CN108319614A - Information acquisition method, device and system - Google Patents
Information acquisition method, device and system Download PDFInfo
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- CN108319614A CN108319614A CN201710035768.6A CN201710035768A CN108319614A CN 108319614 A CN108319614 A CN 108319614A CN 201710035768 A CN201710035768 A CN 201710035768A CN 108319614 A CN108319614 A CN 108319614A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/33—Querying
- G06F16/3331—Query processing
- G06F16/3332—Query translation
- G06F16/3338—Query expansion
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/33—Querying
- G06F16/3331—Query processing
- G06F16/3332—Query translation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0241—Advertisements
- G06Q30/0277—Online advertisement
Abstract
A kind of information acquisition method of the application proposition, device and system, this method include：Receive term；Based on the Machine Translation Model being generated in advance, target word corresponding with the term is obtained, the term has semantic consistency with the target word；The target word is sent to client so that the client shows the target word.This method can realize the conversion between word, to when being applied to the conversion from low value word to high value word, improve whole conversion ratio, lifting system cashability.
Description
Technical field
This application involves Internet technical field more particularly to a kind of information acquisition method, device and system.
Background technology
In the related technology, it is typically after receiving term input by user, extraction is therein when triggering showing advertisement
Core word, then trigger showing for advertisement corresponding to the business word comprising the core word.
But the above-mentioned mode based on text coherence, showing for relevant advertisements cannot be triggered in some cases, to
Whole conversion ratio is limited, system cashability is reduced.
Invention content
The application is intended to solve at least some of the technical problems in related technologies.
For this purpose, the purpose of the application is to propose that a kind of information acquisition method, this method may be implemented between word
Conversion, to when being applied to the conversion from low value word to high value word, improve whole conversion ratio, lifting system becomes
Existing ability.
Further object is to propose a kind of information acquisition device.
Further object is to propose a kind of Information Acquisition System.
The embodiment of the present application proposes a kind of information acquisition method, including：Receive term；Based on the machine being generated in advance
Translation model, obtains target word corresponding with the term, and the term has semantic consistency with the target word.
The embodiment of the present application proposes a kind of information acquisition device, including：Receiving module, for receiving term；First
Acquisition module, for based on the Machine Translation Model being generated in advance, obtaining target word corresponding with the term, the retrieval
Word has semantic consistency with the target word.
The embodiment of the present application proposes a kind of equipment, including：One or more processors；For storing one or more journeys
The memory of sequence；When one or more of programs are executed by one or more of processors so that one or more
A processor executes the embodiment of the present application any one of them method.
The embodiment of the present application proposes a kind of non-volatile computer readable storage medium storing program for executing, and one in the storage medium
When a or multiple programs are executed by the one or more processors of equipment so that one or more of processors execute the application
Embodiment any one of them method.
The embodiment of the present application proposes a kind of computer program product, when the computer program product is by one in equipment
When a or multiple processors execute so that one or more of processors execute any one of the application first aspect embodiment institute
The method stated.
The embodiment of the present application can obtain the mesh for having semantic consistency with term by using Machine Translation Model
Word is marked, entry conversion is realized, to apply in showing advertisement, high value word can be converted to from low value word, to touch
Originating party formula is converted to the triggering of the advertisement based on high value word from the advertisement triggering based on low value word, and then improves conversion ratio, carries
Rise system cashability.
The additional aspect of the application and advantage will be set forth in part in the description, and will partly become from the following description
It obtains obviously, or recognized by the practice of the application.
Description of the drawings
The application is above-mentioned and/or additional aspect and advantage will become from the following description of the accompanying drawings of embodiments
Obviously and it is readily appreciated that, wherein：
Fig. 1 is the flow diagram for the information acquisition method that the application one embodiment proposes；
Fig. 2 is the flow diagram of the information acquisition method of the application another embodiment proposition；
Fig. 3 is the topological structure schematic diagram of Machine Translation Model in the embodiment of the present application；
Fig. 4 is the structural schematic diagram for the information acquisition device that the application one embodiment proposes；
Fig. 5 is the structural schematic diagram of the information acquisition device of the application another embodiment proposition；
Fig. 6 is the structural schematic diagram for the Information Acquisition System that the application one embodiment proposes.
