CN112950256A - Method and system for pushing customized advertisement form based on App - Google Patents
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Abstract
The invention relates to the technical field of networks, in particular to a method and a system for pushing a customized advertisement form based on an App, which comprises the following steps: obtaining: acquiring the related preference commodities of the user, and recording: recording the time of the user for the related commodities and the content of the related commodity retrieval, and counting: and (3) counting the browsing time, browsing times and purchasing times of the related commodities acquired by the user, and comparing: and comparing with other commodity information, pushing: the associated preferred item is pushed to the user. According to the method and the device, the time for browsing the APP related commodities when the user selects the commodities each time is used for obtaining the related preference commodities of the APP browsed by the user, and the advertisements are pushed to the user according to the related preference commodities obtained through recording and comparison, so that the limitation of traditional advertisement display is solved, the display cost of the traditional advertisements is greatly reduced, the convenience of advertisement display operation is greatly improved, the labor cost is saved, and online push management of the advertisements can be controlled.
Description
Technical Field
The invention relates to a method and a system for customizing an advertisement form, in particular to a method and a system for pushing the customized advertisement form based on an App (application), and belongs to the technical field of networks.
Background
The mobile phone software is software installed on a smart phone, a corresponding mobile phone system is required to operate, and the main function of the mobile phone software is to perfect the defects and individuation of an original system, so that the functions of the mobile phone are more perfect, and richer use experience is provided for users.
With the popularization and deep application of networks, the internet gathers extremely rich information resources, and in the network environment of information explosion, people no longer satisfy the active information acquisition mode of portal sites and search engines, and expect to acquire information resources related to own interests, rich sources and vivid themes in a customizable and instant mode through content monitoring.
The existing APP advertisement push is generally not distinguished, when a merchant pushes commodity information to all users, the merchant is not targeted, useless messages are pushed to the users to a great extent, discomfort of the users can be caused, the user's dislike can be caused seriously, and the problems of high advertisement operation and replacement cost, low replacement timeliness and the like exist.
Therefore, there is a need for an improvement of the method and system for customized ad format push based on App to solve the existing problems.
Disclosure of Invention
The invention aims to provide a method and a system for customizing an advertisement form based on App pushing, wherein the method and the system are used for acquiring the relative preference commodities of a user browsing APP through the browsing time of the relative commodities of the APP when the user selects the commodities each time, and pushing the advertisement to the user according to the relative preference commodities obtained through recording and comparison, so that the limitation of traditional advertisement display is solved, the display cost of the traditional advertisement is greatly reduced, meanwhile, the advertisement display with higher timeliness is achieved, the convenience of advertisement display operation is greatly improved, the labor cost is saved, and the pushing management of the advertisement can be controlled on line.
In order to achieve the purpose, the invention adopts the main technical scheme that:
a method for pushing a customized advertisement form based on an App comprises the following steps:
s1: obtaining: acquiring related preference commodities for browsing APP by a user through the browsing time of the related commodities of the APP when the user selects the commodities each time;
s2: recording: a background control system on the APP master server records the stay time of the user for the related commodities and the content of the retrieval of the related commodities;
s3: counting: the background control system counts the browsing time, browsing times and purchasing times of the related commodities acquired by the user;
s4: and (3) comparison: comparing the time of browsing on other commodity information by the user, and counting the relevant preference commodities of the user;
s5: pushing: pushing advertisements to the user according to the related preference commodities obtained through recording and comparison;
through the technical scheme, the time of browsing the APP related commodities by the user each time the user selects the commodities is acquired, the related preference commodities of the APP browsed by the user are acquired, the time of the user staying at the related commodities and the content of related commodity retrieval are recorded, the time of the user acquiring the browsing time, the browsing times and the purchasing times of the related commodities are counted through the background control system, the related preference commodities of the user are counted by comparing with the browsing time of the user on other commodity information, the advertisement is pushed to the user according to the recorded and compared related preference commodities, if a company carries out preferential activities in a certain city, an advertisement information needs to be issued, however, the information accords with the preference information of the user, the user can watch the advertisement, the limitation of traditional advertisement display is solved, the display cost of the traditional advertisement is greatly reduced, and meanwhile, the advertisement display with higher timeliness is achieved, the convenience of advertisement display operation is greatly improved, the labor cost is saved, and online push management of the controllable advertisement is realized.
Preferably, in step S5, the push advertisement includes an advertisement poster, a video advertisement and an H5 applet, the push advertisement is pushed to an APP client through an APP main server, the APP client reports a display log to the APP main server, and the APP main server calculates an advertisement fee.
Preferably, the background control system comprises any one or more of an android system, an IOS system, a Mac system, a Windows system, a NetWare system, a Unix system and a Linux system.
Preferably, the APP establishes a connection with the Internet and the retail management platform for accessing and obtaining related commodities, wherein the related commodities of the APP include living goods, sports goods, literature goods and electronic goods.
