CN109389182A - Method and apparatus for generating information - Google Patents
Method and apparatus for generating information Download PDFInfo
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- CN109389182A CN109389182A CN201811289807.6A CN201811289807A CN109389182A CN 109389182 A CN109389182 A CN 109389182A CN 201811289807 A CN201811289807 A CN 201811289807A CN 109389182 A CN109389182 A CN 109389182A
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- Prior art keywords
- interest
- information
- current information
- target user
- recognition result
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
- G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/50—Network services
- H04L67/55—Push-based network services
Abstract
The embodiment of the present application discloses the method and apparatus for generating information.One specific embodiment of this method includes: to obtain corresponding to target user in current information, wherein corresponding to target user in current information be target user using terminal perform predetermined registration operation in current information；By the acquired interest identification model trained in advance in current information input, obtain recognition result, wherein, interest identification model corresponds at least two default category of interest, and recognition result is used to indicate at least two default category of interest and is inputted the default category of interest to match in current information；Based on recognition result obtained, the user tag of target user is generated, wherein user tag is used to indicate the category of interest of target user.This embodiment improves diversity and accuracy that information generates.
Description
Technical field
The invention relates to field of computer technology, more particularly, to generate the method and apparatus of information.
Background technique
Currently, with the development of science and technology, the electronic equipments such as mobile phone, computer browsing news, wide has can be used in people
Announcement etc. is in current information.It may include multiple types in current information according to the difference of the information content in practice, for example including
Automotive-type is in current information, financial class in current information, health class in current information etc..In general, different users may be to not
Same type is in that current information is interested.
Summary of the invention
The embodiment of the present application proposes the method and apparatus for generating information.
In a first aspect, the embodiment of the present application provides a kind of method for generating information, this method comprises: obtaining target
It is in current information corresponding to user, wherein utilize terminal to execute for target user in current information corresponding to target user
Predetermined registration operation is in current information；By the acquired interest identification model trained in advance in current information input, known
Other result, wherein the corresponding at least two default category of interest of interest identification model, it is default that recognition result is used to indicate at least two
In category of interest with inputted the default category of interest to match in current information；Based on recognition result obtained, generate
The user tag of target user, wherein user tag is used to indicate the category of interest of target user.
In some embodiments, interest identification model includes that at least two interest identify submodel, and at least two interest are known
Interest identification submodel in small pin for the case model is corresponding with the default category of interest at least two default category of interest.
In some embodiments, by the acquired interest identification model trained in advance in current information input, known
Other result, comprising: acquired is separately input into few two interest identification submodel in current information, obtains recognition result.
In some embodiments, interest identification model further includes Feature Selection Model, Feature Selection Model and at least two
Interest identifies submodel connection；And by the acquired interest identification model trained in advance in current information input, known
Other result, comprising: by acquired in current information input Feature Selection Model, obtain special in information corresponding to current information
Sign；Information characteristics obtained are inputted at least two interest identification submodel being connected with Feature Selection Model respectively, are obtained
Obtain recognition result.
In some embodiments, interest identification model is obtained by following steps training: obtaining training sample set, wherein
Training sample includes that sample is in current information and the specimen discerning marked in advance as a result, specimen discerning result is used to indicate in advance really
The default category of interest to match with sample in current information in the default category of interest of fixed at least two；Utilize machine learning side
The sample inputted, as input, is in current in current information by method, the sample for including using the training sample that training sample is concentrated
Specimen discerning result corresponding to information obtains interest identification model as desired output, training.
In some embodiments, after the user tag for generating target user, this method further include: obtain letter to be presented
Breath set；The information input interest identification model to be presented is somebody's turn to do by the information to be presented in information aggregate to be presented
Recognition result corresponding to information to be presented；Based on recognition result obtained, chosen from information aggregate to be presented to be presented
Information is in current information as the target of target user is given for rendering, wherein target is in identification knot corresponding to current information
Default category of interest indicated by fruit is identical as category of interest indicated by the user tag of target user.
It in some embodiments, is in the current information corresponding informance page corresponding to target user, corresponding to target user
In current information for target user click, with present clicked be in current information corresponding to information page.
In some embodiments, predetermined registration operation includes clicking operation.
Second aspect, the embodiment of the present application provide a kind of for generating the device of information, which includes: the first acquisition
Unit is configured to obtain corresponding to target user in current information, wherein be in current information corresponding to target user
Target user using terminal perform predetermined registration operation in current information；First input unit, be configured to be in by acquired
The interest identification model that current information input is trained in advance obtains recognition result, wherein interest identification model corresponding at least two
Default category of interest, recognition result, which is used to indicate at least two default category of interest, to match with what is inputted in current information
Default category of interest；Label generation unit is configured to generate user's mark of target user based on recognition result obtained
Label, wherein user tag is used to indicate the category of interest of target user.
In some embodiments, interest identification model includes that at least two interest identify submodel, and at least two interest are known
Interest identification submodel in small pin for the case model is corresponding with the default category of interest at least two default category of interest, for true
Whether that determines to be inputted matches in current information with corresponding default category of interest.
In some embodiments, the first input unit is further configured to: by it is acquired distinguish in current information it is defeated
Enter at least two interest identification submodel, obtains recognition result.
