CN107295361B - A kind of content delivery method - Google Patents
A kind of content delivery method Download PDFInfo
- Publication number
- CN107295361B CN107295361B CN201710480351.0A CN201710480351A CN107295361B CN 107295361 B CN107295361 B CN 107295361B CN 201710480351 A CN201710480351 A CN 201710480351A CN 107295361 B CN107295361 B CN 107295361B
- Authority
- CN
- China
- Prior art keywords
- user
- content
- push
- attribute tags
- data
- 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.)
- Active
Links
- 238000002716 delivery method Methods 0.000 title claims abstract description 16
- 238000000034 method Methods 0.000 claims abstract description 45
- 238000012545 processing Methods 0.000 claims abstract description 19
- 238000004364 calculation method Methods 0.000 claims description 5
- 230000003542 behavioural effect Effects 0.000 claims description 4
- 238000013499 data model Methods 0.000 claims description 4
- 230000005540 biological transmission Effects 0.000 claims description 3
- 238000006116 polymerization reaction Methods 0.000 claims description 3
- 238000005516 engineering process Methods 0.000 description 10
- 238000010586 diagram Methods 0.000 description 8
- 238000004891 communication Methods 0.000 description 6
- 230000006870 function Effects 0.000 description 5
- 230000003993 interaction Effects 0.000 description 5
- 230000008569 process Effects 0.000 description 5
- 101100368725 Bacillus subtilis (strain 168) tagF gene Proteins 0.000 description 4
- 241001122767 Theaceae Species 0.000 description 4
- 230000006399 behavior Effects 0.000 description 4
- 238000010422 painting Methods 0.000 description 4
- 239000000344 soap Substances 0.000 description 4
- 238000004458 analytical method Methods 0.000 description 3
- 238000011161 development Methods 0.000 description 3
- 230000018109 developmental process Effects 0.000 description 3
- 239000002131 composite material Substances 0.000 description 2
- 235000004280 healthy diet Nutrition 0.000 description 2
- 239000004615 ingredient Substances 0.000 description 2
- 230000011218 segmentation Effects 0.000 description 2
- 241001269238 Data Species 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 238000000354 decomposition reaction Methods 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000003780 insertion Methods 0.000 description 1
- 230000037431 insertion Effects 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 210000003205 muscle Anatomy 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000002360 preparation method Methods 0.000 description 1
- 238000004321 preservation Methods 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
- H04N21/47—End-user applications
- H04N21/482—End-user interface for program selection
- H04N21/4826—End-user interface for program selection using recommendation lists, e.g. of programs or channels sorted out according to their score
-
- 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
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/20—Servers specifically adapted for the distribution of content, e.g. VOD servers; Operations thereof
- H04N21/23—Processing of content or additional data; Elementary server operations; Server middleware
- H04N21/234—Processing of video elementary streams, e.g. splicing of video streams or manipulating encoded video stream scene graphs
- H04N21/23418—Processing of video elementary streams, e.g. splicing of video streams or manipulating encoded video stream scene graphs involving operations for analysing video streams, e.g. detecting features or characteristics
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/20—Servers specifically adapted for the distribution of content, e.g. VOD servers; Operations thereof
- H04N21/25—Management operations performed by the server for facilitating the content distribution or administrating data related to end-users or client devices, e.g. end-user or client device authentication, learning user preferences for recommending movies
- H04N21/262—Content or additional data distribution scheduling, e.g. sending additional data at off-peak times, updating software modules, calculating the carousel transmission frequency, delaying a video stream transmission, generating play-lists
- H04N21/26258—Content or additional data distribution scheduling, e.g. sending additional data at off-peak times, updating software modules, calculating the carousel transmission frequency, delaying a video stream transmission, generating play-lists for generating a list of items to be played back in a given order, e.g. playlist, or scheduling item distribution according to such list
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
- H04N21/43—Processing of content or additional data, e.g. demultiplexing additional data from a digital video stream; Elementary client operations, e.g. monitoring of home network or synchronising decoder's clock; Client middleware
- H04N21/44—Processing of video elementary streams, e.g. splicing a video clip retrieved from local storage with an incoming video stream or rendering scenes according to encoded video stream scene graphs
- H04N21/44008—Processing of video elementary streams, e.g. splicing a video clip retrieved from local storage with an incoming video stream or rendering scenes according to encoded video stream scene graphs involving operations for analysing video streams, e.g. detecting features or characteristics in the video stream
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/80—Generation or processing of content or additional data by content creator independently of the distribution process; Content per se
- H04N21/83—Generation or processing of protective or descriptive data associated with content; Content structuring
- H04N21/835—Generation of protective data, e.g. certificates
- H04N21/8352—Generation of protective data, e.g. certificates involving content or source identification data, e.g. Unique Material Identifier [UMID]
Landscapes
- Engineering & Computer Science (AREA)
- Multimedia (AREA)
- Signal Processing (AREA)
- Databases & Information Systems (AREA)
- Theoretical Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Computer Security & Cryptography (AREA)
- Software Systems (AREA)
- Human Computer Interaction (AREA)
- Information Transfer Between Computers (AREA)
Abstract
This application provides a kind of content delivery methods, this method comprises: receiving the image data that applications client is sent；Wherein, the image and/or video that described image data are shot by the applications client according to photographic device connected to it determine；The attribute tags that data processing obtains the user logged in the applications client are carried out to described image data；Push contents list is generated according to the attribute tags of the user；And the push contents list is handed down to the applications client.Present invention also provides the servers for realizing content push.
Description
Technical field
This application involves information technology field more particularly to a kind of content delivery methods and device.
Background technique
With the development of internet, smart television using more and more extensive, play in smart home extremely important
Role.In general, smart television can also push some video programs to user other than user actively selects video program
Or advertisement, such as Hot Contents etc., therefore, how to carry out content push also becomes one of hot issue.
Summary of the invention
Present application example proposes a kind of content delivery method, comprising: the image data that applications client is sent is received,
In, the image and/or video that described image data are shot by the applications client according to photographic device connected to it determine；
The attribute tags that data processing obtains the user logged in the applications client are carried out to described image data；According to described
Attribute tags generate push contents list；And the push contents list is handed down to the applications client.
Present application example proposes a kind of content push server, comprising:
Receiving module, for receiving the image data of applications client transmission, wherein described image data are by the application
The image and/or video that client is shot according to photographic device connected to it determine；
Module is obtained, obtains the use logged in the applications client for carrying out data processing to described image data
The attribute tags at family；
Determining module, for generating push contents list according to the attribute tags of the user；And
Sending module, for that will push contents list and be handed down to applications client.
