CN107169837A - Method, device, electronic equipment and computer-readable medium for aiding in search - Google Patents
Method, device, electronic equipment and computer-readable medium for aiding in search Download PDFInfo
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- CN107169837A CN107169837A CN201710357106.0A CN201710357106A CN107169837A CN 107169837 A CN107169837 A CN 107169837A CN 201710357106 A CN201710357106 A CN 201710357106A CN 107169837 A CN107169837 A CN 107169837A
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Abstract
A kind of method, device, electronic equipment and computer-readable medium for being used to aid in search of disclosure.This method includes：The search operation of user is responded, ID is obtained；User behavior data is obtained by the ID, the user behavior data includes long-term action data and acts and efforts for expediency data；Search model is aided in obtain alignment score user behavior data input user；And provide auxiliary information to the search operation of the user according to the alignment score.Method, device, electronic equipment and the computer-readable medium disclosed in the present application for being used to aid in search, can more accurately match user's request, realize personalized auxiliary search.
Description
Technical field
The present invention relates to computer information processing field, it is used to aid in the method for search, dress in particular to a kind of
Put, electronic equipment and computer-readable medium.
Background technology
As the product that electric business is provided is more and more, the space that the shopping amount produced by electric field is commercially occupied is more next
It is bigger, the article that user wants how is searched on electric business platform, into it is in the urgent need to address the problem of.It is flat for electric business
Platform, search is the very important approach that user finds commodity.But substantial amounts of product and different product features are faced, in order to
Accurately know the demand of client, the product of various auxiliary user search is derived in recent years, such as is pulled down, hot word, dark text, phase
Close search etc..But search for entrance space it is limited, most start using hot word as Candidate Set, to meet most of demands；With
Consumption upgrading, users ' individualized requirement strengthens increasingly.Recommend the maximally related word of its user for different user, can more aid in user
Search.
Existing auxiliary search plan optimizes for total quality, is searched for, clicked on, lower single act using user's history
Based on basic data, by expanding data source, Optimal scheduling lifts overall keyword quality；Sequence mainly make use of
KPI ranking factors, and machine learning.Prior art has the disadvantage that：Prior art has Matthew effect, and matter is measured past
Front row, user's exposure is clicked on then more, then algorithm thinks its better quality again.What current all users saw is all identical
Data, but for individual, measured matter is exactly not necessarily what user wanted.Also, the data feedback of auxiliary search at present
Do not possess promptness.
Accordingly, it would be desirable to a kind of new method, device, electronic equipment and the computer-readable medium that are used to aid in search.
Above- mentioned information is only used for strengthening the understanding of the background to the present invention, therefore it disclosed in the background section
It can include not constituting the information to prior art known to persons of ordinary skill in the art.
The content of the invention
In view of this, the present invention provides a kind of method, device, electronic equipment and computer-readable Jie for being used to aid in search
Matter, can more accurately match user's request, realize personalized auxiliary search.
Other characteristics and advantage of the present invention will be apparent from by following detailed description, or partially by the present invention
Practice and acquistion.
According to an aspect of the invention, it is proposed that a kind of method for being used to aid in search, this method includes：Response user's searches
Rope is operated, and obtains ID；By ID obtain user behavior data, user behavior data include long-term action data with it is short
Phase behavioral data；Search model is aided in obtain alignment score user behavior data input user；And according to alignment score
Auxiliary information is provided to the search operation of user.
In a kind of exemplary embodiment of the disclosure, in addition to：Auxiliary search is set up by historic user behavioral data
Model.
In a kind of exemplary embodiment of the disclosure, auxiliary search model, bag are set up by historic user behavioral data
Include：Individualized feature data are extracted by historic user behavioral data, individualized feature data include classification preference data, sex
Preference data and recently search data；And set up user's auxiliary search model using individualized feature data.
In a kind of exemplary embodiment of the disclosure, user's auxiliary search model is set up using individualized feature data,
Including：User is set up by classification preference data and aids in search model.
In a kind of exemplary embodiment of the disclosure, user is set up by classification preference data and aids in search model, bag
Include：Obtain historic user behavioral data；Keeper unit data and corresponding classification are extracted by historic user behavioral data
Data；And by keeper unit data and classification data, set up user's auxiliary search model.
In a kind of exemplary embodiment of the disclosure, by keeper unit data and classification data, user is set up
Search model is aided in, including：The first predefined action dependency number is extracted by the corresponding classification data of keeper unit data
According to the second predefined action related data；It is right with it by the first predefined action related data and the second predefined action related data
The score for the Weight Acquisition classification answered；And be ranked up all classifications according to score, obtain predetermined classification numbering.
