CN113052502A - Resource allocation system and method based on influence machine mechanism - Google Patents
Resource allocation system and method based on influence machine mechanism Download PDFInfo
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Abstract
The invention discloses a resource allocation system based on an influence machine mechanism, which is applied to the resource allocation of an advertisement machine and comprises the following components: a terminal configured to interact with a user and upload interaction data; the server is configured to receive the interaction data uploaded by at least two terminal machines, input the interaction data into an influence module configured in the server, and distribute resources to the terminal machines according to the distribution data pair output by the influence module. The invention also discloses a resource allocation method based on the impact mechanism. The resource allocation system and method based on the influence machine mechanism can allocate resources according to the influence, namely contribution, generated by each advertising machine, and greatly improve the utilization rate of the resources.
Description
Technical Field
The invention relates to the technical field of communication information, in particular to a resource allocation system and method based on an influence machine mechanism.
Background
The advertisement player is a new generation of intelligent equipment, forms a complete advertisement broadcasting control system through terminal software control, network information transmission and multimedia terminal display, and carries out advertisement propaganda through multimedia materials such as pictures, characters, videos, small plug-ins (weather, exchange rate and the like). The initial idea of the advertising engine was to change the advertisement to active, so the interactivity of the advertising engine enabled it to serve many public services and thereby attract customers to actively view the advertisement.
An advertisement machine control mechanism in the prior art is disclosed in chinese patent application No. 202011481717.4, which is a method, an apparatus and a system for publishing advertisement of advertisement machines based on a cluster-type background, wherein the method comprises: after a user terminal is connected with a cluster background, the user terminal obtains terminal information of an advertising player in a local area network of the cluster background; obtaining the current layout of the corresponding advertising player terminal based on the advertising player terminal information in the local area network; the user terminal carries out playing, editing and setting on the advertisement information to be played on the cluster background based on the current layout of the corresponding advertising player terminal; publishing the edited and set advertisement information to be played in the cluster background based on the user terminal; and the cluster background pushes the released advertisement information to be played to the advertisement player terminal corresponding to the current layout according to the editing setting to play the advertisement. In the embodiment of the invention, the advertisement information on a plurality of advertisement machine terminals can be replaced, set and played simultaneously, and the maintenance cost is reduced.
The technology can find that all the advertisement machines are simultaneously set and synchronously played, namely that the resource sharing is synchronously carried out without considering the value of the advertisement machines, so that the advertisement machine generating low value can acquire the same resource as the advertisement machine generating high value, and the resource utilization rate is reduced.
Disclosure of Invention
The invention aims to solve the technical problem that in the prior art, the value of an advertising machine is not considered, so that an advertising machine generating low value can acquire the same resource as the advertising machine generating high value, the resource utilization rate is reduced, and the invention aims to provide a resource allocation system and a method based on an influence mechanism to solve the problem.
The invention is realized by the following technical scheme:
the resource allocation system based on the influence machine mechanism is applied to the resource allocation of the advertising machine and comprises the following components:
a terminal configured to interact with a user and upload interaction data;
the server is configured to receive the interaction data uploaded by at least two terminal machines, input the interaction data into an influence module configured in the server, and distribute resources to the terminal machines according to the distribution data pair output by the influence module.
In the invention, the terminal machine can be configured as various advertisement machines, such as advertisement machines of taxi, elevator, various channels and other positions; while resources in this application include, but are not limited to, priority play rights for premium advertising resources, financial rewards for the advertiser owner or carrier, bonus rights granted to the advertiser, and the like.
The invention adopts a right distribution mode for the corresponding resources of the advertisement player, and the advertisement player obtains various interactive data through interaction with a user; the interaction referred to here may be playing information such as advertisement to the user, or the user may interact with the advertisement machine through actions such as code scanning, payment, clicking, sharing, etc., and the interaction data is data generated in the processes, such as advertisement playing quantity, user code scanning times, user payment amount, user sharing times, etc.; the interaction data can be used as a reference for generating influence by an advertising machine. In the invention, a mode of configuring the influence module in the server for calculating the influence is adopted, and the server can be configured in the cloud, so that reliable calculation power can be provided for the calculation of the influence; the distribution data mentioned in the present invention is data distributed based on influence, and in the present technical solution, the distribution data may be generated by any known influence obtaining method. Through the allocation mode based on the influence mechanism, the invention can allocate resources according to the influence, namely contribution, generated by each advertising machine, thereby greatly improving the utilization rate of the resources.