Preferably, step S5 further includes the steps of:
s5.1: when a user browses commodities by using the APP;
when the general APP server pushes the advertisement content of the common commodity to the APP client, stopping advertisement pushing and starting the APP after the APP client receives an advertisement closing instruction;
when the APP general server pushes the content of the related preference commodity advertisement to the APP client, starting the APP after the advertisement is played;
meanwhile, the APP main server receives the user-defined commodity selection through the APP client;
s5.2: the APP master server records commodity keywords input by each user, establishes a word clustering library and sequences the word clustering library according to the input times and the purchase times;
s5.3: the APP general server generates a filtering condition for information pushing according to the clustering word bank, wherein the filtering condition is a relation list, and the relation list comprises a user group, commodity popularity and one or more clustering words corresponding to the user group;
s5.4: the APP main server screens out users containing specified keywords according to filtering conditions;
s5.5: the APP general server pushes information to the APP client side of the screened user, wherein the information pushed to the APP client side of the user comprises advertisement poster information, screen information, H5 information and network article information. .
Preferably, in step S3:
the App master server takes the message type, the message style and the time information input by a user as a part of the filtering condition;
and the App master server takes the message type, the message style and the time information as part of the key words thereof.
Through the technical scheme, the App master server receives user information and/or browsing habit information of a user input by the user on an APP, compares the information with user group characteristic information which is set in a background control system and is allowed to be pushed, the advertisement content of which the information is matched with the user group characteristic information which is allowed to be pushed is the advertisement content meeting the advertisement pushing standard on user dimension, when screening the advertisement content, the APP master server receives the user to self-define and select commodities through an APP client side when the user browses the commodities by using the APP, establishes a word clustering library, sorts the word clustering library according to the input times and the purchase times, generates a filtering condition for information pushing according to the word clustering library, the filtering condition is a relational list, and the relational list comprises a user group, a commodity heat degree and one or more clustering keywords corresponding to the user group, then the APP master server screens out users containing specified keywords according to filtering conditions, the APP master server pushes information to APP clients of the screened users, the advertising content and the advertising content which accords with the current advertising pushing type are equivalent to and calculated to obtain the advertising content which simultaneously meets related preference commodities, of course, different advertising content can be forced advertisement pushing or common advertisement pushing according to the arrangement of merchants, when the equivalent and calculated advertising content has more than one advertising content, the advertising content is pushed according to the priority relation set by the merchants, or the advertising content is pushed in turn, namely, the advertising content can be pushed, another advertising content is pushed next time, and another advertising content is pushed again next time until a turn is carried out for the next round of circulation.
Through the technical scheme, the push information is ordinary push or forced push, the ordinary push means that a user can select to close the advertisement, the forced push means that the user can start the APP only after viewing the advertisement, that is, when the general APP server pushes the advertisement content of the ordinary type to the terminal, a button related to closing the advertisement is reserved on the page of the APP client, after the user clicks the button, the APP client sends an advertisement closing instruction to the general APP server, the general APP server stops pushing the advertisement and starts the APP after receiving the advertisement closing instruction of the APP client, the merchant can set different push information for different advertisement contents, the push information comprises advertisement poster information, video screen information, H5 information and network article information, the push information can be forcibly played for important advertisements, and the advertisement with relatively low importance degree can be set to be closed by the user, the method has the advantages that the user's reaction degree to advertisement pushing is reduced, meanwhile, according to the time for browsing APP related commodities when the user selects the commodities each time through the user, the related preference commodities for browsing the APP by the user are obtained, user experience is improved while advertisement pushing is guaranteed, the display cost of traditional advertisements is greatly reduced, meanwhile, advertisement display with higher timeliness is achieved, convenience in advertisement display operation is greatly improved, labor cost is saved, and online pushing management with controllable advertisements is achieved.
Preferably, in step S2, a method for pushing a customized advertisement format based on App includes:
s2.1: the App master server is used for acquiring the content of the user for searching the related commodities;
s2.2: formatting the acquired content of the related commodity retrieval to obtain initial data, acquiring preset classification characteristics at the same time, and preprocessing the classification characteristics to obtain training data;
s2.3: training the initial data based on the training data to obtain characteristic data of the contents of related commodity retrieval in the initial data;
s2.4: constructing a target data classification model, inputting the characteristic data of the content of the related commodity retrieval in the initial data into the target data classification model, and obtaining a probability output matrix corresponding to the characteristic data of the content of the related commodity retrieval;
s2.5: acquiring a preset weight matrix, and correcting the probability output matrix through the preset weight matrix to obtain a weighted probability output matrix;
the weight matrix is generated according to the classification result of each training sample in a preset training sample set by the target data classification model;
s2.5: determining a classification result of the content retrieved by the related commodity based on the weighted probability output matrix;
s2.6: acquiring characteristic data corresponding to the content of the related commodity retrieval in each category, and determining the characteristic weight of the characteristic data;
s2.7: taking the characteristic data corresponding to the content of the related commodity retrieval in each category as first training data in each category, and calculating Euclidean distance between the first training data in each category and common data corresponding to the content of the related commodity retrieval in the category;
s2.8: determining the weight of common data corresponding to the content of the related commodity retrieval in each category based on the Euclidean distance and the characteristic weight of the characteristic data;
s2.9: obtaining the comprehensive weight of the contents retrieved by the related commodities in each category according to the weight of the common data corresponding to the contents retrieved by the related commodities in each category and the characteristic weight of the characteristic data;
s2.10: and sequencing the classification results and completing the recording of the contents of the related commodity retrieval by the user based on the comprehensive weight of the contents of the related commodity retrieval in each category.