It, can camera or the collected figure of external photographic device based on terminal device by above technical scheme
As analyzing the characteristic of life data of user, the attribute tags of user are obtained, and according to the attribute tags of user in content
Matched content is searched in library, so as to push content that some users need and suitable to user, so that content pushes away
Send it is more accurate, avoid user in order in huge volumes of content find be suitble to oneself content and need terminal device and server
Between it is frequent interaction caused by the wasting of resources.
Detailed description of the invention
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below
There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this
Some embodiments of invention without any creative labor, may be used also for those of ordinary skill in the art
To obtain other drawings based on these drawings.
Fig. 1 is the system structure diagram of one example of the application；
Fig. 2 is the content delivery method flow chart of one example of the application；
Fig. 3 is the method flow diagram that the content and user's matching degree are determined described in one example of the application；
Fig. 4 is the image-recognizing method flow chart of one example of the application；
Fig. 5 is the content delivery method flow chart of one example of the application；
Fig. 6 is the structural schematic diagram of server described in one example of the application；
Fig. 6 A is the structural schematic diagram of acquisition module 602 described in one example of the application；
Fig. 6 B is the structural schematic diagram of determining module 603 described in one example of the application；
Fig. 7 is the composite structural diagram of the calculating equipment 700 where the server 600 of one example of the application.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that the described embodiment is only a part of the embodiment of the present invention, instead of all the embodiments.Based on this
Embodiment in invention, every other reality obtained by those of ordinary skill in the art without making creative efforts
Example is applied, shall fall within the protection scope of the present invention.
It is succinct and intuitive in order to what is described, hereafter by describing several representative embodiments come to the solution of the present invention
It is illustrated.A large amount of details is only used for helping to understand the solution of the present invention in embodiment.However, it will be apparent that technology of the invention
Scheme can be not limited to these details when realizing.In order to avoid unnecessarily having obscured the solution of the present invention, some embodiment party
Formula is not described meticulously, but only gives frame.Hereinafter, " comprising " refers to " including but not limited to ", " root
According to ... " refer to " according at least to ..., but be not limited to according only to ... ".Hereinafter it is not specifically stated the quantity of an ingredient
When, it is meant that the ingredient is either one or more, or can be regarded as at least one.
The example of the application proposes a kind of content delivery method, and this method can pass through the terminal devices such as smart television
Camera is mounted on indoor picture pick-up device shooting image, to collect a plurality of types of user data, and to the user of collection
Data carry out data processing to obtain the attribute tags of user, and the attribute tags based on obtained user push one to user
It is suitble to the content of the user a bit.On the one hand above content method for pushing can make content push more accurate, avoid user
It is needed caused by the frequent interaction between terminal device and server to be suitble to the content of oneself in searching in huge volumes of content
The wasting of resources can be modified the operational model of data processing on the other hand by collecting and accumulating user data for a long time
Keep it more and more clear, so that the content of push is also more and more accurate.
Wherein, in some examples of the application, above-mentioned user data can specifically refer to through terminals such as smart televisions
The camera of equipment is mounted on the reflection user that indoor photographic device shooting is collected and obtained by image recognition analysis
The data of characteristic of life, for example, the data etc. of furnishings, furniture, household electrical appliances, personage and behavior etc..Above-mentioned user
Attribute tags specifically can be some keywords of the representative user personality obtained according to Users'Data Analysis, these keywords
The characteristics of can reflecting user to a certain extent and interest.Above content can specifically refer to that audio, video, picture etc. are more
Content of text such as media content, or the news comprising text, article etc. are also possible to video/audio/picture etc. and text knot
Conjunction obtains the content comprising information.
Fig. 1 shows the system structure diagram that content delivery method described in some examples of the application is applicable in.Such as Fig. 1
Shown, the system of the application includes at least: terminal device 11, network 12, one or more servers 13, one or more data
Library 14 and photographic device 15.
In some examples of the application, above-mentioned terminal device 11 can be smart television, personal computer (PC), notes
The intelligent terminals such as this computer are also possible to the intelligent mobile terminal equipments such as smart phone, PAD or tablet computer.Generally
In the case of, various application software can be installed on terminal device 11, currently needed including user to be used for watching
The application software of the texts such as the videos such as film, TV programme, programme televised live and news, hot spot, comment and/or image content.
In description later, for the convenience of description, user will be used or application software currently in use is known as applications client.
Network 12 may include cable network and wireless network.As shown in Figure 1, netting side in access, terminal device 11 can
Wirelessly or wired mode is linked into network 13；And in core net side, server 13 generally by
Wired mode is connected to network 13.Certainly, server 13 can also be connected to network 12 wirelessly.
Above-mentioned server 13 is the server of above-mentioned target application software, for example, it may be multimedia server, for example rise
Interrogate the server of video；It is also possible to promotion message Platform Server, such as Advertisement Server；It is also possible to provide text for user
The content server of word and/or picture push content, for example, Tencent's NEWS SERVER etc..Server 13 and terminal device 11
On applications client provide service and content together for user, for example, playing video, audio, promotion message and video
The services such as program push, text and/or image content push.In addition to this, server 13 can also be to according to the use being collected into
User data is analyzed, and obtains the attribute tags of user, and obtain wait push away according to the matching that the attribute tags of user carry out content
The content sent.It should be noted that above-mentioned server 13, which can be single server apparatus, is also possible to multiple server sets
The cluster server that group obtains together.
Above-mentioned database 14 is for storing user data relevant to above-mentioned target application software, such as the account letter of user
Breath, the user data of user and attribute tags of user etc..Above-mentioned database 14 can be also used for storing various contents.Number
Can be in the manner shown in figure 1 independently of server 13 according to library 14, server 13 can direct or through the visit of other servers
Ask database 14.Database 14 can also be integrated with server 13.
Above-mentioned photographic device 15 is for shooting image.The photographic device 15 can be integrated with terminal device 11, example
Such as, the camera carried on PAD, tablet computer, smart phone and smart television.The photographic device 15 is also possible to individually
Video camera, such as camera at home is installed.At this time the photographic device 15 can by the short haul connections such as bluetooth mode with
Neighbouring terminal device 11 links together, and the image that itself shoots is sent to terminal device 11；Certainly, the photographic device 15
It can also be directly accessed network 12, the image that itself shoots is sent to by server 13 by network 12.
Under the premise of herein, it is based on above-mentioned system structure shown in FIG. 1, the example of the application provides a kind of content push side
Method.Fig. 2 shows the flow charts for the content delivery method that present application example provides.As shown in Fig. 2, this method can be by server
13 execute, comprising the following steps:
Step 201: receiving the image data that applications client is sent, wherein above-mentioned image data is by applications client root
It is determined according to the image and/or video of photographic device connected to it shooting.