In some embodiments, interest identification model further includes Feature Selection Model, Feature Selection Model and at least two
Interest identifies submodel connection；And first input unit include: the first input module, be configured to acquired in current
Information input Feature Selection Model is obtained in information characteristics corresponding to current information；Second input module is configured to institute
The information characteristics of acquisition input at least two interest identification submodel being connected with Feature Selection Model respectively, obtain identification knot
Fruit.
In some embodiments, interest identification model is obtained by following steps training: obtaining training sample set, wherein
Training sample includes that sample is in current information and the specimen discerning marked in advance as a result, specimen discerning result is used to indicate in advance really
The default category of interest to match with sample in current information in the default category of interest of fixed at least two；Utilize machine learning side
The sample inputted, as input, is in current in current information by method, the sample for including using the training sample that training sample is concentrated
Specimen discerning result corresponding to information obtains interest identification model as desired output, training.
In some embodiments, device further include: second acquisition unit is configured to obtain information aggregate to be presented；
Second input unit is configured to for the information to be presented in information aggregate to be presented, by the information input interest to be presented
Identification model obtains recognition result corresponding to the information to be presented；Information extracting unit is configured to based on knowledge obtained
Not as a result, choosing information to be presented from information aggregate to be presented as rendering to the target of target user in current letter
Breath, wherein target is marked in the user of default category of interest indicated by recognition result corresponding to current information and target user
The indicated category of interest of label is identical.
It in some embodiments, is in the current information corresponding informance page corresponding to target user, corresponding to target user
In current information for target user click, with present clicked be in current information corresponding to information page.
In some embodiments, predetermined registration operation includes clicking operation.
The third aspect, the embodiment of the present application provide a kind of server, comprising: one or more processors；Storage device,
One or more programs are stored thereon with, when one or more programs are executed by one or more processors, so that one or more
The method that a processor realizes any embodiment in the above-mentioned method for generating information.
Fourth aspect, the embodiment of the present application provide a kind of computer-readable medium, are stored thereon with computer program, should
The method of any embodiment in the above-mentioned method for generating information is realized when program is executed by processor.
Method and apparatus provided by the embodiments of the present application for generating information, by being in corresponding to acquisition target user
Current information obtains recognition result, finally then by the acquired interest identification model trained in advance in current information input
Based on recognition result obtained, the user tag of target user is generated, wherein user tag is used to indicate the emerging of target user
Interesting classification identifies the category of interest of target user to efficiently use corresponding to target user in current information,
The user tag for generating target user improves the diversity of information generation, facilitates the subsequent interest based on target user
Classification executes corresponding operating (such as the interested information of target user is presented to target user) to target user；Also, benefit
The accuracy of information generation can be improved in the user tag that target user is generated with interest identification model.
Detailed description of the invention
By reading a detailed description of non-restrictive embodiments in the light of the attached drawings below, the application's is other
Feature, objects and advantages will become more apparent upon:
Fig. 1 is that one embodiment of the application can be applied to exemplary system architecture figure therein；
Fig. 2 is the flow chart according to one embodiment of the method for generating information of the application；
Fig. 3 is the schematic diagram according to an application scenarios of the method for generating information of the embodiment of the present application；
Fig. 4 is the flow chart according to another embodiment of the method for generating information of the application；
Fig. 5 is the structural schematic diagram according to one embodiment of the device for generating information of the application；
Fig. 6 is adapted for the structural schematic diagram for the computer system for realizing the server of the embodiment of the present application.
Specific 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
Convenient for description, part relevant to related invention is illustrated only in attached drawing.
It should be noted that in the absence of conflict, the features in the embodiments and the embodiments of the present application can phase
Mutually combination.The application is described in detail below with reference to the accompanying drawings and in conjunction with the embodiments.
Fig. 1 is shown can be using the method for generating information of the application or the implementation of the device for generating information
The exemplary system architecture 100 of example.
As shown in Figure 1, system architecture 100 may include terminal device 101,102,103, network 104 and server 105.
Network 104 between terminal device 101,102,103 and server 105 to provide the medium of communication link.Network 104 can be with
Including various connection types, such as wired, wireless communication link or fiber optic cables etc..
User can be used terminal device 101,102,103 and be interacted by network 104 with server 105, to receive or send out
Send message etc..Various telecommunication customer end applications can be installed, such as web browser is answered on terminal device 101,102,103
With, shopping class application, searching class application, instant messaging tools, mailbox client, social platform software etc..
Terminal device 101,102,103 can be hardware, be also possible to software.When terminal device 101,102,103 is hard
When part, the various electronic equipments of information transmission, including but not limited to smart phone, plate are can be with display screen and supported
Computer, E-book reader, MP3 player (Moving Picture Experts Group Audio Layer III, dynamic
Image expert's compression standard audio level 3), MP4 (Moving Picture Experts Group Audio Layer IV, move
State image expert's compression standard audio level 4) player, pocket computer on knee and desktop computer etc..When terminal is set
Standby 101,102,103 when being software, may be mounted in above-mentioned cited electronic equipment.Its may be implemented into multiple softwares or
Software module (such as providing multiple softwares of Distributed Services or software module), also may be implemented into single software or soft
Part module.It is not specifically limited herein.
