CN107171949B - Information pushing method, device and system - Google Patents
Information pushing method, device and system Download PDFInfo
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- CN107171949B CN107171949B CN201710574539.1A CN201710574539A CN107171949B CN 107171949 B CN107171949 B CN 107171949B CN 201710574539 A CN201710574539 A CN 201710574539A CN 107171949 B CN107171949 B CN 107171949B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/50—Network services
- H04L67/55—Push-based network services
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L51/00—User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail
- H04L51/21—Monitoring or handling of messages
- H04L51/214—Monitoring or handling of messages using selective forwarding
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L51/00—User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail
- H04L51/21—Monitoring or handling of messages
- H04L51/222—Monitoring or handling of messages using geographical location information, e.g. messages transmitted or received in proximity of a certain spot or area
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- Signal Processing (AREA)
- Information Transfer Between Computers (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The embodiment of the invention provides a shaking-based information pushing method, which comprises the steps of obtaining data information of a client participating in preset type activities, wherein the data information comprises user basic data of the client, a history record of participating in the activities and derivative data, and the user basic data at least comprises a mobile phone number, an age and a gender corresponding to the client. And calculating the activity score of each client to the preset activity according to the participation activity history record and the derivative data, finally determining the client with the activity score larger than the preset score as a target client, and pushing a preset message to the target client. Therefore, the recommendation method provided by the scheme carries out targeted pushing based on the interest of the user, and the information pushing efficiency is improved.
Description
Technical Field
The present invention relates to the field of data processing technologies, and in particular, to an information pushing method, apparatus, and system.
Background
With the continuous development of science and technology, mobile terminals are more and more common, and some operators push data to the mobile terminals quickly.
However, the current information push is generally sent to users in a group by means of short messages or application information, and the inventor finds that, at present, an operator can push the same information to different users without targeting different users, which further causes resource waste of information push, for example, the operator pushes one coupon information to multiple users, such as user a, user B, and user C, but user B and user C may not pay attention to the push message at all, which results in low information push efficiency.
Therefore, how to improve the information pushing efficiency becomes a problem to be solved by those skilled in the art.
Disclosure of Invention
In view of this, embodiments of the present invention provide an information pushing method, apparatus, and system, which recommend information according to a user's interest level, and improve information pushing efficiency.
In order to achieve the above purpose, the embodiments of the present invention provide the following technical solutions:
an information push method is applied to a client with a shaking function, and comprises the following steps:
the method comprises the steps that data information of a plurality of clients based on preset type activities is obtained, the data information comprises user basic data, activity participation history records and derivative data of the clients, the user basic data comprises mobile phone numbers, ages and sexes corresponding to the clients, the activity participation history records comprise activity types, activity affiliated industries, opening activity records, position information, business circle information and merchant information, and the derivative data comprises the total number of coupons, the category of coupons and the proportion of coupons;
calculating the activity score of each client to the preset type of activity according to the participation activity history records and the derivative data;
and determining the client with the activity score larger than the preset score as a target client, and pushing a preset message to the target client.
Optionally, the calculating, according to the participation activity history record and the derivative data, an activity score of each client for the preset activity includes:
determining parameters in the participation activity history record and sub-scores corresponding to the parameters in the derived data;
and calculating to obtain the activity score of each client to the preset activity according to the sub-scores.
Optionally, the calculating, according to the sub-scores, an activity score of each client for the preset type of activity includes:
according to the formula
Calculating the activity score, wherein Ui is the number of clients participating in activity i, CiThe CAL (U, C) scores the activity of the preset type of activity for the client;
accordingly, according to the formula
And calculating the preset score.
Optionally, the calculating, according to the participation activity history record and the derivative data, an activity score of each client for the preset activity includes:
determining the interest degree corresponding to each parameter in the historical record of the participation activity and each parameter in the derived data;
and determining the interestingness as the activity score of each client to the preset activity.
Optionally, the determining the interestingness as an activity score of each client for the preset activity includes:
according to the formula
Calculating activity scores of the preset types of activities, wherein P (i) is the interest degree of the client to the participating activity i, NiAnd C (m) is the activity number of the preset type of activity, C (m) is the interest degree of the client to the activity m, and lambda is the weight.
An information pushing device is applied to a client with a shaking function, and comprises:
the system comprises an acquisition module, a display module and a display module, wherein the acquisition module is used for acquiring data information of a plurality of clients based on preset types of activities, the data information comprises user basic data, activity participation history records and derivative data of the clients, the user basic data comprises mobile phone numbers, ages and sexes corresponding to the clients, the activity participation history records comprise activity categories, activity affiliated industries, activity opening records, position information, business circle information and merchant information, and the derivative data comprises the total number of coupons, the category of the coupons and the coupon occupation ratio;
the calculation module is used for calculating the activity score of each client to the preset type of activity according to the participation activity historical record and the derivative data;
and the determining module is used for determining the client with the activity score larger than the preset score as a target client and pushing a preset message to the target client.
Optionally, the calculation module includes:
the first determining unit is used for determining each parameter in the participation activity history record and the sub-score corresponding to each parameter in the derived data;
and the calculating unit is used for calculating to obtain the activity score of each client to the preset activity according to the sub-scores.
Optionally, the calculation module includes:
the second determining unit is used for determining each parameter in the participation activity history record and the interest degree corresponding to each parameter in the derived data;
and the second determining unit is used for determining the interestingness as the activity score of each client on the preset activity.
An information pushing system comprises any one of the information pushing devices.
Based on the technical scheme, the embodiment of the invention provides an information pushing method which is applied to clients with a shaking function. According to the scheme, the activity scores of the clients for various activities are calculated, the client with higher score is used as the user with high interest degree of the activity, and then the corresponding message is pushed, so that the information pushing efficiency is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
Fig. 1 is a structural diagram of an information push system according to an embodiment of the present application;
fig. 2 is a flowchart of an information pushing method according to an embodiment of the present application;
fig. 3 is a flowchart of an information pushing method according to an embodiment of the present application;
fig. 4 is a flowchart of an information pushing method according to an embodiment of the present application;
fig. 5 is a block diagram of an information pushing apparatus according to an embodiment of the present disclosure;
fig. 6 is a block diagram of another information pushing apparatus according to an embodiment of the present disclosure;
fig. 7 is a block diagram of a structure of another information pushing apparatus according to an embodiment of the present application;
fig. 8 is a schematic hardware structure diagram of a server according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall correspond to the protection scope of the present invention.
Fig. 1 is a block diagram of a structure of an information push system based on a client with a shake-and-shake function according to an embodiment of the present application, where the information push system shown in the figure may be used to implement the information push method according to the embodiment of the present application. Referring to fig. 1, the information push system may include: a server 100 and a plurality of clients 200;
the server is a service device for providing services for users on a network side, and may be a server cluster formed by a plurality of servers or a single server.
The client is a program corresponding to the server and providing a local service for the user, and in practical applications, the client may be generally loaded on user equipment such as a mobile phone, a tablet computer, a notebook computer, and the like.
Based on the information push system shown in fig. 1, the information push method provided by the present application is described below from the perspective of a server. As shown in fig. 2, a flowchart of an information pushing method provided in an embodiment of the present application is shown, where the method may include:
and S21, acquiring data information of a plurality of clients based on preset type activities.
The data of each offline shaking activity is collected, wherein the data information comprises user basic data of a client, a history record of the participation activity and derivative data, the user basic data comprises a mobile phone number, an age and a sex corresponding to the client, the history record of the participation activity comprises the category of the activity, the industry to which the activity belongs, an opening activity record, position information, business circle information and merchant information, and the derivative data comprises the total number of coupons, the category to which the coupons belong, the proportion of the coupons and the like.
And S22, calculating the activity score of each client to the preset type of activity according to the participation activity history records and the derivative data.
S23, determining the client with the activity score larger than the preset score as a target client, and pushing a preset message to the target client.
In this embodiment, two activity scoring models are established, the activity score of each activity is calculated, and then information recommendation is performed according to the activity score, specifically, the activity scoring models can be divided into a model for scoring based on activity content and a model for scoring based on LBS scenarios according to different division dimensions.
As shown in fig. 3, the activity content-based scoring model is implemented by calculating an activity score of each client for the preset activity according to the participation activity history and the derivative data by the following steps:
s31, determining each parameter in the participation activity history record and the sub-score corresponding to each parameter in the derived data;
and S32, calculating the activity score of each client to the preset activity according to the sub-scores.
The embodiment mainly calculates the scores of all types of activities for the user, and the creation process of the score model calculates the scores according to the historical behavior records of the user for certain types of activities. For example: rating of user U under activity type C: u browsed C, scored S1; u-entitled C coupon, score S2; the coupon for C was sold by U, and scored S3; by analogy, U scores various behaviors for C.
In particular, it can be based on the formula
Calculating the activity score, wherein UiNumber of clients participating in Activity i, CiFor sub-scoring of activity i in which the client participates, CAL (U, C) for client to the pre-scoreSet the activity score for the type activity.
For example, when there are 5 activities C1, C2, C3, C4, and C5, respectively, then the scores of these 5 activities for user U1 are in turn: type C1 is scored CAL (U1, C1), type C2 is scored CAL (U1, C2), type C3 is scored CAL (U1, C3), type C4 is scored CAL (U1, C4), type C5 is scored CAL (U1, C5), where UC represents the sub-score of user U in C activity, and Σ U C represents the score of U in C all activities.
Correspondingly, the activity recommendation step is as follows:
setting an activity score threshold value of interest of a user:
calculating the activity score CAL (U, C) of each client to the preset activity when CAL (U, C)>M, recommending activities to the user; otherwise, it is not recommended.
In addition, as shown in fig. 4, the model for scoring based on the LBS scenario is implemented by calculating an activity score of each client for the preset activity according to the participation activity history and the derivative data as follows:
s41, determining each parameter in the participation activity history record and the corresponding interestingness of each parameter in the derived data;
and S42, determining the interestingness as the activity score of each client to the preset activity.
The embodiment determines the interestingness of the user, and then takes the interestingness as the activity score of the preset activity, specifically:
according to the formula
Calculating activity scores of the preset types of activities, wherein P (i) is the interest degree of the client to the participating activity i, NiThe number of activities for the preset type of activities, C is the category of the activities, C (M) is the interest degree of the client to the activities M, lambda is the weight, M is the activity numberiA set of activities related to activity i that the client is involved in.
In addition, the models of interestingness may include user interest models based on location scenarios:
It should be noted that the user interest level model based on the location scene is a three-dimensional spatial array, and records the interest level of the user in the activity interest category in a certain location scene.
Accordingly, the activity recommendation step is as follows:
firstly, obtaining scene information of a current position of a user, predicting a next position of the user and adding the position to the current scene information;
secondly, matching the interests of the user in the expanded position scene;
finally, judging whether the interestingness is greater than a threshold value, if so, matching the category of the activity to be recommended, taking the interest name with the maximum interestingness, and matching the activity resources; otherwise, generalizing the position scene and carrying out classification matching again.
The server provided by the embodiment of the present application is introduced below, and the server described below and the information push described above in the server angle are referred to correspondingly. Referring to fig. 5, a block diagram of a server provided in the embodiment of the present application is shown, and the server may include
An obtaining module 51, configured to obtain data information of a plurality of clients based on preset types of activities.
The data information comprises user basic data, activity participation history records and derivative data of a client, wherein the user basic data comprises a mobile phone number, age and gender corresponding to the client, the activity participation history records comprise activity categories, activity affiliated industries, activity opening records, position information, business circle information and merchant information, and the derivative data comprises the total number of coupons, the category of coupons and the duty ratio of coupons;
a calculating module 52, configured to calculate, according to the participation activity history record and the derivative data, an activity score of each client for the preset type of activity;
the determining module 53 is configured to determine that the client with the activity score greater than the preset score is a target client, and push a preset message to the target client.
On the basis of the above embodiment, as shown in fig. 6, the calculation module 52 includes:
a first determining unit 521, configured to determine each parameter in the participation activity history record and a sub-score corresponding to each parameter in the derived data;
and the calculating unit 522 is configured to calculate, according to the sub-scores, an activity score of each client for the preset activity.
In addition, as shown in fig. 7, the calculation module 52 further includes:
a second determining unit 523, configured to determine parameters in the participation activity history record and interest degrees corresponding to the parameters in the derived data;
a third determining unit 524, configured to determine the interestingness as an activity score of each client on the preset activity.
What has been described above is a software functional module architecture of a server, and on the hardware structure of the server, the server can implement a data processing scheme based on multimedia information in the following manner;
fig. 8 is a block diagram of a hardware structure of a server according to an embodiment of the present application, and referring to fig. 8, the server may include: a processor 81, a communication interface 82, a memory 83 and a communication bus 84;
the processor 81, the communication interface 82 and the memory 83 complete mutual communication through the communication bus 84;
alternatively, the communication interface 82 may be an interface of a communication module, such as an interface of a GSM module;
a processor 81 for executing a program;
a memory 83 for storing programs;
the program may include program code including computer operating instructions.
The processor 81 may be a central processing unit CPU or an application Specific Integrated circuit asic or one or more Integrated circuits configured to implement embodiments of the present application.
The memory 83 may comprise a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.
Among them, the procedure can be specifically used for:
acquiring data information of a plurality of clients based on preset type activities;
calculating the activity score of each client to the preset type of activity according to the participation activity history records and the derivative data;
and determining the client with the activity score larger than the preset score as a target client, and pushing a preset message to the target client.
The present embodiment further provides an information pushing system, a block diagram of the system is shown in fig. 1, and the system includes a server 100 and a plurality of clients 200, where:
the server 100 is configured to obtain data information of a plurality of clients based on preset type activities; calculating the activity score of each client to the preset type of activity according to the participation activity history records and the derivative data; determining the client with the activity score larger than a preset score as a target client, and pushing a preset message to the target client;
the client 200 is used for displaying the push message.
In summary, an embodiment of the present invention provides an information pushing method, which is applied to a client having a shake function, and includes obtaining data information of a plurality of clients based on a preset type of activity, then calculating an activity score of each client for the preset type of activity according to the historical record of participating in the activity and the derivative data, and finally determining that the client having the activity score greater than the preset score is a target client and pushing a preset message to the target client. According to the scheme, the activity scores of the clients for various activities are calculated, the client with higher score is used as the user with high interest degree of the activity, and then the corresponding message is pushed, so that the information pushing efficiency is improved.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (6)
1. An information push method is applied to a client with a shake function, and comprises the following steps:
the method comprises the steps that data information of a plurality of clients based on preset type activities is obtained, the data information comprises user basic data, activity participation history records and derivative data of the clients, the user basic data comprises mobile phone numbers, ages and sexes corresponding to the clients, the activity participation history records comprise activity types, activity affiliated industries, opening activity records, position information, business circle information and merchant information, and the derivative data comprises the total number of coupons, the category of coupons and the proportion of coupons;
calculating the activity score of each client to the preset type of activity according to the participation activity history records and the derivative data;
determining the client with the activity score larger than a preset score as a target client, and pushing a preset message to the target client;
the calculating the activity score of each client to the preset activity according to the participation activity history record and the derivative data comprises:
determining the interest degree corresponding to each parameter in the historical record of the participation activity and each parameter in the derived data;
determining the interestingness as an activity score of each client on the preset activity;
the determining the interestingness as an activity score of each client to the preset activity comprises:
according to the formula
Calculating activity scores of the preset types of activities, wherein P (i) is the interest degree of the client to the participating activity i, lambda is weight, and N isiNumber of activities to participate in type i, NjNumber of activities of type j to participate, C (M) interest level of client in activity M, I activity set related to activity j to participate in by client, MiA set of activities related to activity i that the client is involved in.
2. The information pushing method according to claim 1, wherein the calculating an activity score of each client for the preset activity according to the participation activity history and the derivative data comprises:
determining parameters in the participation activity history record and sub-scores corresponding to the parameters in the derived data;
and calculating to obtain the activity score of each client to the preset activity according to the sub-scores.
3. The information pushing method according to claim 2, wherein the calculating, according to the sub-scores, an activity score of each client for the preset type of activity includes:
according to the formula
Calculating the activity score, wherein UiNumber of clients participating in Activity i, CiThe CAL (U, C) scores the activity of the preset type of activity for the client;
accordingly, according to the formula
And calculating the preset score.
4. An information pushing apparatus, applied to a client with a shake function, includes:
the system comprises an acquisition module, a display module and a display module, wherein the acquisition module is used for acquiring data information of a plurality of clients based on preset types of activities, the data information comprises user basic data, activity participation history records and derivative data of the clients, the user basic data comprises mobile phone numbers, ages and sexes corresponding to the clients, the activity participation history records comprise activity categories, activity affiliated industries, activity opening records, position information, business circle information and merchant information, and the derivative data comprises the total number of coupons, the category of the coupons and the coupon occupation ratio;
the calculation module is used for calculating the activity score of each client to the preset type of activity according to the participation activity historical record and the derivative data;
the determining module is used for determining the client with the activity score larger than the preset score as a target client and pushing a preset message to the target client;
the calculation module comprises:
the second determining unit is used for determining each parameter in the participation activity history record and the interest degree corresponding to each parameter in the derived data;
a third determining unit, configured to determine the interestingness as an activity score of each client on the preset activity;
the calculation module is also used for calculating the formula
Calculating activity scores of the preset types of activities, wherein P (i) is the interest degree of the client to the participating activity i, lambda is weight, and N isiNumber of activities of type I to participate, C (m) interest level of client in activity m, and I activity set related to activity j to which client participatesAnd then, MiA set of activities related to activity i that the client is involved in.
5. The information pushing apparatus according to claim 4, wherein the calculation module comprises:
the first determining unit is used for determining each parameter in the participation activity history record and the sub-score corresponding to each parameter in the derived data;
and the calculating unit is used for calculating to obtain the activity score of each client to the preset activity according to the sub-scores.
6. An information push system, characterized by comprising an information push apparatus according to any one of claims 4 to 5.
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| CN101751448A (en) * | 2009-07-22 | 2010-06-23 | 中国科学院自动化研究所 | Commendation method of personalized resource information based on scene information |
| JP5404662B2 (en) * | 2011-01-17 | 2014-02-05 | 日本電信電話株式会社 | Product recommendation device, method and program |
| CN104699711A (en) * | 2013-12-09 | 2015-06-10 | 华为技术有限公司 | Recommendation method and server |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN102902691B (en) * | 2011-07-28 | 2016-09-07 | 上海拉手信息技术有限公司 | Recommend method and system |
| US20160055377A1 (en) * | 2014-08-19 | 2016-02-25 | International Business Machines Corporation | Real-time analytics to identify visual objects of interest |
| US20160196582A1 (en) * | 2015-01-02 | 2016-07-07 | Verizon Patent And Licensing Inc. | Subscriber location audience insights for enterprise networks |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101751448A (en) * | 2009-07-22 | 2010-06-23 | 中国科学院自动化研究所 | Commendation method of personalized resource information based on scene information |
| JP5404662B2 (en) * | 2011-01-17 | 2014-02-05 | 日本電信電話株式会社 | Product recommendation device, method and program |
| CN104699711A (en) * | 2013-12-09 | 2015-06-10 | 华为技术有限公司 | Recommendation method and server |
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