In a kind of exemplary embodiment of the disclosure, classification score is obtained by equation below：
Wherein, f (uuidM,cid3N) it is user uuidMIn cid3NClassification score under classification N, n1For the first predefined action
Quantity, α be the first predefined action quantity weight, t0 be the first predefined action time of origin, n2For the second predefined action
Quantity, δ is the quantity weight of the second predefined action, and β is the weight of the second predefined action, and t is current time, and t1 is second pre-
Determine the time of origin of behavior.
In a kind of exemplary embodiment of the disclosure, user's auxiliary search model is set up using individualized feature data,
Including：User, which is set up, by boy preference data aids in search model.
In a kind of exemplary embodiment of the disclosure, set up user by boy preference data and aid in search model, bag
Include：User, which is set up, by user's portrait and boy preference data aids in search model.
In a kind of exemplary embodiment of the disclosure, user's auxiliary search model is set up using individualized feature data,
Including：User's auxiliary search model is set up by searching for data recently.
According to an aspect of the invention, it is proposed that a kind of device for being used to aid in search, the device includes：Respond module, is used
ID is obtained in the search operation of response user；Data module, for obtaining user behavior data, Yong Huhang by ID
Include long-term action data and acts and efforts for expediency data for data；Grading module, for user behavior data input user to be aided in
Search model is to obtain alignment score；And supplementary module, for providing auxiliary to the search operation of user according to alignment score
Information.
In a kind of exemplary embodiment of the disclosure, in addition to：Model module, for passing through historic user behavioral data
Set up auxiliary search model.
According to an aspect of the invention, it is proposed that a kind of electronics equipment, the electronic equipment includes：One or more processing
Device；Storage device, for storing one or more programs；When one or more programs are executed by one or more processors, make
Obtain one or more processors and realize such as methodology above.
According to an aspect of the invention, it is proposed that a kind of computer-readable medium, is stored thereon with computer program, its feature
It is, such as methodology above is realized when program is executed by processor.
, can be more according to the method, device, electronic equipment and the computer-readable medium that are used to aid in search of the present invention
User's request is accurately matched, personalized auxiliary search is realized.
It should be appreciated that the general description of the above and detailed description hereinafter are only exemplary, this can not be limited
Invention.
Brief description of the drawings
Its example embodiment is described in detail by referring to accompanying drawing, above and other target, feature and advantage of the invention will
Become more fully apparent.Drawings discussed below is only some embodiments of the present invention, for the ordinary skill of this area
For personnel, on the premise of not paying creative work, other accompanying drawings can also be obtained according to these accompanying drawings.
Fig. 1 is a kind of flow chart for being used to aid in the method for search according to an exemplary embodiment.
Fig. 2 is a kind of processing procedure schematic diagram for being used to aid in the method for search according to an exemplary embodiment.
Fig. 3 is a kind of flow chart for being used to aid in the method for search according to another exemplary embodiment.
Fig. 4 is a kind of processing procedure signal for being used to aid in the method for search according to another exemplary embodiment
Figure.
Fig. 5 is a kind of processing procedure signal for being used to aid in the method for search according to another exemplary embodiment
Figure.
Fig. 6 is a kind of block diagram for being used to aid in the device of search according to an exemplary embodiment.
Fig. 7 is the block diagram of a kind of electronic equipment according to another exemplary embodiment.
Specific embodiment
Example embodiment is described more fully with referring now to accompanying drawing.However, example embodiment can be real in a variety of forms
Apply, and be not understood as limited to embodiment set forth herein；On the contrary, thesing embodiments are provided so that the present invention will be comprehensively and complete
It is whole, and the design of example embodiment is comprehensively conveyed into those skilled in the art.Identical reference is represented in figure
Same or similar part, thus repetition thereof will be omitted.
Implement in addition, described feature, structure or characteristic can be combined in any suitable manner one or more
In example.Embodiments of the invention are fully understood so as to provide there is provided many details in the following description.However,
It will be appreciated by persons skilled in the art that technical scheme can be put into practice without one or more in specific detail,
Or can be using other methods, constituent element, device, step etc..In other cases, it is not shown in detail or describes known side
Method, device, realization operate to avoid fuzzy each aspect of the present invention.
Block diagram shown in accompanying drawing is only functional entity, not necessarily must be corresponding with physically separate entity.
I.e., it is possible to realize these functional entitys using software form, or realized in one or more hardware modules or integrated circuit
These functional entitys, or realize in heterogeneous networks and/or processor device and/or microcontroller device these functional entitys.
Flow chart shown in accompanying drawing is merely illustrative, it is not necessary to including all contents and operation/step,
It is not required to perform by described order.For example, some operation/steps can also be decomposed, and some operation/steps can be closed
And or part merge, therefore the actual order performed is possible to be changed according to actual conditions.
It should be understood that although term first, second, third, etc. may be used to describe various assemblies herein, these groups
Part should not be limited by these terms.These terms are to distinguish a component and another component.Therefore, first group be discussed herein below
Part can be described as teaching of second component without departing from disclosure concept.As used herein, term " and/or " include it is associated
All combinations for listing any one and one or more in project.
