CN116502007A - Big data-based policy configuration generation display method - Google Patents
Big data-based policy configuration generation display method Download PDFInfo
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Abstract
The invention provides a big data-based strategy configuration generation display method, which comprises the following steps: step one: clicking by a user to enter a display interaction interface, displaying interface contents through the display interaction interface by a background, and acquiring browsing record information of the user; step two: and the background determines the attention value of each active page according to the page access frequency, the user residence time and the exposure frequency of the active page of the current user. According to the method, the browsing information of the user is analyzed, the active pages are primarily selected, the information of the user is analyzed through big data, the preference degree of the user for different active pages is determined, the active pages preferred by the user are substituted into the similar matrix, and the optimal active pages which finally meet the user requirements can be screened out through secondary screening of the preference vectors of the user, so that the personalized requirements of the user are met, and the benefit brought by the advertising of the active pages is improved.
Description
Technical Field
The invention relates to a method, in particular to a big data-based strategy configuration generation display method, and belongs to the technical field of advertisement display.
Background
With the rapid development of mobile internet systems, the time for users to use mobile phones is longer and longer, the mobile internet advertising scale is also increased, and the dependence of various financial service enterprises on advertisements is increased gradually. Commodity popularization through a network becomes a new marketing mode. For the vast netizen users, the accurate advertisement is needed, rather than the bombing of various types of advertisements, the excessive advertisements can bring bad webpage browsing experience, and on the other hand, for advertisement suppliers and owners, the accurate advertisement can save advertisement propaganda cost, and better commodity sales drainage is brought. In order to provide users with a richer variety of financial services, financial service providers often provide some additional activity on the basis of implementing basic functions. Meanwhile, the content of the activity is pushed at the application server, so that the user can know and participate in the activity.
For the provider providing comprehensive financial services, the number of activities provided is large and various, if the activities are simply presented to each user in a full-scale pushing mode, the personalized requirements of each user are difficult to meet, and due to the lack of a policy configuration mechanism, the benefit brought by a large number of active page advertisements pushed and displayed by the provider is low, so that a policy configuration generation display method based on big data is proposed.
Disclosure of Invention
In view of this, the present invention provides a big data based policy configuration generation display method to solve or alleviate the technical problems existing in the prior art, and at least provides a beneficial choice.
The technical scheme of the embodiment of the invention is realized as follows: the strategy configuration generation display method based on big data comprises the following steps:
step one: clicking by a user to enter a display interaction interface, displaying interface contents through the display interaction interface by a background, and acquiring browsing record information of the user;
step two: the background determines the attention value of each active page according to the page access frequency, the user residence time and the exposure frequency of the active page of the current user;
step three: uploading the attention value of each active page to a background CRM library and storing;
step four: classifying the attention value of each active page of the user through the background, and establishing a similarity matrix;
step five: analyzing the feature quantity of the material of each active page in the similarity matrix, and simultaneously calculating the similarity between the materials of each active page and caching the similarity to the background;
step six: analyzing the customer data of all users in the background CRM system through big data, and determining the preference vector of the users by substituting and calculating the user data at the moment through the background;
step seven: substituting the preference vector of the user into the CRM library, determining the actual demand of the user, and generating a strategy configuration mechanism according to the actual demand of the user;
step eight: storing the generated strategy configuration to a background, and screening out content links of the optimal active pages in a database according to the strategy configuration;
step nine: determining the display form of the content links of the active page according to the policy configuration;
step ten: and pushing and displaying the active page to the interaction interface by the background according to the strategy configuration and the active page display form.
Further preferably, in the first step, the interactive interface includes two controls, namely an active type configuration control and a target object matching condition configuration control, where the active type configuration control is used to configure a policy of an active page, and the target object matching control is used to match and filter out an active page link to be displayed.
Further preferably, in the second step, according to a preset attention value calculation formula, determining an attention value of each active page through a page access frequency, a user residence time length and an active page exposure frequency; the quality of the page keywords can be known through the attention value, a basis is provided for optimizing keyword title description and optimizing keywords, the attention value ranges from 1 to 10, and the higher the attention value is, the better the keyword quality of the active page is represented.
Further preferably, in the third step, the CRM library is a database in a background of the display interactive interface, and is used for managing customer data, and the CRM can store data information of the user entering into the display interactive interface, where the data information of the user data includes browsing records, activity participation records and customer behavior data.
Further preferably, in the fourth step, the similarity matrix may arrange active pages with similar features, and by arranging active pages with similar features, one active page with the most similar feature value may be selected for display.
Further preferably, in the step six, the background query module searches the corresponding content of the active page by matching keywords in the active page, and then stores the searched and screened active page in the CRM library.
Further preferably, in the step seven, the preference vector of the user is substituted into the CRM library, the active page information in the step six CRM library is matched with the preference vector through the matching module, and the active page links related to the user requirements are screened out.
Further preferably, in the eighth step, the content of the optimal active page meeting the user's requirement is screened out according to the screening method in the seventh step.