Preferably, in step S4, a method for pushing a customized advertisement format based on App includes:
acquiring the time length of the user for browsing related commodities and the time length of the user for browsing other commodity information;
according to the time of the user browsing the information of the related commodities and other commodities, the importance degree value of the related commodities relative to the information of other commodities is calculated, and the accuracy of the user related preference commodities calculated according to the importance degree value is calculated, and the specific steps comprise:
calculating the importance degree value of the related commodities relative to other commodities according to the following formula:
wherein gamma represents the importance degree value of the related commodity relative to other commodities, and the value range is (0, 1); mu represents the tendency coefficient of the user to the related commodities, and the value range is (0.5, 0.7); σ represents a weight value of the related commodity; e represents the tendency coefficient of the user to other commodity information, and the value range is (0.3, 0.5); ω represents a weight value of the other commodity information; τ represents a temporal specific gravity factor; t is t1A value representing a length of time taken by the user to browse the associated item; t is t2A value representing a length of time taken by the user to browse other merchandise information;
calculating the accuracy of the counted user-related preference commodities according to the following formula:
wherein ,
the accuracy of the counted user-related preference commodities is represented, and the value range is (0, 1); gamma represents the importance degree value of the related commodity relative to other commodities, and the value range is (0, 1); theta represents a demand coefficient of the user for the related preference commodity, and the value range is (0.6, 0.8); epsilon represents the number of the related preference commodities;
representing the total number of commodities browsed by the user; beta represents an error coefficient, and the value range is (0.25, 0.56); k represents the number of times that the user browses the related preference goods; q represents the number of times the user purchases the associated preferred item;
comparing the calculated accuracy with a preset accuracy;
if the accuracy is greater than or equal to the preset accuracy, judging that the counting result is qualified, and pushing the related advertisement of the user related preference commodity counted to the user terminal;
otherwise, judging that the statistical result is unqualified, re-acquiring the time length of the user for browsing related commodities and the time length of the user for browsing other commodity information, calculating the accuracy of the statistical user related preference commodities again until the calculated accuracy is greater than or equal to the preset accuracy, and pushing the related advertisements of the user related preference commodities to the user terminal.
A system for pushing and customizing an advertisement form based on an APP comprises an APP main server, a background control system, a retail management platform and an APP client which are respectively connected with the APP main server, wherein the APP main server comprises an acquisition module, a recording module, a statistical module, a comparison module and a pushing module,
the acquisition module is used for acquiring the related preference commodity of the APP browsed by the user through the browsing time of the related commodity of the APP when the user selects the commodity;
the recording module is used for recording the staying time of the user for the related commodities and the retrieved content of the related commodities;
the statistical module is used for counting the browsing time, browsing times and purchasing times of the related commodities acquired by the user;
the comparison module is used for comparing the browsing time of the user on the information of other commodities and counting the related preference commodities of the user;
the pushing module is used for pushing advertisements to the user according to the recorded and compared related preference commodities.
Preferably, the pushing module comprises a receiving module, a category-based keyword lexicon generating module, a filtering condition generating module and a screening module,
the receiving module is used for receiving the user-defined commodity selection through the APP client;
the category-based keyword word stock generation module is used for recording commodity keywords input by each user, establishing a category-based word stock and sequencing the category-based word stock according to the input times and the purchase times;
the filtering condition generating module is used for generating a filtering condition pushed by information according to the clustering word bank, the filtering condition is a relation list, and the relation list comprises a user group, commodity popularity and one or more clustering words corresponding to the user group;
the screening module is used for screening out users containing the specified keywords according to the filtering conditions.
Through the technical scheme, the receiving module is used for receiving the keywords which are required to be contained in the pushing information input by a user through the user-defined App client;
a cluster keyword lexicon generation module, configured to record keywords input by each user, and establish a cluster keyword lexicon, where the generation module is further configured to: and sequencing the clustering keyword lexicon according to the input times of the keywords, selecting N clustering keywords before sequencing to be displayed in an input interface of the App client, and selecting by a user.
The invention has at least the following beneficial effects:
1. the time of browsing the APP related commodities when the user selects the commodities at every time is used for obtaining the related preference commodities of the APP browsed by the user, the advertisements are pushed to the user according to the related preference commodities obtained through recording and comparison, the limitation of traditional advertisement display is solved, the display cost of traditional advertisements is greatly reduced, the advertisement display with higher timeliness is achieved, the convenience of advertisement display operation is greatly improved, the labor cost is saved, and online push management of the controllable advertisements is realized.
2. According to the method, when a user browses commodities by using an APP, the APP general server receives the commodities selected by the user through the APP client side in a self-defined mode, a word clustering library is established, the word clustering library is sequenced according to the input times and the purchase times, filtering conditions for information pushing are generated according to the word clustering library, the filtering conditions are a relation list, the relation list comprises a user group, commodity heat and one or more word clustering words corresponding to the user group, then the APP general server screens out users containing the appointed key words according to the filtering conditions, the APP client side of the screened users pushes information to the APP server of the APP server, the advertising content and the advertising content which accords with the current advertising pushing type are subjected to isocratic calculation to obtain the advertising content which simultaneously meets the related preference commodities, the customer's counter-feeling is avoided, and the popularization purpose is achieved.