Server 105 can be to provide the server of various services, such as to showing on terminal device 101,102,103
The background server supported is provided in current information.Corresponding to the target user of the available using terminal equipment of background server
Be in current information, and analyze etc. processing in data such as current information to getting, acquisition processing result (such as target
The user tag of user).
It should be noted that the method provided by the embodiment of the present application for generating information is generally held by server 105
Row, the device for being respectively used for generating information are generally positioned in server 105.
It should be noted that server can be hardware, it is also possible to software.When server is hardware, may be implemented
At the distributed server cluster that multiple servers form, individual server also may be implemented into.It, can when server is software
It, can also be with to be implemented as multiple softwares or software module (such as providing multiple softwares of Distributed Services or software module)
It is implemented as single software or software module.It is not specifically limited herein.
It should be understood that the number of terminal device, network and server in Fig. 1 is only schematical.According to realization need
It wants, can have any number of terminal device, network and server.In the user tag during institute for generating target user
The data used do not need in the case where long-range obtain, and above system framework can not include network and terminal device, and only
Including server.
With continued reference to Fig. 2, the process of one embodiment of the method for generating information according to the application is shown
200.The method for being used to generate information, comprising the following steps:
Step 201, obtain is in current information corresponding to target user.
In the present embodiment, can lead to for generating the executing subject (such as server shown in FIG. 1) of the method for information
It crosses wired connection mode or radio connection obtains corresponding to target user in current information.Wherein, target user is
The user of user tag to be determined corresponding to it.User tag corresponding to target user can be used for characterizing target user's
Category of interest.The presentation of predetermined registration operation is performed to it using terminal for target user in current information corresponding to target user
Use information.In current information be it is predetermined, for rendering give user information, can include but is not limited to following at least one
: text, numerical value, symbol, image, video, link.Predetermined registration operation can be the predetermined various operations of technical staff, example
Such as browse operation.
In some optional implementations of the present embodiment, letter can be corresponded in current information corresponding to target user
Cease the page.Wherein, information page is displayed for information.Target user's point is used in current information corresponding to target user
Hit, with present clicked in information page corresponding to current information.It should be noted that presentation corresponding to target user
It can be preset by technical staff with the corresponding relationship of information and information page.
In some optional implementations of the present embodiment, target is used in current information corresponding to the target user
User clicks, with present clicked in information page corresponding to current information when, above-mentioned predetermined registration operation may include clicking
Operation.
In the present embodiment, available be pre-stored within corresponding to local, target user of above-mentioned executing subject is in
Current information, also terminal used in available target user send, corresponding to target user be in current information.
Step 202, by the acquired interest identification model trained in advance in current information input, recognition result is obtained.
In the present embodiment, based on being in current information obtained in step 201, above-mentioned executing subject can will be in current letter
Breath input interest identification model trained in advance, obtains recognition result.Wherein, interest identification model is in current information for characterizing
With the corresponding relationship in recognition result corresponding to current information.Specifically, interest identification model corresponding at least two preset it is emerging
Interesting classification.Such as automotive-type and cell phone type.Recognition result is used to indicate at least two default category of interest
The default category of interest that current information matches can include but is not limited at least one of following: text, numerical value, symbol, figure
Picture.For example, recognition result can be text " automobile ", indicate that the default category of interest to match is automotive-type.
In practice, with the default category of interest that matches in current information can at least two default category of interest,
To in the relevant default category of interest of the content of current information.For example, being text " mobile phone price drops " in current information.It can be with
Understand, the content in current information is related to mobile phone, then two default category of interest " automobiles corresponding to interest identification model
It can be cell phone type with the default category of interest to match in current information in class ", " cell phone type ".
In the present embodiment, interest identification model can be used for characterizing in current information and in knowledge corresponding to current information
The corresponding relationship of other result.Specifically, as an example, interest identification model can be technical staff is in advance based on to being largely in
Current information and for the recognition result in current information labeling statistics and pre-establish, be stored with it is multiple in current information
With the mapping table of corresponding recognition result；Or it is based on preset training sample, using machine learning method to first
The mould that beginning model (such as neural network, Logic Regression Models (Logistic Regression, LR) etc.) obtains after being trained
Type.
In some optional implementations of the present embodiment, interest identification model can by above-mentioned executing subject or other
Electronic equipment is obtained by following steps training: firstly, obtaining training sample set.Wherein, training sample includes sample in current
Information and the specimen discerning result marked in advance for sample in current information.Specimen discerning result can serve to indicate that in advance really
The default category of interest to match with sample in current information in the default category of interest of fixed at least two.Then, machine is utilized
Learning method, the sample for including using the training sample that training sample is concentrated are in current information as input, the sample that will be inputted
In specimen discerning result corresponding to current information as desired output, training obtains interest identification model.
Specifically, the sample that can include using the training sample that training sample is concentrated is in current information as predetermined
The input of initial model (such as neural network, Logic Regression Models etc.), by the sample inputted in corresponding to current information
Desired output of the specimen discerning result as initial model, is trained initial model, finally obtains interest identification model.
