending contents unit 15 is further configured to according to pre-configured strategy in the content
Screened in each classifying content that classification recommendation information includes.Screening machine in the present embodiment performed by commending contents unit 15
System refers to the method shown in above-mentioned Fig. 5, and here is omitted.
In a preferred embodiment, content display unit 17 is further configured to record active user to classification subscription
The edit operation of component is simultaneously sent to service end, for optimization user portrait and the related operation operation of progress.In in the present embodiment
Feedback mechanism performed by appearance recommendation unit 17 refers to the method shown in above-mentioned Fig. 6, and here is omitted.
In a preferred embodiment, content display unit 17 is further configured to all the elements in product homepage are equal
The switching display unit of classification is used as using label (tag).
In a preferred embodiment, if content display unit 17 is further configured to obtain the related of the classifying content
The other content portals of Ganlei, and it is aggregated in display in polymerization card assemblies.
A kind of structural representation for equipment that Fig. 8 provides for one embodiment of the invention.
As shown in figure 8, as on the other hand, present invention also provides a kind of equipment 800, including one or more centres
Unit (CPU) 801 is managed, it can add according to the program being stored in read-only storage (ROM) 802 or from storage part 808
The program that is downloaded in random access storage device (RAM) 803 and perform various appropriate actions and processing.In RAM803, also deposit
Contain equipment 800 and operate required various programs and data.CPU801, ROM802 and RAM803 pass through the phase each other of bus 804
Even.Input/output (I/O) interface 805 is also connected to bus 804.
I/O interfaces 805 are connected to lower component：Importation 806 including keyboard, mouse etc.；Penetrated including such as negative electrode
The output par, c 807 of spool (CRT), liquid crystal display (LCD) etc. and loudspeaker etc.；Storage part 808 including hard disk etc.；
And the communications portion 809 of the NIC including LAN card, modem etc..Communications portion 809 via such as because
The network of spy's net performs communication process.Driver 810 is also according to needing to be connected to I/O interfaces 805.Detachable media 811, such as
Disk, CD, magneto-optic disk, semiconductor memory etc., are arranged on driver 810, in order to read from it as needed
Computer program be mounted into as needed storage part 808.
Especially, in accordance with an embodiment of the present disclosure, the content recommendation method of any of the above-described embodiment description can be implemented
For computer software programs.For example, embodiment of the disclosure includes a kind of computer program product, it includes being tangibly embodied in
Computer program on machine readable media, the computer program includes the program code for being used for performing content recommendation method.
In such embodiments, the computer program can be downloaded and installed by communications portion 809 from network, and/or from
Detachable media 811 is mounted.
As another aspect, present invention also provides a kind of computer-readable recording medium, the computer-readable storage medium
Matter can be the computer-readable recording medium included in the device of above-described embodiment；Can also be individualism, it is unassembled
Enter the computer-readable recording medium in equipment.Computer-readable recording medium storage has one or more than one program, should
Program is used for performing by one or more than one processor is described in present context recommendation method.
Flow chart and block diagram in accompanying drawing, it is illustrated that according to the system of various embodiments of the invention, method and computer journey
Architectural framework in the cards, function and the operation of sequence product.At this point, each square frame in flow chart or block diagram can generation
The part of one module of table, program segment or code, the part of the module, program segment or code is used comprising one or more
In the executable instruction for realizing defined logic function.It should also be noted that in some realizations as replacement, being marked in square frame
The function of note can also be with different from the order marked in accompanying drawing generation.For example, two square frames succeedingly represented are actually
It can perform substantially in parallel, they can also be performed in the opposite order sometimes, depending on this is according to involved function.Also
It is noted that the combination of each square frame in block diagram and/or flow chart and the square frame in block diagram and/or flow chart, Ke Yitong
Function as defined in performing or the special hardware based system of operation is crossed to realize, or can be by specialized hardware with calculating
The combination of machine instruction is realized.
Being described in unit or module involved in the embodiment of the present application can be realized by way of software, can also
Realized by way of hardware.Described unit or module can also be set within a processor, for example, each unit can
With the software program being provided in computer or intelligent movable equipment or the hardware unit being separately configured.Wherein, this
The title of a little units or module does not constitute the restriction to the unit or module in itself under certain conditions.
Above description is only the preferred embodiment of the application and the explanation to institute's application technology principle.People in the art
Member should be appreciated that invention scope involved in the application, however it is not limited to the technology of the particular combination of above-mentioned technical characteristic
Scheme, while should also cover in the case where not departing from the application design, is appointed by above-mentioned technical characteristic or its equivalent feature
Other technical schemes formed by meaning combination.Such as features described above has similar functions with (but not limited to) disclosed herein
Technical characteristic carry out mutually replace formed by technical scheme.
Claims (19)
1. a kind of content recommendation method, it is characterised in that methods described includes：
Receive the classifying content recommendation information generated according to user's search behavior；The classifying content recommendation information includes at least one
Item classifying content；
The classifying content is subscribed to for active user.
