CN104537552B - Pass through computer implemented information recommendation method and device - Google Patents
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- CN104537552B CN104537552B CN201410815315.1A CN201410815315A CN104537552B CN 104537552 B CN104537552 B CN 104537552B CN 201410815315 A CN201410815315 A CN 201410815315A CN 104537552 B CN104537552 B CN 104537552B
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Abstract
One kind provided by the invention passes through computer implemented information recommendation method and device.Methods described includes：Receive the demand data of the first user；The recommended data of order models acquisition predetermined number are matched according to the demand of the demand data and training in advance, the recommended data include the information for meeting the second user of the needs of the first user；According to the contact details of second user described in the information extraction of the second user；The demand data of first user is sent to corresponding second user respectively according to the contact details.The technical scheme proposed by the embodiment of the present invention, user's request can be improved and the matching degree of the trade company of service is provided, reduce technical requirements and operation cost that trade company uses system, improved user and find the convenience of service, and improve the efficiency that trade company finds client.
Description
Technical field
The present invention relates to the information processing technology, more particularly to one kind to pass through computer implemented information recommendation method and dress
Put.
Background technology
When domestic consumer needs to obtain various services, it is impossible to trade company is very easily related to, for example, making a reservation, ordering fresh flower
Or Expert English language training by qualified teachers, user have to the businessman searched on website (or APP), and the businessman of site search may from
Family farther out, is not easy to merchandise.
At present, O2O (Online to Offline) marketing model (also known as offline business model, refers to market on line on line
Manage under purchase band moving-wire and consumed under line) it is the most popular, it is by giving a discount, providing the modes such as information, service subscription, under line
The message in shop is pushed to Internet user, for example, through number etc. that the wechat public number of Tengxun's release, Baidu are released.
But just at present now, O2O there is no a good entrance, so that Difficulty on its line, comes for user
Say, user have to each scattered website either the various services of APP removal search or need user remember Merchant name enter
Row search ("@" search of such as wechat public number)；And for trade company, under O2O line, operation cost is high, renewal businessman's letter
Breath cost is higher and accuracy rate is relatively low.
The content of the invention
It is an object of the present invention to provide one kind by computer implemented information recommendation method and device, with preferably
The trade company of demand and offer service to user matches, and provides valuable user's request information to trade company in time.
According to an aspect of the present invention, there is provided it is a kind of by computer implemented information recommendation method, including：Receive first
The demand data of user；Order models are matched according to the demand of the demand data and training in advance and obtain pushing away for predetermined number
Object data is recommended, the recommended data include the information for meeting the second user of the needs of the first user；According to described
The contact details of second user described in the information extraction of two users；According to the contact details respectively by the need of first user
Data are asked to be sent to corresponding second user.
According to another aspect of the present invention, there is provided a kind of information recommending apparatus, including：Data receipt unit, for receiving
The demand data of first user；Object data acquiring unit, for the demand according to the demand data and training in advance
The recommended data of predetermined number are obtained with order models, the recommended data include meeting the needs of the first user
The information of second user；Contact details extraction unit, for second user described in the information extraction according to the second user
Contact details；Demand data transmitting element, for respectively being sent out the demand data of first user according to the contact details
Give corresponding second user.
Computer implemented information recommendation method and device provided in an embodiment of the present invention, to increase O2O entrance, with compared with
The trade company of the demand to user and offer service matches well, and providing valuable user's request to trade company in time believes
Breath, technical requirements and operation cost that trade company uses system are reduced, improve user and find the convenience of service, and improve trade company and look for
To the efficiency of client.
Brief description of the drawings
Fig. 1 is to show exemplary embodiment of the present O2O information transmission and using exemplary plot.
Fig. 2 is the application structure exemplary plot for showing the overall technical architecture of the invention shown in Fig. 1.
Fig. 3 is that the flow by computer implemented information recommendation method for showing exemplary embodiment of the present is illustrated
Figure.
Fig. 4 shows the structured flowchart of the information recommending apparatus of exemplary embodiment of the present.
Embodiment
The present invention basic conception be to establish a kind of O2O service platforms, can by user's request data-pushing to trade company, and
The information of trade company is pushed to the user with corresponding demand, so as to improve the matching of user's request and trade company.
Below in conjunction with the accompanying drawings to exemplary embodiment of the present it is a kind of by computer implemented information recommendation method and
Device is described in detail.
Fig. 1 is to show information transmission of the exemplary embodiment of the present based on O2O service platforms and using exemplary plot.Such as figure
Shown in 1, the demand of oneself can be transferred to O2O service platforms by user, and O2O service platforms carry to the demand information of user
Take, value information (for example, contact details of user) is passed into offline businesses.