Specific implementation mode
Embodiments herein is described below in detail, examples of the embodiments are shown in the accompanying drawings, wherein from beginning to end
Same or similar label indicates same or similar module or module with the same or similar functions.Below with reference to attached
The embodiment of figure description is exemplary, and is only used for explaining the application, and should not be understood as the limitation to the application.On the contrary, this
The embodiment of application includes all changes fallen within the scope of the spiritual and intension of attached claims, modification and is equal
Object.
Fig. 1 is the flow diagram for the information acquisition method that the application one embodiment proposes.
As shown in Figure 1, the method for the present embodiment includes：
S11：Receive term.
For example, client receives term input by user, term is sent to server-side by client later, to take
Business end can receive the term of client transmission, and carry out follow-up relevant treatment.
S12：Based on the Machine Translation Model being generated in advance, target word corresponding with the term, the retrieval are obtained
Word has semantic consistency with the target word.
The input of Machine Translation Model and output are the words pair for having semantic consistency, therefore, after receiving term,
Can using term as the input of Machine Translation Model, after the processing of Machine Translation Model, Machine Translation Model it is defeated
Go out as the target word with term with semantic consistency.For example, the input of Machine Translation Model is " fresh flower ", output can be with
For " tree peony ".
The flow of specific training machine translation model may refer to subsequent descriptions.
Trigger method based on text coherence can have limitation, for example, " dream purchase automobile be what the meaning " with
" all public affairs are read a dream " is being semantically highly relevant, but inconsistent on text, if the triggering based on text coherence
Scheme can not trigger " all public affairs are read a dream " correlation when term input by user is " dreaming what meaning purchase automobile is "
Advertisement shows.And in the present embodiment, as a result of Machine Translation Model, Machine Translation Model is output and input with language
Adopted consistency, then, when term input by user is " dreaming what meaning purchase automobile is ", by Machine Translation Model
" all public affairs are read a dream " can be exported, is showed to which " all public affairs are read a dream " relevant advertisements can be triggered in follow-up process.
Further, target word can be sent to client, be showed by client by server-side after getting target word
To user.
Further, user can be showed with selection target word to trigger relevant advertisements after viewing target word.Example
Such as, when term input by user is " dreaming what meaning purchase automobile is ", processing and client by server-side
Show, " all public affairs are read a dream " can be showed, later when the user clicks after " all public affairs are read a dream ", server-side can obtain and " all public affairs are read a dream "
Relevant advertisement, such as by " all public affairs are read a dream " as business word (bidword) or the advertisement title of advertisement to be showed
(title), show relevant advertisements.
In the present embodiment, by using Machine Translation Model, the target that there is semantic consistency with term can be obtained
Word realizes entry conversion, to apply in showing advertisement, high value word can be converted to from low value word, to trigger
Mode is converted to the triggering of the advertisement based on high value word from the advertisement triggering based on low value word, and then improves conversion ratio, is promoted
System cashability.
Fig. 2 is the flow diagram of the information acquisition method of the application another embodiment proposition.
As shown in Fig. 2, the method for the present embodiment includes：
S201：Server-side collects historical data, and the historical data includes：History term and its corresponding history target
Word, the history target word include：History shows business word or advertisement title corresponding to advertisement, and the history shows advertisement
Showed by history term triggering.
For example, collecting historical data from the retrieval daily record of user.It can log history retrieval phase in the retrieval daily record of user
Data are closed, therefore above-mentioned data can be got from history log.
S202：Server-side determines training data according to the historical data.
Wherein it is possible to directly using historical data as training data, retrieved for example, will directly collect every group of obtained history
Word and its history target word are as one group of training data.Alternatively,
In order to improve the correlation of word pair, by taking the selection instruction of user is click commands as an example, historical data can be removed
In not by user click or the lower word pair of clicking rate.That is, in the historical data, the history that selection rate is more than to preset value shows
History target word and its corresponding history term corresponding to advertisement is as training data.Preset value can be according to application demand
Setting, can be 0 or the value more than 0.For example, historical data includes the first history term and the first history target word,
If the clicking rate that the history corresponding to the first history target word shows advertisement is more than preset value, by the first history term and
First history target word is as one group of training data.