In some optional implementations of the present embodiment, interest identification model may include the identification of at least two interest
Submodel.At least two interest identify submodel in interest identification submodel can at least two default category of interest
Default category of interest is corresponding.As an example, interest identification model includes that two interest identify submodel, respectively the first interest
Identify that submodel and the second interest identify submodel.In turn, the first interest identification submodel can be preset for identification
Category of interest is automotive-type, and the second interest identifies that the category of interest of submodel for identification is cell phone type, so that the first interest is known
Small pin for the case model is corresponding with automotive-type, and the second interest identifies that submodel is corresponding with cell phone type.It is understood that here, interest class
" automotive-type ", " cell phone type " are not two default category of interest corresponding to interest identification model.It should be noted that interest
Identification submodel may include various for generating the structure (such as classifier) of result.
In some optional implementations of the present embodiment, when interest identification model includes at least two interest identification
When model, acquired can be separately input into few two interest identification submodel in current information by above-mentioned executing subject, be obtained
Obtain recognition result.
In some optional implementations of the present embodiment, interest identification model can also include Feature Selection Model.
Feature Selection Model can be used for extracting the feature in current information inputted, may include various for extracting the spy of information
The structure (such as convolutional layer) of sign, also, Feature Selection Model is connect with above-mentioned at least two interest identification submodel.In turn,
Above-mentioned executing subject can be obtained by following steps by the acquired interest identification model trained in advance in current information input
Obtain recognition result: firstly, above-mentioned executing subject can be presented by acquired in current information input Feature Selection Model
The information characteristics corresponding to information.Then, above-mentioned executing subject can input information characteristics obtained and feature respectively
At least two interest identification submodel that model is connected is extracted, recognition result is obtained.
Step 203, it is based on recognition result obtained, generates the user tag of target user.
In the present embodiment, it is based on step 202 recognition result obtained, target user can be generated in above-mentioned executing subject
User tag.Wherein, user tag can serve to indicate that the category of interest of target user, can include but is not limited to down toward
One item missing: text, numerical value, symbol, image.For example, the user tag of target user can be text " automobile ".
Specifically, above-mentioned executing subject can be based on recognition result obtained, adopts and generate target user in various manners
User tag.For example, above-mentioned executing subject can directly mark the user that recognition result obtained is determined as target user
Label；Alternatively, above-mentioned executing subject can be handled recognition result obtained, and recognition result is determined as by treated
The user tag of target user.
As an example, recognition result obtained can be the image of automobile, then above-mentioned executing subject can tie identification
Image corresponding to fruit carries out image recognition, obtains text " automobile ", and then text obtained " automobile " is determined as target
The user tag of user.It should be noted that image recognition technology is the well-known technique studied and applied extensively at present, herein not
It repeats again.
With continued reference to the signal that Fig. 3, Fig. 3 are according to the application scenarios of the method for generating information of the present embodiment
Figure.In the application scenarios of Fig. 3, server 301 can be obtained first corresponding to the transmission of terminal device 302, target user
In current information 303, wherein target user is the user of using terminal equipment 302.It is in current information corresponding to target user
303 for target user it is performed using terminal device 302 predetermined registration operation (such as clicking operation) in current information.So
Afterwards, acquired can be inputted interest identification model 304 trained in advance in current information 303 by server 301, be identified
As a result (such as " automobile ") 305, wherein the default category of interest of interest identification model 304 corresponding at least two (such as automotive-type and
Cell phone type), recognition result 305 is used to indicate at least two default category of interest and presets with what is matched in current information 303
Category of interest (i.e. automotive-type).Finally, server 301 can be based on recognition result 305 obtained, the use of target user is generated
Family label 306, wherein user tag 306 can serve to indicate that the category of interest of target user.For example, referring to Fig. 3, server
301 can directly be determined as recognition result 305 obtained the user tag 306 of target user.
It is in current information corresponding to the method provided by the above embodiment effective use target user of the application, to target
The category of interest of user is identified, the user tag of target user is generated, and is improved the diversity of information generation, is helped
In the subsequent category of interest based on target user, corresponding operating is executed (such as by the interested letter of target user to target user
Breath is presented to target user)；Also, it is raw that information can be improved in the user tag for generating target user using interest identification model
At accuracy.
With further reference to Fig. 4, it illustrates the processes 400 of another embodiment of the method for generating information.The use
In the process 400 for the method for generating information, comprising the following steps:
Step 401, obtain is in current information corresponding to target user.
In the present embodiment, can lead to for generating the executing subject (such as server shown in FIG. 1) of the method for information
It crosses wired connection mode or radio connection obtains corresponding to target user in current information.Wherein, target user is
The user of user tag to be determined corresponding to it.User tag corresponding to target user can be used for characterizing target user's
Category of interest.The presentation of predetermined registration operation is performed to it using terminal for target user in current information corresponding to target user
Use information.In current information be it is predetermined, for rendering give user information, can include but is not limited to following at least one
: text, numerical value, symbol, image, video, link.Predetermined registration operation can be the predetermined various operations of technical staff, example
Such as browse operation.
Step 402, by the acquired interest identification model trained in advance in current information input, recognition result is obtained.