It will be understood by those skilled in the art that accompanying drawing is the schematic diagram of example embodiment, module or flow in accompanying drawing
Not necessarily implement the present invention necessary, therefore cannot be used for limiting the scope of the invention.
Disclosure example embodiment is described in detail below in conjunction with the accompanying drawings.
Fig. 1 is a kind of flow chart for being used to aid in the method for search according to an exemplary embodiment.
As shown in figure 1, in S102, responding the search operation of user, ID is obtained.In embodiments of the present invention, may be used
For example operated by monitoring the user on webpage, judge whether user scans for operation.Can be for example, being searched by capturing user
Clicking operation in rope frame, and then judge that user is scanning for operation.When user scans for operation, the use is obtained
The ID at family.ID is obtained when can be for example by user login operation, can also be for example, being obtained by the cookies files in webpage
Take, the present invention is not limited.
In S104, by ID obtain user behavior data, user behavior data include long-term action data with it is short
Phase behavioral data.In embodiments of the present invention, long-term action data may be, for example, the Long-term Interest data of user, can be for example, logical
The purchase or browse operation for crossing the user of this in system obtain the Long-term Interest data of user, and then generate long-term action data.
Acts and efforts for expediency data may be, for example, the short-term interest data of user, can be for example, being generated by the search data of user recently short-term
Interesting data, and then generate acts and efforts for expediency data.
In S106, search model is aided in obtain alignment score user behavior data input user.User's search is auxiliary
Help model can be for example, being set up by the historical operating data of the user, according to the data of acquisition above, user's search auxiliary mould
Type for example can be set up by the long-term action data in the user's history and acts and efforts for expediency data.In the present embodiment, for a long time with
Acts and efforts for expediency data may be, for example, that user, can also be for example, user's history to the data of a certain classification commodity purchasing in the regular period
Search for data.Can for example, building user by substantial amounts of historical data and currently existing mathematical algorithm aids in search model, with
Just when active user scans for operation, to auxiliary information to be given, each entry is ranked up scoring.Can be for example, a certain
User scans for operation, and the word of key entry is " hand ", and the auxiliary information of search can for example provide following drop-down vocabulary：" hand
Machine, wrist-watch, hand frost, storage ", according to the search submodel of user, scores above-mentioned drop-down vocabulary, gives different
The different score value of vocabulary.
In S108, auxiliary information is provided to the search operation of user according to alignment score.As described above, arranged
After sequence scoring, to above-mentioned drop-down vocabulary according to the data of scoring, sequentially it is limited in the combobox of search column.For user A
For, operation is scanned for, the word of key entry is " hand ", and auxiliary information is followed successively by according to scoring：" wrist-watch, mobile phone, hand frost, receipts
Receive ", then auxiliary information is sequentially shown according to the order of " wrist-watch, mobile phone, hand frost, storage " to user A.For user B, enter
Row search operation, the word of key entry is " hand ", and auxiliary information is followed successively by according to scoring：" storage, hand frost, wrist-watch, mobile phone ", then it is right
User B, auxiliary information is sequentially shown according to the order of " storage, hand frost, wrist-watch, mobile phone ".
According to the method for being used to aid in search of the present invention, search auxiliary information is ranked up by the submodel
Scoring, and then by way of the data of scoring sequentially show auxiliary information, can more accurately match user needs
Ask, realize personalized auxiliary search.
It will be clearly understood that the present disclosure describe how forming and use particular example, but the principle of the present invention is not limited to
Any details of these examples.On the contrary, the teaching based on present disclosure, these principles can be applied to many other
Embodiment.
In a kind of exemplary embodiment of the disclosure, in addition to：Auxiliary search is set up by historic user behavioral data
Model.In a kind of exemplary embodiment of the disclosure, auxiliary search model is set up by historic user behavioral data, including：
Individualized feature data are extracted by historic user behavioral data, it is inclined that individualized feature data include classification preference data, sex
Good data and recently search data；And set up user's auxiliary search model using individualized feature data.Fig. 2 is according to another
A kind of processing procedure schematic diagram for being used to aid in the method for search shown in exemplary embodiment.As shown in Fig. 2 historical data
In, including Long-term Interest data and short-term interest data, last interesting data and short-term interest data are subjected to data processing, number
It may be, for example, data cleansing according to processing, original data (Long-term Interest and short-term interest data) obtained after data cleansing
The data message of predetermined format.Data cleansing is the process for carrying out examining and verifying again to data, it is therefore intended that deletes and repeats
Information, the mistake for correcting presence, and data consistency is provided.Can be for example, using ETL data cleansing technologies.ETL data cleansings are
Data pick-up (Extract), conversion (Transform), the process for loading (Load).Generated by the data after data processing
Individualized feature data, set up user by individualized feature data and aid in search model.