Further, the interactive data comprises first data, second data and third data; the terminal acquires the data volume displayed to the user by the terminal in a preset period as first data, the data volume operated by the user on the terminal in the preset period as second data and the data volume displayed to the user accumulated by the terminal from the activation as third data.
Further, the influence module is configured to perform a first normalization process on the first data, the second data and the third data to form influence data of the terminal, and generate the distribution data according to the influence data; the distribution data is the ratio of the terminal machine influence in all the terminal machine influence; and the first standardization processing adopts weighting processing after obtaining the ratio of the first data, the second data or the third data of the terminal and the maximum value in the corresponding data.
Further, the second data includes fourth data, fifth data, sixth data, seventh data, and eighth data;
the terminal acquires the amount of commodities exchanged by the user on the terminal in a preset period as fourth data, the quantity of commodities exchanged by the user on the terminal in the preset period as fifth data, the quantity of advertisement shared by the user on the terminal in the preset period as sixth data, the quantity of advertisement bound by the user on the terminal in the preset period as seventh data and the quantity of advertisement read by the user on the terminal in the preset period as eighth data.
Further, the influence module is configured to perform a second normalization process on fourth data, fifth data, sixth data, seventh data and eighth data to form second influence data of the terminal, and generate distribution data corresponding to the second data according to the second influence data;
and the second standardization processing adopts weighting processing after obtaining the ratio of the fourth data, the fifth data, the sixth data, the seventh data and the eighth data of the terminal machine to the maximum value in the corresponding data.
Further, the allocation data is obtained according to the following formula:
Fi＝fi(s)+fi(c)+fi(k)；
in the formula DIPiFor the distribution data of the corresponding ith terminal, fi(s) influence data corresponding to the first data of the ith terminal, fi(c) Influence data corresponding to the third data of the ith terminal, fi(k) And influence data corresponding to the second data of the ith terminal.
Further, fi(s) is obtained according to the following formula:
fi(s)＝ω×f(si)÷f(Smax)
f(Smax)＝max(f(si))
in the formula, siFirst data for an ith terminal; ω is a weight when the first data is subjected to the first normalization processing;
fi(c) obtained according to the following formula:
fi(c)＝ν×f(ci)÷f(cmax)
f(cmax)＝max(f(ci))
in the formula, ciThird data for the ith terminal; ν is a weight when the first normalization processing is performed on the third data.
The resource allocation method based on the influence machine mechanism is applied to the resource allocation of the advertisement machine and comprises the following steps:
interacting with a user through a terminal to obtain interactive data;
receiving interactive data uploaded by at least two terminals, and inputting the interactive data into an influence module;
and allocating resources to the terminal according to the allocation data pair output by the influence module.
Further, the influencing module outputting the dispensing data comprises the following substeps:
the interactive data comprises first data, second data and third data; the terminal acquires the data volume displayed to the user by the terminal in a preset period as first data, the data volume operated by the user on the terminal in the preset period as second data and the data volume displayed to the user accumulated by the terminal from the activation as third data;
carrying out first standardization processing on the first data, the second data and the third data to form influence data of the terminal, and generating the distribution data according to the influence data; the distribution data is the ratio of the terminal machine influence in all the terminal machine influence; and the first standardization processing adopts weighting processing after obtaining the ratio of the first data, the second data or the third data of the terminal and the maximum value in the corresponding data.
Further, the step of performing a first normalization process on the first data, the second data and the third data to form influence data of the terminal, and generating the distribution data according to the influence data includes the substeps of:
the second data includes fourth data, fifth data, sixth data, seventh data, and eighth data;
the terminal acquires the amount of commodities exchanged by the user on the terminal in a preset period as fourth data, the quantity of commodities exchanged by the user on the terminal in the preset period as fifth data, the quantity of advertisement shared by the user on the terminal in the preset period as sixth data, the quantity of advertisement bound by the user on the terminal in the preset period as seventh data and the quantity of advertisement read by the user on the terminal in the preset period as eighth data;
performing second standardization processing on fourth data, fifth data, sixth data, seventh data and eighth data to form second influence data of the terminal, and generating distribution data corresponding to the second data according to the second influence data;
and the second standardization processing adopts weighting processing after obtaining the ratio of the fourth data, the fifth data, the sixth data, the seventh data and the eighth data of the terminal machine to the maximum value in the corresponding data.
