CN117290595A - Data recommendation method and device, electronic equipment and computer readable medium - Google Patents

Data recommendation method and device, electronic equipment and computer readable medium Download PDF

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CN117290595A
CN117290595A CN202311206123.6A CN202311206123A CN117290595A CN 117290595 A CN117290595 A CN 117290595A CN 202311206123 A CN202311206123 A CN 202311206123A CN 117290595 A CN117290595 A CN 117290595A
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financial content
financial
content
user
determining
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洪元棋
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China Construction Bank Corp
CCB Finetech Co Ltd
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China Construction Bank Corp
CCB Finetech Co Ltd
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Abstract

The application discloses a data recommendation method, a data recommendation device, electronic equipment and a computer readable medium, and relates to the technical field of mobile interconnection, wherein a specific implementation mode comprises the steps of responding to triggering a preset subscription event and acquiring a corresponding user identifier; acquiring historical user behavior data based on the user identification, and determining a user tag and a financial content click rate according to the historical user behavior data; determining the category of financial business indexes corresponding to financial contents, and determining a corresponding financial content selectable set according to the category and the user label; determining the priority of each financial content in the financial content selectable set based on the financial content click rate; responsive to the intelligent switch being turned on, the corresponding financial content in the selectable set of financial content is presented based on the priority. The method and the device can simultaneously meet the aim of accurately displaying the financial content, flexibly change the financial content, reduce the replacement cost and the maintenance cost of the financial content, well meet the user preference and improve the data recommendation individuation capability.

Description

Data recommendation method and device, electronic equipment and computer readable medium
Technical Field
The present disclosure relates to the field of mobile interconnection technologies, and in particular, to a data recommendation method, a data recommendation device, an electronic device, and a computer readable medium.
Background
At present, when banks develop marketing activities, especially large activities containing more financial content, the problem of optimal presentation schemes is often involved. The existing financial content display scheme can not meet the popularization requirements of financial products or services in the current period of banks. Maximizing the current period of business KPI of the bank cannot be achieved. The user preference cannot be satisfied, and the financial content with the greatest user interest or probability of clicking by the user cannot be displayed to the user. The method has the advantages that all targets of a large number of financial content scenes displayed to the user by the bank in the marketing activities cannot be considered as a whole, and the data recommendation individuation capability is poor.
Disclosure of Invention
In view of this, the embodiments of the present application provide a data recommendation method, apparatus, electronic device, and computer readable medium, which can solve the problem that the existing method and apparatus fail to consider all the targets of a large number of financial content scenes displayed to users in a marketing campaign by banks as a whole, and the data recommendation individuation capability is poor.
To achieve the above object, according to one aspect of the embodiments of the present application, there is provided a data recommendation method, including:
Responding to triggering a preset subscription event, and acquiring a corresponding user identifier;
acquiring historical user behavior data based on the user identification, and determining a user tag and a financial content click rate according to the historical user behavior data;
determining the category of financial business indexes corresponding to financial contents, and determining a corresponding financial content selectable set according to the category and the user label;
determining the priority of each financial content in the financial content selectable set based on the financial content click rate;
responsive to the intelligent switch being turned on, the corresponding financial content in the selectable set of financial content is presented based on the priority.
Optionally, determining the user tag includes:
clustering the historical user behavior data to obtain behavior clustering clusters;
determining the behavior type corresponding to each behavior cluster;
determining target financial content corresponding to the behavior type in the historical user behavior data;
based on the target financial content and the behavior type, a user tag is determined.
Optionally, determining the corresponding financial content selection set includes:
acquiring a corresponding financial content set according to the category;
the user tag is matched with each financial content in the set of financial content to determine a selectable set of financial content corresponding to the user tag.
Optionally, determining the priority of each financial content in the selectable set of financial content based on the financial content click-through rate includes:
sorting the click rate of the financial content in a descending order to obtain the financial content sorted in the descending order;
the priority of the corresponding financial content in the selectable set of financial content is determined based on the descending order of financial content.
Optionally, displaying the corresponding financial content in the financial content selectable set based on the priority, including:
acquiring an interface identifier corresponding to a preset subscription event;
determining a display type according to the interface identifier;
and displaying the corresponding financial content in the financial content selectable set based on the display type and the priority.
Optionally, determining the corresponding financial content selection set includes:
and adding the preset financial content to the financial content selectable set in response to the user tag meeting the preset condition.
Optionally, determining the corresponding financial content selection set includes:
in response to the user tag meeting the preset condition, eliminating the preset financial content from the financial content set to obtain a candidate financial content set;
the user tag is matched with each candidate financial content in the candidate financial content set to obtain a financial content selectable set composed of the matched candidate financial content.
