CN110472146A - Service recommendation method and device, storage medium and computer equipment under line - Google Patents
Service recommendation method and device, storage medium and computer equipment under line Download PDFInfo
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- 238000003066 decision tree Methods 0.000 claims description 4
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Abstract
The invention discloses service recommendation methods under a kind of line and device, storage medium and computer equipment, wherein service recommendation method includes: to obtain user's representation data, user respectively to be presently in corresponding second contextual data of corresponding first contextual data in position and user's history visiting position under the line, wherein the corresponding scene of first contextual data and the corresponding scene of second contextual data are associated；User's representation data, first contextual data and second contextual data are inputted preset prediction model to handle；The prediction data of the reflection potential demand for services project of user exported after prediction model processing is obtained, and the prediction data is sent to client.The present invention solves in the prior art, objective demand under the line of user is seen clearly it is poor, cannot in time the real scene according to locating for user carry out targetedly service recommendation the problem of.
Description
Technical field
The present invention relates to scene service recommendation applied technical fields under line, more particularly to service recommendation method under a kind of line
With device, storage medium and computer equipment.
Background technique
Scene recommendation refers to based on excavation, tracking and the analysis to user data, by time, place, user and relationship
Under the special scenes of composition, connect the behavior of user online and offline, understand and judge the emotion, attitude and demand of user, for
Family provides real-time, orientation, the information and content service of intention, by the interactive communication with user, Branding image or promotion
Conversion ratio realizes the behavior precisely recommended.Instantly, Internet population bonus fades away, and flow cost rises gradually on line.With
This simultaneously, user starts under strike line, and value trend of marketing under line increasingly highlights, and gets through on line data under data and line
Scene marketing, it will the new selection as each side role in marketing industrial chain.Traditional way of recommendation is primarily present following
Problem: the first, behavior and simple ascribed characteristics of population information on the line of user are mainly based upon and is recommended, under the line of user
Objective demand is seen clearly poor；The second, cannot targetedly be recommended the real scene according to locating for user in time.
Summary of the invention
The embodiment of the present invention provides service recommendation method and device, storage medium and computer equipment under a kind of line, with solution
Certainly in the prior art, objective demand under the line of user and potential demand are seen clearly it is poor, cannot be in time according to locating for user
Real scene carry out targetedly service recommendation the problem of.
In order to solve the above technical problems, the first technical solution used in the embodiment of the present invention is as follows:
Service recommendation method under a kind of line, comprising: obtain that user's representation data, that user is presently in position is corresponding respectively
Corresponding second contextual data of first contextual data and user's history visiting position, wherein the corresponding field of first contextual data
Scape and the corresponding scene of second contextual data are associated；By user's representation data, first contextual data and institute
The preset prediction model of the second contextual data input is stated to be handled；Obtain the reflection exported after prediction model processing
The prediction data of the potential demand for services project of user, and the prediction data is sent to client.
Optionally, acquisition user's representation data, comprising: send user's portrait request letter to first object server
Breath；Receive the corresponding user's representation data of user that the first object server returns.
Optionally, the acquisition user is presently in corresponding first contextual data in position, comprising: receives user and uses visitor
The user that family end is sent is presently in the corresponding geomagnetic data in position, WIFI data and the corresponding device id number of the client
According to；According to the geomagnetic data, the WIFI data and the device id data, it is corresponding to identify that user is presently in position
Current scene information；User, which is obtained, according to the current scene information is presently in corresponding first contextual data in position.
Optionally, corresponding second contextual data in acquisition user's history visiting position, comprising: to the second destination service
Device sends historic scenery data request information；It is corresponding to receive the user's history visiting position that second destination server returns
Second contextual data.
Optionally, first contextual data includes scene service item information, the scene title letter that the first scene includes
Breath, scene purposes information and scene address information.
Optionally, second contextual data includes scene service item information, the scene title letter that the second scene includes
The scene service item information of breath, scene purposes information, scene address information and user's history preference.
Optionally, the prediction model is one of LSTM model, Logic Regression Models and decision-tree model model.
In order to solve the above technical problems, the second technical solution used in the embodiment of the present invention is as follows:
Service recommendation device under a kind of line comprising: module is obtained, for obtaining user's representation data, user respectively
It is presently in corresponding second contextual data of corresponding first contextual data in position and user's history visiting position, wherein described the
The corresponding scene of one contextual data and the corresponding scene of second contextual data are associated；Processing module is used for the use
Family representation data, first contextual data and second contextual data input preset prediction model and are handled；It sends
Module, for obtaining the prediction data of the reflection potential demand for services project of user exported after prediction model processing,
And the prediction data is sent to client.