Fig. 2 is the schematic diagram for the O2O service platform overall architectures for showing exemplary embodiment of the present.Reference picture 2, trade company
Trade company's commending system can be reached by its trade company's register system enrolled merchant information；On the other hand, user inputs search term
After (i.e. query), O2O service platforms carry out user requirements analysis to the search term, and user's request is reached into trade company recommends system
System；On the other hand, trade company's commending system according to the demand of training in advance match order models by the information that trade company registers with it is described
User's request carries out matching sequence, and the user's request is pushed to the trade company of matching by trade company's supplying system.
In addition, user can also be evaluated, that the deal message of feedback and trade company, favorable comment information etc. reach merchant is anti-
Feedback system, for providing a user user's evaluation, feedback information and deal message on businessman.
The exemplary embodiment of the present invention is described in detail below with reference to Fig. 3~Fig. 4.
Fig. 3 is that the flow by computer implemented information recommendation method for showing exemplary embodiment of the present is illustrated
Figure.
Reference picture 3, in step S110, the demand data of the first user of reception.The demand data can be searching for user
Rope word.
In step S120, order models are matched according to the demand of the demand data and training in advance and obtain predetermined number
Recommended data, the recommended data include meet the needs of the first user second user information.
Preferably, first user is consumer-user, and the second user is trade company user.
Specifically, following sub-step is included according to the exemplary embodiment of the present invention, step S120：
First, the main demand class data of the first user and sub- demand class data are obtained according to the demand data.It is excellent
Selection of land, natural language analysis is carried out to the demand data, obtains the main demand class data of the first user and sub- demand class
Data.
For example, " I will subscribe evening April 26 18 to user's input:00 point of western-style food ", by entering to the demand data
Row natural language analysis, the main demand class data that can obtain the first user are " food and drink ", and sub- demand class data are " west
Meal ".
Secondly, according to the main demand class data and the multiple Candidate Recommendation data of sub- demand class data acquisition.Wherein,
The main demand class can be the classification belonging to sub- demand class, sub- demand class can be demand user it is more specific,
The demand more refined.
Specifically, can be obtained according to the main demand class data and sub- demand class data from Merchants register information database
Take the Candidate Recommendation data.
Again, made with each Candidate Recommendation data and the main demand class data of acquisition and sub- demand class data
For input, the correlation for matching order models acquisition each Candidate Recommendation object data by the demand of training in advance respectively refers to
Number, wherein, the relative index can be the selection probability of Candidate Recommendation object data.It is existing at present various according to predetermined spy
Sign index is ranked up the technology of model training by the labeled data chosen in advance.
A kind of training method that order models are matched to demand below gives exemplary illustration.First, needed from one group of history
Ask data and for its mark user data (for example, the conclusion of the business quantity of trade company, geographical position, favorable comment number and active in the recent period
Degree)；Hereafter, main demand class data and sub- demand class data are obtained respectively (for example, passing through according to these historic demand data
Natural language analysis acquisition is carried out to historic demand data)；Then, according to the main demand class data, sub- demand class data
The matching order models are established with the user data of the mark and train the demand matching order models, so as to learn
Influence of the value of main demand class and sub- demand class to the relative index of Candidate Recommendation object data.
More specifically, can be by substantial amounts of consumer-user ID (sex, age) in some time (timeslice of burst
Section) some place, what kind of demand (for example, the needs are subjected to layering demand analysis) is expressed, and be to recommendation results
Refusal or receive etc. historic demand data as extraction training characteristics foundation, and use Content Management System (for example,
DNN), common machine learning model and the training fitting of artificial regular fashion obtain.Matching order models by the demand can
So that general features is personalized, so as to evaluate the relative index of candidate data-object, provided more for consumer-user
Personalized demand customization.
The training of the demand matching order models is not limited to use method described above, can also use other features
Parameter and training method carry out the training of the demand matching order models.Because the model training is not the core of the present invention
Above-mentioned example explanation is given in heart improvement, the training for only matching order models to demand herein.
Finally, the Candidate Recommendation object data of predetermined number is chosen as recommended according to the relative index
Data.Specifically, Candidate Recommendation object data is ranked up based on foregoing relative index, therefrom filters out predetermined number
Recommended data.
In step S130, according to the contact details of second user described in the information extraction of the second user.Wherein, second
The information of user can be, but not limited to be second user by registering the address provided during platform registration, contact method, user class
Type, service type, service range etc..
