CN104537552A - Information recommendation method and device implemented through computer - Google Patents
Information recommendation method and device implemented through computer Download PDFInfo
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- CN104537552A CN104537552A CN201410815315.1A CN201410815315A CN104537552A CN 104537552 A CN104537552 A CN 104537552A CN 201410815315 A CN201410815315 A CN 201410815315A CN 104537552 A CN104537552 A CN 104537552A
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Abstract
The invention provides an information recommendation method and device implemented through a computer. The method comprises the steps of receiving demand data of a first user; according to the demand data and a pre-trained demand fit sorting model, obtaining a preset number of recommendation object data, wherein the recommendation object data comprise information of a second user meeting the demand of the first user; according to the information of the second user, extracting contact information of the second user; according to the contact information, sending the demand data of the first user to the corresponding second user. According to the technical scheme, the matching degree of the user demand and a service providing merchant can be improved, the system using technical requirement and operating cost of the merchant can be lowered, more convenience for finding services can be brought for the users, and the merchant efficiency for finding clients is improved.
Description
Technical field
The present invention relates to the information processing technology, particularly relate to a kind of by computer implemented information recommendation method and device.
Background technology
When domestic consumer needs to obtain various service, trade company can not be related to very easily, such as, make a reservation, order fresh flower or Expert English language training by qualified teachers, user is obliged to go the businessman of the upper search in website (or APP), and the businessman of site search may, from user away from, be not easy to conclude the business.
At present, O2O (Online to Offline) marketing model is (also known as off-line business model, refer to and manage and consume under line under line that line markets buying band moving-wire) hot topic the most, it is by giving a discount, providing the mode such as information, service subscription, the message push in shop under line to Internet user, such as, micro-letter public number of Tengxun's release, through number of Baidu's release etc.
But, just at present now, O2O there is no a good entrance, so that Difficulty on its line, for user, user is obliged to go the website of each dispersion or the various service of APP removal search, or needs user to remember Merchant name to carry out searching for (" " as micro-letter public number searches for); And for trade company, under the line of O2O, operation cost is high, renewal Business Information cost is higher and accuracy rate is lower.
Summary of the invention
The object of the invention is to, provide a kind of by computer implemented information recommendation method and device, with preferably to the demand of user and provide the trade company of service to mate, provide valuable user's request information to trade company in time.
According to an aspect of the present invention, provide a kind of by computer implemented information recommendation method, comprising: the demand data receiving first user; Demand according to described demand data and training in advance mates the recommended data that order models obtains predetermined number, and described recommended data comprise the information of the second user of the demand meeting first user; The contact details of the second user according to the information extraction of described second user; Respectively the demand data of described first user is sent to corresponding second user according to described contact details.
According to a further aspect in the invention, a kind of information recommending apparatus is provided, comprises: data receipt unit, for receiving the demand data of first user; Object data acquiring unit, for obtaining the recommended data of predetermined number according to the demand coupling order models of described demand data and training in advance, described recommended data comprise the information of the second user of the demand meeting first user; Contact details extraction unit, for the contact details of the second user according to the information extraction of described second user; Demand data transmitting element, for sending to corresponding second user by the demand data of described first user respectively according to described contact details.
The computer implemented information recommendation method that the embodiment of the present invention provides and device, to increase the entrance of O2O, with preferably to the demand of user and provide the trade company of service to mate, valuable user's request information is provided in time to trade company, reduce technical requirement and operation cost that trade company uses system, improve the convenience that user finds service, and improve the efficiency that trade company finds client.
Accompanying drawing explanation
Fig. 1 is information transmission and application example figure that exemplary embodiment of the present O2O is shown.
Fig. 2 is the application structure exemplary plot that the overall technical architecture of the present invention shown in Fig. 1 is shown.
Fig. 3 is the schematic flow sheet by computer implemented information recommendation method that exemplary embodiment of the present is shown.
Fig. 4 illustrates the structured flowchart of the information recommending apparatus of exemplary embodiment of the present.
Embodiment
Basic conception of the present invention is, sets up a kind of O2O service platform, can by user's request data-pushing to trade company, and by the information pushing of trade company to the user with corresponding demand, thus improves mating of user's request and trade company.
Below in conjunction with accompanying drawing, the one of exemplary embodiment of the present is described in detail by computer implemented information recommendation method and device.