Compared with the prior art, the invention has the following advantages and beneficial effects:
the resource allocation system and method based on the influence machine mechanism can allocate resources according to the influence, namely contribution, generated by each advertising machine, and greatly improve the utilization rate of the resources.
Drawings
The accompanying drawings, which are included to provide a further understanding of the embodiments of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the principles of the invention. In the drawings:
FIG. 1 is a system architecture diagram according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of an exemplary embodiment of an impact module architecture;
FIG. 3 is a schematic diagram of the method steps of an embodiment of the present invention;
FIG. 4 is a schematic diagram of the method steps of an embodiment of the present invention;
FIG. 5 is a schematic diagram of a method according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to examples and accompanying drawings, and the exemplary embodiments and descriptions thereof are only used for explaining the present invention and are not meant to limit the present invention.
Examples
The invention is realized by the following technical scheme:
to facilitate the explanation of the above resource allocation system based on impact mechanism, please refer to fig. 1, which provides a schematic diagram of a communication architecture of the resource allocation system 100 based on impact mechanism according to an embodiment of the present invention. The resource allocation system 100 based on the impact mechanism may include a terminal 300 and a server 200, wherein the terminal 00 is connected to the server in communication.
The present embodiment is mainly applied to resource allocation of an advertisement machine, wherein the terminal 300 is configured to interact with a user and upload interaction data;
the server 200 is configured to receive the interaction data uploaded by at least two terminal machines 300, input the interaction data into the influence module 201 configured in the server 200, and allocate resources to the terminal machines 300 according to the allocation data pairs output by the influence module 201.
In a specific embodiment, the server 200 may be a desktop computer, a tablet computer, a notebook computer, a mobile phone, or other devices capable of implementing data processing and data communication or cloud devices, which is not limited herein.
In this embodiment, the terminal 300 may be configured as various advertisement machines, such as advertisement machines in locations of taxis, elevators, various channels, etc.; while the resources in this embodiment include, but are not limited to, priority play rights for premium advertising resources, financial rewards for the advertiser owner or carrier, bonus rights granted to the advertiser, and the like.
In the embodiment, a right allocation mode for resources corresponding to the advertisement player is adopted, and the advertisement player acquires various interactive data through interaction with a user; the interaction referred to here may be playing information such as advertisement to the user, or the user may interact with the advertisement machine through actions such as code scanning, payment, clicking, sharing, etc., and the interaction data is data generated in the processes, such as advertisement playing quantity, user code scanning times, user payment amount, user sharing times, etc.; the interaction data can be used as a reference for generating influence by an advertising machine. In the invention, a mode of configuring the influence module 201 in the server 200 for influence calculation is adopted, and the server 200 can be configured in the cloud, so that reliable calculation power can be provided for the influence calculation; the distribution data mentioned in this embodiment is data distributed based on influence, and in this technical solution, the distribution data may be generated by any known influence obtaining method.
In one embodiment, the interaction data comprises first data, second data, and third data; the terminal 300 acquires a data amount, which is presented to a user by the terminal 300 in a preset period, as first data and a data amount, which is operated by the user on the terminal 300 in the preset period, as second data, and the data amount, which is presented to the user by the terminal 300 accumulated since activation, is taken as third data.
When the present embodiment is implemented, the advertisement player is used as the terminal 300, and the present embodiment adopts at least three kinds of data as the terminal 300 to provide the interactive data to the server 200. The first data is the data amount displayed to the user by the terminal 300 in a preset period, where the preset period may be configured to be one day, one week, one month or one year according to the needs of those skilled in the art; the display mode can be video, audio or any mode capable of displaying data, and for the first data, the data can be obtained without direct feedback of a user, for example, an advertising machine arranged in an elevator has a working period of generally 24 hours, and when a preset period is defined as one day, the number of videos broadcasted at 24 hours in the day is counted as the first data; similarly, if the advertising machine is arranged in a taxi and the working period of the advertising machine is generally 12 hours, when the preset period is defined as one day, counting the number of videos broadcast in the 12 hours of the day as first data; as is apparent from the above example, the device with the working period of 24 hours can obtain more first data volume than the device with the working period of 12 hours, which shows that the advertising machine in the elevator makes more contribution in data broadcasting and obtains more influence, and the first data represents the self-behavior data of one advertising machine.