Fig. 3 is a kind of flow chart for being used to aid in the method for search according to another exemplary embodiment.Fig. 3 is pair
Set up the exemplary illustration that user aids in search model.
As shown in figure 3, in S302, setting up user by classification preference data and aiding in search model.The one of the disclosure
Plant in exemplary embodiment, setting up user by classification preference data aids in search model, including：Obtain historic user behavior number
According to；Keeper unit data and corresponding classification data are extracted by historic user behavioral data；And pass through quantity in stock list
Position (sku) data and classification data, set up user's auxiliary search model.Growth over time, user browses identical classification
Probability can be greatly decreased.In embodiments of the present invention, it is contemplated that be that classification is directly weighted on line, in order to distinguish difference
Influence of the classification behavior of period to currently sorting, is decayed using greater attenuation function pair classification.The identical classification of user
Navigation patterns are analyzed, and statistics different user browses the frequency analysis of identical classification commodity.
In embodiments of the present invention, sku is keeper unit.Classification may be, for example, cid3, and initial data is obtained first：Number
The sku for browsing and being added to shopping cart of 30 days can for example be gone over from App end datas according to source.Initial data may be, for example, as follows
Form：
User behavior data
| User | Browse sku | time | Sku correspondences cid3 | Behavior |
| uuid1 | sku 7 | 2016/12/8 10:47 | E | Extra bus |
| uuid1 | sku 7 | 2016/12/8 10:46 | E | Browse |
| uuid1 | sku 6 | 2016/12/8 10:46 | E | Browse |
| uuid1 | sku 5 | 2016/12/7 10:45 | B | Browse |
| uuid1 | sku 4 | 2016/12/6 10:45 | W | Browse |
| uuid2 | sku 3 | 2016/12/5 10:45 | D | Browse |
| uuid2 | sku 2 | 2016/12/4 10:45 | C | Browse |
| uuid2 | sku 1 | 2016/12/3 10:45 | A | Extra bus |
| uuid2 | sku 1 | 2016/12/3 10:44 | A | Browse |
| …… |
Then, on the basis of certain one-level classification, such purpose score is calculated.In the present embodiment, with three-level classification score
Exemplified by calculating, the fraction of all sku under certain cid3 is added up, final score of the user in the cid3 is obtained.Calculation formula is under
Exemplary description is carried out in text.
Finally, each cid3 classification score is calculated, user uuid1 is calculated with this, the cid3 where all sku in 30 days
Score, finally according to obtain the row of pouring in separately output.Simply can be for example, only selecting the top of each user of generation in order to calculate
Cid3list, top cid3list are first 10 of a certain user classifications most liked.
User 1
| Sequence number | User Top cid3list |
| 1 | A |
| 2 | B |
| 3 | C |
| 4 | D |
| 5 | E |
| 6 | F |
| 7 | G |
| 8 | H |
| 9 | I |
| 10 | J |
In a kind of exemplary embodiment of the disclosure, by keeper unit data and classification data, user is set up
Search model is aided in, including：The first predefined action dependency number is extracted by the corresponding classification data of keeper unit data
According to the second predefined action related data；It is right with it by the first predefined action related data and the second predefined action related data
The score for the Weight Acquisition classification answered；And be ranked up all classifications according to score, obtain predetermined classification numbering.At this
In inventive embodiments, the high relevant classification information of three-level belonging to commodity.First predefined action may be, for example, " extra bus " behavior, be
User adds sku to the behavior of shopping cart.Second predefined action may be, for example, " browsing ", the sku that as user browses.
In embodiments of the present invention, the shopping row of the ageing of model, commodity number and user is considered, by as follows
Formula obtains classification score：
Wherein, f (uuidM,cid3N) it is user uuidMIn cid3NClassification score under classification N, n1For the first predefined action
Quantity, α be the first predefined action quantity weight, t0 be the first predefined action time of origin, n2For the second predefined action
Quantity, δ is the quantity weight of the second predefined action, and β is the weight of the second predefined action, and t is current time, and t1 is second pre-
Determine the time of origin of behavior.
In S304, set up user by boy preference data and aid in search model.In a kind of exemplary reality of the disclosure
Apply in example, setting up user by boy preference data aids in search model, including：Built by user's portrait with boy preference data
Vertical user's auxiliary search model.The sex that user's portrait module obtains user is introduced, it is inclined according to the word of query words portrait-sex
It is good to be matched.Sex Portrait brand technology method is as follows in specific word portrait：
1. field attribute explanation
Word _ sex character=score, score belongs to [0,1000], and numerical value is bigger, and masculinity is stronger, for not when being 0
Know, be 400~500 or be neutral during a middle interval.
2. the scheme of excavation
The other data of authenticity screened from registered user take male, the word of the term of women as sample
Collection, calculates the probability that word X occurs in male's set A and women set B respectively；Word is used in combination in man by bayesian theory
The frequency and the scale factor of word that occur in property sample represents the male gender feature of word.