Fig. 1 illustrates that exemplary embodiment of the present is based on the information transmission of O2O service platform and application example figure.As shown in Figure 1, the demand of oneself can be passed to O2O service platform by user, and the demand information of O2O service platform to user extracts, and value information (such as, the contact details of user) is passed to offline businesses.
Fig. 2 is the schematic diagram of the O2O service platform overall architecture that exemplary embodiment of the present is shown.With reference to Fig. 2, trade company can pass through its trade company's register system enrolled merchant information, reaches trade company's commending system; On the other hand, after user's inputted search word (i.e. query), O2O service platform carries out user requirements analysis to described search word, user's request is reached trade company's commending system; On the other hand, the information that trade company registers according to the demand of training in advance coupling order models by trade company's commending system is carried out mating with described user's request and is sorted, and described user's request is pushed to the trade company of coupling by trade company's supplying system.
In addition, also user can being evaluated, to feed back and the conclusion of the business information, favorable comment information etc. of trade company reach trade company's service feedback system, evaluating about the user of businessman for providing to user, feedback information and conclusion of the business information.
Exemplary embodiment of the present invention is described in detail below with reference to Fig. 3 ~ Fig. 4.
Fig. 3 is the schematic flow sheet by computer implemented information recommendation method that exemplary embodiment of the present is shown.
With reference to Fig. 3, in step S110, receive the demand data of first user.Described demand data can be the search word of user.
In step S120, the demand according to described demand data and training in advance mates the recommended data that order models obtains predetermined number, and described recommended data comprise the information of the second user of the demand meeting first user.
Preferably, described first user is consumer-user, and described second user is trade company user.
Particularly, according to exemplary embodiment of the present invention, step S120 comprises following sub-step:
First, the main demand class data of first user and sub-demand class data are obtained according to described demand data.Preferably, natural language analysis is carried out to described demand data, obtain the main demand class data of first user and sub-demand class data.
Such as, user inputs " I will subscribe the western-style food of 18:00 point in evening April 26 ", and by carrying out natural language analysis to described demand data, can obtain the main demand class data of first user for " food and drink ", sub-demand class data are " western-style food ".
Secondly, according to described main demand class data and the multiple Candidate Recommendation data of sub-demand class data acquisition.Wherein, described main demand class can be the classification belonging to sub-demand class, and sub-demand class can be the demand of more specific, the more refinement of demand user.
Particularly, described Candidate Recommendation data can be obtained according to described main demand class data and sub-demand class data from trade company's registration information database.
Again, using the main demand class data of Candidate Recommendation data described in each and acquisition and sub-demand class data as input, demand coupling order models respectively by training in advance obtains the relative index of described each Candidate Recommendation object data, wherein, this relative index can be Candidate Recommendation object data choose probability.Existing various technology of being carried out order models training according to predetermined characteristic index by the labeled data chosen in advance at present.
Exemplary illustration is given below to a kind of training method of demand coupling order models.First, from one group of historic demand data and the user data (such as, the conclusion of the business quantity of trade company, geographic position, favorable comment number and liveness in the recent period) for its mark; After this, main demand class data and sub-demand class data (such as, by carrying out natural language analysis acquisition to historic demand data) are obtained respectively according to these historic demand data; Then, set up described coupling order models according to the user data of these main demand class data, sub-demand class data and described mark and train described demand to mate order models, thus the value learning main demand class and sub-demand class is on the impact of the relative index of Candidate Recommendation object data.
More specifically, can by a large amount of consumer-user ID (sex, age) in certain time (time slice of burst) certain place, have expressed what kind of demand (such as, this is needed carry out layering demand analysis), and be that refusal or the historic demand data such as acceptance are as the foundations extracting training characteristics to recommendation results, and adopt Content Management System (such as, DNN), common machine learning model and artificial regular fashion training matching to obtain.Can be personalized by general features by described demand coupling order models, thus the relative index of candidate data-object is evaluated, for consumer-user provides more personalized demand customization.
The training of described demand coupling order models is not limited to the method using aforementioned description, and other characteristic parameters and training method can also be used to carry out the training of described demand coupling order models.Because described model training is not core improvement of the present invention, only give above-mentioned exemplary illustration to the training of demand coupling order models at this.
Finally, the described Candidate Recommendation object data of predetermined number is chosen as recommended data according to described relative index.Particularly, based on aforesaid relative index, Candidate Recommendation object data is sorted, therefrom filter out predetermined number recommended data.
