CN112950306A - Recommendation scheme definition method, device, medium and equipment - Google Patents
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Abstract
The invention discloses a method, a device, a medium and equipment for defining a recommendation scheme, wherein the method comprises the following steps: creating a basic information list of a recommended scheme; creating a recommendation rule list of recommendation schemes; creating a recommendation rule management list according to the recommendation rule list; and organizing the basic information list, the recommendation rule list and the recommendation rule management list into a user interface so that a user can input an expected value. The invention provides the basic information list and the recommendation rule list of the recommendation scheme for the user, so that the client can carry out the universal definition of the configuration of the recommendation scheme aiming at a certain scene, facing a specific group of people and using a certain or a plurality of recommendation rules, thereby realizing the recommendation of a plurality of scenes and further meeting the requirement of continuous change of the recommendation scheme of an enterprise due to the rapid development of business.
Description
Technical Field
The invention belongs to the technical field of intelligent recommendation, and particularly relates to a recommendation scheme definition method, device, medium and equipment.
Background
With the rapid development of IT technology and the explosion and growth of enterprise data, new opportunities and challenges are brought to business of enterprises. The enterprise develops basic information and behavior data of the client deeply by deploying an intelligent recommendation platform and adopting a big data technology, an artificial intelligence technology and a machine learning algorithm, learns the characteristics of 'thousands of people and thousands of faces' of the client, pushes personalized recommendation information and marketing information to the client through a service channel, powerfully pushes the enterprise to change to an intelligent marketing and service mode, improves the marketing efficiency of the enterprise, improves the service quality of the enterprise, and promotes the business development of the enterprise.
In the prior art, generally, one recommendation scheme is configured corresponding to one scene, for example, a home page of a mobile banking APP, and if the scene is divided into a plurality of scenes, for example, 4 scenes, such as home page fund recommendation, home page financing product recommendation, home page advertisement recommendation, home page UI template, and the like, 4 recommendation schemes need to be configured; according to the conventional method, a recommendation scheme configuration function needs to be developed for one scene, and 4 definition functions need to be developed to support the configuration of the recommendation schemes for the 4 scenes. By adopting the traditional method, in development, only the configuration function of the recommendation scheme corresponding to a certain scene needs to be realized, the configuration including other recommendation schemes does not need to be considered, and the realization is simpler and quicker; in the aspect of user use, one scheme is configured in one scene, so that the operation and the maintenance are easy; however, the conventional method is not a general method, and cannot adapt to changes of scenes and recommended schemes due to changes of services, new services and new scene requirements require developers to develop new recommended schemes, and changes of scenes require developers to modify corresponding recommended schemes, which results in slow speed of response of a decision center to service requirements, large development workload and high maintenance cost.
Disclosure of Invention
In order to overcome the technical defects, the invention provides a method, a device, a medium and equipment for defining a recommendation scheme, which can recommend recommendation schemes of different scenes.
In order to solve the problems, the invention is realized according to the following technical scheme:
a method for defining a recommendation, comprising the steps of:
creating a basic information list of a recommended scheme;
creating a recommendation rule list of recommendation schemes;
creating a recommendation rule management list according to the recommendation rule list;
and organizing the basic information list, the recommendation rule list and the recommendation rule management list into a user interface so that a user can input an expected value.
As a further improvement of the present invention, the recommendation rule list includes: a guest group setting field;
when the customer group setting bar is selected, providing a rule designer for a user to input a customer label;
when a plurality of client tags of different clients are obtained, defining the obtained tags as a 'and' relationship;
when a plurality of client tags of the same client are acquired, the acquired tags are defined as an OR relationship.
As a further improvement of the present invention, the recommendation rule list includes: a recommendation mode column and a set recommendation object column, wherein the recommendation mode column comprises: an algorithm model recommender and a rule recommender;
when the algorithm model recommender is selected, the set recommendation object column comprises a plurality of algorithm model recommenders associated with set recommendation categories for selection by a user, and meanwhile, a parameter input column is provided for input by the user;
when the rule recommender is selected, the set recommendation object column includes a plurality of recommendation categories and a plurality of recommenders contained in the recommendation categories.