Mark purpose be in order to word mark it is upper based on the fact that correct sex, it is special that such as " lipstick " is labeled as strong women
Levy.Can also be for example, marking the sex for giving platform user use habit to word, such as hypothesis " lipstick " is all that boy student buys, then
" lipstick " is labeled as strong masculinity；(most of boy student buys, then pushes away being appreciated that to boy student).
A. for each word in test set, N number of sample is taken (to search the people of this word in others in having learned that property
And known sex men and women for a sample)；
| Word | Total number of samples amount | Set A=men | Set B=female |
| Word X1 | N=X1,1+X1,2 | X1,1 | X1,2 |
| Word X2 | N=X2,1+X2,2 | X2,1 | X2,2 |
| Word X3 | N=X3,1+X3,2 | X3,1 | X3,2 |
| …… | …… | …… | …… |
| Word Xn | N=Xn,1+Xn,2 | Xn,1 | Xn,2 |
B. according to bayesian theory, the probability that male user is searched in word Xn is P (Xn,1|Xn)=(Xn,1/ N), for the word
Masculinity；Word XnThe probability of middle female user search is P (Xn,2|Xn)=(Xn,2/ N)=1-P (Xn,2|Xn)。
C. the probability (changing word frequency of occurrence/total frequency of word set) or the frequency occurred using the word in complete or collected works is used as scale
The factor.
D. the male gender of word is inclined to p=(scale factor) × (Xn,1/N)。
In embodiments of the present invention, can be for example, in user's auxiliary search model, being set not for different boy preferences
Same weight, with the prioritizing selection when carrying out assistance messages push.
In S304, user's auxiliary search model is set up by searching for data recently.Using clickstream data, obtain nearest
The history word of search.The flow chart shown in Fig. 4 is referred to, user clickstream is received, message tuple is parsed, parses message tuple
In relevant information, may be, for example, ID and search term, and above- mentioned information is preserved.User's auxiliary search is being supplied in real time
During information, nearest N bars user search record is obtained by storing and calling in real time.Member correspondence user's search terms；score
Correspondence association member timestamp, storing order may be, for example,：zAdd key member score.
According to the method for being used to aid in search of the present invention, user is set up by classification preference data and aids in search model,
Numerical procedure formula simple effects substantially, are applicable the classification preference for calculating user very much, future individualized ubiquitous, in electric business
The personalization most often having i.e. user's classification preference, rear extended meeting largely supports business demand using this method.
According to the method for being used to aid in search of the present invention, set up user by boy preference data and aid in search model,
In the prior art, the feature possessed in itself using word is excavated, in the present invention, according to the behavior of a large amount of known users sexes profit
Remember scale factor to count whether the word has boy preference with Bayesian probability, can obtain accurately distinguishing result.
Fig. 5 is a kind of processing procedure signal for being used to aid in the method for search according to another exemplary embodiment
Figure.
Flow as shown in Figure 5, can be according to the number of user individual according to the method for being used to aid in search of the present invention
According to setting up the search submodel for different user, and then the different search auxiliary informations of offer in the face of thousand people thousand.Can also example
Such as there is provided simple and effective calculating classification preference methods formula, it is easy to rapid multiplexing.Individualized experience is introduced, user's body is lifted
Test, and lifting user's conversion ratio.Exemplified by searching for auxiliary product drop-down word, specific personalized application bandwagon effect is as follows：
1st, the user id of service is pulled down according to request, nearest search term is obtained, its prefix is set up to its nearest search term
Inverted index, if the prefix of user's input is matching, takes nearest one as first drop-down word.If unmatching,
Skip.
2nd, the user id of service is pulled down according to request, the classification preference of user is obtained, to the drop-down word candidate of certain prefix word
User's search keyword of concentration, if its high relevant classification is the preference classification of user, adds according to preference weight * coefficients to it
Divide before row.
3rd, identical class has boy preference now, for jeans, for male, typically likes search jeans man,
And for women, general ox trousers female's broken hole, Korea Spro's version etc., whether boy preference is had according to the above-mentioned word that we excavate, to enter
Row precisely matching.According to user id association users portrait module, user's sex is obtained.Under being obtained further according to the prefix that user inputs
Candidate Set is drawn, according to the boy preference and preference weight of these user's search keywords, is matched with user's sex, reinforced platoon is carried out
Before.
It will be appreciated by those skilled in the art that realizing that all or part of step of above-described embodiment is implemented as being performed by CPU
Computer program.When the computer program is performed by CPU, the above-mentioned work(that the above method of the invention provided is limited is performed
Energy.Described program can be stored in a kind of computer-readable recording medium, and the storage medium can be read-only storage, magnetic
Disk or CD etc..