The second data is the amount of data operated by the user on the terminal 300 in a predetermined period, and similarly, the predetermined period may be configured as one day, one week, one month or one year as required by those skilled in the art, and the predetermined period is generally configured as the same as the predetermined period of the first data.
The second data covers a wide range, and may include but is not limited to user click times, user sharing times, and other contents, which are necessarily acquired through interaction with a user, and by collecting data of the interaction, the second data may represent behavioral and effect data of an advertisement machine.
In this embodiment, the third data is the amount of data accumulated to be displayed to the user since the terminal 300 is activated, similar to the first data, the third data may be displayed in a video or audio manner or in any manner capable of displaying data, and the inventor has found that when the terminal 300 displays data, the acceptance of the data by the audience is gradually increased as the data display time is prolonged; for example, if a broadcast is required to call xxx-xxxxx at a certain time, a mind is formed for the audience with the increase of the playing times, and when the audience is confronted with the requirement, the audience can adopt the information data with a high probability, so that the inventor creatively selects the accumulated data as reference data, and the contribution degree of the terminal 300, namely the influence data can be more accurately represented by analyzing the influence of the three data.
Similarly, the operation process in this embodiment is a dynamic algorithm because of the adoption of the preset time mode, and the multidimensional consideration can be realized by adjusting the preset time mode, so that the method has strong adaptability.
In one embodiment, the influence module 201 is configured to perform a first normalization process on the first data, the second data, and the third data to form influence data of the terminal, and generate the distribution data according to the influence data; the distribution data is the ratio of the terminal machine influence in all the terminal machine influence; and the first standardization processing adopts weighting processing after obtaining the ratio of the first data, the second data or the third data of the terminal and the maximum value in the corresponding data.
In the prior art, it is difficult to accurately quantify the contribution values provided by different terminal machines 300, but in this embodiment, the effects of the terminal machines 300 are quantified to a certain extent by quantifying various behaviors and interaction results of the terminal machines 300, and the representation of the value of the terminal machines 300 is represented by a weighting process; in this embodiment, when the terminal 300 is used as an advertisement player, the value of the terminal 300 is the value of the advertisement transmission, and the advertisement transmission value can be more effectively evaluated after quantification in this way.
In this embodiment, the first normalization processing is preferably performed by obtaining a ratio of the first data, the second data, or the third data of the terminal to a maximum value in the corresponding data and then performing weighting processing, and the same method is also applicable to this embodiment as another method capable of performing normalization processing, such as a normalization algorithm.
In the present embodiment, the weight obtaining manner of the weighting process is different from that in the prior art, the obtaining of each influence factor of the influence is more than that in the big data analysis and the empirical judgment, the big data analysis needs a huge data group, and there are many disputes for the classification of the categories in the big data analysis, and the influence of different categories on the weight is fatal.
In the present embodiment, please refer to fig. 2 in combination, based on the above contents:
the influence module 201 further includes:
a generating module 211 configured to receive the first data, the second data and the third data, receive a preset weight and generate predicted influence data according to the preset weight, the first data, the second data and the third data;
a verification module 221, configured to receive the real influence data and the predicted influence data of the terminal 300 and generate a LOSS function according to a comparison between the real influence data and the predicted influence data;
when the LOSS function meets a preset requirement, the influence module 201 generates distribution data according to the weight corresponding to the predicted influence data;
when the LOSS function does not meet the preset requirement, the generating module 211 corrects the weight according to the LOSS function, and generates predicted influence data according to the corrected weight, the first data, the second data and the third data until the predicted influence data passes through the verification module 221; and verifying that the LOSS function meets preset requirements through the verification module 221.
In another embodiment, the second data includes fourth data, fifth data, sixth data, seventh data, and eighth data;
the terminal acquires the amount of commodities exchanged by the user on the terminal in a preset period as fourth data, the quantity of commodities exchanged by the user on the terminal in the preset period as fifth data, the quantity of advertisement shared by the user on the terminal in the preset period as sixth data, the quantity of advertisement bound by the user on the terminal in the preset period as seventh data and the quantity of advertisement read by the user on the terminal in the preset period as eighth data.
In this embodiment, as a specific implementation manner, the second data is classified in detail, the fourth data is an amount of commodity exchanged by the user on the terminal in a preset period, which may be defined according to the needs of those skilled in the art, similar to the first data, and the amount of commodity exchanged by the user and the terminal includes, but is not limited to, an amount of data for purchasing commodity, transferring money, borrowing money, and the like.