As a further improvement of the present invention, the recommendation rule list includes: screening a rule column; the screening rule column includes: filtering rules, sorting rules and priority rules;
when the filtering rule is selected, providing a rule designer for user input, wherein the rule designer is provided with: a product attribute filtering rule and a product association attribute filtering rule;
when the sorting rule is selected, providing a rule designer for a user to set the sorting rule;
and when the priority rule is selected, providing a rule designer for setting the priority rule by a user.
As a further improvement of the present invention, the recommendation rule list includes: a default recommendation field;
when the default recommendation column is selected, providing a rule designer for a user to input a plurality of recommenders as default recommendation rules;
and filling the default recommendation rule into the rules set by the user when the recommendation result list is empty or the recommendation number is insufficient.
As a further improvement of the present invention, the recommendation rule list includes: push to the recommendation bar;
and when the push recommendation column is selected, providing a rule designer for a user to set a push recommendation, and setting the push recommendation to be the highest priority.
As a further improvement of the present invention, the basic information list includes: a recommended scheme coding column, a recommended scheme name column, a recommended scheme description column, an effective date column, an expiration date column, a recommended number column, and a recommended category column.
As another object of the present invention, there is provided a definition apparatus including:
the basic information list creating module is used for creating a basic information list of a recommendation scheme;
the recommendation rule list creating module is used for creating a recommendation rule list of a recommendation scheme;
a recommendation rule management list creating module, configured to create a recommendation rule management list according to the basic information list and the recommendation rule list;
and the interactive interface creating module is used for organizing the basic information list, the recommendation rule list and the recommendation rule management list into a user interface for a user to input an expected value.
Furthermore, the present invention also provides a computer-readable storage medium having at least one instruction, at least one program, code set, or set of instructions stored therein, which is loaded and executed by a processor to implement the above-defined method.
The present invention also provides a computer device comprising a processor and a memory, said memory having stored therein at least one instruction, at least one program, set of codes or set of instructions, which is loaded and executed by said processor to implement the above defined method.
Compared with the prior art, the invention has the following beneficial effects: the invention provides the basic information list and the recommendation rule list of the recommendation scheme for the user, so that the client can carry out the general definition of the configuration of the recommendation scheme aiming at a certain scene, facing a specific group of people and using a certain or a plurality of recommendation rules, thereby realizing the recommendation of a plurality of scenes, greatly reducing the development workload, improving the response speed of the service requirement of the decision center, reducing the maintenance cost and further meeting the requirement of continuous change of the recommendation scheme of an enterprise caused by the rapid development of the service.
Drawings
Embodiments of the invention are described in further detail below with reference to the attached drawing figures, wherein:
FIG. 1 is a flow chart of a defining method according to an embodiment;
FIG. 2 is a diagram illustrating a basic information list according to an embodiment;
FIG. 3 is a diagram illustrating a recommendation management list according to an embodiment;
FIG. 4 is a diagram illustrating a recommendation rule list according to an embodiment;
fig. 5 is a schematic diagram of the defining apparatus according to the second embodiment.
Description of the labeling: 1. a basic information list creation module; 2. a recommendation rule list creation module; 3. a recommendation rule management list creation module; 4. and an interactive interface creating module.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
Example one
The embodiment provides a method for defining a recommendation scheme, as shown in fig. 1, including the steps of:
s1, creating a basic information list of the recommended solution, as shown in fig. 2, the basic information list includes: the recommendation scheme coding column, the recommendation scheme name column, the recommendation scheme description column, the validation date column, the expiration date column, the recommendation number column and the recommendation category column are used for a user to fill in basic information of a recommendation scheme; the effective date column and the failure date column are used for the user to fill in an effective date range for limiting the recommendation scheme; the recommended number column is used for the user to define the number of the recommended objects which are returned at most after the recommended scheme is executed, and when the recommended result list is finally output, the on-sale/effective recommended objects of which the number is not more than the recommended number are output; the recommendation category column is used for a user to specify a certain category of recommendation, such as fund, financing, advertisement or UI template.