In some instances, with terminal device 11 intelligence it is higher and higher, including camera etc. including outside set
It is standby or the standard configuration of terminal device 11 to be become namely terminal device 11 itself just be integrated with photographic device 15.Therefore, eventually
End equipment 11 can collect image data related with user's characteristic of life by being integrated into the photographic device 15 of itself,
Such as indoor photo or video etc..It, indoors can also be in addition, even if without integrated photographic device 15 on terminal device 11
The photographic devices such as individual camera 15 are installed to carry out the acquisition of image.Moreover, between photographic device 15 and terminal device 11
It can be attached by the short haul connections such as WIFI or Zigbee mode or other network communication modes.Then, camera shooting is set
The image of acquisition can also be sent to terminal device 11 by standby 15.In this case, the application visitor installed on terminal device 11
Image data can be sent to server 13 by network 12 by family end, and server 13 can receive by collecting on terminal device 11
At or individual 15 acquired image data of picture pick-up device, to carry out subsequent analysis processing.
In some examples of the application, above-mentioned image data can be the photographic device 15 or single on terminal device 11
The image file that only photographic device 15 is shot perhaps video file such as bitmap file or jpeg file or other standards
The image file or video file of format.
In other examples of the application, above-mentioned image data is also possible to the applications client pair on terminal device 11
The image or video that photographic device 15 is shot obtain and acquire the number of image-related text formatting after carrying out image recognition
According to, such as may include furnishings data, furniture data, appliance data, character data and behavioral data etc..In general,
These data can be one or more keywords.The above-mentioned method for carrying out image recognition to image or video will below
Explanation.
Step 202: the received image data of institute being analyzed and processed, obtains the user's logged in applications client
Attribute tags.
As previously mentioned, in some instances, the 13 received image data of institute of server is obtained after having already passed through image recognition
The data of the text formatting image-related arrived, for example, being the one or more keywords obtained after image recognition.
In other examples, the received image datas of the institute of server 13 are image file or video file, then at this time
Server 13 will carry out image recognition to the received image file of institute or video file first, extract with it is received image-related
Text formatting image data, such as may include furnishings data, furniture data, appliance data, character data and
Behavioral data etc..As previously mentioned, these data can be one or more keywords.It is above-mentioned that figure is carried out to image or video
It will be described later as knowing method for distinguishing.
The data that text formatting image-related is obtained by image recognition or from applications client receive with
After the data of image-related text formatting, server 13 can be the text formatting that index will acquire with the user identifier of user
A part with image-related data as user data save into the data to safeguard the user data of all users
In library.Here, as previously mentioned, the data image-related of text formatting can be one or more keywords, and can
To be divided into different classifications, for example, may include any sort or several in furnishings, furniture, household electrical appliances, personage and behavior
Class.Wherein, furnishings, furniture, household electrical appliances, personage and behavior have corresponded to type belonging to keyword, and under each type,
The descending sequence of the scope according to belonging to information, the information of each keyword may include the information of many levels again.
For example, server 13 receives after applications client sends image file, by image recognition technology from above-mentioned
The article of the indoor placements such as calligraphy and painting, fitness equipment, tea table, sofa can be identified in image file, therefore can extract " word
Picture ", " fitness equipment ", " tea table ", " sofa " this four keywords, and be that index keeps extracting with the user identifier of above-mentioned user
Keyword out.In storage, can also classify preservation, for example " calligraphy and painting ", " fitness equipment " are stored in point of furnishings
Under class, and " tea table ", " sofa " are stored under the classification of furniture.In addition, if can be further by image recognition
Identify that the author of calligraphy and painting perhaps work title or identifies the brand and/or model of fitness equipment, tea table and sofa,
It then can go out keyword according to these information extractions and be stored in database for these keywords as a part of user data
In, and the keyword stored is also with different levels.
Other than the keywords such as indoor furnishings and furniture, image is constantly acquired by picture pick-up device and by terminal
Client device or server 13 in equipment 11 carry out image recognition, can also obtain the character data and behavior number of user
According to.Such as can analyze the kinsfolk for obtaining user and gender, age and the behavioral characteristic of each member etc..
For example, obtained from showing the image acquired as image recognition as live pick up equipment 15 such as the following table 1 some
The example of a part of user data of user.Wherein, user identifier is different from for what the user generated when server 13 is registered
The mark of other users.Based on the user identifier, user can pass through the applications client login service device on terminal device 11
13。
| User identifier | Furnishings | Calligraphy and painting | Leonardo da Vinci's " Mona Lisa Smile " |
| User identifier | Furnishings | Fitness equipment | Fast that treadmill F65 |
| User identifier | Furniture | Tea table | Bright Furniture Stocks Trading Co. |
| User identifier | Furniture | Sofa | Bright Furniture Stocks Trading Co. |
| User identifier | Personage | Old man | Female, 50-70 years old |
| User identifier | Personage | Children | Male, 7-10 years old |
| User identifier | Personage | Pet | Dog, Labrador |
| User identifier | …… | …… | …… |
Table 1
In some instances, the user data itself stored is passed through the data model pre-established and is divided by server 13
Type of Collective and statistical calculation obtain the attribute tags of user.For example, server 13 passes through user data shown in above-mentioned table 1
After the operations such as the classification polymerization of big data model and statistics, " culture " can be obtained, " art work collection ", " body-building ", " supported
The attribute tags such as life " and " pet dog ".
It, can be with above by the obtained data of analysis 15 acquired image of picture pick-up device in some examples of the application
The a part for the user data that only server and/or database are stored can also include that user is daily in user data
The data generated when carrying out various operations on the internet, for example, history viewing record, the historical viewings record, concern of user
Channel and the data of application etc. installed on its terminal device of user.These user data can be used to generate together
The attribute tags of user, so that the attribute tags of user can more precisely embody the characteristic and interest of user.
Step 203: determining push content according to the attribute tags of the user, generate push contents list.
In some instances, the every content saved in the database can also summarize the category of content with attribute tags
Property.The attribute tags of content are usually the keyword relevant to the content that these contents are arranged when launching by publisher, example
It such as, may include related personnel's information such as title, type and author, the publisher of content etc..These attribute tags are usual
It can be used as the mark of the content, commonly used in the classification and retrieval to content.Certainly, the label of content can also be by user
It is constantly added during browsing the content, so that the keyword of content is more abundant and comprehensive.In general, interior
The attribute tags of appearance may be embodied in the title of the content, in interior perhaps brief introduction, can retrieve institute according to the attribute tags
Content is stated, the attribute tags can be any Chinese, English, number, or the mixture of Chinese English digital.In such case
Under, server 13 can be according to the content saved by the attribute tags for analyzing the user that user data obtains from itself
In search out with the matched push content of the user, and generate push contents list.