2. content recommendation method according to claim 1, it is characterised in that described to subscribe to the content point for active user
Class includes：
The recommendation subscription component for recommending to subscribe to the classifying content is shown in result of page searching；
In response to clicking on the recommendation subscription component, the classification subscription component of corresponding content classification is added in subscriptions page；
In response to clicking on or sliding into the classification subscription component, related content and the display of the classifying content are obtained.
3. content recommendation method according to claim 1, it is characterised in that described to subscribe to the content point for active user
Class includes：
The classification subscription component of the classifying content is added in subscriptions page；
In response to clicking on or sliding into the classification subscription component, related content and the display of the classifying content are obtained.
4. the content recommendation method according to claim any one of 1-3, it is characterised in that user's search behavior includes
At least one of below：This search behavior of active user, the historical search behavior of active user, active user's owning user point
The search behavior of each user under class, the search behavior for possessing each user of same attribute with active user, present period institute is useful
The popular search behavior at family.
5. the content recommendation method according to claim any one of 1-3, it is characterised in that described to subscribe to institute for active user
Also include before stating classifying content：
Screened according to pre-configured strategy in each classifying content that the classifying content recommendation information includes.
6. the content recommendation method according to Claims 2 or 3, it is characterised in that described to be subscribed to for active user in described
Hold also includes after classifying：
Active user is recorded to the edit operation of the classification subscription component and is sent to service end, for optimization user portrait and
Carry out related operation operation.
7. the content recommendation method according to Claims 2 or 3, it is characterised in that the subscriptions page is product homepage, institute
It is label (tag) to state classification subscription component.
8. content recommendation method according to claim 7, it is characterised in that all the elements in the product homepage with
Label (tag) is used as the switching display unit classified.
9. the content recommendation method according to Claims 2 or 3, it is characterised in that the phase of the acquisition classifying content
Hold inside the Pass and show including：
The content portals of related some classifications of the classifying content are obtained, and are aggregated in display in same polymerizing component.
10. content recommendation method according to claim 9, it is characterised in that the polymerizing component is polymerization card, described
Classification includes following at least two：Encyclopaedia, video, novel, mhkc, keyword.
11. a kind of content recommendation device, it is characterised in that described device includes：
Search unit, is configured to scan for, so that service end obtains the search behavior of active user；
Feedback information receiving unit is searched for, is configured to receive the classifying content that the service end is generated according to user's search behavior
Recommendation information；The classifying content recommendation information includes at least one classifying content；
Commending contents unit, is configured to subscribe to the classifying content for active user；
Content display unit, the related content for the classifying content being configured to ordered by obtaining and display.
12. content recommendation device according to claim 11, it is characterised in that the commending contents unit is further configured
For showing the recommendation subscription component for recommending to subscribe to the classifying content in result of page searching；And, in response to clicking on institute
Recommendation subscription component is stated, the classification subscription component of corresponding content classification is added in subscriptions page；
The content display unit is further configured to, in response to clicking on or sliding into the classification subscription component, obtain described
The related content of classifying content and display.
13. content recommendation device according to claim 11, it is characterised in that the commending contents unit is further configured
Classification subscription component for adding the classifying content in subscriptions page；
The content display unit is further configured to, in response to clicking on or sliding into the classification subscription component, obtain described
The related content of classifying content and display.
14. the content recommendation device according to claim any one of 11-13, it is characterised in that the commending contents unit
Further it is configured to be sieved in each classifying content that the classifying content recommendation information includes according to pre-configured strategy
Choosing.
15. the content recommendation device according to claim 12 or 13, it is characterised in that the content display unit is further
It is configured to record active user to the edit operation of the classification subscription component and sends to service end, so that optimization user draws
Picture and the related operation operation of progress.
16. the content recommendation device according to claim 12 or 13, it is characterised in that the subscriptions page is that product is first
Page, the classification subscription component is label (tag), and the content display unit is further configured in the product homepage
All the elements using label (tag) be used as classification switching display unit.
17. the content recommendation device according to claim 12 or 13, it is characterised in that the content display unit is further
It is configured to obtain the content portals of related some classifications of the classifying content, and is aggregated in aobvious in polymerization card assemblies
Show；The classification includes following at least two：Encyclopaedia, video, novel, mhkc, keyword.
18. a kind of equipment, it is characterised in that the equipment includes：
One or more processors；
Memory, for storing one or more programs,
When one or more of programs are by one or more of computing devices so that one or more of processors
Perform the method as any one of claim 1-10.
19. a kind of computer-readable recording medium for the computer program that is stored with, it is characterised in that the program is executed by processor
Methods of the Shi Shixian as any one of claim 1-10.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710154429.XA CN107122397A (en) | 2017-03-15 | 2017-03-15 | Content recommendation method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710154429.XA CN107122397A (en) | 2017-03-15 | 2017-03-15 | Content recommendation method and device |
Publications (1)
| Publication Number | Publication Date |
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| CN107122397A true CN107122397A (en) | 2017-09-01 |
Family
ID=59717402
Family Applications (1)
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