S2, creating a recommendation rule list of recommendation schemes, wherein the recommendation rule list is used for a user to set one or more recommendation rules, the recommendation rules in the recommendation schemes are not intersected, and the added recommendation rules are added into the recommendation rule list; and the decision center executes the recommendation rule list to obtain the recommended object recommended by the customer.
S3, creating a recommendation rule management list according to the recommendation rule list, wherein the recommendation rule management list is used for a client to manage recommendation rules, the user can delete added recommendation rules through 'deleting' functional links, and can also adjust the sequence of the recommendation rules through a downward moving/upward moving function, when a certain recommendation scheme is executed by a decision center, the recommendation rules in the recommendation rule list are sequentially executed, when a certain recommendation rule is executed, whether the user belongs to a set guest group is judged firstly, if the user belongs to the set guest group, the rule is executed, a recommendation result is returned, and the following rules are skipped to be not executed; if the client does not belong to the set client group, the next rule is checked in sequence, and if the rule meets the condition, the next rule is executed.
And S4, organizing the basic information list, the recommendation rule list and the recommendation rule management list into a user interface for a user to input an expected value.
In the above embodiment, as shown in fig. 4, the recommendation rule list includes: a guest group setting field; when the customer group setting bar is selected, providing a rule designer for a user to input a customer label; when a plurality of client tags of different clients are obtained, defining the obtained tags as a 'and' relationship; when a plurality of client tags of the same client are acquired, defining the acquired tags as an OR relationship; the recommendation rule is directed to a specific customer group, and recommends an appropriate recommendation to the specific customer group, if the customer group is not set, the recommendation rule is directed to all users, and the rule logic for setting the customer group is to combine the customer tags to define a customer group, if the customer group is set as: "whether the guest client is ' the life stage grouping of the clients (' in and out society ' or ' home establishment ')".
Further, as shown in fig. 4, the recommendation rule list includes: a recommendation mode column and a set recommendation object column, wherein the recommendation mode column comprises: an algorithm model recommender and a rule recommender; when the algorithm model recommender is selected, the set recommendation object column comprises a plurality of algorithm model recommenders associated with the set recommendation categories for selection by the user, and meanwhile, a parameter input column is provided for input by the user; when the rule recommender is selected, the recommendation object setting column includes a plurality of recommendation categories and a plurality of recommenders contained in the recommendation categories.
The recommendation rule sets a recommendation mode suitable for recommending the set specific guest group; when the user clicks the 'algorithm model recommender', clicking the 'set recommendation object column', selecting one algorithm model recommender under the set recommendation category (such as fund), and setting the relevant input parameters of the algorithm recommender. The algorithm model recommender is provided by an algorithm engine; when the user clicks the "rule recommender", the "set recommendation object column" is clicked, and a business rule for recommending a suitable recommendation is set by the rule designer, where the business rule may set a certain recommendation category (e.g., stock fund) under the recommendation category (e.g., fund), and may also set one or more recommendations (e.g., a certain medical index fund, a certain technological innovation fund) under the recommendation category (e.g., fund).
Further, as shown in fig. 4, the recommendation rule list includes: a screening rule column for screening a recommendation result list corresponding to the setting of the "set recommendation object column"; the screening rule column includes: filtering rules, ordering rules, and precedence rules.