In addition, the application also provides a data recommendation device, which comprises:
the acquisition unit is configured to respond to triggering a preset subscription event and acquire a corresponding user identifier;
the analysis unit is configured to acquire historical user behavior data based on the user identification, and determine a user tag and a financial content click rate according to the historical user behavior data;
the selectable set determining unit is configured to determine the category of the financial business index corresponding to the financial content and determine the corresponding selectable set of the financial content according to the category and the user tag;
a priority determining unit configured to determine priorities of the respective financial contents in the financial content selectable set based on the financial content click rate;
and a display unit configured to display the corresponding financial content in the financial content selectable set based on the priority in response to the intelligent switch being turned on.
Optionally, the analysis unit is further configured to:
clustering the historical user behavior data to obtain behavior clustering clusters;
determining the behavior type corresponding to each behavior cluster;
determining target financial content corresponding to the behavior type in the historical user behavior data;
based on the target financial content and the behavior type, a user tag is determined.
Optionally, the option set determining unit is further configured to:
acquiring a corresponding financial content set according to the category;
the user tag is matched with each financial content in the set of financial content to determine a selectable set of financial content corresponding to the user tag.
Optionally, the priority determining unit is further configured to:
sorting the click rate of the financial content in a descending order to obtain the financial content sorted in the descending order;
the priority of the corresponding financial content in the selectable set of financial content is determined based on the descending order of financial content.
Optionally, the display unit is further configured to:
acquiring an interface identifier corresponding to a preset subscription event;
determining a display type according to the interface identifier;
and displaying the corresponding financial content in the financial content selectable set based on the display type and the priority.
Optionally, the option set determining unit is further configured to:
and adding the preset financial content to the financial content selectable set in response to the user tag meeting the preset condition.
Optionally, the option set determining unit is further configured to:
in response to the user tag meeting the preset condition, eliminating the preset financial content from the financial content set to obtain a candidate financial content set;
The user tag is matched with each candidate financial content in the candidate financial content set to obtain a financial content selectable set composed of the matched candidate financial content.
In addition, the application also provides data recommendation electronic equipment, which comprises: one or more processors; and a storage device for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to implement the data recommendation method as described above.
In addition, the application also provides a computer readable medium, on which a computer program is stored, which when executed by a processor, implements the data recommendation method as described above.
To achieve the above object, according to yet another aspect of the embodiments of the present application, a computer program product is provided.
A computer program product of an embodiment of the present application includes a computer program, which when executed by a processor implements a data recommendation method provided by the embodiment of the present application.
One embodiment of the above invention has the following advantages or benefits: the method comprises the steps of responding to a triggering preset subscription event to obtain a corresponding user identifier; acquiring historical user behavior data based on the user identification, and determining a user tag and a financial content click rate according to the historical user behavior data; determining the category of financial business indexes corresponding to financial contents, and determining a corresponding financial content selectable set according to the category and the user label; determining the priority of each financial content in the financial content selectable set based on the financial content click rate; responsive to the intelligent switch being turned on, the corresponding financial content in the selectable set of financial content is presented based on the priority. The method and the device can simultaneously meet the aim of accurately displaying the financial content, flexibly change the financial content, reduce the replacement cost and the maintenance cost of the financial content, well meet the user preference and improve the data recommendation individuation capability.
Further effects of the above-described non-conventional alternatives are described below in connection with the embodiments.
Drawings
The drawings are included to provide a better understanding of the present application and are not to be construed as unduly limiting the present application. Wherein:
FIG. 1 is a schematic diagram of the main flow of a data recommendation method according to one embodiment of the present application;
FIG. 2 is a schematic diagram of the main flow of a data recommendation method according to one embodiment of the present application;
FIG. 3 is a schematic flow diagram of a data recommendation method according to one embodiment of the present application;
FIG. 4 is a schematic diagram of the main units of a data recommendation device according to an embodiment of the present application;
FIG. 5 is an exemplary system architecture diagram in which embodiments of the present application may be applied;
fig. 6 is a schematic diagram of a computer system suitable for use in implementing the terminal device or server of the embodiments of the present application.
Detailed Description
Exemplary embodiments of the present application are described below in conjunction with the accompanying drawings, which include various details of the embodiments of the present application to facilitate understanding, and should be considered as merely exemplary. Accordingly, one of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present application. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness. In the technical scheme of the application, the aspects of acquisition, analysis, use, transmission, storage and the like of the related user personal information all meet the requirements of related laws and regulations, are used for legal and reasonable purposes, are not shared, leaked or sold outside the aspects of legal use and the like, and are subjected to supervision and management of a supervision department. Necessary measures should be taken for the personal information of the user to prevent illegal access to such personal information data, ensure that personnel having access to the personal information data comply with the regulations of the relevant laws and regulations, and ensure the personal information of the user. Once these user personal information data are no longer needed, the risk should be minimized by limiting or even prohibiting the data collection and/or deletion.