And the fifth data adopts the number of commodities interacted by the user on the terminal in a preset period, and the number of commodities can better reflect the number interacted by the user relative to the commodity price. The sixth data, the seventh data, and the eighth data are all important embodiments of the user interaction with the terminal 300.
In one embodiment, the influence module is configured to perform a second normalization process on fourth data, fifth data, sixth data, seventh data, and eighth data to form second influence data of the terminal, and generate assignment data corresponding to the second data according to the second influence data;
and the second standardization processing adopts weighting processing after obtaining the ratio of the fourth data, the fifth data, the sixth data, the seventh data and the eighth data of the terminal machine to the maximum value in the corresponding data.
In this embodiment, in addition to processing the first data, the second data, and the third data, the fourth data, the fifth data, the sixth data, the seventh data, and the eighth data are also processed as the second data, and this hierarchical processing manner can further ensure the accuracy of data processing. The weighting processing for the fourth data, the fifth data, the sixth data, the seventh data, and the eighth data may be implemented by the generation module 211 and the check module 221.
In a specific implementation, the generating module 211 is configured to receive the fourth data, the fifth data, the sixth data, the seventh data, and the eighth data, receive a preset secondary weight, and generate predicted secondary influence data according to the preset secondary weight, the fourth data, the fifth data, the sixth data, the seventh data, and the eighth data;
a verification module 221 configured to receive the real secondary influence data and the predicted secondary influence data of the terminal 300 and generate a secondary LOSS function according to a comparison of the real secondary influence data and the predicted secondary influence data;
when the secondary LOSS function meets a preset requirement, the influence module 201 generates correction data corresponding to second data according to the secondary weight corresponding to the predicted secondary influence data;
when the secondary LOSS function does not meet the preset requirement, the generating module 211 corrects the secondary weight according to the secondary LOSS function, and generates predicted secondary influence data according to the corrected secondary weight, fourth data, fifth data, sixth data, seventh data, and eighth data until the secondary predicted influence data passes through the verification module 221; the secondary LOSS function is verified to meet the preset requirement by the verification module 221.
Through the weight generation process of above-mentioned mode, carry out approximation step by step to the truest weight equivalently, because the server can be built at the high in the clouds, the powerful calculation power in application high in the clouds, can accomplish this operation, and data change has taken place in arbitrary period, this embodiment also can utilize this kind of mode to carry out the generation of weight, the uncertainty that the mode of having avoided acquireing the weight through experience brought, and simultaneously, the sample that needs is also very few, only need a sample once complete operation cycle, can the effectual suitability that improves this application.
In another embodiment, the allocation data is obtained according to the following equation:
Fi＝fi(s)+fi(c)+fi(k)；
in the formula DIPiFor the distribution data of the corresponding ith terminal, fi(s) influence data corresponding to the first data of the ith terminal, fi(c) Influence data corresponding to the third data of the ith terminal, fi(k) And influence data corresponding to the second data of the ith terminal.
Further, fi(s) is obtained according to the following formula:
fi(s)＝ω×f(si)÷f(Smax)
f(Smax)＝max(f(si))
in the formula, siFirst data for an ith terminal; ω is a weight when the first data is subjected to the first normalization processing;
fi(c) obtained according to the following formula:
fi(c)＝ν×f(ci)÷f(cmax)
f(cmax)＝max(f(ci))
in the formula, ciThird data for the ith terminal; ν is a weight when the first normalization processing is performed on the third data.
In the present embodiment, a first normalization processing manner is shown, and algorithms that can achieve such effects in addition to this processing manner can be used instead in the present embodiment.
In a further embodiment, the fourth data, the fifth data, the sixth data, the seventh data and the eighth data may also be processed based on the following processes:
fi(k)＝(fi(gv)+fi(gn))×fi(t)+fi(b)+fi(share)+fi(r)
the processing procedure of the fourth data is as follows:
fi(gv)＝α×f(gvi)÷f(gvmax)
f(gvmax)＝max(f(gvi))
in the formula gviFourth data for the ith terminal; α is a weight when the fourth data is subjected to the second normalization processing.
The processing procedure of the fifth data is as follows:
fi(gn)＝β×f(gni)÷f(gnmax)
f(gnmax)＝max(f(gni))
in the formula gniFifth data for the ith terminal; β is a weight when the fifth data is subjected to the second normalization processing.