Further, it should be noted that above-mentioned accompanying drawing is only the place included by method according to an exemplary embodiment of the present invention
That manages schematically illustrates, rather than limitation purpose.It can be readily appreciated that above-mentioned processing shown in the drawings is not intended that or limited at these
The time sequencing of reason.In addition, being also easy to understand, these processing for example can be performed either synchronously or asynchronously in multiple modules.
Following is apparatus of the present invention embodiment, can be used for performing the inventive method embodiment.It is real for apparatus of the present invention
The details not disclosed in example is applied, the inventive method embodiment is refer to.
Fig. 6 is a kind of block diagram for being used to aid in the device of search according to an exemplary embodiment.
The search operation that respond module 602 is used to respond user obtains ID.
Data module 604 is used to obtain user behavior data by ID, and user behavior data includes long-term action number
According to acts and efforts for expediency data.
Grading module 606 is used to user behavior data input user auxiliary search model obtain alignment score.
Supplementary module 608 is used to provide auxiliary information to the search operation of user according to alignment score.
According to the device for being used to aid in search of the present invention, search auxiliary information is ranked up by the submodel
Scoring, and then by way of the data of scoring sequentially show auxiliary information, can more accurately match user needs
Ask, realize personalized auxiliary search.
In a kind of exemplary embodiment of the disclosure, in addition to：Model module (not shown) is used to pass through history
User behavior data sets up auxiliary search model.
Fig. 7 is the block diagram of a kind of electronic equipment according to another exemplary embodiment.
Below with reference to Fig. 7, it illustrates suitable for for the structural representation for the electronic equipment 70 for realizing the embodiment of the present application.
Electronics equipment shown in Fig. 7 is only an example, should not come any to the function of the embodiment of the present application and using range band
Limitation.
As shown in fig. 7, computer system 70 includes CPU (CPU) 701, it can be according to being stored in read-only deposit
Program in reservoir (ROM) 702 is held from the program that storage part 708 is loaded into random access storage device (RAM) 703
Row various appropriate actions and processing.In RAM 703, the system that is also stored with 70 operates required various programs and data.
CPU701, ROM 702 and RAM 703 are connected with each other by bus 704.Input/output (I/O) interface 705 is also connected to always
Line 704.
I/O interfaces 705 are connected to lower component：Importation 706 including keyboard, mouse etc.；Penetrated including such as negative electrode
The output par, c 707 of spool (CRT), liquid crystal display (LCD) etc. and loudspeaker etc.；Storage part 708 including hard disk etc.；
And the communications portion 709 of the NIC including LAN card, modem etc..Communications portion 709 via such as because
The network of spy's net performs communication process.Driver 710 is also according to needing to be connected to I/O interfaces 705.Detachable media 711, such as
Disk, CD, magneto-optic disk, semiconductor memory etc., are arranged on driver 710, in order to read from it as needed
Computer program be mounted into as needed storage part 708.
Especially, in accordance with an embodiment of the present disclosure, the process described above with reference to flow chart may be implemented as computer
Software program.For example, embodiment of the disclosure includes a kind of computer program product, it includes being carried on computer-readable medium
On computer program, the computer program include be used for execution flow chart shown in method program code.In such reality
Apply in example, the computer program can be downloaded and installed by communications portion 709 from network, and/or from detachable media
711 are mounted.When the computer program is performed by CPU (CPU) 701, limited in the system for performing the application
Above-mentioned functions.
It should be noted that the computer-readable medium shown in the application can be computer-readable signal media or meter
Calculation machine readable storage medium storing program for executing either the two any combination.Computer-readable recording medium for example can be --- but not
Be limited to --- electricity, magnetic, optical, electromagnetic, system, device or the device of infrared ray or semiconductor, or it is any more than combination.Meter
The more specifically example of calculation machine readable storage medium storing program for executing can include but is not limited to：Electrical connection with one or more wires, just
Take formula computer disk, hard disk, random access storage device (RAM), read-only storage (ROM), erasable type and may be programmed read-only storage
Device (EPROM or flash memory), optical fiber, portable compact disc read-only storage (CD-ROM), light storage device, magnetic memory device,
Or above-mentioned any appropriate combination.In this application, computer-readable recording medium can any include or store journey
The tangible medium of sequence, the program can be commanded execution system, device or device and use or in connection.And at this
In application, computer-readable signal media can be included in a base band or as the data-signal of carrier wave part propagation,
Wherein carry computer-readable program code.The data-signal of this propagation can take various forms, including but not limit
In electromagnetic signal, optical signal or above-mentioned any appropriate combination.Computer-readable signal media can also be that computer can
Any computer-readable medium beyond storage medium is read, the computer-readable medium, which can send, propagates or transmit, to be used for
Used by instruction execution system, device or device or program in connection.Included on computer-readable medium
Program code can be transmitted with any appropriate medium, be included but is not limited to：Wirelessly, electric wire, optical cable, RF etc., or above-mentioned
Any appropriate combination.