Further preferably, in the step nine, according to the content of the active page, a final active page display form is determined, where the active page display form includes: the number of the pushing active pages, the sequence of pushing the active pages, and the display time point and the display duration of the active pages.
Further preferably, in the step ten, the final active page is displayed through the display interaction interface, and when the active page is closed, the steps are repeated, and the optimal active page is matched and displayed again.
By adopting the technical scheme, the embodiment of the invention has the following advantages: according to the method, the browsing information of the user is analyzed, the active pages can be initially selected, the information of the user is analyzed through big data, the preference degree of the user for different active pages is determined, the active pages preferred by the user are substituted into the similar matrix, then the corresponding active pages are selected in the similar matrix according to the preference vector of the user to serve as alternative active pages, the optimal active pages which finally meet the user requirements can be screened out through secondary screening of the preference vector of the user, and further the active pages can meet the personalized requirements of the user, so that the benefit brought by the active page advertisements is improved.
The foregoing summary is for the purpose of the specification only and is not intended to be limiting in any way. In addition to the illustrative aspects, embodiments, and features described above, further aspects, embodiments, and features of the present invention will become apparent by reference to the drawings and the following detailed description.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of the steps of the present invention.
Detailed Description
Hereinafter, only certain exemplary embodiments are briefly described. As will be recognized by those of skill in the pertinent art, the described embodiments may be modified in various different ways without departing from the spirit or scope of the present invention. Accordingly, the drawings and description are to be regarded as illustrative in nature and not as restrictive.
Embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
As shown in fig. 1, the embodiment of the invention provides a big data-based policy configuration generation display method, which comprises the following steps:
step one: clicking by a user to enter a display interaction interface, displaying interface contents through the display interaction interface by a background, and acquiring browsing record information of the user;
step two: the background determines the attention value of each active page according to the page access frequency, the user residence time and the exposure frequency of the active page of the current user;
step three: uploading the attention value of each active page to a background CRM library and storing;
step four: classifying the attention value of each active page of the user through the background, and establishing a similarity matrix;
step five: analyzing the feature quantity of the material of each active page in the similarity matrix, and simultaneously calculating the similarity between the materials of each active page and caching the similarity to the background;
step six: analyzing the customer data of all users in the background CRM system through big data, and determining the preference vector of the users by substituting and calculating the user data at the moment through the background;
step seven: substituting the preference vector of the user into the CRM library, determining the actual demand of the user, and generating a strategy configuration mechanism according to the actual demand of the user;
step eight: storing the generated strategy configuration to a background, and screening out content links of the optimal active pages in a database according to the strategy configuration;
step nine: determining the display form of the content links of the active page according to the policy configuration;
step ten: and pushing and displaying the active page to the interaction interface by the background according to the strategy configuration and the active page display form.
In one embodiment, in the first step, the interactive interface comprises two controls, namely an active type configuration control and a target object matching condition configuration control, wherein the active type configuration control is used for configuring a strategy of an active page, the target object matching control is used for matching and screening out an active page link to be displayed, and in the second step, according to a preset attention value calculation formula, the attention value of each active page is determined through page access frequency, user residence time and active page exposure frequency; the method can be used for knowing the advantages and disadvantages of the page keywords through the attention value, providing basis for optimizing keyword title description and optimizing keywords, enabling the attention value to be in a range of 1 to 10, enabling the keyword quality representing the active page to be better as the attention value is higher, enabling the active page possibly interested by the user to be initially selected through analysis of browsing information of the user, and enabling 1-15 initially satisfactory interactive page contents to be selected according to the display requirements of a financial service provider.
In a third step, the CRM library is a database in a background of the display interactive interface, and is used for managing customer data, the CRM can store data information of the customer entering the display interactive interface, the customer data information includes browsing records, activity participation records and customer behavior data, the CRM library in the background can store the customer information in a mass manner, and when the customer enters the display interactive interface next time, the customer data can be directly retrieved through a subsequent matching module, and the last activity page browsing data of the customer can be substituted into the current policy configuration.
In a fourth step, the similar matrix may arrange active pages with similar characteristics, one active page with the most similar characteristic value may be selected for display by arranging the similar active pages, in a sixth step, the background query module searches the corresponding active page content by matching keywords in the active pages, then stores the searched active pages in the CRM library, in a seventh step, the preference vector of the user is substituted into the CRM library, the active page information in the sixth CRM library is matched with the preference vector of the user by the matching module, the active page links related to the user needs are screened out, the information of the user is analyzed by big data, the preference degree of the user for different active pages can be determined, the active pages with the user preference are substituted into the similar matrix, and then the corresponding active pages are selected as alternative active pages in the similar matrix according to the preference vector of the user.
In an embodiment, in step eight, according to the screening method in step seven, the content of the optimal active page meeting the user requirement is screened out, the optimal active page eventually meeting the user requirement can be screened out through secondary screening of the user preference vector, and 1-5 optimal active pages are finally selected according to the display requirement of the financial service provider.
In one embodiment, in step nine, according to the content of the active page, a final active page display form is determined, where the active page display form includes: the number of the pushing active pages, the sequence of the pushing active pages, the display time point and the display duration of the active pages, and the active pages can be displayed through the display interaction interface after the display form of the active pages is determined through the user data.