S203：Server-side is trained the training data, generates Machine Translation Model.
After training data determination, preset topological structure can be based on and carry out model training, corresponding machine is generated and turn over
Translate model.
In the present embodiment, as shown in figure 3, using topological structure as Recognition with Recurrent Neural Network (Recurrent neural
Network, RNN) for structure.
It is understood that training data can also be pre-processed before model training, such as cutting word, removal nothing
Word etc..
Training when, by training data history term and its corresponding history target word carry out cutting word after, obtain
Entry (term), the entry for being included using history term are obtained as the input of RNN after the processing of each layer parameter of model
Model export, by model output be used as predicted value, and the entry for being included using the corresponding history target word of history term as
Actual value determines error function by actual value after predicted value, based on error function and the backpropagation that passes through the time
(Backpropagation Through Time, BPTT) algorithm carries out model parameter update, to generate Machine Translation Model.
Further, after obtaining entry, as shown in figure 3, one-hot codings can also be carried out to entry.In order to ensure
All term can find corresponding one-hot codings, and a coding is reserved in one-hot encoder dictionaries and comes unified representation institute
There is the term not in term set, additionally incorporate two spcial characters, the beginning and end of query is marked respectively, to assist
Translation generates model and is blocked to query translation process.
It is understood that S201-S203 can be completed offline in advance, it can be used for subsequent entry later and turn online
It changes.
S204：Client receives term input by user.
For example, user inputs " dreaming what meaning purchase automobile is " in the client.
S205：Term is sent to server-side by client.
S206：Server-side receives the term that client is sent.
S207：Server-side obtains target word corresponding with the term, institute based on the Machine Translation Model being generated in advance
Stating term and the target word has semantic consistency.
It is understood that server-side can first pre-process term after receiving term, for example cut
Word, removal stop word etc..
After being pre-processed to term, entry included in pretreated term can be turned over as machine
The input for translating model regard model output as the corresponding target word of term after the processing of Machine Translation Model, for example,
Target word is " all public affairs are read a dream ".
S208：Target word is sent to client by server-side.
S209：Client shows target word.
It is understood that server-side after getting target word, can also carry out packing processes, so as to visitor to target word
Family, which is rectified, often shows target word, for example is encoded to target word, and it is medium to insert it into html codes.
S210：Client receives click commands of the user to target word.
S211：Client will click on instruction and be sent to server-side.
S212：Server-side determines that user has selected target word according to click commands, and obtains advertisement corresponding with target word.
For example, server-side can be using target word as business word, and pair being pre-configured between business word and advertisement
It should be related to, to which according to the correspondence, advertisement corresponding with target word can be obtained.Alternatively, server-side can be obtained mesh
Advertisement of the word as advertisement title is marked, as advertisement corresponding with target word.
S213：Advertisement corresponding with target word is sent to client by server-side.
S214：Client shows advertisement corresponding with target word.
In the present embodiment, by obtaining history term by its corresponding history target word, history target word is based on history
Show advertisement determination, semantic consistency can be based on and generate Machine Translation Model, to which semanteme may be implemented in later retrieval
The entry of consistency is converted, and is realized from low value word and is converted to high value word, by showing high value word, user can select height
It is worth word, to which triggering mode is converted to the triggering of the advertisement based on high value word from the advertisement triggering based on low value word, into
And conversion ratio is improved, lifting system cashability.
Fig. 4 is the structural schematic diagram for the information acquisition device that the application one embodiment proposes.
As shown in figure 4, the device 40 of the present embodiment includes：Receiving module 41 and the first acquisition module 42.
Receiving module 41, for receiving term；
First acquisition module 42, for based on the Machine Translation Model being generated in advance, obtaining corresponding with the term
Target word, the term have semantic consistency with the target word.
In some embodiments, referring to Fig. 5, which further includes：
First sending module 43, for the target word to be sent to client so that the client shows the mesh
Mark word.