3. The obtained contents of the related commodity retrieval by the user are classified, the weight values of all the categories are determined, and the categories of the commodities retrieved by the user are sorted and recorded according to the weight values, so that the efficiency of determining the deviation of the user to the commodities is improved, meanwhile, the commodities liked by the user can be accurately recommended to the user according to the sorting result, and the accuracy of advertisement pushing is improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
FIG. 1 is a schematic flow diagram of the process of the present invention;
FIG. 2 is a flow chart illustrating a push method according to the present invention;
FIG. 3 is a schematic structural view of the present invention;
fig. 4 is a schematic diagram of a push information structure according to the present invention.
Detailed Description
Embodiments of the present application will be described in detail with reference to the drawings and examples, so that how to implement technical means to solve technical problems and achieve technical effects of the present application can be fully understood and implemented.
As shown in fig. 1 to 4, the method for pushing a customized advertisement format based on App provided by the present embodiment includes the following steps:
s1: obtaining: acquiring related preference commodities for browsing APP by a user through the browsing time of the related commodities of the APP when the user selects the commodities each time;
s2: recording: a background control system on the APP master server records the stay time of a user for related commodities and the content of related commodity retrieval;
s3: counting: the background control system counts the browsing time, browsing times and purchasing times of the related commodities acquired by the user;
s4: and (3) comparison: comparing the time of browsing on other commodity information by the user, and counting the relevant preference commodities of the user;
s5: pushing: and pushing the advertisement to the user according to the related preference commodity obtained by recording and comparing.
The existing APP advertisement push is generally not distinguished, when a merchant pushes commodity information to all users, the merchant does not have targeting property, useless messages are pushed to the users to a great extent, discomfort of the users can be caused, and the user's objections can be caused if the messages are serious, the user browses the APP related commodities by the time when the user browses the APP related commodities each time the user selects the commodities, the stay time of the user for the related commodities and the content of related commodity retrieval are recorded, the browsing time, browsing times and purchasing times of the user for the related commodities are counted by a background control system, the time is compared with the browsing time of the user on other commodity information, the related preferred commodities of the user are counted, the advertisement is pushed to the user according to the recorded and compared related preferred commodities, and if a company makes activity preference in a certain city, need issue an advertisement information, however this information accords with user's preference information, and the user can watch, has solved the limitation that traditional advertisement showed, has reduced the show cost of traditional advertisement greatly, reaches the advertisement show that the ageing is higher simultaneously, has greatly improved the convenience of advertisement show operation, has practiced thrift the human cost, realizes the online push management with regard to steerable advertisement.
In step S5, the propelling movement advertisement includes advertisement poster, video advertisement and H5 applet, the propelling movement advertisement passes through APP total server propelling movement to APP customer end, APP customer end will show that the log reports to APP total server, APP total server calculates the advertising cost, at first make picture advertisement poster or video advertisement, applet or APP total server upload advertisement poster or video propelling movement show to APP customer end, APP end will show that the log reports to APP total server, APP total server carries out the advertising cost calculation, unify by the demonstration of online management advertisement, make advertisement poster or video on-line, give APP end through background program propelling movement, carry out the advertisement show, promote the efficiency of popularization greatly.
The background control system comprises any one or combination of more of an android system, an IOS system, a Mac system, a Windows system, a NetWare system, a Unix system and a Linux system, and the application range of the background control system is widened.
In this embodiment, as shown in fig. 3, the APP establishes a connection with the internet and the retail management platform for accessing and obtaining related commodities, where the related commodities of the APP include living goods, sports goods, literature goods, and electronic goods, the commodity coverage area is enlarged, and the profit of retail sale is improved.
In the present embodiment, as shown in fig. 2, step S5 further includes the following steps:
s5.1: when a user browses commodities by using the APP;
when the general APP server pushes the advertisement content of the common commodity to the APP client, stopping advertisement pushing and starting the APP after the APP client receives an advertisement closing instruction;
when the APP general server pushes the content of the related preference commodity advertisement to the APP client, the APP is started after the advertisement playing is finished
Meanwhile, the APP main server receives the user-defined commodity selection through the APP client;
s5.2: the APP master server records commodity keywords input by each user, establishes a word clustering library and sequences the word clustering library according to the input times and the purchase times;
s5.3: the APP general server generates a filtering condition of information pushing according to the category word bank, wherein the filtering condition is a relation list, and the relation list comprises a user group, commodity heat and one or more category words corresponding to the user group;
s5.4: the APP master server screens out users containing the specified keywords according to the filtering conditions;
s5.5: the APP master server pushes information to the screened APP client of the user, wherein the information pushed to the APP client of the user comprises advertisement poster information, screen information, H5 information and network article information. .
In the present embodiment, as shown in fig. 4, the push information includes advertisement poster information, video information, H5 information, and web article information, and the push information is pushed to the APP client through the APP main server.
In step S3:
the App master server takes the message type, the message style and the time information input by the user as a part of the filtering condition;
the App master server takes the message type, the message style and the time information as part of the key words.