Flow chart and block diagram in accompanying drawing, it is illustrated that according to the system of the various embodiments of the application, method and computer journey
Architectural framework in the cards, function and the operation of sequence product.At this point, each square frame in flow chart or block diagram can generation
The part of one module of table, program segment or code, a part for above-mentioned module, program segment or code is comprising one or more
Executable instruction for realizing defined logic function.It should also be noted that in some realizations as replacement, institute in square frame
The function of mark can also be with different from the order marked in accompanying drawing generation.For example, two square frames succeedingly represented are actual
On can perform substantially in parallel, they can also be performed in the opposite order sometimes, and this is depending on involved function.Also
It is noted that the combination of each square frame in block diagram or flow chart and the square frame in block diagram or flow chart, can use and perform rule
Fixed function or the special hardware based system of operation realize, or can use the group of specialized hardware and computer instruction
Close to 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 can also be set within a processor, for example, can be described as：A kind of processor bag
Include transmitting element, acquiring unit, determining unit and first processing units.Wherein, the title of these units is under certain conditions simultaneously
The restriction in itself to the unit is not constituted, for example, transmitting element is also described as " sending picture to the service end connected
Obtain the unit of request ".
As on the other hand, present invention also provides a kind of computer-readable medium, the computer-readable medium can be
Included in equipment described in above-described embodiment；Can also be individualism, and without be incorporated the equipment in.Above-mentioned calculating
Machine computer-readable recording medium carries one or more program, when said one or multiple programs are performed by the equipment, makes
Obtaining the equipment includes：The search operation of user is responded, ID is obtained；User behavior data, Yong Huhang are obtained by ID
Include long-term action data and acts and efforts for expediency data for data；Search model is aided in obtain user behavior data input user
Alignment score；And provide auxiliary information to the search operation of user according to alignment score.
It will be appreciated by those skilled in the art that above-mentioned each module can be distributed in device according to the description of embodiment, also may be used
To carry out respective change uniquely different from one or more devices of the present embodiment.The module of above-described embodiment can be merged into
One module, can also be further split into multiple submodule.
The description of embodiment more than, those skilled in the art is it can be readily appreciated that example embodiment described herein
It can be realized, can also be realized by way of software combines necessary hardware by software.Therefore, according to present invention implementation
The technical scheme of example can be embodied in the form of software product, and the software product can be stored in a non-volatile memories
In medium (can be CD-ROM, USB flash disk, mobile hard disk etc.) or on network, including some instructions are make it that a computing device (can
To be personal computer, server, mobile terminal or network equipment etc.) perform method according to embodiments of the present invention.
Detailed description more than, those skilled in the art are it can be readily appreciated that according to embodiments of the present invention being used for is auxiliary
Method, device, electronic equipment and the computer-readable medium of search is helped to have one or more of the following advantages.
According to some embodiments, the method for being used to aid in search of the invention is aided in search by the submodel
Information is ranked up scoring, and then by way of the data of scoring sequentially show auxiliary information, can be more accurate
Matching user's request, realize personalized auxiliary search.
According to other embodiments, the method for being used to aid in search of the invention sets up user by classification preference data
Search model is aided in, numerical procedure formula simple effects substantially, are applicable the classification preference for calculating user, future individualized nothing very much
Place does not exist, the personalization most often having in electric business i.e. user's classification preference, and rear extended meeting largely supports business demand using this method.
According to still other embodiments, the method for being used to aid in search of the invention sets up user by boy preference data
Search model is aided in, in the prior art, feature in itself that possess using word is excavated, in the present invention, according to a large amount of known use
The Behavioral availability Bayesian probability of family sex remembers scale factor to count whether the word has boy preference, can obtain accurately
Distinguish result.
The exemplary embodiment of the present invention is particularly shown and described above.It should be appreciated that the invention is not restricted to
Detailed construction described herein, set-up mode or implementation method；On the contrary, it is intended to cover included in appended claims
Various modifications and equivalence setting in spirit and scope.
In addition, structure, ratio, size shown by this specification Figure of description etc., only to coordinate specification institute
Disclosure, for skilled in the art realises that with reading, be not limited to the enforceable qualifications of the disclosure, therefore
Do not have technical essential meaning, the modification of any structure, the change of proportionate relationship or the adjustment of size are not influenceing the disclosure
Under the technique effect that can be generated and achieved purpose, it all should still fall and obtain and can cover in the technology contents disclosed in the disclosure
In the range of.Meanwhile, in this specification it is cited such as " on ", " first ", the term of " second " and " one ", be also only and be easy to
Narration understands, and is not used to limit the enforceable scope of the disclosure, and its relativeness is altered or modified, without substantive change
Under technology contents, when being also considered as enforceable category of the invention.