In the present embodiment, based on being in current information obtained in step 401, above-mentioned executing subject can will be in current letter
Breath input interest identification model trained in advance, obtains recognition result.Wherein, interest identification model is in current information for characterizing
With the corresponding relationship in recognition result corresponding to current information.Specifically, interest identification model corresponding at least two preset it is emerging
Interesting classification.Such as automotive-type and cell phone type.Recognition result is used to indicate at least two default category of interest
The default category of interest that current information matches can include but is not limited at least one of following: text, numerical value, symbol, figure
Picture.For example, recognition result can be text " automobile ", indicate that the default category of interest to match is automotive-type.
Step 403, it is based on recognition result obtained, generates the user tag of target user.
In the present embodiment, it is based on step 402 recognition result obtained, target user can be generated in above-mentioned executing subject
User tag.Wherein, user tag can serve to indicate that the category of interest of target user, can include but is not limited to down toward
One item missing: text, numerical value, symbol, image.
Step 404, information aggregate to be presented is obtained.
In the present embodiment, after the user tag for generating target user based on step 403, above-mentioned executing subject can be obtained
Take information aggregate to be presented.Wherein, information to be presented can be information predetermined, to present to target user.Wait be in
It may include multiple information to be presented in existing information aggregate.
Specifically, above-mentioned executing subject is available to be pre-stored within local multiple information to be presented, form to be presented
Information aggregate；Alternatively, multiple information to be presented that the available electronic equipment for communicating connection of above-mentioned executing subject is sent,
Form information aggregate to be presented.
Step 405, for the information to be presented in information aggregate to be presented, which is identified into mould
Type obtains recognition result corresponding to the information to be presented.
In the present embodiment, for the information to be presented in the information aggregate to be presented that is obtained in step 404, above-mentioned execution
The above-mentioned interest identification model of information input to be presented can be obtained recognition result corresponding to the information to be presented by main body.
Here, recognition result corresponding to information to be presented is used to indicate at least two default interest class corresponding to interest identification model
In not, the default category of interest that matches with information to be presented.
Step 406, it is based on recognition result obtained, information to be presented is chosen from information aggregate to be presented as being used for
The target of target user is presented in current information.
In the present embodiment, based on the recognition result obtained in step 405, above-mentioned executing subject can be from information to be presented
Information to be presented is chosen in set as rendering to the target of target user in current information.Wherein, target is in current letter
Category of interest phase indicated by user tag of the default category of interest with target user indicated by the corresponding recognition result of breath
Together.
As an example, interest identification model corresponds to two default category of interest, respectively automotive-type and cell phone type.Pass through step
Rapid 403 generate the user tag " automobile " of target user.Information aggregate to be presented includes two information to be presented, respectively the
One information to be presented and the second information to be presented.By step 405, recognition result corresponding to the first information to be presented is obtained
Recognition result " mobile phone " corresponding to " automobile " and the second information to be presented.In turn, due to the user tag " vapour of target user
Category of interest indicated by vehicle " is automotive-type, is preset indicated by recognition result " automobile " corresponding to the first information to be presented
Category of interest is also automotive-type, therefore can choose the first information to be presented as rendering to the target of target user in current
Information.
Above-mentioned steps 401, step 402, step 403 respectively with step 201, step 202, the step in previous embodiment
203 is consistent, and the description above with respect to step 201, step 202 and step 203 is also applied for step 401, step 402 and step
403, details are not described herein again.
Figure 4, it is seen that the method for generating information compared with the corresponding embodiment of Fig. 2, in the present embodiment
Process 400 highlight obtain target user user tag after, the user tag based on target user, from information to be presented
Chosen in set for rendering give target user information to be presented the step of.The scheme of the present embodiment description can be as a result,
After the user tag for generating target user, it is based on user tag, determines that the interested target of target user in current information, improves
Information processing it is comprehensive；Also, facilitate target user and operation (such as clicking operation) executed in current information to target,
Improve the validity of information processing.
With further reference to Fig. 5, as the realization to method shown in above-mentioned each figure, this application provides one kind for generating letter
One embodiment of the device of breath, the Installation practice is corresponding with embodiment of the method shown in Fig. 2, which can specifically answer
For in various electronic equipments.
As shown in figure 5, the present embodiment includes: that first acquisition unit 501, first is defeated for generating the device 500 of information
Enter unit 502, label generation unit 503.First acquisition unit 501 is configured to obtain corresponding to target user in current letter
Breath, wherein corresponding to target user in current information be target user using terminal perform predetermined registration operation in current letter
Breath；First input unit 502 is configured to obtain the acquired interest identification model trained in advance in current information input
Recognition result, wherein the corresponding at least two default category of interest of interest identification model, it is pre- that recognition result is used to indicate at least two
If in category of interest with inputted the default category of interest to match in current information；Label generation unit 503 is configured to
Based on recognition result obtained, the user tag of target user is generated, wherein user tag is used to indicate the emerging of target user
Interesting classification.
It in the present embodiment, can be by wired connection side for generating the first acquisition unit 501 of the device 500 of information
It is in current information corresponding to target user that formula or radio connection, which obtain,.Wherein, its is right to be to be determined by target user
The user for the user tag answered.User tag corresponding to target user can be used for characterizing the category of interest of target user.Mesh
Corresponding to mark user in current information be target user it is performed using terminal predetermined registration operation in current information.It presents
With information be it is predetermined, for rendering to the information of user, can include but is not limited at least one of following: text, number
Value, symbol, image, video, link.Predetermined registration operation can be the predetermined various operations of technical staff, such as browse operation.