In the example of the application, it can be searched out from the content that itself is saved and the user by a variety of methods
The push content matched.Specific method will be described below.
Step 204: above-mentioned push contents list is handed down to applications client.
In some examples of the application, the applications client on terminal device 11 is receiving above-mentioned push contents list
Afterwards, it will show that above content pushes list, so that user can therefrom select itself interested content.
In some examples of the application, server 13 user data is analyzed, search for user it is matched in
Hold and generate push contents list during, by the mark using user identifier as the push contents list, with table
The bright push contents list is the push for which user.In this case, server 13 can be according to push content column
User identifier corresponding to table determines the push contents list which applications client be handed down to, particularly as being user's login
Applications client used in server 13.Especially if photographic device 15 and terminal device 11 be not physically same
The case where equipment, when server 13 directly receives image data from photographic device 15, which will be with the user of user
Be identified as mark, server 13 user data is handled and obtain with after the matched push contents list of the user,
The push contents list also will be mark with the user identifier of user.Then, server 13 will be corresponding according to push contents list
User identifier by push contents list be sent to corresponding applications client.
By above technical scheme as can be seen that camera or external photographic device of this method based on terminal device
Acquired image analyzes the characteristic of life data of user, obtains the attribute tags of user, and according to the attribute of user
Label searches for matched content in content library, so as to push content that some users need and suitable to user.
On the one hand the content delivery method can collect user's characteristic of life data, and carry out content according to the characteristic of life of user and push away
It send, so that content push is more accurate, avoids user to find in huge volumes of content and be suitble to the content of oneself and need end
Between end equipment and server it is frequent interaction caused by the wasting of resources, the another aspect above method can continuously into
Row so that the operational model of big data processing is more and more clear, and then is pushed interior by collecting and accumulating user data for a long time
Hold also more and more precisely.
It further, can also be further according to user to the reflection tune of content push in some examples of the application
The content of whole push.Specifically, server 13, which can further record user, shows push content column to terminal device 11
The operation of table generates push efficient data depending on the user's operation, and using the push effective percentage data of generation as number of users
According to a part be stored in the database for safeguarding user data.These push are effective during carrying out content matching
Rate data will be applied to the matching of content in turn, then the content being matched to can be made more accurate.Above-mentioned push is efficient
Data can be the content for some type and the data that are counted, such as specifically can be user and click certain one kind
Number and user that the number of the push content of type, the push content of a certain type are pushed click the push of a certain type
The ratio of number etc. that the number of content and the push content of the type are pushed.
It in some instances, can be preferentially efficient highest from push according to the push effective percentage data of the user
Content is chosen in the content of type generates object content list.For example, server 13 once issues sport category push content to user X
100 times (or referred to as sport category push content shows number for 100), user X to above-mentioned sport category push content click 90 times (or
Person is known as sport category push content hits or effective reading number is that 90), then for user X, sport category pushes the point of content
Hitting and count/issuing several ratio is 0.9, i.e. the push effective percentage of sport category push content is 0.9；In another example 13 Zeng Xiangyong of server
Family X issues amusement class and pushes content 100 times, and user X hits above-mentioned amusement class push content points 5 times, then entertains class push content
Push effective percentage be 0.05；Equally, server 13 once issues finance and economic to user X and pushes content 100 times, and user X is to above-mentioned
Finance and economic pushes content and clicks 5 times, then the push effective percentage of finance and economic push content is 0.05.Server 13 is according to the above sport
The push that class pushes content is efficient, amusement class push content push is efficient and the push of finance and economic push content is efficient
Value can determine user X compare concern sport category push content, to amusement class push content and finance and economic push content not
It pays close attention to very much, so as to correct big data processing model, to reduce the push of amusement class push content and finance and economic push content,
And increase the push of sport category push content.For example, user property label and interior can be carried out preferentially in the content of sport category
The matching of the attribute tags of appearance, to preferentially determine push content in the content of sport category.
Further, the content of above-mentioned push is also and can be not merely directly related with the attribute tags of the user
Content, the common trait and each user group common concern of user group can also be summarized by big data operational model
Content, with derivative more push contents.For example, the regular people that works and rests under normal circumstances also can especially close healthy diet
Note can push some healthy diet class programs or advertisement etc. to they are more.In another example general three mouthfuls/family of four is to trip
The content of trip, child-parent education and parent-offspring's activity etc. can compare concern, can push some tourisms, Qin Zifang to they are more
The program in face or advertisement etc..
Below by specific example in detail according to the determination of the attribute tags of user and the matched push content of user
The method of list.
In the example of the application, firstly, server 13 will be according to the attribute tags of content and the attribute tags of user
It determines the matching degree of user and each content, is then generated and the matched push of user according to the matching degree of user and each content
Contents list.
Fig. 3 shows the method flow of the determination content and user's matching degree described in one example of the application
Figure.As shown in figure 3, method includes the following steps:
It is performed the following operations respectively for each content:
Step 301: obtaining the attribute tags vector of each content.
Here, the corresponding relationship of content and the attribute tags of user can be as follows:
Content ID1:tag1, tag2, tag3 ..., tagM
Content ID2:tag1, tag2, tag3 ..., tagM
Content ID is that the mark, such as title etc. of content are capable of the mark of unique identification above content in above formula, and tag is indicated
The all properties label of user, wherein above-mentioned attribute tags are referred to as keyword.First attribute of tag1 expression user
Label, tag2 indicate second attribute tags of user, and tag3 indicates the third attribute tags of user, and so on, tagM
Indicate the m-th attribute tags of user, M indicates the quantity of whole attribute tags of all users.All include according to a content
There are the attribute tags of which user, can determine that attribute tags vector corresponding with the content, such as content ID1 include
Tag1 and tag3, then attribute tags vector corresponding with content ID1 is (1,0,1,0,0,0 ...).
Step 302: content and the matching degree of user are determined according to the attribute tags vector.
In some examples of the application, it is interior can be defined as this for 1 number in the attribute tags vector of some content
Hold the matching degree with user.Since above-mentioned attribute tags vector can reflect some content and the degree of correlation of user, according to
The attribute tags vector can determine content and the matching degree of user.
It can also be each curriculum offering in some examples of the application in addition to the method for above-mentioned attribute tags vector
One matching degree counter, for recording the matching degree between the content and the attribute tags of user.It in operation, can be by it
Initial value is denoted as zero.During matched, server 13 is by each attribute tags of the user and some content
Attribute tags are compared one by one, and whenever the attribute tags of the user and an attribute tags of the content are identical or phase
When close, the corresponding matching degree counter of the content is added one, until all properties label and the content of the completeer user
Attribute tags.It is above-mentioned identical to refer to that attribute tags are identical on text；It is above-mentioned close to refer to that attribute tags are identical in meaning.