The processing procedure of the sixth data is as follows:
fi(share)＝γ×f(sharei)÷f(sharemax)
f(sharemax)＝max(f(sharei))
in the formula shareiSixth data for the ith terminal; γ is a weight when the sixth data is subjected to the second normalization processing.
The seventh data processing procedure is as follows:
fi(b)＝ε×f(bi)÷f(bmax)
f(bmax)＝max(f(bi))
in the formula biSeventh data for the ith terminal; ε is a weight of the seventh data when the second normalization process is performed.
The eighth data processing procedure is as follows:
fi(r)＝θ×f(ri)÷f(rmax)
f(rmax)＝max(f(ri))
in the formula riEighth data for the ith terminal; θ is a weight when the eighth data is subjected to the second normalization processing.
The resources finally acquired by the terminal 300 are acquired as follows:
Yi＝DIPi×Z
in the formula YiZ is the total resource amount for the acquired resource of the ith terminal.
Based on the same inventive concept, please refer to fig. 3, which is a schematic flow chart of the resource allocation method based on the impact mechanism according to the embodiment of the present invention, and is applied to resource allocation of the advertisement player, including the following steps:
s1: interacting with a user through the terminal 300 to obtain interactive data;
s2: receiving the interactive data uploaded by at least two terminals 300, and inputting the interactive data into the influence module 201;
s3: resources are allocated to the terminal 300 according to the allocation data pairs output by the influence module 201.
In this embodiment, the execution main body may be a cloud server, a local server, or one or more of a desktop computer and a notebook computer. The resource allocation method based on the impact mechanism may be applied to the server 200 in fig. 1.
Further, referring to fig. 4, the resource allocation method based on the impact mechanism may specifically include the following steps described in step S21-step S22, and the impact module 201 outputting the allocation data includes the following sub-steps:
s21, the interactive data comprises first data, second data and third data; the terminal 300 acquires a data volume displayed to a user by the terminal 300 in a preset period as first data and a data volume operated by the user on the terminal 300 in the preset period as second data, and the terminal 300 accumulates the data volume displayed to the user since activation as third data;
s22, carrying out first standardization processing on the first data, the second data and the third data to form influence data of the terminal 300, and generating the distribution data according to the influence data; the allocation data is a percentage of the terminal 300 impact among all terminal 300 impacts; the first normalization process is a weighting process that obtains a ratio of the first data, the second data, or the third data of the terminal 300 to a maximum value among the corresponding data.
Further, referring to fig. 5, the resource allocation method based on the impact mechanism may specifically include the following steps S221 to S222, where performing a first normalization process on the first data, the second data, and the third data to form impact data of the terminal 300, and generating the allocation data according to the impact data includes the following sub-steps:
s221, the second data comprises fourth data, fifth data, sixth data, seventh data and eighth data;
the terminal acquires the amount of commodities exchanged by the user on the terminal in a preset period as fourth data, the quantity of commodities exchanged by the user on the terminal in the preset period as fifth data, the quantity of advertisement shared by the user on the terminal in the preset period as sixth data, the quantity of advertisement bound by the user on the terminal in the preset period as seventh data and the quantity of advertisement read by the user on the terminal in the preset period as eighth data;
s222, carrying out second standardization processing on fourth data, fifth data, sixth data, seventh data and eighth data to form second influence data of the terminal, and generating distribution data corresponding to the second data according to the second influence data; and the second standardization processing adopts weighting processing after obtaining the ratio of the fourth data, the fifth data, the sixth data, the seventh data and the eighth data of the terminal machine to the maximum value in the corresponding data.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are merely exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (10)
1. A resource allocation system based on an impact force mechanism, comprising:
a terminal configured to interact with a user and upload interaction data;
the server is configured to receive the interaction data uploaded by at least two terminal machines, input the interaction data into an influence module configured in the server, and distribute resources to the terminal machines according to the distribution data pair output by the influence module.
2. The force-based resource allocation system of claim 1, wherein the interaction data comprises first data, second data, and third data; the terminal acquires the data volume displayed to the user by the terminal in a preset period as first data, the data volume operated by the user on the terminal in the preset period as second data and the data volume displayed to the user accumulated by the terminal from the activation as third data.
3. The resource allocation system according to claim 2, wherein the influence module is configured to perform a first normalization process on the first data, the second data and the third data to form influence data of the terminal, and generate the allocation data according to the influence data; the distribution data is the ratio of the terminal machine influence in all the terminal machine influence; and the first standardization processing adopts weighting processing after obtaining the ratio of the first data, the second data or the third data of the terminal and the maximum value in the corresponding data.
4. The force-based resource allocation system of claim 3, wherein the second data comprises fourth data, fifth data, sixth data, seventh data, and eighth data;
the terminal acquires the amount of commodities exchanged by the user on the terminal in a preset period as fourth data, the quantity of commodities exchanged by the user on the terminal in the preset period as fifth data, the quantity of advertisement shared by the user on the terminal in the preset period as sixth data, the quantity of advertisement bound by the user on the terminal in the preset period as seventh data and the quantity of advertisement read by the user on the terminal in the preset period as eighth data.
5. The resource allocation system based on an impact mechanism as claimed in claim 4, wherein the impact module is configured to perform a second normalization process on the fourth data, the fifth data, the sixth data, the seventh data and the eighth data to form second impact data of the terminal, and generate allocation data corresponding to the second data according to the second impact data;
and the second standardization processing adopts weighting processing after obtaining the ratio of the fourth data, the fifth data, the sixth data, the seventh data and the eighth data of the terminal machine to the maximum value in the corresponding data.
6. The force-impact-mechanism-based resource allocation system of claim 3, wherein the allocation data is obtained according to the following equation:
Fi＝fi(s)+fi(c)+fi(k)；
in the formula DIPiFor the distribution data of the corresponding ith terminal, fi(s) influence data corresponding to the first data of the ith terminal, fi(c) Influence data corresponding to the third data of the ith terminal, fi(k) And influence data corresponding to the second data of the ith terminal.
7. The force-of-influence mechanism-based resource allocation system of claim 6, wherein fi(s) is obtained according to the following formula:
fi(s)＝ω×f(si)÷f(Smax)
f(Smax)＝max(f(si))
in the formula, siFirst data for an ith terminal; ω is a weight when the first data is subjected to the first normalization processing;
fi(c) obtained according to the following formula:
fi(c)＝ν×f(ci)÷f(cmax)
f(cmax)＝max(f(ci))
in the formula, ciThird data for the ith terminal; ν is a weight when the first normalization processing is performed on the third data.
8. The resource allocation method based on the impact mechanism is characterized by comprising the following steps of:
interacting with a user through a terminal to obtain interactive data;
receiving interactive data uploaded by at least two terminals, and inputting the interactive data into an influence module;
and allocating resources to the terminal according to the allocation data pair output by the influence module.
9. The method of claim 8, wherein the impact module outputting allocation data comprises the substeps of:
the interactive data comprises first data, second data and third data; the terminal acquires the data volume displayed to the user by the terminal in a preset period as first data, the data volume operated by the user on the terminal in the preset period as second data and the data volume displayed to the user accumulated by the terminal from the activation as third data;
carrying out first standardization processing on the first data, the second data and the third data to form influence data of the terminal, and generating the distribution data according to the influence data; the distribution data is the ratio of the terminal machine influence in all the terminal machine influence; and the first standardization processing adopts weighting processing after obtaining the ratio of the first data, the second data or the third data of the terminal and the maximum value in the corresponding data.
10. The method of claim 8, wherein the first normalizing the first data, the second data, and the third data to form the impact data of the terminal, and the generating the allocation data according to the impact data comprises the following sub-steps:
the second data includes fourth data, fifth data, sixth data, seventh data, and eighth data;
the terminal acquires the amount of commodities exchanged by the user on the terminal in a preset period as fourth data, the quantity of commodities exchanged by the user on the terminal in the preset period as fifth data, the quantity of advertisement shared by the user on the terminal in the preset period as sixth data, the quantity of advertisement bound by the user on the terminal in the preset period as seventh data and the quantity of advertisement read by the user on the terminal in the preset period as eighth data;
performing second standardization processing on fourth data, fifth data, sixth data, seventh data and eighth data to form second influence data of the terminal, and generating distribution data corresponding to the second data according to the second influence data;
and the second standardization processing adopts weighting processing after obtaining the ratio of the fourth data, the fifth data, the sixth data, the seventh data and the eighth data of the terminal machine to the maximum value in the corresponding data.
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