User privacy is protected by de-identifying data when used, including in some related applications, such as by removing a particular identifier, controlling the amount or specificity of stored data, controlling how data is stored, and/or other methods.
Fig. 1 is a schematic diagram of main flow of a data recommendation method according to an embodiment of the present application, and as shown in fig. 1, the data recommendation method includes:
step S101, responding to triggering a preset subscription event, and acquiring a corresponding user identifier.
In this embodiment, the execution body (for example, may be a server) of the data recommendation method may detect whether to trigger the preset subscription event by using a wired connection or a wireless connection. The preset subscription event, such as an access event, a click event, etc., is not specifically limited in the embodiment of the present application. When a user accesses a page or clicks a control on the page, an access event or a click event is triggered, and then the execution body can acquire a user identifier corresponding to the triggered access event or the click event. The user identifier, for example, the number or the user name of the user triggering the preset subscription event, is not specifically limited in the embodiment of the present application.
Step S102, historical user behavior data is obtained based on the user identification, and the user tag and the financial content click rate are determined according to the historical user behavior data.
The historical user behavior data acquired based on the user identification may include click data, browse data, order settlement data and the like of the user in a historical time period, and the form and the content of the historical user behavior data are not particularly limited in the embodiment of the application.
The executive may extract descriptive words from the historical user behavior data to take the extracted descriptive words as user tags. By way of example, the extracted descriptive words may be small deposit, large deposit, long term deposit, small loan, corporate legal, etc., and the content of the descriptive words is not specifically limited in the embodiments of the present application.
And extracting the counted clicking times of the user on the financial content from the historical user behavior data, and determining the clicking rate of the financial content according to the clicking times of the user. As another implementation manner, the executing body may also add a code parameter into the relevant links of the financial content, count the clicking times of the financial content through the code, and determine the clicking rate of the financial content according to the clicking times.
Step S103, determining the category of the financial business index corresponding to the financial content, and determining the corresponding financial content selectable set according to the category and the user label.
In one implementation manner of the embodiment of the present application, the category of the financial business index may be determined by: and acquiring the financial user portrait corresponding to the user identifier, extracting the category identifier corresponding to the business index in the financial user portrait, and further determining the category of the financial business index corresponding to the financial content according to the category identifier. The class may include, for example, a state class and a numeric class.
Specifically, determining the corresponding financial content selectable set includes: acquiring a corresponding financial content set according to the category, namely according to the category of the financial business index; the user tag is matched with each financial content in the set of financial content to determine a selectable set of financial content corresponding to the user tag.
By way of example, the categories of financial business indicators may include status categories and numeric categories. The financial content of the state classes and the numeric classes may be different. For example, the state class may correspond to whether to open a class of users, and the like, and the state corresponding to the state class is not specifically limited in the embodiment of the present application. The value class may correspond to the number of payment transactions in the past 30 days, the number of refunds in the past week, etc., and the value corresponding to the value class in the embodiment of the present application is not particularly limited. The executing body can acquire the financial content set composed of the corresponding financial content according to the financial content type. And performing similarity matching on the user tag and each financial content in the corresponding financial content set, and determining a set consisting of the corresponding financial content when the similarity is larger than a preset threshold value as a financial content selectable set corresponding to the user tag.
Step S104, based on the click rate of the financial content, the priority of each financial content in the financial content selectable set is determined.
The higher the click rate of the financial content, the higher the priority of the corresponding financial content.
Specifically, determining the priority of each financial content in the selectable set of financial content based on the financial content click-through rate includes: sorting the click rate of the financial content in a descending order to obtain the financial content sorted in the descending order; the priority of the corresponding financial content in the selectable set of financial content is determined based on the descending order of financial content. So that more accurate data recommendation can be achieved.
Of course, the executing entity may also group the financial contents, where each group of financial contents corresponds to a priority. Specifically, the execution body may set a plurality of click rate ranges, divide financial contents corresponding to click rates corresponding to each click rate range into a group, and set a corresponding priority for each click rate range. Thereby realizing more accurate and quick determination of the priority of the financial content.
Step S105, responding to the intelligent switch to open, and displaying the corresponding financial content in the financial content selectable set based on the priority.
Specifically, displaying the corresponding financial content in the financial content selectable set based on the priority comprises: acquiring an interface identifier corresponding to a preset subscription event; determining a display type according to the interface identifier; and displaying the corresponding financial content in the financial content selectable set based on the display type and the priority.
Each interface identifier characterizes a display type, for example, when the interface identifier is 1, the corresponding display type is list position display, when the interface identifier is 2, the corresponding display type is carousel position display, and when the interface identifier is 3, the corresponding display type is popup window position display. And displaying the corresponding financial content according to the display type according to the descending order of the priority. Therefore, accurate and personalized display of the financial content can be realized, and the user preference can be well met.