For example, the attribute tags of user are " South Korean TV soaps ", the attribute tags of candidate's push content are also " South Korean TV soaps ", then it is assumed that the two is identical.
In another example the attribute tags of user are " South Korean TV soaps fan ", and the attribute tags of candidate push content are " South Korean TV soaps fan ", and the two is in text
On it is not fully identical, it is but essentially identical in meaning, then it is assumed that the two is close.After attribute tags whole is completeer,
The numerical value of the matching degree counter is the matching degree of the user Yu the content.
The matching degree that server 13 passes through above-mentioned a variety of the method available users and all the elements.Below according to
The matching degree of family and each content produces push contents list.
In some examples of the application, server 13 takes according to the matching degree of the obtained user and all the elements
The highest N number of content of matching degree generates push contents list, also i.e. by the highest N number of content of matching degree as push content
Push contents list is added in mark.Wherein, N is preset natural number, for the content that can be pushed in push contents list
Maximum quantity.Certainly, if the quantity of content of the matching degree greater than zero is less than N, it is big that server can only push matching degree
In zero content (such as n content), or be again zero from matching degree content in select the content of difference quantity (N-n).
At this point, the mode of selection can be preset, such as randomly choose or selected according to browsing time etc..
In other examples of the application, after the matching degree of user and content has been determined, server 13 can be with
The corresponding matching degree of all the elements is compared with predetermined threshold value, the threshold value will be greater than or equal to matching degree
The mark of content is added in push contents list.
Identification server through the above can uniquely determine a certain content.
In some examples of the application, the sequence of push content listed in contents list is pushed, it can also basis
The content and the matching degree of user are arranged, for example, sorting from large to small according to matching degree.
The method that image recognition is carried out by specific example in detail applications client or server 13 again below.
Specific method can be as shown in Figure 4, comprising:
Step 401: the image file being split, each component part is obtained.
Wherein, decision process is considered as to the segmentation of the image file, decomposited from object view image object and it
Component part, component part are made of picture element again.The algorithm of decision can be divided into two class of picture point technology and regional development and technology.Picture point
Technology is to be classified with threshold method to each picture point, such as found out in character image by the comparison of picture point gray scale and threshold value
Stroke.Regional development and technology is to utilize Feature detections boundary, lines, the regions such as texture, some areas grey-scale contrast etc., and use area
The technologies such as domain growth, merging, decomposition find out each component part of image.
Step 402: each component part being identified, determines the corresponding object of each component part.
When being identified to each component part, for each component part, according to the shape and ash of the component part
Degree information classifies to the structure of the component part, identifies the corresponding object of the component part according to the result of classification；Or
The component part and pre-set object model are matched each component part by person, are known according to matched result
The not corresponding object of the component part.
Step 403: each object being explained, pass of the respective keyword of each object as the image file is obtained
Keyword.
When being explained to each object, can be established with heuristic or human-computer interaction technology combination recognition methods
The hierarchy construction of object view illustrates there is what object in object view, and there are what relationships between object.The three-dimensional object view the case where
Under, it can use the knowledge for the restricting relation that each object is mutual in the various Given informations and object view of object view.For example, from two
Shades of gray, texture variations, surface profile wire shaped etc. in dimension image are inferred to the surface trend of three-dimensional object view；It can also basis
Distance measurement information, or from the calculating of the two dimensional image of the several different angles progress depth of field, obtain describing and explaining for three-dimensional object view.
By the processing of above-mentioned segmentation, identification and explanation, the keyword namely attribute of each image file can be extracted
Label, and all attribute tags can be stored according to format shown in table 1.
It should be noted that the method for the determination method and image recognition of above content and user's matching degree is only one
Citing, the application can also be using other matching process and image-recognizing method without exceeding scope of the present application.
The example of the application additionally provides a kind of content delivery method.The content that Fig. 5 shows present application example offer pushes away
The flow chart of delivery method.As shown in figure 5, this method can be executed by terminal device 11, comprising the following steps:
Step 501: collecting image data.
In some instances, with terminal device 11 intelligence it is higher and higher, including camera etc. including outside set
Standby or to become the standard configuration of terminal device 11, therefore, in user's using terminal equipment 11 when browsing content, terminal is set
Standby 11 can collect image data related with user by external equipment.Wherein, as previously mentioned, above-mentioned image data can
To be the image or video of picture format.After above-mentioned image data can also be image or video the progress image recognition to acquisition
Obtained text data image-related, such as the keyword of image etc..
Further, applications client further can also report other kinds of user data to server 13, for example,
Applications client can obtain the process that user states application software in use by the application software that terminal device 11 is installed
The data of middle generation, for example obtain by wechat that user browses the record data of article or the related of the public platform of concern is believed
It ceases, or obtains the historical record data etc. of user's viewing media by Tencent's video.
Step 502: described image data being sent to server 13, to allow to carry out data to the user data
Processing to obtain the attribute tags of the user, and determines the push content for being directed to the user according to the attribute tags of user
List.
Step 503: receiving the push contents list that server 13 issues and be shown for selection by the user.
Mark comprising one or more contents in above-mentioned push contents list.The mark of some content when the user clicks
Afterwards, applications client will request the content to server 13, and the mark of content is carried in the request.Server 13 is receiving request
Afterwards, according to the mark of the content wherein carried, the storage address of the content, such as uniform resource locator are obtained from database
(URL), applications client and by storage address is fed back to, corresponding content is obtained according to the storage address by applications client.
By above technical scheme as can be seen that user of this method based on user data it is required and concern content to
User pushes content that some users need and suitable.On the one hand the content delivery method can make content push more
Precisely, user is avoided to need between terminal device and server to be suitble to the content of oneself in searching in huge volumes of content
The frequently wasting of resources caused by interaction, on the other hand by collecting and accumulating user data for a long time, so that the fortune of big data processing
Calculation model is more and more clear, and then the content pushed is also more and more accurate.
The method of the corresponding above content push, present invention also provides the content push servers 600 for realizing the above method.
In some examples of the application, the server 600 of above-mentioned realization content delivery method can structure as shown in Figure 6
Figure is realized, including receiving module 601, acquisition module 602 and determining module 603, the function of each module are as follows:
Receiving module 601, for receiving the image data of applications client transmission, wherein above-mentioned image data is by applying
The image and video that client is shot according to photographic device connected to it determine；
Module 602 is obtained, for carrying out data processing to the user data, acquisition logs in the applications client
User attribute tags；And
Determining module 603, for determining push contents list according to the attribute tags of the user；
Sending module 604, for that will push contents list and be handed down to applications client.