In the present embodiment, based on first acquisition unit 501 obtain in current information, the first input unit 502 can be with
The interest identification model that will be trained in advance in current information input obtains recognition result.Wherein, interest identification model is for characterizing
In current information and the corresponding relationship in recognition result corresponding to current information.Specifically, interest identification model is corresponding at least
Two default category of interest.Such as automotive-type and cell phone type.Recognition result be used to indicate at least two default category of interest with
The default category of interest to match in current information inputted can include but is not limited at least one of following: text, number
Value, symbol, image.For example, recognition result can be text " automobile ", indicate that the default category of interest to match is automotive-type.
In the present embodiment, it is based on the recognition result obtained of the first input unit 502, label generation unit 503 can be with
Generate the user tag of target user.Wherein, user tag can serve to indicate that the category of interest of target user, may include but
It is not limited at least one of following: text, numerical value, symbol, image.For example, the user tag of target user can be text " vapour
Vehicle ".
In some optional implementations of the present embodiment, interest identification model may include the identification of at least two interest
Submodel, at least two interest identify the interest identification submodel in submodel and presetting at least two default category of interest
Category of interest is corresponding.
In some optional implementations of the present embodiment, the first input unit 502 can be further configured to: will
Acquired is separately input into few two interest identification submodel in current information, obtains recognition result.
In some optional implementations of the present embodiment, interest identification model can also include Feature Selection Model,
Feature Selection Model is connect at least two interest identification submodel；And first input unit 502 may include: the first input
Module (not shown) is configured to acquired in current information input Feature Selection Model, and obtaining is in current information
Corresponding information characteristics；Second input module (not shown) is configured to respectively input information characteristics obtained
At least two interest identification submodel being connected with Feature Selection Model, obtains recognition result.
In some optional implementations of the present embodiment, interest identification model can be obtained by following steps training
: obtain training sample set, wherein training sample includes that sample is in current information and the specimen discerning marked in advance as a result, sample
This recognition result be used to indicate in predetermined at least two default category of interest with sample in current information match it is pre-
If category of interest；Using machine learning method, the sample that includes using the training sample that training sample is concentrated in current information as
Input, using the sample inputted in specimen discerning result corresponding to current information as desired output, training obtains interest knowledge
Other model.
In some optional implementations of the present embodiment, device 500 can also include: second acquisition unit (in figure
It is not shown), it is configured to obtain information aggregate to be presented；Second input unit (not shown), is configured to for wait be in
The information input interest identification model to be presented it is right to be obtained the information institute to be presented by the information to be presented in existing information aggregate
The recognition result answered；Information extracting unit (not shown) is configured to based on recognition result obtained, from letter to be presented
Information to be presented is chosen in breath set as rendering to the target of target user in current information, wherein target is in current
Category of interest indicated by default category of interest and the user tag of target user indicated by recognition result corresponding to information
It is identical.
In some optional implementations of the present embodiment, letter can be corresponded in current information corresponding to target user
The page is ceased, is clicked in current information for target user corresponding to target user, is in current information institute to be presented clicked
Corresponding information page.
In some optional implementations of the present embodiment, predetermined registration operation may include clicking operation.
It is understood that all units recorded in the device 500 and each step phase in the method with reference to Fig. 2 description
It is corresponding.As a result, above with respect to the operation of method description, the beneficial effect of feature and generation be equally applicable to device 500 and its
In include unit, details are not described herein.
It is in current information corresponding to target user that the device provided by the above embodiment 500 of the application, which efficiently uses, right
The category of interest of target user is identified, the user tag of target user is generated, and improves the diversity of information generation,
Facilitate the subsequent category of interest based on target user, it is (such as interested by target user to execute corresponding operating to target user
Information be presented to target user)；Also, the user tag that target user is generated using interest identification model, can be improved letter
Cease the accuracy generated.
Below with reference to Fig. 6, it illustrates the computer systems 600 for the server for being suitable for being used to realize the embodiment of the present application
Structural schematic diagram.Server shown in Fig. 6 is only an example, should not function and use scope band to the embodiment of the present application
Carry out any restrictions.
As shown in fig. 6, computer system 600 includes central processing unit (CPU) 601, it can be read-only according to being stored in
Program in memory (ROM) 602 or be loaded into the program in random access storage device (RAM) 603 from storage section 608 and
Execute various movements appropriate and processing.In RAM 603, also it is stored with system 600 and operates required various programs and data.
CPU 601, ROM 602 and RAM 603 are connected with each other by bus 604.Input/output (I/O) interface 605 is also connected to always
Line 604.
I/O interface 605 is connected to lower component: the importation 606 including keyboard, mouse etc.；It is penetrated including such as cathode
The output par, c 607 of spool (CRT), liquid crystal display (LCD) etc. and loudspeaker etc.；Storage section 608 including hard disk etc.；
And the communications portion 609 of the network interface card including LAN card, modem etc..Communications portion 609 via such as because
The network of spy's net executes communication process.Driver 610 is also connected to I/O interface 605 as needed.Detachable media 611, such as
Disk, CD, magneto-optic disk, semiconductor memory etc. are mounted on as needed on driver 610, in order to read from thereon
Computer program be mounted into storage section 608 as needed.