In step S140, the demand data of first user is sent to corresponding respectively according to the contact details
Two users.Preferably, the contact details of first user are obtained, according to the contact details of second user general respectively
The demand data and its contact details of first user is sent to corresponding second user.
After second user gets the demand data and its contact details of the first user, the first use can also be actively contacted
Family, for example, by phone, social APP etc., so as to increase user under the line of second user, increase trade company (second user) into
Friendship amount.
Computer implemented information recommendation method provided in an embodiment of the present invention, with the demand preferably to user and is carried
Matched for the trade company of service, providing valuable user's request information to trade company in time reduces technology of the trade company using system
It is required that and operation cost, improve user and find the convenience of service, and improve the efficiency that trade company finds client.
Fig. 4 shows the structured flowchart of the information recommending apparatus of exemplary embodiment of the present.
Reference picture 4, described information recommendation apparatus include data receipt unit 310, object data acquiring unit 320, contact
Information extraction unit 330 and demand data transmitting element 340.
Data receipt unit 310 is used for the demand data for receiving the first user.
Object data acquiring unit 320 is used for the demand data that is got according to the data receipt unit 310 and pre-
The demand matching order models first trained obtain the recommended data of predetermined number, and the recommended data include meeting the
The information of the second user of the demand of one user.
For example, first user is consumer-user, the second user is trade company user.
Specifically, it is used for according to the exemplary embodiment of the present invention, object data acquiring unit 320 according to data receiver list
The demand data that member 310 is got obtains the main demand class data of the first user and sub- demand class data, according to the master
Demand class data and the multiple Candidate Recommendation data of sub- demand class data acquisition, with each Candidate Recommendation data and are obtained
The main demand class data taken and sub- demand class data match order models by the demand of training in advance respectively as input
The relative index of each Candidate Recommendation object data is obtained, the time of predetermined number is chosen according to the relative index
Recommended data are selected as recommended data.
Preferably, object data acquiring unit 320 carries out natural language analysis to the demand data, obtains the first user
Main demand class data and sub- demand class data.
Contact details extraction unit 330 is used for the contact letter of the second user according to the information extraction of the second user
Breath.
Demand data transmitting element 340 is used to respectively be sent out the demand data of first user according to the contact details
Give corresponding second user.
Preferably, the demand data transmitting element 340 is used for the contact details for obtaining first user, according to described
The demand data of first user and its contact details are sent to corresponding second respectively and used by the contact details of second user
Family.
Computer implemented information recommending apparatus provided in an embodiment of the present invention, with the demand preferably to user and is carried
Matched for the trade company of service, provide valuable user's request information to trade company in time, reduce the skill that trade company uses system
Art requirement, and operation cost, the convenience that user finds service is improved, and improve the efficiency that trade company finds client.
It may be noted that according to the needs of implementation, each step described in this application can be split as more multi-step, also may be used
The part operation of two or more steps or step is combined into new step, to realize the purpose of the present invention.
Above-mentioned the method according to the invention can be realized in hardware, firmware, or be implemented as being storable in recording medium
Software or computer code in (such as CD ROM, RAM, floppy disk, hard disk or magneto-optic disk), or it is implemented through network download
Original storage in long-range recording medium or nonvolatile machine readable media and the meter that will be stored in local recording medium
Calculation machine code, so as to which method described here can be stored in using all-purpose computer, application specific processor or programmable or special
With such software processing in hardware (such as ASIC or FPGA) recording medium.It is appreciated that computer, processor, micro-
Processor controller or programmable hardware include can storing or receive software or computer code storage assembly (for example, RAM,
ROM, flash memory etc.), when the software or computer code are by computer, processor or hardware access and when performing, realize herein
The processing method of description.In addition, when all-purpose computer accesses the code for realizing the processing being shown in which, the execution of code
All-purpose computer is converted into the special-purpose computer for performing the processing being shown in which.
The foregoing is only a specific embodiment of the invention, but protection scope of the present invention is not limited thereto, any
Those familiar with the art the invention discloses technical scope in, change or replacement can be readily occurred in, should all be contained
Cover within protection scope of the present invention.Therefore, protection scope of the present invention should be based on the protection scope of the described claims.
Claims (8)
1. one kind passes through computer implemented information recommendation method, it is characterised in that methods described includes：
Receive the demand data of the first user, according to the demand data obtain first user main demand class data and
Sub- demand class data；
According to the main demand class data and the multiple Candidate Recommendation data of sub- demand class data acquisition；
Using the main demand class data and sub- demand class data of each Candidate Recommendation data and acquisition as input, point
The relative index of order models acquisition Candidate Recommendation object data is not matched by the demand of training in advance；
It is described according to the Candidate Recommendation object data of relative index selection predetermined number as recommended data
Recommended data include the information for meeting the second user of the needs of the first user；
According to the contact details of second user described in the information extraction of the second user；
The demand data of first user is sent to corresponding second user respectively according to the contact details.