In some instances, above-mentioned acquisition module 602 can the structure chart as shown in Fig. 6 A realize, including recognition unit
6021, storage unit 6022 and acquiring unit 6023, the function of each unit are as follows:
Recognition unit 6021, the image data for the picture format to user carry out image recognition, obtain text formatting
Image data；
Storage unit 6022, for using the user identifier of user be the image data of text formatting that will acquire of index as
A part of user data is saved into database；And
The user data saved in the database is passed through the data model pre-established and is divided by acquiring unit 6023
Type of Collective and statistical calculation obtain the attribute tags of the user.
In some instances, above-mentioned determining module 603 can the structure chart as shown in Fig. 6 B realize, including matching degree determine it is single
Member 6031 and push contents list generation unit 6032.The function of each unit is as follows:
Matching degree determination unit 6031, for true according to the attribute tags of the user and the attribute tags of any content
The matching degree of the fixed content and the user；And
Contents list generation unit 6032 is pushed, for generating in push according to the matching degree of the content and the user
Hold list.
Above-mentioned matching degree determination unit 6031 can be used method above-mentioned and determine content and the matching degree of user.
In some instances, the push contents list generation unit 6032 can be to of all the elements and the user
It is ranked up with degree；It is pushed being added in described all the elements with the mark of the highest N number of push content of user's matching degree
In contents list；Wherein, N is preset natural number.
In some instances, the push contents list generation unit 6032 can be by of all the elements and the user
It is compared with degree with predetermined threshold value, the mark that matching degree is greater than or equal to the content of the threshold value is added in push
Hold in list.
In some examples of the application, above-mentioned receiving module can also be further used for according to user for the push
The operation of contents list, which generates, pushes efficient data；At this point, above-mentioned server 600 of stating may further include: storage unit,
For storing using the efficient data of the push as a part of user data into database.
Fig. 7 shows the composite structural diagram of the calculating equipment 700 where content push server 600.As shown in fig. 7, should
Calculating equipment includes one or more processor (CPU) 702, communication module 704, memory 706, user interface 710, and
For interconnecting the communication bus 708 of these components.
Processor 702 can send and receive data by communication module 704 to realize network communication and/or local communication.
User interface 710 includes one or more output equipments 712 comprising one or more speakers and/or one
Or multiple visual displays.User interface 710 also includes one or more input equipments 714 comprising such as, keyboard, mouse
Mark, voice command input unit or loudspeaker, touch screen displays, touch sensitive tablet, posture capture camera or other inputs are pressed
Button or control etc..
Memory 706 can be high-speed random access memory, such as DRAM, SRAM, DDR RAM or other deposit at random
Take solid storage device；Or nonvolatile memory, such as one or more disk storage equipments, optical disc memory apparatus, sudden strain of a muscle
Deposit equipment or other non-volatile solid-state memory devices.
The executable instruction set of 706 storage processor 702 of memory, comprising:
Operating system 716, including the program for handling various basic system services and for executing hardware dependent tasks；
Using 718, including the various application programs for content push, this application program can be realized above-mentioned each example
In process flow, for example may include unit some or all of in content push server 600 shown in fig. 6.Each unit
Or at least one module in module 601-603 can store machine-executable instruction.Processor 702 is by executing memory
Machine-executable instruction in 706 in each module 601-603 at least one module, and then can be realized above-mentioned each module 601-
The function of at least one module in 603.
It should be noted that step and module not all in above-mentioned each process and each structure chart be all it is necessary, can
To ignore certain steps or module according to the actual needs.Each step execution sequence be not it is fixed, can according to need into
Row adjustment.The division of each module is intended merely to facilitate the division functionally that description uses, and in actual implementation, a module can
It is realized with point by multiple modules, the function of multiple modules can also be realized by the same module, these modules can be located at same
In a equipment, it can also be located in different equipment.
Hardware module in each embodiment can in hardware or hardware platform adds the mode of software to realize.Above-mentioned software
Including machine readable instructions, it is stored in non-volatile memory medium.Therefore, each embodiment can also be presented as software product.
Therefore, some examples of the application additionally provide a kind of computer readable storage medium, are stored thereon with computer
Instruction, wherein the computer instruction realizes the step of any figure the method in above-mentioned Fig. 2-7 when being executed by processor.
In each example, hardware can be by special hardware or the hardware realization of execution machine readable instructions.For example, hardware can be with
Permanent circuit or logical device (such as application specific processor, such as FPGA or ASIC) specially to design are used to complete specifically to grasp
Make.Hardware also may include programmable logic device or circuit by software provisional configuration (as included general processor or other
Programmable processor) for executing specific operation.
In addition, each example of the application can pass through the data processor by data processing equipment such as computer execution
To realize.Obviously, data processor constitutes the application.In addition, being commonly stored data processing in one storage medium
Program is by directly reading out storage medium or the storage by program being installed or being copied to data processing equipment for program
It is executed in equipment (such as hard disk and/or memory).Therefore, such storage medium also constitutes the application, and present invention also provides one
Kind non-volatile memory medium, wherein being stored with data processor, this data processor can be used for executing in the application
State any one of method example example.
The corresponding machine readable instructions of module in Fig. 6 can be such that operating system operated on computer etc. completes here
The some or all of operation of description.Non-volatile computer readable storage medium storing program for executing can be in the expansion board in insertion computer
In set memory or write the memory being arranged in the expanding element being connected to a computer.Be mounted on expansion board or
CPU on person's expanding element etc. can be according to instruction execution part and whole practical operations.
It, can also be in addition, the device and each module in each example of the application can integrate in one processing unit
It is that modules physically exist alone, can also be integrated in one unit with two or more devices or module.Above-mentioned collection
At unit both can take the form of hardware realization, can also realize in the form of software functional units.
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, all in essence of the invention
Within mind and principle, any modification, equivalent substitution, improvement and etc. done be should be included within the scope of the present invention.
Claims (9)
1. a kind of content delivery method, wherein the described method includes:
Receive the image data related with characteristic of life that applications client is sent, wherein the figure related with characteristic of life
The image related with characteristic of life and/or view shot by the applications client according to photographic device connected to it as data
Frequency determines that the image data related with characteristic of life includes the gender of kinsfolk, the row at age and mirror life rule
For data；
Data processing is carried out to the image data related with characteristic of life and obtains the use logged in the applications client
The attribute tags at family；
Push contents list is generated according to the attribute tags；And
The push contents list is handed down to the applications client,
The push effective percentage data of the user are generated for the operation of the push contents list according to user；And
It stores using the efficient data of the push as a part of the user data of the user into database, to push
The matching of the attribute tags of the user property label and content is carried out in the content of efficient highest type, and is pushed away from described
It send and determines push content in the content of efficient highest type；
Wherein, described that data processing acquisition is carried out in the applications client to the image data related with characteristic of life
The attribute tags of the user of login include:
Image recognition is carried out to the image data related with characteristic of life, obtains the picture number related with characteristic of life
According to one or more keywords；
It is to index the one or more of keywords that will acquire as reflection user's characteristic of life using the user identifier of user
A part of user data is saved into database；And
The user data of the reflection user's characteristic of life saved in the database is passed through to the data model pre-established to carry out
Classification polymerization and statistical calculation, obtain the attribute tags of the user.