In some embodiments, referring to Fig. 5, which further includes：
Second acquisition module 44, for after determining that user selects the target word, using the target word as business word
Or advertisement title, obtain advertisement corresponding with the target word；
Second sending module 45, for the advertisement to be sent to client so that the client shows the advertisement.
In some embodiments, referring to Fig. 5, which further includes：
Collection module 46, for collecting historical data, the historical data includes：History term and its corresponding history
Target word, the history target word include：History shows business word or advertisement title corresponding to advertisement, and the history shows
Advertisement is showed by history term triggering；
Determining module 47, for determining training data according to the historical data；
Training module 48 generates the Machine Translation Model for being trained to the training data.
In some embodiments, the determining module 47 is specifically used for：
Using the historical data as training data；Alternatively,
In the historical data, the history that selection rate is more than to preset value shows history target word corresponding to advertisement and its right
The history term answered is as training data.
In some embodiments, the topological structure of the Machine Translation Model includes：RNN structures.
It is understood that the device of the present embodiment is corresponding with above method embodiment, particular content may refer to method
The associated description of embodiment, is no longer described in detail herein.
In the present embodiment, by using Machine Translation Model, the target that there is semantic consistency with term can be obtained
Word realizes entry conversion, to apply in showing advertisement, high value word can be converted to from low value word, to trigger
Mode is converted to the triggering of the advertisement based on high value word from the advertisement triggering based on low value word, and then improves conversion ratio, is promoted
System cashability.
Fig. 6 is the structural schematic diagram for the Information Acquisition System that the application one embodiment proposes.
As shown in fig. 6, the system of the present embodiment includes：Client 61 and server-side 62.
Client 61, for receiving term input by user；
Server-side 62, the term sent for receiving the client；And it is turned over based on the machine being generated in advance
Model is translated, target word corresponding with the term is obtained, the term has semantic consistency with the target word.
Client 61 is additionally operable to：The target word that the server-side is sent is received, and the target word is presented to institute
State user.
In Fig. 6 by taking client and server-side are by wireless network connection as an example, it is to be understood that client and server-side
It can also be connected by cable network.
It is understood that the function of server-side is consistent with above-mentioned device, therefore, the concrete composition of server-side can join
See Fig. 4 or shown in fig. 5 devices, this will not be detailed here.
In the present embodiment, by using Machine Translation Model, the target that there is semantic consistency with term can be obtained
Word realizes entry conversion, to apply in showing advertisement, high value word can be converted to from low value word, to trigger
Mode is converted to the triggering of the advertisement based on high value word from the advertisement triggering based on low value word, and then improves conversion ratio, is promoted
System cashability.
The embodiment of the present application proposes a kind of equipment, including：One or more processors；For storing one or more journeys
The memory of sequence；When one or more of programs are executed by one or more of processors so that one or more
A processor executes：Receive term；Based on the Machine Translation Model being generated in advance, target corresponding with the term is obtained
Word, the term have semantic consistency with the target word；The target word is sent to client so that the client
End shows target word the embodiment of the present application any one of them method.
The embodiment of the present application proposes a kind of non-volatile computer readable storage medium storing program for executing, and one in the storage medium
When a or multiple programs are executed by the one or more processors of equipment so that one or more of processors execute：It receives
Term；Based on the Machine Translation Model being generated in advance, target word corresponding with the term, the term and institute are obtained
Stating target word has semantic consistency；The target word is sent to client so that the client shows the target word
The embodiment of the present application any one of them method.
The embodiment of the present application proposes a kind of computer program product, when the computer program product is by one in equipment
When a or multiple processors execute so that one or more of processors execute：Receive term；Based on the machine being generated in advance
Device translation model, obtains target word corresponding with the term, and the term has semantic consistency with the target word；
The target word is sent to client so that the client shows described target word the embodiment of the present application any one of them
Method.
It is understood that same or similar part can mutually refer in the various embodiments described above, in some embodiments
Unspecified content may refer to same or analogous content in other embodiment.