In the embodiment, a corresponding user identifier is obtained by responding to triggering a preset subscription event; acquiring historical user behavior data based on the user identification, and determining a user tag and a financial content click rate according to the historical user behavior data; determining the category of financial business indexes corresponding to financial contents, and determining a corresponding financial content selectable set according to the category and the user label; determining the priority of each financial content in the financial content selectable set based on the financial content click rate; responsive to the intelligent switch being turned on, the corresponding financial content in the selectable set of financial content is presented based on the priority. The method and the device can simultaneously meet the aim of accurately displaying the financial content, flexibly change the financial content, reduce the replacement cost and the maintenance cost of the financial content, well meet the user preference and improve the data recommendation individuation capability.
Fig. 2 is a main flow chart of a data recommendation method according to an embodiment of the present application, and as shown in fig. 2, the data recommendation method includes:
step S201, responding to triggering a preset subscription event, and acquiring a corresponding user identifier.
Step S202, historical user behavior data is acquired based on the user identification, and the click rate of the financial content is determined according to the historical user behavior data.
Step S203, clustering is carried out on the historical user behavior data to obtain each behavior cluster.
And extracting behavior keywords in the user behavior data, and clustering according to the behavior keywords. The action keywords may be, for example, transfer, deposit, withdrawal, purchase, sale, etc., and the embodiment of the present application does not specifically limit the action keywords. The specific clustering mode can classify the user behavior data corresponding to the deposit related behaviors into one type so as to obtain corresponding clustering clusters; user behavior data corresponding to behaviors related to financial transactions are classified into a class to obtain corresponding clustering clusters. Therefore, data recommendation analysis based on the cluster is facilitated, and accuracy and individuation of data recommendation are improved.
Step S204, determining the behavior type corresponding to each behavior cluster.
The behavior keywords in the user behavior data in the cluster can be summarized to obtain summarized words, and corresponding behavior types are determined according to the summarized words. Specifically, the determination of the summary word may be extracting a word composed of a common word in the behavior keyword, or may be determined according to the semantics corresponding to the behavior keyword. The behavior types corresponding to the behavior cluster are determined in a word summarizing mode, so that the determined behavior types are more accurate, a data recommendation program can be simplified, and the data recommendation efficiency is improved. For example, when the summarization word is financial transaction, the corresponding behavior type is financial transaction, and when the summarization word is deposit, the corresponding behavior type is deposit transaction.
Step S205, determining a target financial content corresponding to the behavior type in the historical user behavior data.
And matching the financial content related to the historical user behavior data with the behavior type so as to determine the matched financial content as target financial content. The matching mode may be to match behaviors corresponding to the preset financial content with behavior types, and determine the financial content corresponding to the behavior matched with the behavior types as the target financial content.
Step S206, determining the user tag based on the target financial content and the behavior type.
The user tag may include target financial content and a behavior type. The user tab page may include keywords corresponding to the target financial content and a behavior type associated with the target financial content.
Step S207, determining the category of the financial business index corresponding to the financial content, and determining the corresponding financial content selectable set according to the category and the user tag.
Specifically, determining the corresponding financial content selectable set includes: and adding the preset financial content to the financial content selectable set in response to the user tag meeting the preset condition.
For example, a forward rule is configured. If a certain tag value of the user meets a preset condition (e.g., a certain numerical condition), it should be ensured that the user's financial content selection set contains a certain financial content or certain financial content, so as to obtain a financial content selection set containing a certain financial content or certain financial content.
Specifically, determining the corresponding financial content selectable set includes: in response to the user tag meeting the preset condition, eliminating the preset financial content from the financial content set to obtain a candidate financial content set; the user tag is matched with each candidate financial content in the candidate financial content set to obtain a financial content selectable set composed of the matched candidate financial content.
Illustratively, the rules are reversed. If a certain tag value of the user meets a preset condition (e.g., a certain numerical condition), it should be ensured that the user's financial content selection set does not contain a certain financial content or certain financial content, so as to obtain a financial content selection set that does not contain a certain financial content or certain financial content.
Step S208, based on the click rate of the financial content, the priority of each financial content in the financial content selectable set is determined.
The financial content click-through rates are progressively ordered, thereby determining the priority of the corresponding financial content. The higher the priority of the financial content corresponding to the top-ranked financial content click rate.
In step S209, in response to the intelligent switch being turned on, the corresponding financial content in the financial content selectable set is displayed based on the priority.
For example, in the embodiment of the present application, the intelligent recommendation switch module includes an interface for interaction of service/operators, and is used for controlling whether the front-end interface of the marketing campaign performs front-end presentation according to the recommendation sequence output by the algorithm reasoning module. If the intelligent switch is turned on, the front end performs rendering and displaying according to the recommended sequence; if the intelligent switch is closed, the front end performs rendering and displaying according to the default ordering. Thereby facilitating the temporary full promotion of financial products or services by business/operators.