When the filtering rule is selected, providing a rule designer for user input, wherein the rule designer is provided with: the product attribute filtering rule is specifically filtering through the attribute of the product, and if the product is only pushed to have a low risk level, the product attribute filtering rule is related to the product attribute filtering rule; the product associated attribute filtering rule refers to filtering by associating product attributes and client attributes, such as pushing only products sold in a client account area; if the base metal property and the customer attribute have an association, then filtering may be performed by associating the base metal property and the customer attribute.
And when the sorting rule is selected, providing a rule designer for a user to set the sorting rule, wherein the sorting rule comprises ascending sorting and descending sorting.
And when the priority rule is selected, providing a rule designer for a user to set the priority rule, wherein the priority rule is used for sequentially moving the recommended objects meeting the priority rule to the front of a recommendation result list, and preferentially selecting the products set by the priority rule in the recommendation list after filtering by the filtering rule, namely, arranging the products defined by the priority rule at the top.
In the above embodiment, as shown in fig. 4, the recommendation rule list includes: a default recommendation field; when the default recommendation column is selected, a rule designer is provided for a user to input a plurality of recommenders as default recommendation rules, and the user can change the sequence of the default recommenders by moving up/down; and filling the default recommendation rule into the rule set by the user when the recommendation result list is empty or the recommendation number is insufficient.
In the above embodiment, as shown in fig. 4, the recommendation rule list includes: push to the recommendation bar; when the push recommendation column is selected, a rule designer is provided for a user to set a push recommendation object, the user can change the sequence of the push recommendation object by moving up/down, and meanwhile, the push recommendation object is set to be the highest priority, namely, if the user sets the push recommendation object, the push recommendation object is arranged at the top of a recommendation result list, and other recommendation objects move backwards.
Under a normal condition, a decision center receives a recommendation application sent by a scene engine, the decision center selects a recommendation scheme according to a scene ID to execute and inputs a user ID parameter, the decision center judges which guest group the user belongs to, selects a recommendation rule aiming at the guest group, selects an algorithm model recommender or a rule recommender according to a recommendation mode to execute to obtain a preliminary recommendation result, then obtains a screened intermediate recommendation result through a screening rule column (the screening rule column is divided into a filtering rule, a sorting rule and a priority rule), and finally obtains a final recommendation result by combining a default recommendation rule and a necessary recommendation rule, and returns the final recommendation result to the scene engine. The decision center analyzes and executes the set rules or the rule recommender through a rule engine, or analyzes and executes the set algorithm model recommender through an algorithm engine. The scene engine simultaneously collects user behavior data and sends the user behavior data to the decision center, the decision center is responsible for processing and displaying evaluation indexes, and the purpose of optimizing a recommendation scheme is achieved by optimizing rules or algorithm models of the decision center through analysis of the evaluation indexes.
Example two
The present embodiment provides a definition apparatus, as shown in fig. 5, including: a basic information list creating module 1, a recommendation rule list creating module 2, a recommendation rule management list creating module 3 and an interactive interface creating module 4; the basic information list creating module 1 is used for creating a basic information list of a recommended scheme; the recommendation rule list creating module 2 is used for creating a recommendation rule list of recommendation schemes; the recommendation rule management list creating module 3 is configured to create a recommendation rule management list according to the basic information list and the recommendation rule list; the interactive interface creating module 3 is configured to organize the basic information list, the recommendation rule list, and the recommendation rule management list into a user interface, so that a user can input an expected value.
For a specific implementation process of this embodiment, please refer to embodiment one, and details are not repeated again.
EXAMPLE III
The present embodiment provides a computer-readable storage medium, in which at least one instruction, at least one program, a code set, or a set of instructions is stored, and the at least one instruction, the at least one program, the code set, or the set of instructions is loaded and executed by a processor to implement the defining method of the first embodiment.
Example four
The present embodiment provides a computer device, which includes a processor and a memory, where at least one instruction, at least one program, a code set, or a set of instructions is stored in the memory, and the at least one instruction, the at least one program, the code set, or the set of instructions is loaded and executed by the processor to implement the defining method of the first embodiment.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the present invention in any way, so that any modification, equivalent change and modification made to the above embodiment according to the technical spirit of the present invention are within the scope of the technical solution of the present invention.