In step S130, the contact details of the second user according to the information extraction of described second user.Wherein, the information of the second user can be, but not limited to be the address, contact method, user type, COS, service range etc. of the second user by providing during the registration of registration platform.
In step S140, respectively the demand data of described first user is sent to corresponding second user according to described contact details.Preferably, obtain the contact details of described first user, the demand data of described first user and contact details thereof are sent to corresponding second user by contact details according to described second user respectively.
After the demand data that second user gets first user and contact details thereof, initiatively can also contact first user, such as, by phone, social APP etc., thus user under increasing the line of the second user, increase the trading volume of trade company (the second user).
The computer implemented information recommendation method that the embodiment of the present invention provides, with preferably to the demand of user and provide the trade company of service to mate, valuable user's request information reduction trade company is provided to use technical requirement and the operation cost of system to trade company in time, improve the convenience that user finds service, and improve the efficiency that trade company finds client.
Fig. 4 illustrates the structured flowchart of the information recommending apparatus of exemplary embodiment of the present.
With reference to Fig. 4, described information recommending apparatus comprises data receipt unit 310, object data acquiring unit 320, contact details extraction unit 330 and demand data transmitting element 340.
Data receipt unit 310 is for receiving the demand data of first user.
Object data acquiring unit 320 obtains the recommended data of predetermined number for the demand coupling order models of the demand data that gets according to described data receipt unit 310 and training in advance, and described recommended data comprise the information of the second user of the demand meeting first user.
Such as, described first user is consumer-user, and described second user is trade company user.
Particularly, according to exemplary embodiment of the present invention, object data acquiring unit 320 obtains the main demand class data of first user and sub-demand class data for the demand data got according to data receipt unit 310, according to described main demand class data and the multiple Candidate Recommendation data of sub-demand class data acquisition, using the main demand class data of Candidate Recommendation data described in each and acquisition and sub-demand class data as input, demand coupling order models respectively by training in advance obtains the relative index of described each Candidate Recommendation object data, the described Candidate Recommendation object data of predetermined number is chosen as recommended data according to described relative index.
Preferably, object data acquiring unit 320 carries out natural language analysis to described demand data, obtains the main demand class data of first user and sub-demand class data.
Contact details extraction unit 330 is for the contact details of the second user according to the information extraction of described second user.
Demand data transmitting element 340 is for sending to corresponding second user by the demand data of described first user respectively according to described contact details.
Preferably, described demand data transmitting element 340 is for obtaining the contact details of described first user, and the demand data of described first user and contact details thereof are sent to corresponding second user by contact details according to described second user respectively.
The computer implemented information recommending apparatus that the embodiment of the present invention provides, with preferably to the demand of user and provide the trade company of service to mate, valuable user's request information is provided in time to trade company, reduce the technical requirement that trade company uses system, and operation cost, improve the convenience that user finds service, and improve the efficiency that trade company finds client.
It may be noted that the needs according to implementing, each step described can be split as more multi-step, also the part operation of two or more step or step can be combined into new step, to realize object of the present invention in the application.
Above-mentioned can at hardware according to method of the present invention, realize in firmware, or be implemented as and can be stored in recording medium (such as CD ROM, RAM, floppy disk, hard disk or magneto-optic disk) in software or computer code, or be implemented and will be stored in the computer code in local recording medium by the original storage of web download in remote logging medium or nonvolatile machine readable media, thus method described here can be stored in use multi-purpose computer, such software process on the recording medium of application specific processor or able to programme or specialized hardware (such as ASIC or FPGA).Be appreciated that, computing machine, processor, microprocessor controller or programmable hardware comprise and can store or receive the memory module of software or computer code (such as, RAM, ROM, flash memory etc.), when described software or computer code by computing machine, processor or hardware access and perform time, realize disposal route described here.In addition, when the code for realizing the process shown in this accessed by multi-purpose computer, multi-purpose computer is converted to the special purpose computer for performing the process shown in this by the execution of code.
The above; be only the specific embodiment of the present invention, but protection scope of the present invention is not limited thereto, is anyly familiar with those skilled in the art in the technical scope that the present invention discloses; change can be expected easily or replace, all should be encompassed within protection scope of the present invention.Therefore, protection scope of the present invention should be as the criterion with the protection domain of described claim.