In order to solve the above technical problems, third technical solution used in the embodiment of the present invention is as follows:
A kind of storage medium is stored thereon with computer program, and it is such as above-mentioned that the computer program is performed realization
Dialing Method.
In order to solve the above technical problems, the 4th technical solution used in the embodiment of the present invention is as follows:
A kind of computer equipment comprising processor, memory and be stored on the memory and can be in the processing
The computer program run on device, the processor realize such as above-mentioned Dialing Method when executing the computer program.
The beneficial effect of the embodiment of the present invention is: being in contrast to the prior art, under a kind of line of the embodiment of the present invention
Service recommendation method and device, storage medium and computer equipment, by the way that user's representation data, user are presently in position pair
Corresponding second contextual data in the first contextual data and user's history visiting position answered inputs at preset prediction model
Reason obtains the prediction data of the reflection potential demand for services project of user exported after prediction model processing, and by institute
It states prediction data and is sent to client for user's selection, this method can effectively combine scene preference and user's row under user's line
For track, service recommendation under line is carried out, the behavior based on scene under line can more in time, accurately see clearly the objective demand of user
And potential demand, preferably recommendation service under line is provided for user.
Detailed description of the invention
Fig. 1 be the embodiment of the present invention one line under one embodiment of service recommendation method implementation flow chart；
Fig. 2 be the embodiment of the present invention two line under one embodiment of service recommendation device part-structure frame diagram；
Fig. 3 is the part-structure frame diagram of one embodiment of storage medium of the embodiment of the present invention three；
Fig. 4 is the part-structure frame diagram of one embodiment of computer equipment of the embodiment of the present invention four.
Specific embodiment
Embodiment one
Referring to Fig. 1, Fig. 1 be the embodiment of the present invention line under service recommendation method implementation flow chart.It refering to fig. 1 can be with
It obtains, service recommendation method under line of the invention, comprising the following steps:
Step S101: user's representation data is obtained respectively, user is presently in corresponding first contextual data in position and use
Corresponding second contextual data in family history visiting position.Wherein, the corresponding scene of first contextual data and second described
The corresponding scene of scape data is associated, that is, the corresponding scene of second contextual data got and first contextual data
Corresponding scene is similar or even identical, so that the scene preference to user makes accurate judgement.
In this step, whether user's representation data includes the gender of user, age bracket, educational background, consuming capacity, has
The information such as vehicle, style of cooking preference, style of cooking Brang Preference, shopping preferences and shopping genre preference.
Step S102: user's representation data, first contextual data and second contextual data are inputted pre-
If prediction model handled.
In this step, optionally, the prediction model is in LSTM model, Logic Regression Models and decision-tree model
A kind of model.Wherein, LSTM (Long Short-Term Memory) is shot and long term memory network, is a kind of time circulation nerve
Network is suitable for being spaced and postpone relatively long critical event in processing and predicted time sequence.Logic Regression Models are one
The predictive modeling technique of kind, what it was studied is the relationship between dependent variable (target) and independent variable (fallout predictor).This technology
Commonly used in forecast analysis, causality between time series models and discovery variable, such as driver drive rashly with
Relationship between road traffic accident quantity, best research method are exactly to return.Decision-tree model is exactly by decision point, strategy
The arborescence that point (case point) and result are constituted, is generally used in Sequence Decision, usually with maximum return desired value or minimum
Expected cost is solved the benefit value of all kinds of schemes at different conditions by graphic mode, then passes through ratio as decision rule
Compared with making a policy.
In the present embodiment, optionally, when model training, trained purpose acquires user to various labels
Preference weight.It is that the label of the label in shop and user preference is done into intersection when recommendation, the intersection the more, illustrate that preference is weighed
Again bigger, final marking is also higher, i.e., expression user gets over preference.Model when input data, can by input data into
Row labelization processing, the history visiting data of user may be as a plurality of training data, such as user's history was visited quotient
Adidas (Adidas) shop, the shop adidas established in 1949, be German sporting goods manufacturer Adidas AG at
Member company, then can construct following several training samples:
First, user is presently in scene (market), user tag information, user portrait information, current slot, mark
Label are preference clothes shop.
Article 2, user are presently in scene (market), user tag information, user portrait information, current slot, mark
Label are preference sports wear style.
Article 3, user are presently in scene (market), user tag information, user portrait information, current slot, mark
Label are preference middle-grade.