Fig. 3 is an application scenario diagram of a data recommendation method according to an embodiment of the present application. The data recommendation method can be applied to data recommendation scenes. In the embodiment of the application, the financial content refers to advertisements related to commercial banking financial business or tasks which can be completed by users and are contained in a banking marketing campaign, wherein the advertisements are usually presented to the users in the form of banner or popup windows, and the tasks are usually presented to the users in the form of cards or lists. Common interfaces for displaying financial content at the active front end of the mechanism can be divided into 3 types, namely an interface 1 column epitope (for example, column epitope 1, column epitope 2 and column epitope 3 … can be included), an interface 2 carousel bit (for example, carousel bit 2 … can be included) and an interface 3 carousel bit from top to bottom. Although the window level of the interface 3 is finally displayed to the user at only 1 position, a plurality of candidate financial contents can exist, and the financial content with the highest priority is selected for window level display.
When data recommendation is performed, user identification is performed first, the user logs in the front-end interface of the activity, and the bank can acquire user information by actively inputting information (such as a mobile phone number), micro-signal public number authorization, self-owned App (such as a mobile phone bank) login authorization and other forms of the user, and the user information is compared with user/client information data, so that the user logged in the front-end interface of the activity is identified.
The financial content accurate display central control module is a core module for solving the optimal display of financial content of a bank marketing campaign, and each module is contained as follows in detail:
the front-end data acquisition module adopts a code embedded point technology, predefines data acquisition standards (field names and field value fields), writes trigger logic into the front-end code, executes code logic when a user triggers corresponding events (access, clicking and the like), transmits corresponding behavior data to the embedded point database, and transmits key information including user identification, behavior type and financial content related information (financial content identification ID, financial content sequencing and the like). The module is used for collecting interaction data of the user and the financial content, and supporting algorithm training and reasoning.
The financial content configuration module comprises a business/operator interaction interface which supports the operations of loading and unloading financial content and editing and changing. The module records the data of a certain financial content to a database by setting options in an interface or receiving user uploading/inputting, wherein the recorded information comprises: financial content name, identification ID (for uniquely defining one financial content), picture material (which may include different sizes), financial content tag, default ordering of financial content (i.e., the order in which financial content is presented in the front-end interface to be delivered, wherein for interface 3, only financial content ordered as 1 is presented at the front-end), and so forth. The financial content label needs to be specially designed, and the specific scheme is as follows: around the business banking personal business, the financial business indexes are divided into a state class and a numerical value class, and each tag metadata at least comprises a tag ID, a tag name, a tag class (b represents the state class and v represents the numerical value class) and a tag description 4 fields.
And the user tag module processes and integrates the bank customer data through an ETL technology, and calculates a user tag consistent with the financial content tag for each customer. For example, for a customer to open a three, FT0001-BDAccSetUp tag, the user tag module will obtain the open status of the class I user for the three from the bank account open correlation data table and write the value of that customer's tag (e.g., 1, representing open) to the user tag database table.
The business rule module obtains the data of the financial content configuration module and the user tag module, outputs a user-level financial content selectable set (namely, a set of all financial contents which can be displayed to the user) through 2 calculation modes, wherein the initial financial content selectable set of each user is equal to all financial contents which are configured in the financial content configuration module, and the specific process is as follows: and (3) intelligent calculation: and (5) taking out all tag data of the user A, including tag ID, tag type and tag specific value. All data in which the type is b (state class) and the tag value is 1 are screened. Based on each label selected in the previous step, all financial content containing the same label is removed from the user selectable set. Manually configuring: the method comprises a background interface which can be interacted by a service/operator, and supports 2 kinds of manual rule configuration, as follows: the forward rule is configured to ensure that the user's selection of financial content includes one or more financial content if the user's tag value satisfies a numeric condition. Reverse rule configuration should ensure that the user's selectable set of financial content does not contain a certain financial content or contents if a certain tag value of the user satisfies a certain numerical condition.
And the algorithm training module is used for acquiring the user interaction data acquired by the front-end data acquisition module and the user-level financial content selectable set output by the business rule module to perform algorithm training. The specific algorithm can select collaborative filtering, logistic regression and the like which are commonly used in the industry according to the bank reality, and the probability of clicking a certain financial content by a user is maximized.
And the algorithm recommendation module is used for acquiring the result of the algorithm training module, reasoning the user set of the current access activity and sequencing the recommendation of the output user level of the financial content (from 1, the smaller the number is, the earlier the sequencing is).
The intelligent recommendation switch comprises an interface for interaction of business/operators and is used for controlling whether a front-end interface of a marketing campaign performs front-end display according to recommendation sequences output by the algorithm reasoning module. If the switch is turned on, the front end performs rendering and displaying according to the recommended sequence; if the switch is closed, the front end performs rendering and displaying according to the default ordering. And the intelligent recommendation switch is designed, so that the business/operator can temporarily and fully popularize financial products or services.