In one embodiment, in step ten, a final active page is displayed through a display interaction interface, after the active page is closed, the steps are repeated, the optimal active page is matched and displayed again, according to the requirements of a financial service provider, 1-5 selectable optimal active pages can be provided for a user in the display interaction interface, then five optimal active pages are displayed in the interaction interface in a popup window mode, the user can click one of the five active pages according to the actual requirements of the user, the user can further obtain the content of the completed active page through clicking, after the active page is clicked, the background obtains browsing information of the user again, and then the optimal active page pushed next time is screened and matched through the steps one-nine, so that in order to provide richer and various selectable services for the user, the user can learn and participate in activities by pushing and displaying the active content in the display interaction interface.
The foregoing is merely illustrative of the present invention, and the present invention is not limited thereto, and any person skilled in the art will readily recognize that various changes and substitutions are possible within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. The big data-based strategy configuration generation display method is characterized by comprising the following steps of:
step one: clicking by a user to enter a display interaction interface, displaying interface contents through the display interaction interface by a background, and acquiring browsing record information of the user;
step two: the background determines the attention value of each active page according to the page access frequency, the user residence time and the exposure frequency of the active page of the current user;
step three: uploading the attention value of each active page to a background CRM library and storing;
step four: classifying the attention value of each active page of the user through the background, and establishing a similarity matrix;
step five: analyzing the feature quantity of the material of each active page in the similarity matrix, and simultaneously calculating the similarity between the materials of each active page and caching the similarity to the background;
step six: analyzing the customer data of all users in the background CRM system through big data, and determining the preference vector of the users by substituting and calculating the user data at the moment through the background;
step seven: substituting the preference vector of the user into the CRM library, determining the actual demand of the user, and generating a strategy configuration mechanism according to the actual demand of the user;
step eight: storing the generated strategy configuration to a background, and screening out content links of the optimal active pages in a database according to the strategy configuration;
step nine: determining the display form of the content links of the active page according to the policy configuration;
step ten: and pushing and displaying the active page to the interaction interface by the background according to the strategy configuration and the active page display form.
2. The big data based policy configuration generation presentation method of claim 1, wherein: in the first step, the interactive interface includes two controls, namely an active type configuration control and a target object matching condition configuration control, wherein the active type configuration control is used for configuring strategies of active pages, and the target object matching control is used for matching and screening out active page links to be displayed.
3. The big data based policy configuration generation presentation method of claim 1, wherein: in the second step, according to a preset attention value calculation formula, determining an attention value of each active page through page access frequency, user residence time and active page exposure frequency; the quality of the page keywords can be known through the attention value, a basis is provided for optimizing keyword title description and optimizing keywords, the attention value ranges from 1 to 10, and the higher the attention value is, the better the keyword quality of the active page is represented.
4. The big data based policy configuration generation presentation method of claim 1, wherein: in the third step, the CRM library is a database in the background of the display interactive interface, and is used for managing customer data, and the CRM can store the data information of the user entering the display interactive interface, wherein the data information of the user data comprises browsing records, activity participation records and customer behavior data.
5. The big data based policy configuration generation presentation method of claim 1, wherein: in the fourth step, the similarity matrix may arrange active pages with similar features, and by arranging active pages with similar features, one active page with the most similar feature value may be selected for display.
6. The big data based policy configuration generation presentation method of claim 1, wherein: in the step six, the background query module searches the corresponding content of the active page by matching the keywords in the active page, and then stores the searched and screened active page in the CRM library.
7. The big data based policy configuration generation presentation method of claim 1, wherein: in the seventh step, the preference vector of the user is substituted into the CRM library, the active page information in the sixth CRM library is matched with the preference vector of the user through the matching module, and the active page links related to the user demands are screened out.
8. The big data based policy configuration generation presentation method of claim 1, wherein: in the eighth step, the optimal active page content meeting the user requirement is screened out according to the screening method in the seventh step.
9. The big data based policy configuration generation presentation method of claim 1, wherein: in the step nine, according to the content of the active page, determining a final active page display form, where the active page display form includes: the number of the pushing active pages, the sequence of pushing the active pages, and the display time point and the display duration of the active pages.
10. The big data based policy configuration generation presentation method of claim 1, wherein: in the step ten, the final active page is displayed through the display interaction interface, and when the active page is closed, the steps are repeated, and the optimal active page is matched and displayed again.
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| Application Number | Priority Date | Filing Date | Title |
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| CN202310487997.7A CN116502007A (en) | 2023-04-28 | 2023-04-28 | Big data-based policy configuration generation display method |
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| CN202310487997.7A CN116502007A (en) | 2023-04-28 | 2023-04-28 | Big data-based policy configuration generation display method |
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| CN116502007A true CN116502007A (en) | 2023-07-28 |
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| CN202310487997.7A Withdrawn CN116502007A (en) | 2023-04-28 | 2023-04-28 | Big data-based policy configuration generation display method |
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Application publication date: 20230728 |