The arbitrary combination of one or more computer-readable media may be used.Computer-readable medium can be calculated
Machine readable signal medium or computer readable storage medium.Computer readable storage medium for example can be --- but it is unlimited
In --- electricity, system, device or the device of magnetic, optical, electromagnetic, infrared ray or semiconductor, or the arbitrary above combination.It calculates
The more specific example (non exhaustive list) of machine readable storage medium storing program for executing includes：Electrical connection with one or more conducting wires, just
It takes formula computer disk, hard disk, random access memory (RAM), read-only memory (ROM), erasable type and may be programmed read-only storage
Device (EPROM or flash memory), optical fiber, portable compact disc read-only memory (CD-ROM), light storage device, magnetic memory device,
Or above-mentioned any appropriate combination.In this document, can be any include computer readable storage medium or storage journey
The tangible medium of sequence, the program can be commanded the either device use or in connection of execution system, device.
Computer-readable signal media may include in a base band or as the data-signal that a carrier wave part is propagated,
Wherein carry computer-readable program code.Diversified forms may be used in the data-signal of this propagation, including --- but
It is not limited to --- electromagnetic signal, optical signal or above-mentioned any appropriate combination.Computer-readable signal media can also be
Any computer-readable medium other than computer readable storage medium, which can send, propagate or
Transmission for by instruction execution system, device either device use or program in connection.
The program code for including on computer-readable medium can transmit with any suitable medium, including --- but it is unlimited
In --- wireless, electric wire, optical cable, RF etc. or above-mentioned any appropriate combination.
It can be write with one or more programming languages or combinations thereof for executing the computer that operates of the present invention
Program code, described program design language include object oriented program language-such as Java, Smalltalk, C++,
Further include conventional procedural programming language-such as " C " language or similar programming language.Program code can be with
It fully executes, partly execute on the user computer on the user computer, being executed as an independent software package, portion
Divide and partly executes or executed on a remote computer or server completely on the remote computer on the user computer.
Be related in the situation of remote computer, remote computer can pass through the network of any kind --- including LAN (LAN) or
Wide area network (WAN)-be connected to subscriber computer, or, it may be connected to outer computer (such as carried using Internet service
It is connected by internet for quotient).
It should be noted that in the description of the present application, term " first ", " second " etc. are used for description purposes only, without
It can be interpreted as indicating or implying relative importance.In addition, in the description of the present application, unless otherwise indicated, the meaning of " multiple "
Refer at least two.
Any process described otherwise above or method description are construed as in flow chart or herein, and expression includes
It is one or more for realizing specific logical function or process the step of executable instruction code module, segment or portion
Point, and the range of the preferred embodiment of the application includes other realization, wherein can not press shown or discuss suitable
Sequence, include according to involved function by it is basic simultaneously in the way of or in the opposite order, to execute function, this should be by the application
Embodiment person of ordinary skill in the field understood.
It should be appreciated that each section of the application can be realized with hardware, software, firmware or combination thereof.Above-mentioned
In embodiment, software that multiple steps or method can in memory and by suitable instruction execution system be executed with storage
Or firmware is realized.It, and in another embodiment, can be under well known in the art for example, if realized with hardware
Any one of row technology or their combination are realized：With the logic gates for realizing logic function to data-signal
Discrete logic, with suitable combinational logic gate circuit application-specific integrated circuit, programmable gate array (PGA), scene
Programmable gate array (FPGA) etc..
Those skilled in the art are appreciated that realize all or part of step that above-described embodiment method carries
Suddenly it is that relevant hardware can be instructed to complete by program, the program can be stored in a kind of computer-readable storage medium
In matter, which includes the steps that one or a combination set of embodiment of the method when being executed.
In addition, each functional unit in each embodiment of the application can be integrated in a processing module, it can also
That each unit physically exists alone, can also two or more units be integrated in a module.Above-mentioned integrated mould
The form that hardware had both may be used in block is realized, can also be realized in the form of software function module.The integrated module is such as
Fruit is realized in the form of software function module and when sold or used as an independent product, can also be stored in a computer
In read/write memory medium.
Storage medium mentioned above can be read-only memory, disk or CD etc..