Finally, if the interface identifier corresponding to the preset subscription event is 1, displaying the financial content ordered based on the priority in a list form, for example, financial content 1, financial content 2, financial content 3 and the like, if the interface identifier corresponding to the preset subscription event is 2, displaying the financial content ordered based on the priority in a carousel form, for example, financial content B, financial content C and the like, and if the interface identifier corresponding to the preset subscription event is 3, displaying the financial content ordered based on the priority in a popup form, for example, financial content a popup window, financial content B popup window and the like. The data recommendation method provided by the embodiment of the application can close intelligent recommendation at any time through the control of the intelligent recommendation switch, switch to a mode of showing the same financial content to a whole number of users, and better meet the first target of banking business in a temporary and large-scale financial product or service popularization scene; the business rule module is matched with the design of the financial content tag and the user tag, and accords with the display content control of the banking viewing angle, so that the second objective of banking is met; and the algorithm training and reasoning module is used for further sequencing the financial content selectable sets on the basis of the preamble module so as to meet a third target of banking. In summary, the data recommendation method of the embodiment of the application can simultaneously meet the aim of banks in the aspect of accurately displaying financial contents of marketing activities. For example, the first objective of banking may include meeting financial product or service promotion needs of the current period of banking, the second objective of banking may include maximizing the KPI (Key Performance Indicator acronym for banking, referring to the key objective of operation of banking, such as establishing a new customer relationship, activating a customer-type business transaction, promoting a managed AUM (Asset Under Management) total, etc.) to achieve, and the third objective of banking may include meeting user preferences, revealing financial content of greatest interest or probability of clicking by the user to the user as much as possible. The embodiment of the application does not specifically limit the first target of banking business, the second target of banking business and the third target of banking business.
Therefore, the method and the device can simultaneously meet the aim of accurately displaying the financial content, flexibly change the financial content, reduce the replacement cost and the maintenance cost of the financial content, well meet the user preference and improve the individuation capability of data recommendation.
Fig. 4 is a schematic diagram of main units of the data recommendation device according to the embodiment of the present application. As shown in fig. 4, the data recommendation apparatus 400 includes an acquisition unit 401, an analysis unit 402, an option set determination unit 403, a priority determination unit 404, and a presentation unit 405.
The obtaining unit 401 is configured to obtain the corresponding user identifier in response to triggering the preset subscription event.
An analysis unit 402 configured to obtain historical user behavior data based on the user identification, determine a user tag and a financial content click rate from the historical user behavior data.
The selectable set determining unit 403 is configured to determine a category of a financial business index corresponding to the financial content, and determine a corresponding selectable set of the financial content according to the category and the user tag.
The priority determining unit 404 is configured to determine the priority of each financial content in the financial content selectable set based on the financial content click rate.
And a presentation unit 405 configured to present the corresponding financial content in the financial content selectable set based on the priority in response to the intelligent switch being turned on.
In some embodiments, the analysis unit 402 is further configured to: clustering the historical user behavior data to obtain behavior clustering clusters; determining the behavior type corresponding to each behavior cluster; determining target financial content corresponding to the behavior type in the historical user behavior data; based on the target financial content and the behavior type, a user tag is determined.
In some embodiments, the alternative set determination unit 403 is further configured to: acquiring a corresponding financial content set according to the category; the user tag is matched with each financial content in the set of financial content to determine a selectable set of financial content corresponding to the user tag.
In some embodiments, the priority determination unit 404 is further configured to: sorting the click rate of the financial content in a descending order to obtain the financial content sorted in the descending order; the priority of the corresponding financial content in the selectable set of financial content is determined based on the descending order of financial content.
In some embodiments, the presentation unit 405 is further configured to: acquiring an interface identifier corresponding to a preset subscription event; determining a display type according to the interface identifier; and displaying the corresponding financial content in the financial content selectable set based on the display type and the priority.
In some embodiments, the alternative set determination unit 403 is further configured to: and adding the preset financial content to the financial content selectable set in response to the user tag meeting the preset condition.
In some embodiments, the alternative set determination unit 403 is further configured to: in response to the user tag meeting the preset condition, eliminating the preset financial content from the financial content set to obtain a candidate financial content set; the user tag is matched with each candidate financial content in the candidate financial content set to obtain a financial content selectable set composed of the matched candidate financial content.
Note that, the data recommendation method and the data recommendation device of the present application have a corresponding relationship in the implementation content, so the repeated content will not be described.
Fig. 5 illustrates an exemplary system architecture 500 in which the data recommendation method or apparatus of embodiments of the present application may be applied.