Claims (10)
1., by a computer implemented information recommendation method, it is characterized in that, described method comprises:
Receive the demand data of first user;
Demand according to described demand data and training in advance mates the recommended data that order models obtains predetermined number, and described recommended data comprise the information of the second user of the demand meeting first user;
The contact details of the second user according to the information extraction of described second user;
Respectively the demand data of described first user is sent to corresponding second user according to described contact details.
2. method according to claim 1, is characterized in that, describedly the demand data of described first user is sent to the process of corresponding second user to comprise respectively according to described contact details:
Obtain the contact details of described first user,
The demand data of described first user and contact details thereof are sent to corresponding second user by contact details according to described second user respectively.
3. method according to claim 2, is characterized in that, the process that the described coupling of the demand according to described demand data and training in advance order models obtains the recommended data of predetermined number comprises:
The main demand class data of first user and sub-demand class data are obtained according to described demand data,
According to described main demand class data and the multiple Candidate Recommendation data of sub-demand class data acquisition,
Using the main demand class data of Candidate Recommendation data described in each and acquisition and sub-demand class data as input, the demand coupling order models respectively by training in advance obtains the relative index of described each Candidate Recommendation object data,
The described Candidate Recommendation object data of predetermined number is chosen as recommended data according to described relative index.
4. the method according to any one of claims 1 to 3, is characterized in that, describedly obtains the main demand class data of first user according to described demand data and the process of sub-demand class data comprises:
Natural language analysis is carried out to described demand data, obtains the main demand class data of first user and sub-demand class data.
5. method according to claim 4, is characterized in that, described first user is consumer-user, and described second user is trade company user.
6. an information recommending apparatus, is characterized in that, described device comprises:
Data receipt unit, for receiving the demand data of first user;
Object data acquiring unit, for obtaining the recommended data of predetermined number according to the demand coupling order models of described demand data and training in advance, described recommended data comprise the information of the second user of the demand meeting first user;
Contact details extraction unit, for the contact details of the second user according to the information extraction of described second user;
Demand data transmitting element, for sending to corresponding second user by the demand data of described first user respectively according to described contact details.
7. device according to claim 6, it is characterized in that, described demand data transmitting element is for obtaining the contact details of described first user, and the demand data of described first user and contact details thereof are sent to corresponding second user by contact details according to described second user respectively.
8. device according to claim 7, is characterized in that, described object data acquiring unit is used for obtaining the main demand class data of first user and sub-demand class data according to described demand data,
According to described main demand class data and the multiple Candidate Recommendation data of sub-demand class data acquisition,
Using the main demand class data of Candidate Recommendation data described in each and acquisition and sub-demand class data as input, the demand coupling order models respectively by training in advance obtains the relative index of described each Candidate Recommendation object data,
The described Candidate Recommendation object data of predetermined number is chosen as recommended data according to described relative index.
9. the device according to any one of claim 6 ~ 8, is characterized in that, object data acquiring unit carries out natural language analysis to described demand data, obtains the main demand class data of first user and sub-demand class data.
10. device according to claim 9, is characterized in that, described first user is consumer-user, and described second user is trade company user.
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| Application Number | Priority Date | Filing Date | Title |
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| 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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| CN201410815315.1A CN104537552B (en) | 2014-12-23 | 2014-12-23 | Pass through computer implemented information recommendation method and device |
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| CN104537552B CN104537552B (en) | 2018-01-05 |
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
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| WO2016101881A1 (en) * | 2014-12-23 | 2016-06-30 | 百度在线网络技术（北京）有限公司 | Method and apparatus for information recommendation realized by computer, and computer device |
| WO2017125020A1 (en) * | 2016-01-22 | 2017-07-27 | 腾讯科技（深圳）有限公司 | Message processing method, device and system |
| 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 |
| 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 |
| 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 |
| WO2022262752A1 (en) * | 2021-06-18 | 2022-12-22 | 诺正集团股份有限公司 | Information recommendation method and apparatus based on data interaction, and device and storage medium |
| CN115964397A (en) * | 2022-09-20 | 2023-04-14 | 成都比特信安科技有限公司 | Data seed implantation and tracing method |
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| 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 |
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Also Published As
| Publication number | Publication date |
|---|---|
| CN104537552B (en) | 2018-01-05 |
| WO2016101881A1 (en) | 2016-06-30 |
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