In the description of this specification, reference term " one embodiment ", " some embodiments ", " example ", " specifically show
The description of example " or " some examples " etc. means specific features, structure, material or spy described in conjunction with this embodiment or example
Point is contained at least one embodiment or example of the application.In the present specification, schematic expression of the above terms are not
Centainly refer to identical embodiment or example.Moreover, particular features, structures, materials, or characteristics described can be any
One or more embodiments or example in can be combined in any suitable manner.
Although embodiments herein has been shown and described above, it is to be understood that above-described embodiment is example
Property, it should not be understood as the limitation to the application, those skilled in the art within the scope of application can be to above-mentioned
Embodiment is changed, changes, replacing and modification.
Claims (13)
1. a kind of information acquisition method, which is characterized in that including：
Receive term；
Based on the Machine Translation Model being generated in advance, obtain target word corresponding with the term, the term with it is described
Target word has semantic consistency.
2. according to the method described in claim 1, it is characterized in that, further including：
The target word is sent to client so that the client shows the target word.
3. according to the method described in claim 2, it is characterized in that, further including：
After determining that user selects the target word, regard the target word as business word or advertisement title, acquisition with it is described
The corresponding advertisement of target word；
The advertisement is sent to client so that the client shows the advertisement.
4. according to the method described in claim 3, it is characterized in that, further including：
Historical data is collected, the historical data includes：History term and its corresponding history target word, the history target
Word includes：History shows business word or advertisement title corresponding to advertisement, and the history, which shows advertisement, to be examined by the history
The triggering of rope word shows；
Training data is determined according to the historical data；
The training data is trained, the Machine Translation Model is generated.
5. according to the method described in claim 4, it is characterized in that, described determine training data according to the historical data, packet
It includes：
Using the historical data as training data；Alternatively,
In the historical data, the history that selection rate is more than to preset value shows history target word corresponding to advertisement and its corresponding
History term is as training data.
6. a kind of information acquisition device, which is characterized in that including：
Receiving module, for receiving term；
First acquisition module, for based on the Machine Translation Model being generated in advance, obtaining target word corresponding with the term,
The term has semantic consistency with the target word.
7. device according to claim 6, which is characterized in that further include：
First sending module, for the target word to be sent to client so that the client shows the target word.
8. device according to claim 7, which is characterized in that further include：
Second acquisition module, for after determining that user selects the target word, using the target word as business word or extensively
Title is accused, advertisement corresponding with the target word is obtained；
Second sending module, for the advertisement to be sent to client so that the client shows the advertisement.
9. device according to claim 8, which is characterized in that further include：
Collection module, for collecting historical data, the historical data includes：History term and its corresponding history target
Word, the history target word include：History shows business word or advertisement title corresponding to advertisement, and the history shows advertisement
Showed by history term triggering；
Determining module, for determining training data according to the historical data；
Training module generates the Machine Translation Model for being trained to the training data.
10. device according to claim 9, which is characterized in that the determining module is specifically used for：
Using the historical data as training data；Alternatively,
In the historical data, the history that selection rate is more than to preset value shows history target word corresponding to advertisement and its corresponding
History term is as training data.
11. a kind of Information Acquisition System, which is characterized in that including：
Server-side, such as claim 6-10 any one of them devices；And
Client is sent to the server-side for receiving term input by user, and by the term, and, it receives
The target word that the server-side is sent, and the target word is presented to the user.
12. a kind of equipment, which is characterized in that including：
One or more processors；
Memory for storing 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
Execute method as described in any one in claim 1-5.
13. a kind of non-volatile computer readable storage medium storing program for executing, which is characterized in that when one or more of described storage medium
When program is executed by the one or more processors of equipment so that one or more of processors execute such as claim 1-5
Any one of them method.
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| CN201710035768.6A CN108319614A (en) | 2017-01-18 | 2017-01-18 | Information acquisition method, device and system |
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| CN201710035768.6A CN108319614A (en) | 2017-01-18 | 2017-01-18 | Information acquisition method, device and system |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112132601A (en) * | 2019-06-25 | 2020-12-25 | 百度在线网络技术（北京）有限公司 | Advertisement title rewriting method, device and storage medium |
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