As shown in fig. 5, the system architecture 500 may include terminal devices 501, 502, 503, a network 504, and a server 505. The network 504 is used as a medium to provide communication links between the terminal devices 501, 502, 503 and the server 505. The network 504 may include various connection types, such as wired, wireless communication links, or fiber optic cables, among others.
A user may interact with the server 505 via the network 504 using the terminal devices 501, 502, 503 to receive or send messages or the like. Various communication client applications may be installed on the terminal devices 501, 502, 503, such as shopping class applications, web browser applications, search class applications, instant messaging tools, mailbox clients, social platform software, etc. (by way of example only).
The terminal devices 501, 502, 503 may be various electronic devices with data recommendation processing screens and supporting web browsing, including but not limited to smartphones, tablets, laptop and desktop computers, and the like.
The server 505 may be a server providing various services, such as a background management server (by way of example only) providing support for preset subscription events triggered by users using the terminal devices 501, 502, 503. The background management server can respond to triggering a preset subscription event to acquire a corresponding user identifier; acquiring historical user behavior data based on the user identification, and determining a user tag and a financial content click rate according to the historical user behavior data; determining the category of financial business indexes corresponding to financial contents, and determining a corresponding financial content selectable set according to the category and the user label; determining the priority of each financial content in the financial content selectable set based on the financial content click rate; responsive to the intelligent switch being turned on, the corresponding financial content in the selectable set of financial content is presented based on the priority. The method and the device can simultaneously meet the aim of accurately displaying the financial content, flexibly change the financial content, reduce the replacement cost and the maintenance cost of the financial content, well meet the user preference and improve the data recommendation individuation capability.
It should be noted that, the data recommendation method provided in the embodiment of the present application is generally executed by the server 505, and accordingly, the data recommendation device is generally disposed in the server 505.
It should be understood that the number of terminal devices, networks and servers in fig. 5 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
Referring now to FIG. 6, a schematic diagram of a computer system 600 suitable for use in implementing the terminal device of an embodiment of the present application is shown. The terminal device shown in fig. 6 is only an example, and should not impose any limitation on the functions and the scope of use of the embodiments of the present application.
As shown in fig. 6, the computer system 600 includes a Central Processing Unit (CPU) 601, which can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM) 602 or a program loaded from a storage section 608 into a Random Access Memory (RAM) 603. In the RAM603, various programs and data required for the operation of the computer system 600 are also stored. The CPU601, ROM602, and RAM603 are connected to each other through a bus 604. An input/output (I/O) interface 605 is also connected to bus 604.
The following components are connected to the I/O interface 605: an input portion 606 including a keyboard, mouse, etc.; an output portion 607 including a Cathode Ray Tube (CRT), a liquid crystal credit authorization query processor (LCD), and the like, and a speaker, and the like; a storage section 608 including a hard disk and the like; and a communication section 609 including a network interface card such as a LAN card, a modem, or the like. The communication section 609 performs communication processing via a network such as the internet. The drive 610 is also connected to the I/O interface 605 as needed. Removable media 611 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is installed as needed on drive 610 so that a computer program read therefrom is installed as needed into storage section 608.
In particular, according to embodiments of the present disclosure, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, embodiments disclosed herein include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method shown in the flowcharts. In such an embodiment, the computer program may be downloaded and installed from a network through the communication portion 609, and/or installed from the removable medium 611. The above-described functions defined in the system of the present application are performed when the computer program is executed by a Central Processing Unit (CPU) 601.
It should be noted that the computer readable medium shown in the present application may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium may include, for example, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present application, however, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, with computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units involved in the embodiments of the present application may be implemented by software, or may be implemented by hardware. The described units may also be provided in a processor, for example, described as: a processor includes an acquisition unit, an analysis unit, an option set determination unit, a priority determination unit, and a presentation unit. Wherein the names of the units do not constitute a limitation of the units themselves in some cases.
As another aspect, the present application also provides a computer-readable medium that may be contained in the apparatus described in the above embodiments; or may be present alone without being fitted into the device. The computer readable medium carries one or more programs which, when executed by one of the devices, cause the device to obtain a corresponding user identification in response to triggering a preset subscription event; acquiring historical user behavior data based on the user identification, and determining a user tag and a financial content click rate according to the historical user behavior data; determining the category of financial business indexes corresponding to financial contents, and determining a corresponding financial content selectable set according to the category and the user label; determining the priority of each financial content in the financial content selectable set based on the financial content click rate; responsive to the intelligent switch being turned on, the corresponding financial content in the selectable set of financial content is presented based on the priority.
The computer program product of the present application comprises a computer program which, when executed by a processor, implements the data recommendation method in the embodiments of the present application.
According to the technical scheme of the embodiment of the application, the aim of accurately displaying the financial content can be simultaneously met, the financial content can be flexibly changed, the replacement cost and the maintenance cost of the financial content are reduced, the preference of a user can be well met, and the individuation capability of data recommendation is improved.