Claims (14)
1. a kind of method for being used to aid in search, it is characterised in that including：
The search operation of user is responded, ID is obtained；
User behavior data is obtained by the ID, the user behavior data includes long-term action data and acts and efforts for expediency
Data；
Search model is aided in obtain alignment score user behavior data input user；And
According to the alignment score auxiliary information is provided to the search operation of the user.
2. the method as described in claim 1, it is characterised in that also include：
The auxiliary search model is set up by historic user behavioral data.
3. method as claimed in claim 2, it is characterised in that described to set up the auxiliary by historic user behavioral data and search
Rope model, including：
Individualized feature data are extracted by the historic user behavioral data, the individualized feature data include classification preference
Data, boy preference data and data are searched for recently；And
User's auxiliary search model is set up using the individualized feature data.
4. method as claimed in claim 3, it is characterised in that described to set up user's auxiliary using the individualized feature data
Search model, including：
The user is set up by the classification preference data and aids in search model.
5. method as claimed in claim 4, it is characterised in that described to set up the user by the classification preference data auxiliary
Search model is helped, including：
Obtain historic user behavioral data；
Keeper unit data and corresponding classification data are extracted by historic user behavioral data；And
By the keeper unit data and the classification data, user's auxiliary search model is set up.
6. method as claimed in claim 5, it is characterised in that described to pass through the keeper unit data and the classification
Data, set up user's auxiliary search model, including：
The first predefined action related data and the second predetermined row are extracted by the corresponding classification data of keeper unit data
For related data；
By the first predefined action related data and the corresponding Weight Acquisition classification of the second predefined action related data
Point；And
All classifications are ranked up according to score, predetermined classification numbering is obtained.
7. method as claimed in claim 6, it is characterised in that the classification score is obtained by equation below：
<mrow>
<mi>f</mi>
<mrow>
<mo>(</mo>
<msub>
<mi>uuid</mi>
<mi>M</mi>
</msub>
<mo>,</mo>
<mi>c</mi>
<mi>i</mi>
<mi>d</mi>
<msub>
<mn>3</mn>
<mi>N</mi>
</msub>
<mo>)</mo>
</mrow>
<mo>=</mo>
<munderover>
<mo>&Sigma;</mo>
<mn>1</mn>
<msub>
<mi>n</mi>
<mn>1</mn>
</msub>
</munderover>
<msup>
<mi>e</mi>
<mrow>
<mo>-</mo>
<mi>&alpha;</mi>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>-</mo>
<mi>t</mi>
<mn>0</mn>
<mo>)</mo>
</mrow>
</mrow>
</msup>
<mo>+</mo>
<mi>&beta;</mi>
<munderover>
<mo>&Sigma;</mo>
<mn>1</mn>
<msub>
<mi>n</mi>
<mn>2</mn>
</msub>
</munderover>
<msup>
<mi>e</mi>
<mrow>
<mo>-</mo>
<mi>&delta;</mi>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>-</mo>
<mi>t</mi>
<mn>1</mn>
<mo>)</mo>
</mrow>
</mrow>
</msup>
<mo>;</mo>
</mrow>
Wherein, f (uuidM,cid3N) it is user uuidMIn cid3NClassification score under classification N, t is current time, n1For first
The quantity of predefined action, α is the quantity weight of the first predefined action, and t0 is the time of origin of the first predefined action, n2For second
The quantity of predefined action, δ is the quantity weight of the second predefined action, and β is the weight of the second predefined action, and t1 is the second predetermined row
For time of origin.
8. method as claimed in claim 3, it is characterised in that described to set up user's auxiliary using the individualized feature data
Search model, including：
The user, which is set up, by the boy preference data aids in search model.
9. method as claimed in claim 8, it is characterised in that described to set up the user by the boy preference data auxiliary
Search model is helped, including：
The user, which is set up, by user's portrait and the boy preference data aids in search model.
10. method as claimed in claim 3, it is characterised in that it is auxiliary that the utilization individualized feature data set up user
Search model is helped, including：
The user, which is set up, by the nearest search data aids in search model.
11. a kind of device for being used to aid in search, it is characterised in that including：
Respond module, the search operation for responding user obtains ID；
Data module, for obtaining user behavior data by the ID, the user behavior data includes long-term action
Data and acts and efforts for expediency data；
Grading module, for user behavior data input user auxiliary search model to be obtained into alignment score；And
Supplementary module, for providing auxiliary information to the search operation of the user according to the alignment score.
12. device as claimed in claim 11, it is characterised in that also include：
Model module, for setting up the auxiliary search model by historic user behavioral data.
13. a kind of electronic equipment, it is characterised in that including：
One or more processors；
Storage device, for storing one or more programs；
When one or more of programs are by one or more of computing devices so that one or more of processors are real
The existing method as described in any in claim 1-10.
14. a kind of computer-readable medium, is stored thereon with computer program, it is characterised in that described program is held by processor
The method as described in any in claim 1-10 is realized during row.
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