Claims (10)
1. A method for defining a recommendation, comprising the steps of:
creating a basic information list of a recommended scheme;
creating a recommendation rule list of recommendation schemes;
creating a recommendation rule management list according to the recommendation rule list;
and organizing the basic information list, the recommendation rule list and the recommendation rule management list into a user interface so that a user can input an expected value.
2. The definition method according to claim 1, wherein the recommendation rule list comprises: a guest group setting field;
when the customer group setting bar is selected, providing a rule designer for a user to input a customer label;
when a plurality of client tags of different clients are obtained, defining the obtained tags as a 'and' relationship;
when a plurality of client tags of the same client are acquired, the acquired tags are defined as an OR relationship.
3. The definition method according to claim 1, wherein the recommendation rule list comprises: a recommendation mode column and a set recommendation object column, wherein the recommendation mode column comprises: an algorithm model recommender and a rule recommender;
when the algorithm model recommender is selected, the set recommendation object column comprises a plurality of algorithm model recommenders associated with set recommendation categories for selection by a user, and meanwhile, a parameter input column is provided for input by the user;
when the rule recommender is selected, the set recommendation object column includes a plurality of recommendation categories and a plurality of recommenders contained in the recommendation categories.
4. The definition method according to claim 3, wherein the recommendation rule list comprises: screening a rule column; the screening rule column includes: filtering rules, sorting rules and priority rules;
when the filtering rule is selected, providing a rule designer for user input, wherein the rule designer is provided with: a product attribute filtering rule and a product association attribute filtering rule;
when the sorting rule is selected, providing a rule designer for a user to set the sorting rule;
and when the priority rule is selected, providing a rule designer for setting the priority rule by a user.
5. The definition method according to claim 3, wherein the recommendation rule list comprises: a default recommendation field;
when the default recommendation column is selected, providing a rule designer for a user to input a plurality of recommenders as default recommendation rules;
and filling the default recommendation rule into the rules set by the user when the recommendation result list is empty or the recommendation number is insufficient.
6. The definition method according to claim 1, wherein the recommendation rule list comprises: push to the recommendation bar;
and when the push recommendation column is selected, providing a rule designer for a user to set a push recommendation, and setting the push recommendation to be the highest priority.
7. The definition method according to claim 1, wherein the basic information list comprises: a recommended scheme coding column, a recommended scheme name column, a recommended scheme description column, an effective date column, an expiration date column, a recommended number column, and a recommended category column.
8. A definition apparatus, comprising:
the basic information list creating module is used for creating a basic information list of a recommendation scheme;
the recommendation rule list creating module is used for creating a recommendation rule list of a recommendation scheme;
a recommendation rule management list creating module, configured to create a recommendation rule management list according to the basic information list and the recommendation rule list;
and the interactive interface creating module is used for organizing the basic information list, the recommendation rule list and the recommendation rule management list into a user interface for a user to input an expected value.
9. A computer readable storage medium having stored therein at least one instruction, at least one program, set of codes, or set of instructions, which is loaded and executed by a processor to implement a method as defined in any one of claims 1 to 8.
10. A computer device comprising a processor and a memory, the memory having stored therein at least one instruction, at least one program, set of codes, or set of instructions, which is loaded and executed by the processor to implement a method as defined in any one of claims 1 to 8.
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2020
- 2020-12-31 CN CN202011636778.3A patent/CN112950306A/en active Pending
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| CN102831543A (en) * | 2012-09-19 | 2012-12-19 | 河南锐之旗信息技术有限公司 | E-commerce recommendation method |
| US20160104067A1 (en) * | 2014-10-08 | 2016-04-14 | Salesforce.Com, Inc. | Recommendation platform |
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Application publication date: 20210611 |