Particularly, in accordance with an embodiment of the present disclosure, it may be implemented as computer above with reference to the process of flow chart description
Software program.For example, embodiment of the disclosure includes a kind of computer program product comprising be carried on computer-readable medium
On computer program, which includes the program code for method shown in execution flow chart.In such reality
It applies in example, which can be downloaded and installed from network by communications portion 609, and/or from detachable media
611 are mounted.When the computer program is executed by central processing unit (CPU) 601, limited in execution the present processes
Above-mentioned function.It should be noted that computer-readable medium described herein can be computer-readable signal media or
Computer readable storage medium either the two any combination.Computer readable storage medium for example can be --- but
Be not limited to --- electricity, magnetic, optical, electromagnetic, infrared ray or semiconductor system, device or device, or any above combination.
The more specific example of computer readable storage medium can include but is not limited to: have one or more conducting wires electrical connection,
Portable computer diskette, hard disk, random access storage device (RAM), read-only memory (ROM), erasable type may be programmed read-only deposit
Reservoir (EPROM or flash memory), optical fiber, portable compact disc read-only memory (CD-ROM), light storage device, magnetic memory
Part or above-mentioned any appropriate combination.In this application, computer readable storage medium, which can be, any include or stores
The tangible medium of program, the program can be commanded execution system, device or device use or in connection.And
In the application, computer-readable signal media may include in a base band or the data as the propagation of carrier wave a part are believed
Number, wherein carrying computer-readable program code.The data-signal of this propagation can take various forms, including but not
It is limited to electromagnetic signal, optical signal or above-mentioned any appropriate combination.Computer-readable signal media can also be computer
Any computer-readable medium other than readable storage medium storing program for executing, the computer-readable medium can send, propagate or transmit use
In by the use of instruction execution system, device or device or program in connection.Include on computer-readable medium
Program code can transmit with any suitable medium, including but not limited to: wireless, electric wire, optical cable, RF etc., Huo Zheshang
Any appropriate combination stated.
Flow chart and block diagram in attached drawing are illustrated according to the system of the various embodiments of the application, method and computer journey
The architecture, function and operation in the cards of sequence product.In this regard, each box in flowchart or block diagram can generation
A part of one module, program segment or code of table, a part of the module, program segment or code include one or more use
The executable instruction of the logic function as defined in realizing.It should also be noted that in some implementations as replacements, being marked in box
The function of note can also occur in a different order than that indicated in the drawings.For example, two boxes succeedingly indicated are actually
It can be basically executed in parallel, they can also be executed in the opposite order sometimes, and this depends on the function involved.Also it to infuse
Meaning, the combination of each box in block diagram and or flow chart and the box in block diagram and or flow chart can be with holding
The dedicated hardware based system of functions or operations as defined in row is realized, or can use specialized hardware and computer instruction
Combination realize.
Being described in unit involved in the embodiment of the present application can be realized by way of software, can also be by hard
The mode of part is realized.Described unit also can be set in the processor, for example, can be described as: a kind of processor packet
Include first acquisition unit, the first input unit and label generation unit.Wherein, the title of these units is not under certain conditions
The restriction to the unit itself is constituted, for example, label generation unit is also described as " generating the user tag of target user
Unit ".
As on the other hand, present invention also provides a kind of computer-readable medium, which be can be
Included in server described in above-described embodiment；It is also possible to individualism, and without in the supplying server.It is above-mentioned
Computer-readable medium carries one or more program, when said one or multiple programs are executed by the server,
So that the server: obtaining is in current information corresponding to target user, wherein is in current information corresponding to target user
Target user using terminal perform predetermined registration operation in current information；By acquired in the training in advance of current information input
Interest identification model obtains recognition result, wherein the corresponding at least two default category of interest of interest identification model, recognition result
It is used to indicate at least two default category of interest and is inputted the default category of interest to match in current information；Based on institute
The recognition result of acquisition generates the user tag of target user, wherein user tag is used to indicate the interest class of target user
Not.
Above description is only the preferred embodiment of the application and the explanation to institute's application technology principle.Those skilled in the art
Member is it should be appreciated that invention scope involved in the application, however it is not limited to technology made of the specific combination of above-mentioned technical characteristic
Scheme, while should also cover in the case where not departing from foregoing invention design, it is carried out by above-mentioned technical characteristic or its equivalent feature
Any combination and the other technical solutions formed.Such as features described above has similar function with (but being not limited to) disclosed herein
Can technical characteristic replaced mutually and the technical solution that is formed.
Claims (18)
1. a kind of method for generating information, comprising:
Obtain target user corresponding to be in current information, wherein corresponding to target user in current information be target user
Using terminal perform predetermined registration operation in current information；
By the acquired interest identification model trained in advance in current information input, recognition result is obtained, wherein interest identification
Model corresponds at least two default category of interest, and recognition result is used to indicate in described at least two default category of interest defeated with institute
The default category of interest to match in current information entered；
Based on recognition result obtained, the user tag of the target user is generated, wherein the user tag is used to indicate
The category of interest of the target user.