The method comprises the steps that an App master server receives user information input by a user on an APP and/or browsing habit information of the user, the information is compared with user group characteristic information which is set in a background control system and is allowed to be pushed aiming at each advertisement content, the advertisement content of which the information is matched with the user group characteristic information which is allowed to be pushed is advertisement content meeting the advertisement pushing standard on user dimension, when the advertisement content is screened, the APP master server receives user-defined selection of commodities through an APP client side when the user browses commodities by using the APP, establishes a word clustering library, sorts the word clustering library according to the input times and the purchase times and generates a filtering condition for information pushing according to the word clustering library, the filtering condition is a relation list, and the relation list comprises a user group, commodity heat and one or more word clustering words corresponding to the user group, then the APP master server screens out users containing specified keywords according to filtering conditions, the APP master server pushes information to APP clients of the screened users, the advertising content and the advertising content which accords with the current advertising pushing type are equivalent to and calculated to obtain the advertising content which simultaneously meets related preference commodities, of course, different advertising content can be forced advertisement pushing or common advertisement pushing according to the arrangement of merchants, when the equivalent and calculated advertising content has more than one advertising content, the advertising content is pushed according to the priority relation set by the merchants, or the advertising content is pushed in turn, namely, the advertising content can be pushed, another advertising content is pushed next time, and another advertising content is pushed again next time until a turn is carried out for the next round of circulation.
The push information is ordinary push or forced push, the ordinary push means that a user can select to close the advertisement, the forced push means that the user can start the APP only after watching the advertisement, that is, when the general APP server pushes the advertisement content of the ordinary type to the terminal, a button related to closing the advertisement is reserved on the APP client page, after the user clicks the button, the APP client sends an advertisement closing instruction to the general APP server, the general APP server stops advertisement push and starts the APP after receiving the advertisement closing instruction of the APP client, a merchant can set different push information for different advertisement contents, the push information comprises advertisement poster information, video screen information, H5 information and network article information, the important advertisement can be forcibly played, and the advertisement with relatively low importance degree can be set to be closed by the user, the method has the advantages that the user's reaction degree to advertisement pushing is reduced, meanwhile, according to the time for browsing APP related commodities when the user selects the commodities each time through the user, the related preference commodities for browsing the APP by the user are obtained, user experience is improved while advertisement pushing is guaranteed, the display cost of traditional advertisements is greatly reduced, meanwhile, advertisement display with higher timeliness is achieved, convenience in advertisement display operation is greatly improved, labor cost is saved, and online pushing management with controllable advertisements is achieved.
The invention provides a method for pushing a customized advertisement form based on App, which comprises the following steps of S2:
s2.1: the App master server is used for acquiring the content of the user for searching the related commodities;
s2.2: formatting the acquired content of the related commodity retrieval to obtain initial data, acquiring preset classification characteristics at the same time, and preprocessing the classification characteristics to obtain training data;
s2.3: training the initial data based on the training data to obtain characteristic data of the contents of related commodity retrieval in the initial data;
s2.4: constructing a target data classification model, inputting the characteristic data of the content of the related commodity retrieval in the initial data into the target data classification model, and obtaining a probability output matrix corresponding to the characteristic data of the content of the related commodity retrieval;
s2.5: acquiring a preset weight matrix, and correcting the probability output matrix through the preset weight matrix to obtain a weighted probability output matrix;
the weight matrix is generated according to the classification result of each training sample in a preset training sample set by the target data classification model;
s2.5: determining a classification result of the content retrieved by the related commodity based on the weighted probability output matrix;
s2.6: acquiring characteristic data corresponding to the content of the related commodity retrieval in each category, and determining the characteristic weight of the characteristic data;
s2.7: taking the characteristic data corresponding to the content of the related commodity retrieval in each category as first training data in each category, and calculating Euclidean distance between the first training data in each category and common data corresponding to the content of the related commodity retrieval in the category;
s2.8: determining the weight of common data corresponding to the content of the related commodity retrieval in each category based on the Euclidean distance and the characteristic weight of the characteristic data;
s2.9: obtaining the comprehensive weight of the contents retrieved by the related commodities in each category according to the weight of the common data corresponding to the contents retrieved by the related commodities in each category and the characteristic weight of the characteristic data;
s2.10: and sequencing the classification results and completing the recording of the contents of the related commodity retrieval by the user based on the comprehensive weight of the contents of the related commodity retrieval in each category.
In this embodiment, the formatting process is to process the retrieved content of the relevant product to obtain data corresponding to the product, so as to facilitate processing of the data corresponding to the product.
In this embodiment, the classification feature refers to a classification rule set in advance, and may be, for example, a use object by a commodity, a material attribute of the commodity, or the like.
In this embodiment, the feature data refers to a certain key data segment that can represent the entire data in the data corresponding to the product, and is used to represent the attribute of the data corresponding to the product.
In this embodiment, the feature weight refers to a proportion of feature data in data corresponding to the commodity to all data.
In this embodiment, the integrated weight is obtained by integrating a weight value of the feature data in the data corresponding to the product and a weight of data other than the feature data.
In this embodiment, the common data refers to data other than the feature data in the data corresponding to the product.
In this embodiment, each matrix element in the probability output matrix corresponds to a probability value that the content retrieved from the related product belongs to each category, for example, the probability that the retrieved content of the cosmetics is classified into the cosmetics category is 0.2, and the probability that the retrieved content of the daily necessities is classified into the living goods category is 0.4.
In this embodiment, the weight matrix is generated according to the classification result of each training sample in the training sample set by the target data classification model, that is, the weight matrix is the highest value of the classification evaluation index, the classification evaluation quality guarantee may be the accuracy of classification, and each matrix element in the weight matrix is to correct each matrix element in the probability output matrix, for example, the probability correction weight for the cosmetics class is 0.5, and the probability correction weight for the living goods class is 0.3.
In this embodiment, the weighted probability output matrix is obtained by multiplying elements at the same position in the probability output matrix and the weight matrix, and is a final basis for distinguishing the category of the search content of the related commodity.