2. according to the method for claim 1, it is characterised in that described to be used respectively by described first according to the contact details
The processing that the demand data at family is sent to corresponding second user includes：
The contact details of first user are obtained,
The demand data of first user and its contact details are sent to respectively according to the contact details of the second user
Corresponding second user.
3. according to method according to any one of claims 1 to 2, it is characterised in that obtain first according to the demand data
The processing of the main demand class data and sub- demand class data of user includes：
Natural language analysis is carried out to the demand data, obtains the main demand class data of the first user and sub- demand class number
According to.
4. according to the method for claim 3, it is characterised in that first user is consumer-user, and described second uses
Family is trade company user.
5. a kind of information recommending apparatus, it is characterised in that described device includes：
Data receipt unit, for receiving the demand data of the first user, the demand data includes the master of first user
Demand class data and sub- demand class data；
Object data acquiring unit, for being pushed away according to the main demand class data and the sub- multiple candidates of demand class data acquisition
Data are recommended, using the main demand class data and sub- demand class data of each Candidate Recommendation data and acquisition as defeated
Enter, match the relative index of order models acquisition Candidate Recommendation object data, and root by the demand of training in advance respectively
The Candidate Recommendation object data of predetermined number is chosen as recommended data, the recommendation pair according to the relative index
Image data includes the information for meeting the second user of the needs of the first user；
Contact details extraction unit, the contact details for second user described in the information extraction according to the second user；
Demand data transmitting element, for the demand data of first user to be sent into phase respectively according to the contact details
The second user answered.
6. device according to claim 5, it is characterised in that the demand data transmitting element is used to obtain described first
The contact details of user, according to the contact details of the second user respectively by the demand data of first user and its contact
Information is sent to corresponding second user.
7. the device according to any one of claim 5~6, it is characterised in that object data acquiring unit is to the need
Ask data to carry out natural language analysis, obtain the main demand class data of the first user and sub- demand class data.
8. device according to claim 7, it is characterised in that first user is consumer-user, and described second uses
Family is trade company user.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410815315.1A CN104537552B (en) | 2014-12-23 | 2014-12-23 | Pass through computer implemented information recommendation method and device |
| PCT/CN2015/098344 WO2016101881A1 (en) | 2014-12-23 | 2015-12-22 | Method and apparatus for information recommendation realized by computer, and computer device |
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410815315.1A CN104537552B (en) | 2014-12-23 | 2014-12-23 | Pass through computer implemented information recommendation method and device |
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| CN104537552A CN104537552A (en) | 2015-04-22 |
| CN104537552B true CN104537552B (en) | 2018-01-05 |
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| WO (1) | WO2016101881A1 (en) |
Families Citing this family (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104537552B (en) * | 2014-12-23 | 2018-01-05 | 百度在线网络技术（北京）有限公司 | Pass through computer implemented information recommendation method and device |
| CN106997357B (en) * | 2016-01-22 | 2020-10-09 | 腾讯科技（深圳）有限公司 | Message processing method, device and system |
| CN108022142A (en) * | 2016-11-03 | 2018-05-11 | 阿里巴巴集团控股有限公司 | The definite method, apparatus and electronic equipment of a kind of shopping guide user |
| CN107977860A (en) * | 2017-11-15 | 2018-05-01 | 广东原始源正电子商务股份有限公司 | A kind of information processing method and system based on mobile network |
| CN109919704A (en) * | 2019-01-21 | 2019-06-21 | 浙江口碑网络技术有限公司 | A kind of distribution method of resource data, apparatus and system |
| CN113688311A (en) * | 2021-06-18 | 2021-11-23 | 诺正集团股份有限公司 | Information recommendation method, device and equipment based on data interaction and storage medium |
| CN114500430A (en) * | 2022-02-09 | 2022-05-13 | 携程计算机技术（上海）有限公司 | Dialogue method, system, device and storage medium |
| CN115964397B (en) * | 2022-09-20 | 2023-09-19 | 成都比特信安科技有限公司 | Data seed implantation and tracing method |
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Also Published As
| Publication number | Publication date |
|---|---|
| WO2016101881A1 (en) | 2016-06-30 |
| CN104537552A (en) | 2015-04-22 |
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