It is described to generate push contents list according to the attribute tags and include: 2. according to the method described in claim 1, wherein
The matching degree of content Yu the user is determined according to the attribute tags of the attribute tags and any content；And
Push contents list is generated according to content and the matching degree of the user.
3. according to the method described in claim 2, wherein, the determining content and the matching degree of the user include:
It is performed the following operations respectively for each candidate's push content of candidate push contents list:
One matching degree counter of curriculum offering is pushed for each candidate, and its initial value is denoted as zero；
Each attribute tags of the user are compared with each attribute tags of the candidate push content, work as institute
When one attribute tags of an attribute tags and the candidate push content for stating user are same or similar, the candidate is pushed away
The matching degree counter of content is sent to add 1, until all properties label of the completeer user and the candidate push content
All properties label；And
Using the numerical value of the matching degree counter of the candidate push content as of candidate the push content and the user
With degree.
4. according to the method described in claim 2, wherein, the determining content and the matching degree of the user include:
It is performed the following operations respectively for each object content of object content list:
Obtain the attribute tags vector of each content, wherein the attribute tags vector is for reflecting that content is included described
The attribute tags of user；And
The matching degree of content Yu the user is determined according to the attribute tags vector.
5. according to the method described in claim 2, wherein, generating push contents list according to content and the matching degree of the user
Include:
All the elements and the matching degree of the user are ranked up；
The mark of all the elements and the highest N number of content of user's matching degree is added in the push contents list；Wherein,
N is preset natural number.
6. according to the method described in claim 2, wherein, generating push contents list according to content and the matching degree of the user
Include:
All the elements are compared with the matching degree of the user with predetermined threshold value, the matching degree is greater than or is waited
It is added in the push contents list in the mark of the content of the threshold value.
7. a kind of content push server, wherein the server includes:
Receiving module, for receiving the image data related with characteristic of life of applications client transmission, wherein described and life
The related image data of feature is shot by the applications client according to photographic device connected to it related with characteristic of life
Image and/or video determine, the image data related with characteristic of life includes gender, age and the reflection of kinsfolk
The behavioral data of rule of life；
Module is obtained, is obtained for carrying out data processing to the image data related with characteristic of life in the application client
The attribute tags of the user logged on end；
Determining module, for generating push contents list according to the attribute tags of the user；And
Sending module, for that will push contents list and be handed down to applications client,
The receiving module is further used for generating pushing away for the user for the operation of the push contents list according to user
Send efficient data；And
The server further comprises: storage unit, for pushing efficient data as one of user data for described
It point stores into database, to carry out the user property label and content in the content of the efficient highest type of push
The matching of attribute tags, and push content is determined from the content of the efficient highest type of the push；
Wherein, the acquisition module includes:
Recognition unit obtains described special with life for carrying out image recognition to the image data related with characteristic of life
Levy one or more keywords of related image data；
The storage unit, for being to index the one or more of keywords that will acquire as instead using the user identifier of user
The a part for reflecting the user data of user's characteristic of life is saved into database；And
The user data of the reflection user's characteristic of life saved in the database is passed through the data pre-established by acquiring unit
Model carries out classification polymerization and statistical calculation, obtains the attribute tags of the user.
8. server according to claim 7, wherein the determining module includes:
Matching degree determination unit, for according to the attribute tags of the user and the attribute tags of any content determine content with
The matching degree of the user；And
Contents list generation unit is pushed, generates push contents list for the matching degree according to content and the user.
9. a kind of computer readable storage medium, is stored thereon with computer instruction, wherein the computer instruction is by processor
The step of any one of claims 1 to 6 the method is realized when execution.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710480351.0A CN107295361B (en) | 2017-06-22 | 2017-06-22 | A kind of content delivery method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710480351.0A CN107295361B (en) | 2017-06-22 | 2017-06-22 | A kind of content delivery method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN107295361A CN107295361A (en) | 2017-10-24 |
| CN107295361B true CN107295361B (en) | 2019-07-19 |
Family
ID=60097410
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710480351.0A Active CN107295361B (en) | 2017-06-22 | 2017-06-22 | A kind of content delivery method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107295361B (en) |
Families Citing this family (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107959865A (en) * | 2017-11-14 | 2018-04-24 | 广州虎牙信息科技有限公司 | Main broadcaster's method for pushing, device and computer equipment |
| CN107948743A (en) * | 2017-11-29 | 2018-04-20 | 腾讯科技（深圳）有限公司 | Video pushing method and its device, storage medium |
| CN109522493A (en) * | 2018-09-04 | 2019-03-26 | 西安艾润物联网技术服务有限责任公司 | Information-pushing method and Related product |
| CN109522426B (en) * | 2018-12-05 | 2021-06-22 | 北京达佳互联信息技术有限公司 | Multimedia data recommendation method, device, equipment and computer readable storage medium |
| CN109688458A (en) * | 2019-01-14 | 2019-04-26 | 四川长虹电器股份有限公司 | The implementation method of smart television cloud desktop operation system based on big data algorithm |
| CN110046940A (en) * | 2019-04-22 | 2019-07-23 | 福建工程学院 | A kind of Ads on Vehicles personalized push method and device |
| CN111143611B (en) * | 2019-12-31 | 2024-01-16 | 新疆联海创智信息科技有限公司 | Information acquisition method and device |
| CN111866528A (en) * | 2020-04-30 | 2020-10-30 | 火币（广州）区块链科技有限公司 | Live program pushing method and readable storage medium |