When actual prediction, it can be believed according to user's current label information, model label preference weight and POI label
Breath, acquires user in current scene most preference POI.Wherein, POI is the abbreviation of " Point of Interest ", and Chinese can turn over
It is translated into " point of interest ".In GIS-Geographic Information System, a POI can be a house, a retail shop, a mailbox, a public affairs
Hand over station etc..POI label information includes the information categories such as the food and drink style of cooking, shopping category, class, pre-capita consumption, style and brand.
Step S103: the pre- of the reflection potential demand for services project of user exported after prediction model processing is obtained
Measured data, and the prediction data is sent to client.
In the present embodiment, optionally, acquisition user's representation data, comprising:
First, user's portrait solicited message is sent to first object server, wherein the first object server stores
There is user's representation data.
Second, receive the corresponding user's representation data of user that the first object server returns.
In the present embodiment, optionally, the acquisition user is presently in corresponding first contextual data in position, comprising:
First, user, which is received, using the user that client is sent is presently in the corresponding geomagnetic data in position, WIFI data
And the corresponding device id data of the client.
Second, according to the geomagnetic data, the WIFI data and the device id data, identify that user is presently in
The corresponding current scene information in position.
Third obtains user according to the current scene information and is presently in corresponding first contextual data in position.
In the present embodiment, optionally, corresponding second contextual data in acquisition user's history visiting position, comprising:
First, historic scenery data request information is sent to the second destination server, wherein second destination server
It is stored with second contextual data.
Second, receive the corresponding second scene number in user's history visiting position that second destination server returns
According to.
In the present embodiment, optionally, first contextual data includes the scene service item letter that the first scene includes
Breath, scene name information, scene purposes information and scene address information.
In the present embodiment, optionally, second contextual data includes the scene service item letter that the second scene includes
Breath, scene name information, scene purposes information, the scene service item information of scene address information and user's history preference.
Wherein, first contextual data and the corresponding scene of second contextual data include comprehensive scene and subdivision field
Scape, comprehensive scene includes the scenes such as market, hospital, school and airport, a part scene in the comprehensive scene of subdivision scene, example
Some shop in such as market, such as (shop includes following information: the pre-capita consumption amount of money, the style of cooking and brand to seabed fishing chafing dish restaurant
Etc. information), the clothes shop adidas (shop includes following information: the information such as garment language, brand and class) in market and
Some department in hospital etc..
The embodiment of the present invention is by being presently in corresponding first contextual data in position and use for user's representation data, user
Corresponding second contextual data in family history visiting position inputs preset prediction model and is handled, and obtains and passes through the prediction mould
The prediction data of the reflection potential demand for services project of user exported after type processing, and the prediction data is sent to client
It is selected for user, this method can effectively combine scene preference and user behavior track under user's line, and the service under line that carries out pushes away
Recommend, the behavior based on scene under line can more in time, accurately see clearly the objective demand and potential demand of user, preferably for
Family provides recommendation service under line.
Embodiment two
Referring to Fig. 2, Fig. 2 be the embodiment of the present invention line under service recommendation device part-structure frame diagram.Refering to fig. 1
It is available, service recommendation device 100 under line of the invention, comprising:
Obtain module 110, for obtaining user's representation data respectively, user be presently in the corresponding first scene number in position
According to corresponding second contextual data in user's history visiting position, wherein the corresponding scene of first contextual data and described the
The corresponding scene of two contextual datas is associated.
Processing module 120 is used for user's representation data, first contextual data and second contextual data
Preset prediction model is inputted to be handled.
Sending module 130, for obtaining the potential demand for services of reflection user exported after prediction model processing
The prediction data of project, and the prediction data is sent to client.
Service recommendation device 100 under the line of the embodiment of the present invention, by the way that user's representation data, user are presently in position
Corresponding second contextual data of corresponding first contextual data and user's history visiting position inputs preset prediction model and carries out
Processing obtains the prediction data of the reflection potential demand for services project of user exported after prediction model processing, and will
The prediction data is sent to client and selects for user, and this method can effectively combine scene preference and user under user's line
Action trail, carries out service recommendation under line, and the behavior based on scene under line can more in time, accurately see clearly the objective need of user
Summation potential demand, preferably provides recommendation service under line for user.
Embodiment three
Referring to Fig. 3, can see with reference to Fig. 3, a kind of storage medium 10 of the embodiment of the present invention, the storage medium
10, such as: ROM/RAM, magnetic disk, CD are stored thereon with computer program 11, and the computer program 11 is performed realization
Service recommendation method under line as described in embodiment one.Since service recommendation method has carried out in detail in embodiment one under the line
Thin explanation, this will not be repeated here.