The above embodiments do not limit the scope of the application. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives can occur depending upon design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application are intended to be included within the scope of the present application.

Claims (16)

1. A data recommendation method, comprising:
responding to triggering a preset subscription event, and acquiring a corresponding user identifier;
acquiring historical user behavior data based on the user identification, and determining a user tag and a financial content click rate according to the historical user behavior data;
determining the category of financial business indexes corresponding to financial contents, and determining a corresponding financial content selectable set according to the category and the user tag;
determining a priority of each financial content in the selectable set of financial content based on the financial content click rate;
and responding to the opening of the intelligent switch, and displaying the corresponding financial content in the financial content selectable set based on the priority.
2. The method of claim 1, wherein the determining the user tag comprises:
Clustering the historical user behavior data to obtain behavior clustering clusters;
determining the behavior type corresponding to each behavior cluster;
determining target financial content corresponding to the behavior type in the historical user behavior data;
a user tag is determined based on the target financial content and the behavior type.
3. The method of claim 1, wherein the determining the corresponding financial content selectable set comprises:
acquiring a corresponding financial content set according to the category;
and matching the user tag with each financial content in the financial content set to determine a financial content selectable set corresponding to the user tag.
4. The method of claim 1, wherein the determining the priority of each financial content in the selectable set of financial content based on the financial content click-through rate comprises:
sorting the click rate of the financial content in a descending order to obtain the financial content sorted in the descending order;
priorities of the corresponding financial content in the selectable set of financial content are determined based on the descending order of financial content.
5. The method of claim 1, wherein the presenting the corresponding financial content in the selectable set of financial content based on the priority comprises:
Acquiring an interface identifier corresponding to the preset subscription event;
determining a display type according to the interface identifier;
and displaying the corresponding financial content in the financial content selectable set based on the display type and the priority.
6. The method of claim 1, wherein the determining the corresponding financial content selectable set comprises:
and adding the preset financial content to the financial content selectable set in response to the user tag meeting a preset condition.
7. The method of claim 1, wherein the determining the corresponding financial content selectable set comprises:
in response to the user tag meeting a preset condition, eliminating preset financial content from the financial content set to obtain a candidate financial content set;
and matching the user tag with each candidate financial content in the candidate financial content set to obtain a financial content selectable set composed of the matched candidate financial content.
8. A data recommendation device, comprising:
the acquisition unit is configured to respond to triggering a preset subscription event and acquire a corresponding user identifier;
an analysis unit configured to obtain historical user behavior data based on the user identification, and determine a user tag and a financial content click rate according to the historical user behavior data;
The selectable set determining unit is configured to determine the category of the financial business index corresponding to the financial content, and determine the corresponding financial content selectable set according to the category and the user tag;
a priority determining unit configured to determine a priority of each financial content in the financial content selectable set based on the financial content click rate;
and the display unit is configured to display the corresponding financial content in the financial content selectable set based on the priority in response to the intelligent switch being turned on.
9. The apparatus of claim 8, wherein the analysis unit is further configured to:
clustering the historical user behavior data to obtain behavior clustering clusters;
determining the behavior type corresponding to each behavior cluster;
determining target financial content corresponding to the behavior type in the historical user behavior data;
a user tag is determined based on the target financial content and the behavior type.
10. The apparatus of claim 8, wherein the option set determination unit is further configured to:
acquiring a corresponding financial content set according to the category;
And matching the user tag with each financial content in the financial content set to determine a financial content selectable set corresponding to the user tag.
11. The apparatus of claim 8, wherein the priority determination unit is further configured to:
sorting the click rate of the financial content in a descending order to obtain the financial content sorted in the descending order;
priorities of the corresponding financial content in the selectable set of financial content are determined based on the descending order of financial content.
12. The apparatus of claim 8, wherein the display unit is further configured to:
acquiring an interface identifier corresponding to the preset subscription event;
determining a display type according to the interface identifier;
and displaying the corresponding financial content in the financial content selectable set based on the display type and the priority.
13. The apparatus of claim 8, wherein the option set determination unit is further configured to:
and adding the preset financial content to the financial content selectable set in response to the user tag meeting a preset condition.
14. A data recommendation electronic device, comprising:
One or more processors;
storage means for storing one or more programs,
the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method of any of claims 1-7.
15. A computer readable medium, on which a computer program is stored, characterized in that the program, when being executed by a processor, implements the method according to any of claims 1-7.
16. A computer program product comprising a computer program which, when executed by a processor, implements the method according to any of claims 1-7.
CN202311206123.6A 2023-09-19 2023-09-19 Data recommendation method and device, electronic equipment and computer readable medium Pending CN117290595A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
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Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
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Publications (1)

Publication Number Publication Date
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