The beneficial effects of the above technical scheme are: the obtained contents of the related commodity retrieval by the user are classified, the weight values of all the categories are determined, and the categories of the commodities retrieved by the user are sorted and recorded according to the weight values, so that the efficiency of determining the deviation of the user to the commodities is improved, meanwhile, the commodities liked by the user can be accurately recommended to the user according to the sorting result, and the accuracy of advertisement pushing is improved.
The invention provides a method for pushing a customized advertisement form based on App, which comprises the following steps of S4:
acquiring the time length of the user for browsing related commodities and the time length of the user for browsing other commodity information;
according to the time of the user browsing the information of the related commodities and other commodities, the importance degree value of the related commodities relative to the information of other commodities is calculated, and the accuracy of the user related preference commodities calculated according to the importance degree value is calculated, and the specific steps comprise:
calculating the importance degree value of the related commodities relative to other commodities according to the following formula:
wherein gamma represents the importance degree value of the related commodity relative to other commodities, and the value range is (0, 1); mu represents the tendency coefficient of the user to the related commodities, and the value range is (0.5, 0.7); σ represents a weight value of the related commodity; e represents the tendency coefficient of the user to other commodity information, and the value range is (0.3, 0.5); ω represents a weight value of the other commodity information; τ represents a temporal specific gravity factor; t is t1A value representing a length of time taken by the user to browse the associated item; t is t2Indicating a time taken by the user to browse other merchandise informationA length value;
calculating the accuracy of the counted user-related preference commodities according to the following formula:
wherein ,
the accuracy of the counted user-related preference commodities is represented, and the value range is (0, 1); gamma represents the importance degree value of the related commodity relative to other commodities, and the value range is (0, 1); theta represents a demand coefficient of the user for the related preference commodity, and the value range is (0.6, 0.8); epsilon represents the number of the related preference commodities;
representing the total number of commodities browsed by the user; beta represents an error coefficient, and the value range is (0.25, 0.56); k represents the number of times that the user browses the related preference goods; q represents the number of times the user purchases the associated preferred item;
comparing the calculated accuracy with a preset accuracy;
if the accuracy is greater than or equal to the preset accuracy, judging that the counting result is qualified, and pushing the related advertisement of the user related preference commodity counted to the user terminal;
otherwise, judging that the statistical result is unqualified, re-acquiring the time length of the user for browsing related commodities and the time length of the user for browsing other commodity information, calculating the accuracy of the statistical user related preference commodities again until the calculated accuracy is greater than or equal to the preset accuracy, and pushing the related advertisements of the user related preference commodities to the user terminal.
In this embodiment, the time-specific gravity factor has a value range of (0.5, 0.8).
In the embodiment, the preset accuracy is trained in advance, and is used for measuring and counting a parameter of the accuracy of the commodity preferred by the user, and when the value of the parameter is exceeded, the statistical result is judged to be qualified.
The beneficial effects of the above technical scheme are: the method and the device have the advantages that the importance degree value of the related commodity relative to other commodity information is calculated, the accuracy of the user related preference commodity is calculated according to the importance degree value, the importance degree value of the related commodity and other commodity information is related to the weighted value and the length value of the browsing time of the user on the commodity when the importance degree is calculated, the importance degree value of the related commodity relative to other commodities is accurate and reliable in calculation, the number of times of browsing the related commodity by the user, the number of times of purchasing the related commodity and the error coefficient are related to when the accuracy is calculated, the accuracy of a calculation result is ensured, the accuracy of pushing the advertisement to the user is ensured, and the user experience is improved.
A system for pushing and customizing an advertisement form based on an APP comprises an APP main server, a background control system, a retail management platform and an APP client which are respectively connected with the APP main server, wherein the APP main server comprises an acquisition module, a recording module, a statistical module, a comparison module and a pushing module,
the acquisition module is used for acquiring the related preference commodity of the APP browsed by the user through the browsing time of the related commodity of the APP when the user selects the commodity;
the recording module is used for recording the staying time of the user for the related commodities and the retrieved content of the related commodities;
the statistical module is used for counting the browsing time, browsing times and purchasing times of the related commodities acquired by the user;
the comparison module is used for comparing the browsing time of the user on the information of other commodities and counting the related preference commodities of the user;
and the pushing module is used for pushing the advertisement to the user according to the recorded and compared related preference commodities.
The background control system is used for inputting advertisement content and pushing the advertisement content to the terminal initiating the advertisement pushing request.
In this embodiment, as shown in fig. 3, the pushing module includes a receiving module, a category-based keyword lexicon generating module, a filtering condition generating module, and a filtering module.
The receiving module is used for receiving keywords which need to be contained in the pushing information input by a user through the App client in a user-defined mode;
a cluster keyword lexicon generation module, configured to record keywords input by each user, and establish a cluster keyword lexicon, where the generation module is further configured to: and sequencing the clustering keyword lexicon according to the input times of the keywords, selecting N clustering keywords before sequencing to be displayed in an input interface of the App client, and selecting by a user.
The limitation of traditional advertisement display is solved, the display cost of traditional advertisements is greatly reduced, meanwhile, advertisement display with higher timeliness is achieved, convenience of advertisement display operation is greatly improved, and labor cost is saved.
As shown in fig. 1 to 4, the method for pushing customized advertisement formats based on App provided by the present embodiment is as follows:
the time of browsing the APP related commodities is acquired by a user each time the user selects the commodities, the time of the user staying at the related commodities and the content of related commodity retrieval are recorded, the time of the user acquiring the browsing time, the browsing times and the purchasing times of the related commodities are counted by a background control system, the time is compared with the browsing time of the user on other commodity information, the related preferred commodities of the user are counted, advertisements are pushed to the user according to the recorded and compared related preferred commodities, and if a company does preferential activities in a certain city, an advertisement information needs to be issued, however, the information accords with the preference information of the user, the user can watch the related preferred commodities, the limitation of traditional advertisement display is solved, the display cost of the traditional advertisements is greatly reduced, and meanwhile, the advertisement display with higher timeliness is achieved, greatly improved the facility of advertisement show operation, the human cost has been practiced thrift, realize the online push management with regard to steerable advertisement, at first make picture advertisement poster or video advertisement, applet or APP total server upload advertisement poster or video propelling movement show to APP customer end, the APP end will show the log and report for APP total server, APP total server carries out the advertisement expense calculation, the unified demonstration of managing the advertisement by online, online customization advertisement poster or video, give APP end through backstage program propelling movement, carry out the advertisement show, promote the efficiency of popularization greatly.
As used in the specification and in the claims, certain terms are used to refer to particular components. As one skilled in the art will appreciate, manufacturers may refer to a component by different names. This specification and claims do not intend to distinguish between components that differ in name but not function. In the following description and in the claims, the terms "include" and "comprise" are used in an open-ended fashion, and thus should be interpreted to mean "include, but not limited to. "substantially" means within an acceptable error range, and a person skilled in the art can solve the technical problem within a certain error range to achieve the technical effect basically.
It is noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a good or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such good or system. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of additional like elements in the article or system in which the element is included.
The foregoing description shows and describes several preferred embodiments of the invention, but as aforementioned, it is to be understood that the invention is not limited to the forms disclosed herein, but is not to be construed as excluding other embodiments and is capable of use in various other combinations, modifications, and environments and is capable of changes within the scope of the inventive concept as expressed herein, commensurate with the above teachings, or the skill or knowledge of the relevant art. And that modifications and variations may be effected by those skilled in the art without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (10)
1. A method for pushing a customized advertisement form based on an App is characterized by comprising the following steps:
s1: obtaining: acquiring related preference commodities for browsing APP by a user through the browsing time of the related commodities of the APP when the user selects the commodities each time;
s2: recording: a background control system on the APP master server records the stay time of the user for the related commodities and the content of the retrieval of the related commodities;
s3: counting: the background control system counts the browsing time, browsing times and purchasing times of the related commodities acquired by the user;
s4: and (3) comparison: comparing the time of browsing on other commodity information by the user, and counting the relevant preference commodities of the user;
s5: pushing: and pushing advertisements to the user according to the related preference commodities obtained by recording and comparing.
2. The method according to claim 1, wherein the method comprises the following steps: in step S5, the push advertisement includes advertisement poster, video advertisement and H5 applet, the push advertisement is pushed to the APP client through the APP main server, the APP client reports the display log to the APP main server, and the APP main server calculates the advertisement fee.
3. The method according to claim 1, wherein the method comprises the following steps: the background control system comprises any one or a plurality of combinations of an android system, an IOS system, a Mac system, a Windows system, a NetWare system, a Unix system and a Linux system.
4. The method according to claim 1, wherein the method comprises the following steps: the APP establishes a connection with the Internet and the retail management platform and is used for accessing and obtaining related commodities, wherein the related commodities of the APP comprise living goods, sports goods, literature goods and electronic goods.
5. The method according to claim 1, wherein the method comprises the following steps: step S5 further includes the steps of:
s5.1: when a user browses commodities by using the APP;
when the general APP server pushes the advertisement content of the common commodity to the APP client, stopping advertisement pushing and starting the APP after the APP client receives an advertisement closing instruction;
when the APP general server pushes the content of the related preference commodity advertisement to the APP client, starting the APP after the advertisement is played;
meanwhile, the APP main server receives the user-defined commodity selection through the APP client;
s5.2: the APP master server records commodity keywords input by each user, establishes a word clustering library and sequences the word clustering library according to the input times and the purchase times;
s5.3: the APP general server generates a filtering condition for information pushing according to the clustering word bank, wherein the filtering condition is a relation list, and the relation list comprises a user group, commodity popularity and one or more clustering words corresponding to the user group;
s5.4: the APP main server screens out users containing specified keywords according to filtering conditions;
s5.5: the APP general server pushes information to the APP client side of the screened user, wherein the information pushed to the APP client side of the user comprises advertisement poster information, screen information, H5 information and network article information.
6. The method according to claim 1, wherein the method comprises the following steps: in step S3:
the App master server takes the message type, the message style and the time information input by a user as a part of the filtering condition;
and the App master server takes the message type, the message style and the time information as part of the key words thereof.
7. The method according to claim 1, wherein the method comprises the following steps: step S2 includes:
s2.1: acquiring the content of a user for searching related commodities based on an App master server;
s2.2: formatting the acquired content of the related commodity retrieval to obtain initial data, acquiring preset classification characteristics at the same time, and preprocessing the classification characteristics to obtain training data;
s2.3: training the initial data based on the training data to obtain characteristic data of the contents of related commodity retrieval in the initial data;
s2.4: constructing a target data classification model, inputting the characteristic data of the related commodity retrieval content in the initial data into the target data classification model, and obtaining a probability output matrix corresponding to the characteristic data of the related commodity retrieval content;
s2.5: acquiring a preset weight matrix, and correcting the probability output matrix through the preset weight matrix to obtain a weighted probability output matrix;
the weight matrix is generated according to the classification result of each training sample in a preset training sample set by the target data classification model;
s2.5: determining a classification result of the content retrieved by the related commodity based on the weighted probability output matrix;
s2.6: acquiring characteristic data corresponding to the content of the related commodity retrieval in each category, and determining the characteristic weight of the characteristic data;
s2.7: taking the characteristic data corresponding to the content of the related commodity retrieval in each category as first training data in each category, and calculating Euclidean distance between the first training data in each category and common data corresponding to the content of the related commodity retrieval in the category;
s2.8: determining the weight of common data corresponding to the content of the related commodity retrieval in each category based on the Euclidean distance and the characteristic weight of the characteristic data;
s2.9: obtaining the comprehensive weight of the contents retrieved by the related commodities in each category according to the weight of the common data corresponding to the contents retrieved by the related commodities in each category and the characteristic weight of the characteristic data;
s2.10: and sequencing the classification results and completing the recording of the contents of the related commodity retrieval by the user based on the comprehensive weight of the contents of the related commodity retrieval in each category.
8. The method according to claim 1, wherein the method comprises the following steps: step S4 includes:
acquiring the time length of the user for browsing related commodities and the time length of the user for browsing other commodity information;
according to the time of the user browsing the information of the related commodities and other commodities, the importance degree value of the related commodities relative to other commodities is calculated, and the accuracy of the user related preference commodities calculated according to the importance degree value is calculated, and the specific steps comprise:
calculating the importance degree value of the related commodities relative to other commodities according to the following formula:
wherein gamma represents the importance degree value of the related commodity relative to other commodities, and the value range is (0, 1); mu represents the tendency coefficient of the user to the related commodities, and the value range is (0.5, 0.7); σ represents a weight value of the related commodity; e represents the tendency coefficient of the user to other commodities, and the value range is (0.3, 0.5); ω represents a weight value of the other commodity information; τ represents a temporal specific gravity factor; t is t1A value representing a length of time taken by the user to browse the associated item; t is t2A value representing a length of time taken by the user to browse other merchandise;
calculating the accuracy of the counted user-related preference commodities according to the following formula:
wherein ,
the accuracy of the counted user-related preference commodities is represented, and the value range is (0, 1); gamma represents the importance degree value of the related commodity relative to other commodities, and the value range is (0, 1); theta represents a demand coefficient of the user for the related preference commodity, and the value range is (0.6, 0.8); epsilon represents the number of the related preference commodities;
representing the total number of commodities browsed by the user; beta represents an error coefficient, and the value range is (0.25, 0.56); k represents the number of times that the user browses the related preference goods; q represents the number of times the user purchases the associated preferred item;
comparing the calculated accuracy with a preset accuracy;
if the accuracy is greater than or equal to the preset accuracy, judging that the counting result is qualified, and pushing the related advertisement of the user related preference commodity counted to the user terminal;
otherwise, judging that the statistical result is unqualified, re-acquiring the time length of the user for browsing related commodities and the time length of the user for browsing other commodity information, calculating the accuracy of the statistical user related preference commodities again until the calculated accuracy is greater than or equal to the preset accuracy, and pushing the related advertisements of the user related preference commodities to the user terminal.
9. The utility model provides a system based on App propelling movement customization advertisement form which characterized in that: comprises an APP main server, a background control system, a retail management platform and an APP client which are respectively connected with the APP main server, wherein the APP main server comprises an acquisition module, a recording module, a statistic module, a comparison module and a push module,
the acquisition module is used for acquiring the related preference commodity of the APP browsed by the user through the browsing time of the related commodity of the APP when the user selects the commodity;
the recording module is used for recording the staying time of the user for the related commodities and the retrieved content of the related commodities;
the statistical module is used for counting the browsing time, browsing times and purchasing times of the related commodities acquired by the user;
the comparison module is used for comparing the browsing time of the user on the information of other commodities and counting the related preference commodities of the user;
the pushing module is used for pushing advertisements to the user according to the recorded and compared related preference commodities.
10. The system of claim 9, wherein the system comprises: the push module comprises a receiving module, a category keyword word bank generating module, a filtering condition generating module and a screening module,
the receiving module is used for receiving the user-defined commodity selection through the APP client;
the category-based keyword word stock generation module is used for recording commodity keywords input by each user, establishing a category-based word stock and sequencing the category-based word stock according to the input times and the purchase times;
the filtering condition generating module is used for generating a filtering condition pushed by information according to the clustering word bank, the filtering condition is a relation list, and the relation list comprises a user group, commodity popularity and one or more clustering words corresponding to the user group;
the screening module is used for screening out users containing the specified keywords according to the filtering conditions.
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| CN115115401A (en) * | 2022-06-27 | 2022-09-27 | 上海汇付支付有限公司 | Network advertisement aggregation platform system and operation method thereof |
| CN115293823A (en) * | 2022-09-26 | 2022-11-04 | 深圳媒介之家文化传播有限公司 | User preference identification method based on advertisement click data analysis |
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