| CN111726649B (en) * | 2020-06-28 | 2021-12-28 | 百度在线网络技术（北京）有限公司 | Video stream processing method, device, computer equipment and medium |
| CN112632370A (en) * | 2020-12-08 | 2021-04-09 | 青岛海尔科技有限公司 | Method, device and equipment for article pushing |
| CN113254419B (en) * | 2021-01-19 | 2022-05-03 | 深圳市神州通在线科技有限公司 | Internet of things cloud platform management system and method based on big data micro-service |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103618918A (en) * | 2013-11-27 | 2014-03-05 | 青岛海信电器股份有限公司 | Method and device for controlling display of smart television |
| CN103634617A (en) * | 2013-11-26 | 2014-03-12 | 乐视致新电子科技（天津）有限公司 | Video recommending method and device in intelligent television |
| CN104202718A (en) * | 2014-08-05 | 2014-12-10 | 百度在线网络技术（北京）有限公司 | Method and device for providing information for user |
| CN104853230A (en) * | 2015-05-14 | 2015-08-19 | 无锡天脉聚源传媒科技有限公司 | Hot-spot video push method and apparatus |
| CN105872790A (en) * | 2015-12-02 | 2016-08-17 | 乐视网信息技术（北京）股份有限公司 | Method and system for recommending audio/video program |
| CN105898576A (en) * | 2016-06-17 | 2016-08-24 | 青岛海信传媒网络技术有限公司 | Data recommending method based on television application, and data server |
Family Cites Families (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101094335B (en) * | 2006-06-20 | 2010-10-13 | 株式会社日立制作所 | TV program recommender and method thereof |
| CN100471262C (en) * | 2006-12-30 | 2009-03-18 | 上海文广互动电视有限公司 | Contents supply system and method of network TV. |
| JP5322550B2 (en) * | 2008-09-18 | 2013-10-23 | 三菱電機株式会社 | Program recommendation device |
| CN101998161A (en) * | 2009-08-14 | 2011-03-30 | Tcl集团股份有限公司 | Face recognition-based television program watching method |
| US8966376B2 (en) * | 2010-12-10 | 2015-02-24 | Wyse Technology L.L.C. | Methods and systems for remote desktop session redrawing via HTTP headers |
| CN103024464B (en) * | 2011-12-31 | 2016-03-30 | 中国科学院计算技术研究所 | System and method with video-frequency playing content relevant information is provided |
| CN103428539B (en) * | 2012-05-15 | 2017-08-22 | 腾讯科技（深圳）有限公司 | The dissemination method and device of a kind of pushed information |
| CN102957743A (en) * | 2012-10-18 | 2013-03-06 | 北京天宇朗通通信设备股份有限公司 | Data pushing method and device |
| CN102984219B (en) * | 2012-11-13 | 2015-09-09 | 浙江大学 | A kind of travel mobile terminal information-pushing method of expressing based on media multi-dimensional content |
| CN103164518A (en) * | 2013-03-06 | 2013-06-19 | 杭州九树网络科技有限公司 | Mobile terminal (MT) augmented reality application system and method |
| CN103577516A (en) * | 2013-07-01 | 2014-02-12 | 北京百纳威尔科技有限公司 | Method and device for displaying contents |
| CN103716702A (en) * | 2013-12-17 | 2014-04-09 | 三星电子（中国）研发中心 | Television program recommendation device and method |
| CN104010220B (en) * | 2014-04-30 | 2017-07-14 | 小米科技有限责任公司 | Content service provides method and apparatus |
| CN104268187B (en) * | 2014-09-17 | 2016-09-28 | 合一网络技术(北京)有限公司 | The online content optimum decision system of the many scenes of support based on user feedback |
| CN104301758A (en) * | 2014-10-10 | 2015-01-21 | 安徽华米信息科技有限公司 | Method, device and system for pushing videos |
| CN104394471A (en) * | 2014-11-19 | 2015-03-04 | 四川长虹电器股份有限公司 | Method for intelligently recommending favorite program to user |
| US10097896B2 (en) * | 2015-12-01 | 2018-10-09 | DISH Technologies L.L.C. | Recommend future video recordings for users from audiovisual content |
-
2017
- 2017-06-22 CN CN201710480351.0A patent/CN107295361B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103634617A (en) * | 2013-11-26 | 2014-03-12 | 乐视致新电子科技（天津）有限公司 | Video recommending method and device in intelligent television |
| CN103618918A (en) * | 2013-11-27 | 2014-03-05 | 青岛海信电器股份有限公司 | Method and device for controlling display of smart television |
| CN104202718A (en) * | 2014-08-05 | 2014-12-10 | 百度在线网络技术（北京）有限公司 | Method and device for providing information for user |
| CN104853230A (en) * | 2015-05-14 | 2015-08-19 | 无锡天脉聚源传媒科技有限公司 | Hot-spot video push method and apparatus |
| CN105872790A (en) * | 2015-12-02 | 2016-08-17 | 乐视网信息技术（北京）股份有限公司 | Method and system for recommending audio/video program |
| CN105898576A (en) * | 2016-06-17 | 2016-08-24 | 青岛海信传媒网络技术有限公司 | Data recommending method based on television application, and data server |
Also Published As
| Publication number | Publication date |
|---|---|
| CN107295361A (en) | 2017-10-24 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107295361B (en) | A kind of content delivery method | |
| US11238066B2 (en) | Generating personalized clusters of multimedia content elements based on user interests | |
| US10832738B2 (en) | Computerized system and method for automatically generating high-quality digital content thumbnails from digital video | |
| US20200273063A1 (en) | Dynamic campaign analytics via hashtag detection | |
| CN108028962B (en) | Processing video usage information to deliver advertisements | |
| US9442933B2 (en) | Identification of segments within audio, video, and multimedia items | |
| CN106326391B (en) | Multimedia resource recommendation method and device | |
| CN109388760B (en) | Recommendation label obtaining method, media content recommendation method, device and storage medium | |
| CN107894998B (en) | Video recommendation method and device | |
| CN109086439A (en) | Information recommendation method and device | |
| US11120093B1 (en) | System and method for providing a content item based on computer vision processing of images | |
| CN103885951A (en) | Graphics and text information releasing and generating method and graphics and text information releasing and generating device | |
| CN105847985A (en) | Video recommendation method and device | |
| CN104144181B (en) | A kind of Video Terminal polymerization and system | |
| CN104899306B (en) | Information processing method, information display method and device | |
| Mei et al. | ImageSense: Towards contextual image advertising | |
| US9449231B2 (en) | Computerized systems and methods for generating models for identifying thumbnail images to promote videos | |
| US11423096B2 (en) | Method and apparatus for outputting information | |
| CN108959323B (en) | Video classification method and device | |
| CN101668176A (en) | Multimedia content-on-demand and sharing method based on social interaction graph | |
| US20170185690A1 (en) | System and method for providing content recommendations based on personalized multimedia content element clusters | |
| Zhou et al. | An intelligent video tag recommendation method for improving video popularity in mobile computing environment | |
| CN114845149B (en) | Video clip method, video recommendation method, device, equipment and medium | |
| CN106980662A (en) | Based on magnanimity across the user tag sorting technique for shielding viewing behavior data | |
| CN107105030A (en) | Promotional content method for pushing 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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |