CN111639976A - Target popularization place determining method and device, storage medium and electronic equipment - Google Patents

Target popularization place determining method and device, storage medium and electronic equipment Download PDF

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CN111639976A
CN111639976A CN202010507003.XA CN202010507003A CN111639976A CN 111639976 A CN111639976 A CN 111639976A CN 202010507003 A CN202010507003 A CN 202010507003A CN 111639976 A CN111639976 A CN 111639976A
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historical
personnel
place
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CN111639976B (en
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栾英英
童楚婕
严洁
彭勃
李福洋
徐晓健
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Bank of China Ltd
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Abstract

The invention provides a method and a device for determining a target popularization place, a storage medium and electronic equipment. And then, establishing a user popularization acceptance model based on feedback acceptance data of the historical popularized users and characteristic attribute data of historical staying personnel at the candidate place, and establishing a candidate place personnel mobility prediction model based on historical personnel mobility data of the candidate place and characteristic attribute data of the historical staying personnel at the candidate place. And then, determining the product promotion success rate of each candidate site corresponding to the day to be promoted based on the user promotion acceptance model and the candidate site personnel mobility prediction model, and determining the candidate site with the product promotion success rate larger than the preset value as the target promotion site. Namely, the target is predicted to be popularized by creating a model, and the target is not influenced by human subjectivity.

Description

Target popularization place determining method and device, storage medium and electronic equipment
Technical Field
The invention relates to the technical field of data processing, in particular to a method and a device for determining a target popularization place, a storage medium and electronic equipment.
Background
At present, many products need to be popularized, such as small program popularization, APP popularization, credit card popularization, food popularization and the like, and the selection of a popularization place can influence the popularization success rate of the products to a certain extent. Generally, when a popularization person carries out product popularization, the popularization place is determined according to personal experience, for example, a place with a large flow of people is selected as a target popularization place, so that the popularization success rate of the popularized product is increased.
The inventor finds that the situation with large pedestrian volume is selected as the target popularization place through artificial experience, the determined target popularization place is not suitable for the popularization product, and the phenomenon of manpower cost waste caused by inaccurate popularization place determination is caused.
Therefore, how to provide a method for determining a target popularization, which can improve the popularization success rate of the popularized product, is a great technical problem to be solved urgently by technical personnel in the field.
Disclosure of Invention
In view of this, the embodiment of the present invention provides a method for determining a target popularization area, which can improve a popularization success rate of a popularized product.
In order to achieve the above purpose, the embodiments of the present invention provide the following technical solutions:
a targeted promotion location determination method, comprising:
acquiring feedback acceptance data of a historical promoted user, historical personnel flow data of a candidate place and characteristic attribute data of historical staying personnel of the candidate place;
establishing a user popularization acceptance model based on the feedback acceptance data of the historical popularized users and the characteristic attribute data of the historical staying personnel in the candidate places;
establishing a candidate site personnel mobility prediction model based on the historical personnel mobility data of the candidate site and the characteristic attribute data of the historical staying personnel of the candidate site;
determining the product promotion success rate of each candidate place corresponding to the day to be promoted based on the user promotion acceptance model and the candidate place personnel mobility prediction model;
and determining the candidate place with the product promotion success rate larger than a preset value as the target promotion place.
Optionally, the method further includes:
and displaying the target popularization place according to the product popularization success rate.
Optionally, the establishing a user popularization acceptance model based on the feedback acceptance data of the historical popularized user and the characteristic attribute data of the historical staying personnel in the candidate location includes:
inputting feedback acceptance data of the historical promoted users and characteristic attribute data of the historical staying personnel in the candidate places into a first preset regression algorithm to obtain a user promotion acceptance model;
the establishing of the candidate location personnel mobility prediction model based on the historical personnel mobility data of the candidate location and the characteristic attribute data of the historical staying personnel of the candidate location comprises the following steps:
and inputting the historical personnel mobility data of the candidate place and the characteristic attribute data of the historical staying personnel of the candidate place into a second preset regression algorithm to obtain the candidate place personnel mobility prediction model.
Optionally, the determining the product promotion success rate of each candidate location corresponding to the day to be promoted based on the user promotion acceptance model and the candidate location personnel mobility prediction model includes:
acquiring a staying personnel group matrix of the candidate site personnel mobility prediction model based on the target candidate site predicted by the to-be-promoted day;
and determining the product promotion success rate of each candidate place predicted by the user promotion acceptance model based on the staying personnel group matrix of the target candidate place.
An targeted promotion location determination apparatus comprising:
the acquisition module is used for acquiring feedback acceptance data of a historical promoted user, historical personnel flow data of a candidate place and characteristic attribute data of historical staying personnel of the candidate place;
the first creating module is used for creating a user popularization acceptance model based on the feedback acceptance data of the historical popularized users and the characteristic attribute data of the historical staying personnel in the candidate places;
the second creating module is used for building a candidate place personnel mobility prediction model based on the historical personnel mobility data of the candidate place and the characteristic attribute data of the historical staying personnel of the candidate place;
the first determination module is used for determining the product promotion success rate of each candidate place corresponding to the day to be promoted based on the user promotion acceptance model and the candidate place personnel mobility prediction model;
and the second determination module is used for determining the candidate site with the product promotion success rate larger than the preset value as the target promotion site.
Optionally, the method further includes:
and the display module is used for displaying the target popularization place according to the product popularization success rate.
Optionally, the first creating module includes:
the first generation unit is used for inputting feedback acceptance data of the historical promoted users and characteristic attribute data of the historical staying personnel in the candidate places into a first preset regression algorithm to obtain a user promotion acceptance model;
the second creation module includes:
and the second generation unit is used for inputting the historical personnel mobility data of the candidate site and the characteristic attribute data of the historical staying personnel of the candidate site into a second preset regression algorithm to obtain the candidate site personnel mobility prediction model.
Optionally, the first determining module includes:
the acquisition unit is used for acquiring a staying personnel population matrix of the candidate site personnel mobility prediction model based on the target candidate site predicted by the to-be-promoted day;
and the determining unit is used for determining the product promotion success rate of each candidate place predicted by the user promotion acceptance model based on the staying personnel group matrix of the target candidate place.
A storage medium comprising a stored program, wherein the program, when executed, controls a device on which the storage medium is located to execute any one of the above-mentioned target promotion location determination methods.
An electronic device comprising at least one processor, and at least one memory, bus connected to the processor; the processor and the memory complete mutual communication through the bus; the processor is configured to call program instructions in the memory to perform any one of the above-described target promotion location determination methods.
Based on the technical scheme, the embodiment of the invention provides a method, a device, a storage medium and electronic equipment for determining a target popularization place. And then, establishing a user popularization acceptance model based on feedback acceptance data of the historical popularized users and characteristic attribute data of historical staying personnel at the candidate place, and establishing a candidate place personnel mobility prediction model based on historical personnel mobility data of the candidate place and characteristic attribute data of the historical staying personnel at the candidate place. And then, determining the product promotion success rate of each candidate site corresponding to the day to be promoted based on the user promotion acceptance model and the candidate site personnel mobility prediction model, and determining the candidate site with the product promotion success rate larger than the preset value as the target promotion site. Therefore, the invention provides a method for predicting the target popularization place based on the created model, which is not influenced by human subjectivity, determines the candidate place with the product popularization success rate larger than the preset value as the target popularization place based on historical data, and further improves the popularization success rate of the popularized product.
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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 schematic flow chart of a method for determining a target popularization location according to an embodiment of the present invention;
fig. 2 is a schematic flowchart of a method for determining a target popularization location according to an embodiment of the present invention;
fig. 3 is a schematic flowchart of a method for determining a target popularization location according to an embodiment of the present invention;
fig. 4 is a schematic flowchart of a method for determining a target popularization location according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of a target popularization location determining apparatus according to an embodiment of the present invention;
fig. 6 is a hardware configuration diagram of a target popularization location determining apparatus according to an embodiment of the present invention.
Detailed Description
As background art, at present, a place with a large flow of people is selected as a target popularization place through human experience, which may cause that the determined target popularization place is not suitable for a popularization product, and a phenomenon of manpower cost waste caused by inaccurate popularization place determination is generated.
Based on the method, the target popularization place is predicted based on the created model, the method is not influenced by human subjectivity, and the candidate place with the product popularization success rate larger than the preset value is determined to be the target popularization place based on historical data, so that the popularization success rate of the popularized product is improved.
Specifically, as shown in fig. 1, fig. 1 is a schematic flow chart of a method for determining a target popularization location according to an embodiment of the present invention, where the method for determining a target popularization location includes:
s11, obtaining feedback acceptance data of a historical promoted user, historical personnel flow data of a candidate place and characteristic attribute data of historical staying personnel of the candidate place;
the feedback acceptance data of the history promoted users represents the acceptance data of the history promoted products fed back by the users, for example, a certain APP is promoted at a certain market gate on a certain day, it is assumed that the APP is promoted to 50 users on the same day, and the receptivity of the 50 users to the APP is collected on the spot, wherein the receptivity is divided into three receiving states of euphoria acceptance, disapproval acceptance and no-so-called acceptance, and the receptivity of the 50 users includes 10 disapproval receptions, 20 disapproval receptions and 20 natural receptions, so in this embodiment, the feedback acceptance data of the history promoted users may be 10 disapproval, 20 no-so-called receptions and 20 clear-received data on a certain day.
The historical people flow data of the candidate sites represents the people flow data of each candidate site at a certain site on a certain historical day, for example, 500 people flow at a certain mall on a certain day, 100 people flow at a certain school gate on a certain day, or 1000 people flow at a certain intersection on a certain day.
The characteristic attribute data of the historical stay people in the candidate place represents some preset attributes of people who receive the promoted product from the people who pass through the candidate place at a certain time, for example, 50 people stay at the gate of a certain market on a certain day, and then in this embodiment, the characteristic attribute data of the historical stay people in the candidate place may be the gender, the academic background, and the like of the 50 people.
In order to further improve the effectiveness of the data, the embodiment of the present invention further performs data preprocessing on the acquired feedback acceptance data of the history promoted user, the historical people movement amount data of the candidate location, and the feature attribute data of the historical staying people of the candidate location, for example, performs abnormal value cleaning, null value filling, feature vectorization, and the like on the data.
S12, establishing a user popularization acceptance model based on feedback acceptance data of historical popularized users and characteristic attribute data of historical staying personnel at candidate places;
s13, establishing a candidate site personnel mobility prediction model based on the historical personnel mobility data of the candidate site and the characteristic attribute data of the historical staying personnel of the candidate site;
in this embodiment, a regression algorithm is used for modeling, and specifically, an embodiment of the present invention provides a specific implementation manner for establishing a user popularization acceptance model based on feedback acceptance data of a history promoted user and feature attribute data of history staying people in a candidate place, as shown in fig. 2, including the steps of:
s21, inputting feedback acceptance data of the historical promoted users and characteristic attribute data of the historical staying personnel at the candidate places into a first preset regression algorithm to obtain a user promotion acceptance model;
in addition, the embodiment of the present invention further provides a specific implementation manner for establishing a candidate location personnel mobility prediction model based on historical personnel mobility data of a candidate location and characteristic attribute data of historical staying personnel of the candidate location, as shown in fig. 2, including the steps of:
and S22, inputting the historical personnel mobility data of the candidate site and the characteristic attribute data of the historical staying personnel of the candidate site into a second preset regression algorithm to obtain a candidate site personnel mobility prediction model.
Illustratively, the embodiment of the invention constructs a model by using a regression algorithm (linear regression, logistic regression, svm regression, etc.) through processed feedback acceptance data of the historical promoted users and feature attribute data of historical staying personnel at the candidate places, and forms a user promotion acceptance model.
And constructing a model by using a regression algorithm (linear regression, logistic regression, svm regression and the like) through the processed historical personnel mobility data of the candidate places and the characteristic attribute data of the historical staying personnel of the candidate places to form a candidate place personnel mobility prediction model.
S14, determining the product promotion success rate of each candidate site corresponding to the day to be promoted based on the user promotion acceptance model and the candidate site personnel mobility prediction model;
specifically, as shown in fig. 3, an embodiment of the present invention provides a specific implementation manner for determining a product promotion success rate of each candidate location corresponding to a day to be promoted based on a user promotion acceptance model and a candidate location personnel mobility prediction model, including the steps of:
s31, acquiring a staying personnel population matrix of the candidate site personnel mobility prediction model based on the target candidate site predicted by the to-be-promoted day;
and S32, determining the product promotion success rate of each candidate place predicted by the user promotion acceptance model based on the stay personnel population matrix of the target candidate place.
Illustratively, a staying person group matrix of a target candidate location corresponding to a day to be promoted is predicted through a candidate location person mobility prediction model, and for example, the matrix can be represented as:
Figure BDA0002526882380000071
wherein u ismRepresenting a user that contains n-dimensional feature attributes. And after determining a staying personnel group matrix of the target candidate site corresponding to the day to be promoted, predicting the product promotion success rate of each candidate site through a user promotion acceptance model according to the staying personnel group matrix.
And S15, determining the candidate site with the product promotion success rate larger than the preset value as the target promotion site.
Specifically, the product promotion success rates corresponding to the candidate locations determined in step S14 may be sorted according to the success rate, and then the candidate locations greater than a certain preset success rate may be determined as the target promotion locations.
Therefore, the invention provides a method for predicting the target popularization place based on the created model, which is not influenced by human subjectivity, determines the candidate place with the product popularization success rate larger than the preset value as the target popularization place based on historical data, and further improves the popularization success rate of the popularized product.
On the basis of the foregoing embodiment, as shown in fig. 4, the method for determining a target popularization location according to an embodiment of the present invention further includes:
and S41, displaying the target popularization place according to the product popularization success rate.
The product popularization success rate can be visually processed, so that the user can select a target popularization place.
On the basis of the above-described embodiment, as shown in fig. 5, the present embodiment further provides a target popularization place determination apparatus, including:
the obtaining module 51 is configured to obtain feedback acceptance data of a historical promoted user, historical people flow data of a candidate location, and feature attribute data of historical staying people of the candidate location;
the first creating module 52 is configured to create a user popularization acceptance model based on feedback acceptance data of a historical popularized user and feature attribute data of historical staying personnel in a candidate place;
the second creating module 53 is configured to create a candidate location personnel mobility prediction model based on the historical personnel mobility data of the candidate location and the characteristic attribute data of the historical staying personnel of the candidate location;
the first determining module 54 is configured to determine, based on the user popularization acceptance model and the candidate location personnel mobility prediction model, a product popularization success rate of each candidate location corresponding to a day to be popularized;
and a second determining module 55, configured to determine that the candidate location with the product promotion success rate greater than the preset value is the target promotion location.
On the basis of the foregoing embodiment, the apparatus for determining a target popularization location according to an embodiment of the present invention may further include:
and the display module is used for displaying the target popularization place according to the product popularization success rate.
Specifically, the embodiment of the present invention further provides a specific implementation structure of the first creating module and the second creating module, which is as follows:
the first creating module includes:
the first generation unit is used for inputting feedback acceptance data of historical promoted users and characteristic attribute data of historical staying personnel in candidate places into a first preset regression algorithm to obtain a user promotion acceptance model;
the second creating module includes:
and the second generation unit is used for inputting the historical personnel mobility data of the candidate site and the characteristic attribute data of the historical staying personnel of the candidate site into a second preset regression algorithm to obtain a candidate site personnel mobility prediction model.
In addition, in the device for determining a target popularization location provided in the embodiment of the present invention, the first determining module may include:
the acquisition unit is used for acquiring a staying personnel group matrix of a target candidate place predicted by a candidate place personnel mobility prediction model based on a to-be-promoted day;
and the determining unit is used for determining the product promotion success rate of each candidate place predicted by the user promotion acceptance model based on the staying personnel group matrix of the target candidate place.
The working principle of the target popularization point determining device is described in the above method embodiment, and the description is not repeated here.
The target popularization place determining device comprises a processor and a memory, wherein the acquiring module, the first creating module, the second creating module, the first determining module, the second determining module and the like are stored in the memory as program units, and the processor executes the program units stored in the memory to realize corresponding functions.
The processor comprises a kernel, and the kernel calls the corresponding program unit from the memory. The kernel can be set to be one or more than one, and the promotion success rate of the promoted product is improved by adjusting the kernel parameters.
An embodiment of the present invention provides a storage medium on which a program is stored, which when executed by a processor implements the above-described target popularization place determination method.
The embodiment of the invention provides a processor, wherein the processor is used for running a program, and the target popularization place determining method is executed when the program runs.
An embodiment of the present invention provides an apparatus, as shown in fig. 6, the apparatus includes at least one processor 61, and at least one memory 62 and a bus 63 connected to the processor; the processor and the memory complete mutual communication through a bus; the processor is used for calling the program instructions in the memory so as to execute the target popularization place determination method. The device herein may be a server, a PC, a PAD, a mobile phone, etc.
The present application further provides a computer program product adapted to perform a program for initializing the following method steps when executed on a data processing device:
acquiring feedback acceptance data of a historical promoted user, historical personnel flow data of a candidate place and characteristic attribute data of historical staying personnel of the candidate place;
establishing a user popularization acceptance model based on feedback acceptance data of historical popularized users and characteristic attribute data of historical staying personnel in candidate places;
establishing a candidate site personnel mobility prediction model based on historical personnel mobility data of the candidate site and characteristic attribute data of historical staying personnel of the candidate site;
determining the product promotion success rate of each candidate place corresponding to the day to be promoted based on the user promotion acceptance model and the candidate place personnel mobility prediction model;
and determining the candidate place with the product promotion success rate larger than the preset value as a target promotion place.
Besides, the method also comprises the following steps:
and displaying the target popularization place according to the product popularization success rate.
The method for establishing the user popularization acceptance model based on the feedback acceptance data of the historical popularized users and the characteristic attribute data of the historical staying personnel in the candidate places comprises the following steps:
inputting feedback acceptance data of historical promoted users and characteristic attribute data of historical staying personnel in candidate places into a first preset regression algorithm to obtain a user promotion acceptance model;
establishing a candidate location personnel mobility prediction model based on historical personnel mobility data of the candidate location and characteristic attribute data of historical staying personnel of the candidate location, wherein the model comprises the following steps:
and inputting the historical personnel mobility data of the candidate site and the characteristic attribute data of the historical staying personnel of the candidate site into a second preset regression algorithm to obtain a candidate site personnel mobility prediction model.
Specifically, determining the product promotion success rate of each candidate location corresponding to the day to be promoted based on the user promotion acceptance model and the candidate location personnel mobility prediction model comprises:
acquiring a staying personnel group matrix of a candidate site personnel mobility prediction model based on a target candidate site predicted on a to-be-promoted day;
and determining the product promotion success rate of each candidate place predicted by the user promotion acceptance model based on the stay personnel group matrix of the target candidate place.
In summary, the embodiments of the present invention provide a method, an apparatus, a storage medium, and an electronic device for determining a target popularization place, where the method for determining a target popularization place first obtains feedback acceptability data of a historical promoted user, historical people flow amount data of a candidate place, and feature attribute data of historical staying people of the candidate place. And then, establishing a user popularization acceptance model based on feedback acceptance data of the historical popularized users and characteristic attribute data of historical staying personnel at the candidate place, and establishing a candidate place personnel mobility prediction model based on historical personnel mobility data of the candidate place and characteristic attribute data of the historical staying personnel at the candidate place. And then, determining the product promotion success rate of each candidate site corresponding to the day to be promoted based on the user promotion acceptance model and the candidate site personnel mobility prediction model, and determining the candidate site with the product promotion success rate larger than the preset value as the target promotion site. Therefore, the invention provides a method for predicting the target popularization place based on the created model, which is not influenced by human subjectivity, determines the candidate place with the product popularization success rate larger than the preset value as the target popularization place based on historical data, and further improves the popularization success rate of the popularized product.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a device includes one or more processors (CPUs), memory, and a bus. The device may also include input/output interfaces, network interfaces, and the like.
The memory may include volatile memory in a computer readable medium, Random Access Memory (RAM) and/or nonvolatile memory such as Read Only Memory (ROM) or flash memory (flash RAM), and the memory includes at least one memory chip. The memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in the process, method, article, or apparatus that comprises the element.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The above are merely examples of the present application and are not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims (10)

1. A method for determining a target popularization location is characterized by comprising the following steps:
acquiring feedback acceptance data of a historical promoted user, historical personnel flow data of a candidate place and characteristic attribute data of historical staying personnel of the candidate place;
establishing a user popularization acceptance model based on the feedback acceptance data of the historical popularized users and the characteristic attribute data of the historical staying personnel in the candidate places;
establishing a candidate site personnel mobility prediction model based on the historical personnel mobility data of the candidate site and the characteristic attribute data of the historical staying personnel of the candidate site;
determining the product promotion success rate of each candidate place corresponding to the day to be promoted based on the user promotion acceptance model and the candidate place personnel mobility prediction model;
and determining the candidate place with the product promotion success rate larger than a preset value as the target promotion place.
2. The method for determining a target promotion location according to claim 1, further comprising:
and displaying the target popularization place according to the product popularization success rate.
3. The targeted promotion location determination method of claim 1,
the step of establishing a user popularization acceptance model based on the feedback acceptance data of the historical popularized users and the characteristic attribute data of the historical staying personnel in the candidate places comprises the following steps:
inputting feedback acceptance data of the historical promoted users and characteristic attribute data of the historical staying personnel in the candidate places into a first preset regression algorithm to obtain a user promotion acceptance model;
the establishing of the candidate location personnel mobility prediction model based on the historical personnel mobility data of the candidate location and the characteristic attribute data of the historical staying personnel of the candidate location comprises the following steps:
and inputting the historical personnel mobility data of the candidate place and the characteristic attribute data of the historical staying personnel of the candidate place into a second preset regression algorithm to obtain the candidate place personnel mobility prediction model.
4. The method for determining the target popularization site according to claim 3, wherein the step of determining the product popularization success rate of each candidate site corresponding to the day to be popularized based on the user popularization acceptance model and the candidate site personnel mobility prediction model comprises:
acquiring a staying personnel group matrix of the candidate site personnel mobility prediction model based on the target candidate site predicted by the to-be-promoted day;
and determining the product promotion success rate of each candidate place predicted by the user promotion acceptance model based on the staying personnel group matrix of the target candidate place.
5. An targeted promotion location determination apparatus, comprising:
the acquisition module is used for acquiring feedback acceptance data of a historical promoted user, historical personnel flow data of a candidate place and characteristic attribute data of historical staying personnel of the candidate place;
the first creating module is used for creating a user popularization acceptance model based on the feedback acceptance data of the historical popularized users and the characteristic attribute data of the historical staying personnel in the candidate places;
the second creating module is used for building a candidate place personnel mobility prediction model based on the historical personnel mobility data of the candidate place and the characteristic attribute data of the historical staying personnel of the candidate place;
the first determination module is used for determining the product promotion success rate of each candidate place corresponding to the day to be promoted based on the user promotion acceptance model and the candidate place personnel mobility prediction model;
and the second determination module is used for determining the candidate site with the product promotion success rate larger than the preset value as the target promotion site.
6. The targeted promotion location determination apparatus of claim 5, further comprising:
and the display module is used for displaying the target popularization place according to the product popularization success rate.
7. The targeted promotion location determination apparatus of claim 5,
the first creation module includes:
the first generation unit is used for inputting feedback acceptance data of the historical promoted users and characteristic attribute data of the historical staying personnel in the candidate places into a first preset regression algorithm to obtain a user promotion acceptance model;
the second creation module includes:
and the second generation unit is used for inputting the historical personnel mobility data of the candidate site and the characteristic attribute data of the historical staying personnel of the candidate site into a second preset regression algorithm to obtain the candidate site personnel mobility prediction model.
8. The targeted promotional location determination apparatus according to claim 7, wherein said first determination module comprises:
the acquisition unit is used for acquiring a staying personnel population matrix of the candidate site personnel mobility prediction model based on the target candidate site predicted by the to-be-promoted day;
and the determining unit is used for determining the product promotion success rate of each candidate place predicted by the user promotion acceptance model based on the staying personnel group matrix of the target candidate place.
9. A storage medium, characterized in that the storage medium includes a stored program, wherein, when the program runs, a device in which the storage medium is located is controlled to execute the target popularization place determination method according to any one of claims 1 to 4.
10. An electronic device comprising at least one processor, and at least one memory, bus connected to the processor; the processor and the memory complete mutual communication through the bus; the processor is configured to call program instructions in the memory to perform the targeted promotion location determination method of any one of claims 1 to 4.
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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US10346870B1 (en) * 2012-05-08 2019-07-09 Groupon, Inc. Dynamic promotion analytics
CN110084634A (en) * 2019-03-18 2019-08-02 平安科技（深圳）有限公司 Optimization method, device, computer equipment and storage medium are launched in advertisement
CN110837930A (en) * 2019-11-07 2020-02-25 腾讯科技（深圳）有限公司 Address selection method, device, equipment and storage medium

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US10346870B1 (en) * 2012-05-08 2019-07-09 Groupon, Inc. Dynamic promotion analytics
CN110084634A (en) * 2019-03-18 2019-08-02 平安科技（深圳）有限公司 Optimization method, device, computer equipment and storage medium are launched in advertisement
CN110837930A (en) * 2019-11-07 2020-02-25 腾讯科技（深圳）有限公司 Address selection method, device, equipment and storage medium

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