Service recommendation method under the line that the embodiment of the present invention is realized, by the way that user's representation data, user are presently in position
Set corresponding second contextual data of corresponding first contextual data and user's history visiting position input preset prediction model into
Row processing obtains the prediction data of the reflection potential demand for services project of user exported after prediction model processing, and
The prediction data is sent to client to select for user, this method can effectively combine scene preference and use under user's line
Family action trail, carries out service recommendation under line, and the behavior based on scene under line more timely, accurate can see clearly the objective of user
Demand and potential demand preferably provide recommendation service under line for user.
Example IV
Referring to Fig. 4, can see with reference to Fig. 4, a kind of computer equipment 20 of the embodiment of the present invention comprising processor
21, memory 22 and it is stored in the computer program 221 that can be run on the memory 22 and on the processor 21, it is described
Processor 21 realizes service recommendation method under the line as described in embodiment one when executing the computer program 221.Due to the line
Lower service recommendation method is described in detail in embodiment one, and this will not be repeated here.
Service recommendation method under the line that the embodiment of the present invention is realized, by the way that user's representation data, user are presently in position
Set corresponding second contextual data of corresponding first contextual data and user's history visiting position input preset prediction model into
Row processing obtains the prediction data of the reflection potential demand for services project of user exported after prediction model processing, and
The prediction data is sent to client to select for user, this method can effectively combine scene preference and use under user's line
Family action trail, carries out service recommendation under line, and the behavior based on scene under line more timely, accurate can see clearly the objective of user
Demand and potential demand preferably provide recommendation service under line for user.
Mode the above is only the implementation of the present invention is not intended to limit the scope of the invention, all to utilize this
Equivalent structure or equivalent flow shift made by description of the invention and accompanying drawing content, it is relevant to be applied directly or indirectly in other
Technical field is included within the scope of the present invention.
Claims (10)
1. service recommendation method under a kind of line characterized by comprising
Obtain user's representation data respectively, user is presently in corresponding first contextual data in position and user's history visiting position
Corresponding second contextual data, wherein the corresponding scene of first contextual data and the corresponding scene of second contextual data
It is associated；
By user's representation data, first contextual data and second contextual data input preset prediction model into
Row processing；
The prediction data of the reflection potential demand for services project of user exported after prediction model processing is obtained, and by institute
It states prediction data and is sent to client.
2. service recommendation method under line according to claim 1, which is characterized in that acquisition user's representation data, packet
It includes:
User's portrait solicited message is sent to first object server；
Receive the corresponding user's representation data of user that the first object server returns.
3. service recommendation method under line according to claim 1, which is characterized in that the acquisition user is presently in position
Corresponding first contextual data, comprising:
It receives user and is presently in the corresponding geomagnetic data in position, WIFI data and the client using the user that client is sent
Hold corresponding device id data；
According to the geomagnetic data, the WIFI data and the device id data, it is corresponding to identify that user is presently in position
Current scene information；
User, which is obtained, according to the current scene information is presently in corresponding first contextual data in position.
4. service recommendation method under line according to claim 1, which is characterized in that acquisition user's history visiting position
Corresponding second contextual data, comprising:
Historic scenery data request information is sent to the second destination server；
Receive corresponding second contextual data in user's history visiting position that second destination server returns.
5. service recommendation method under line according to claim 1, which is characterized in that first contextual data includes first
Scene service item information, scene name information, scene purposes information and the scene address information that scene includes.
6. service recommendation method under line according to claim 1, which is characterized in that second contextual data includes second
Scene service item information, scene name information, scene purposes information, scene address information and the user's history that scene includes are inclined
Good scene service item information.
7. service recommendation method under line according to claim 1, which is characterized in that the prediction model be LSTM model,
One of Logic Regression Models and decision-tree model model.
8. service recommendation device under a kind of line characterized by comprising
Obtain module, for obtaining user's representation data respectively, user be presently in corresponding first contextual data in position and use
Corresponding second contextual data in family history visiting position, wherein the corresponding scene of first contextual data and second scene
The corresponding scene of data is associated；
Processing module, it is pre- for inputting user's representation data, first contextual data and second contextual data
If prediction model handled；
Sending module, for obtaining the pre- of the reflection potential demand for services project of user exported after prediction model processing
Measured data, and the prediction data is sent to client.
9. a kind of storage medium, which is characterized in that be stored thereon with computer program, the computer program is performed realization
Service recommendation method under the described in any item lines of claim 1~7.
10. a kind of computer equipment, which is characterized in that it includes processor, memory and is stored on the memory and can
The computer program run on the processor, the processor realize claim 1~7 when executing the computer program
Service recommendation method under described in any item lines.
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Application publication date: 20191119 |