2. according to the method described in claim 1, wherein, the interest identification model includes that at least two interest identify submodule
Type, at least two interest identify the interest identification submodel in submodel and the default interest at least two default category of interest
Classification is corresponding.
3. described by the acquired interest trained in advance in current information input according to the method described in claim 2, wherein
Identification model obtains recognition result, comprising:
Acquired is inputted into at least two interest identification submodel in current information respectively, obtains recognition result.
4. according to the method described in claim 2, wherein, the interest identification model further includes Feature Selection Model, the spy
Sign is extracted model and is connect at least two interest identification submodel；And
It is described by the acquired interest identification model trained in advance in current information input, obtain recognition result, comprising:
By acquired in Feature Selection Model described in current information input, obtain in information characteristics corresponding to current information；
Information characteristics obtained are inputted at least two interest identification submodule being connected with the Feature Selection Model respectively
Type obtains recognition result.
5. according to the method described in claim 1, wherein, the interest identification model is obtained by following steps training:
Obtain training sample set, wherein training sample includes that sample is in current information and the specimen discerning marked in advance as a result, sample
This recognition result be used to indicate in predetermined at least two default category of interest with sample in current information match it is pre-
If category of interest；
Using machine learning method, the sample for including using the training sample that training sample is concentrated is in current information as input, will
For the sample inputted in specimen discerning result corresponding to current information as desired output, training obtains interest identification model.
6. described after the user tag for generating the target user according to the method described in claim 1, wherein
Method further include:
Obtain information aggregate to be presented；
For the information to be presented in the information aggregate to be presented, by interest identification model described in the information input to be presented,
Obtain recognition result corresponding to the information to be presented；
Based on recognition result obtained, information to be presented is chosen from information aggregate to be presented as rendering to the mesh
The target for marking user is in current information, wherein the target is emerging in presetting indicated by recognition result corresponding to current information
Interesting classification is identical as category of interest indicated by the user tag of the target user.
7. method described in one of -6 according to claim 1, wherein be in current information corresponding informance page corresponding to target user
Face is clicked in current information for target user corresponding to target user, is in corresponding to current information to be presented clicked
Information page.
8. according to the method described in claim 7, wherein, the predetermined registration operation includes clicking operation.
9. a kind of for generating the device of information, comprising:
First acquisition unit is configured to obtain corresponding to target user in current information, wherein corresponding to target user
In current information be target user using terminal perform predetermined registration operation in current information；
First input unit is configured to obtain the acquired interest identification model trained in advance in current information input
Recognition result, wherein the corresponding at least two default category of interest of interest identification model, recognition result are used to indicate described at least two
In a default category of interest with inputted the default category of interest to match in current information；
Label generation unit is configured to generate the user tag of the target user based on recognition result obtained,
In, the user tag is used to indicate the category of interest of the target user.
10. device according to claim 9, wherein the interest identification model includes that at least two interest identify submodule
Type, at least two interest identify the interest identification submodel in submodel and the default interest at least two default category of interest
Classification is corresponding.
11. device according to claim 10, wherein first input unit is further configured to:
Acquired is inputted into at least two interest identification submodel in current information respectively, obtains recognition result.
12. device according to claim 10, wherein the interest identification model further includes Feature Selection Model, described
Feature Selection Model is connect at least two interest identification submodel；And
First input unit includes:
First input module is configured to obtain acquired in Feature Selection Model described in current information input in current
Information characteristics corresponding to information；
Second input module, is configured to respectively to input information characteristics obtained and is connected with the Feature Selection Model
At least two interest identify submodel, obtain recognition result.
13. device according to claim 9, wherein the interest identification model is obtained by following steps training:
Obtain training sample set, wherein training sample includes that sample is in current information and the specimen discerning marked in advance as a result, sample
This recognition result be used to indicate in predetermined at least two default category of interest with sample in current information match it is pre-
If category of interest；
Using machine learning method, the sample for including using the training sample that training sample is concentrated is in current information as input, will
For the sample inputted in specimen discerning result corresponding to current information as desired output, training obtains interest identification model.
14. device according to claim 9, wherein described device further include:
Second acquisition unit is configured to obtain information aggregate to be presented；
Second input unit is configured to for the information to be presented in the information aggregate to be presented, by the information to be presented
The interest identification model is inputted, recognition result corresponding to the information to be presented is obtained；
Information extracting unit is configured to choose letter to be presented from information aggregate to be presented based on recognition result obtained
It ceases as rendering to the target of the target user in current information, wherein the target is in corresponding to current information
Default category of interest indicated by recognition result is identical as category of interest indicated by the user tag of the target user.
15. the device according to one of claim 9-14, wherein be in current information corresponding informance corresponding to target user
The page is clicked in current information for target user corresponding to target user, with present clicked it is right in current information
The information page answered.
16. device according to claim 15, wherein the predetermined registration operation includes clicking operation.
17. a kind of server, comprising:
One or more processors；
Storage device is stored thereon with one or more programs,
When one or more of programs are executed by one or more of processors, so that one or more of processors are real
Now such as method described in any one of claims 1-8.
18. a kind of computer-readable medium, is stored thereon with computer program, wherein the realization when program is executed by processor
Such as method described in any one of claims 1-8.
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Application publication date: 20190226 |