CN113033938B - Method, device, terminal equipment and storage medium for determining resource allocation strategy - Google Patents

Method, device, terminal equipment and storage medium for determining resource allocation strategy Download PDF

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CN113033938B
CN113033938B CN202010797812.9A CN202010797812A CN113033938B CN 113033938 B CN113033938 B CN 113033938B CN 202010797812 A CN202010797812 A CN 202010797812A CN 113033938 B CN113033938 B CN 113033938B
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event
resource
data
simulation environment
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CN113033938A (en
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肖冰
石航
肖亚红
李政道
国星
国世平
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Shenzhen University
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    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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Abstract

The application provides a method, a device, terminal equipment and a storage medium for determining a resource allocation strategy, relates to the technical field of data processing, and can effectively improve the accuracy of the resource allocation strategy. The method for determining the resource allocation policy comprises the following steps: acquiring a user portrait of a user; determining an event simulation environment according to the user profile, wherein the event simulation environment comprises simulation events aiming at least one resource product; pushing the event simulation environment to the user, and acquiring biological characteristic information of the user in the event simulation environment; updating the user portrait according to the biological characteristic information; and determining a resource allocation strategy for the resource product according to the updated user portrait.

Description

Method, device, terminal equipment and storage medium for determining resource allocation strategy
Technical Field
The present application belongs to the technical field of data processing, and in particular, relates to a method, an apparatus, a terminal device, and a storage medium for determining a resource allocation policy.
Background
Along with the continuous improvement of the living standard of people, the distribution of resource products also gradually enters the field of vision of people. At present, due to the insufficient knowledge of users on resource products, in the process of allocating the resource products to obtain corresponding value added resource products, corresponding resource allocation auxiliary mechanism personnel generally collect data of the users, risk grade assessment is carried out in advance according to the collected user basic data, and then the users allocate the resource products based on the assessment result.
However, because the existing risk level evaluation mode is simpler, the matching degree between the obtained risk evaluation result and the user is lower, so that the accuracy of the resource product allocation strategy obtained by the user for decision making based on the risk level evaluation with low matching degree is also poorer.
Disclosure of Invention
The embodiment of the application provides a method, a device, terminal equipment and a storage medium for determining a resource allocation strategy, which are used for solving the problem of poor accuracy of the resource allocation strategy obtained based on the existing mode.
In a first aspect, an embodiment of the present application provides a method for determining a resource allocation policy, which is characterized in that the method includes:
acquiring a user portrait of a user;
Determining an event simulation environment according to the user profile, wherein the event simulation environment comprises simulation events aiming at least one resource product;
pushing the event simulation environment to the user, and acquiring biological characteristic information of the user in the event simulation environment;
Updating the user portrait according to the biological characteristic information;
and determining a resource allocation strategy for the resource product according to the updated user portrait.
Optionally, the obtaining the user portrait includes:
acquiring user basic data, and generating an initial user portrait based on the user basic data;
acquiring selection data of the user in at least one simulation scene;
and matching the selection data with target selection data, and updating the initial user portrait according to a matching result to obtain the user portrait.
Optionally, before determining the event simulation environment according to the user portrait, the method further includes:
processing the user basic data and/or the first selection data through a preset data analysis model to obtain at least one reference variable;
Processing the at least one reference variable through a quantization model to determine at least one of the resource products.
Optionally, said processing said at least one reference variable by a quantization model to determine at least one of said resource products comprises:
Acquiring resource product configuration information input by the user;
Configuring at least one resource product parameter according to the resource product configuration information;
And processing the at least one reference variable and the at least one resource product parameter through the quantization model to determine at least one resource product.
Optionally, the biometric information includes at least one of static feature information and dynamic feature information;
the updating of the user portrait according to the biometric information comprises:
Enriching the user portrait according to the static characteristic information and/or the dynamic characteristic information.
Optionally, the enriching the user portrait according to the static feature information and/or the dynamic feature information includes:
Determining a static risk variable according to the static characteristic information;
Enriching the user portraits according to the static risk variables;
Or, determining a dynamic risk variable according to the dynamic characteristic information;
enriching the user portrait according to the dynamic risk variable.
Optionally, pushing the event simulation environment to the user and acquiring the biometric information of the user in the event simulation environment includes:
pushing the event simulation environment to the user, and acquiring second selection data of the user in the event simulation environment;
the updating of the user portrait according to the biometric information comprises:
And updating the user portrait according to the second selection data.
Optionally, after determining the resource allocation policy for the resource product according to the updated user portrait, the method further includes:
Acquiring feedback data of a user;
and updating the resource allocation strategy according to the feedback data of the user.
In a second aspect, an embodiment of the present application provides an apparatus for determining a resource allocation policy, including:
The acquisition module is used for acquiring a user image of a user;
A simulation module, configured to determine an event simulation environment according to the user profile, where the event simulation environment includes a simulation event for at least one resource product;
the pushing module is used for pushing the event simulation environment to the user and acquiring the biological characteristic information of the user in the event simulation environment;
The updating module is used for updating the user portrait according to the biological characteristic information;
and the determining module is used for determining a resource allocation strategy for the resource product according to the updated user portrait.
In a third aspect, an embodiment of the present application provides a terminal device, including: a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the method of determining a resource allocation policy when executing the computer program.
In a fourth aspect, embodiments of the present application provide a computer readable storage medium storing a computer program which, when executed by a processor, implements a method of determining a resource allocation policy.
In a fifth aspect, an embodiment of the present application provides a computer program product, which, when run on a terminal device, causes the terminal device to perform the method of determining a resource allocation policy according to any of the first aspects above.
By adopting the method for determining the resource allocation strategy, firstly, the user portrait is acquired so as to be convenient for knowing the condition of the user approximately through the user portrait, then the event simulation environment containing the simulation event for at least one resource product is determined according to the user portrait, the event simulation environment is pushed to the user, and the biological characteristic information of the user reflected under the event simulation environment is acquired so as to be convenient for knowing the preference of the user to one resource product through the biological characteristic information of the user. Then, updating the user portrait according to the biological characteristic information, namely, the user portrait for describing the user is more accurate, and a resource allocation strategy for the resource product is determined according to the updated user portrait, so that the customization requirement of the user can be better met, and the matching degree of the resource allocation strategy and the user is higher.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed 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 flowchart of a method for determining a resource allocation policy according to an embodiment of the present application.
Fig. 2 is a schematic structural diagram of an apparatus for determining a resource allocation policy according to an embodiment of the present application.
Fig. 3 is a schematic structural diagram of a terminal device according to an embodiment of the present application.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth such as the particular system architecture, techniques, etc., in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.
As used in the present description and the appended claims, the term "if" may be interpreted as "when..once" or "in response to a determination" or "in response to detection" depending on the context. Similarly, the phrase "if a determination" or "if a [ described condition or event ] is detected" may be interpreted in the context of meaning "upon determination" or "in response to determination" or "upon detection of a [ described condition or event ]" or "in response to detection of a [ described condition or event ]".
Furthermore, the terms "first," "second," "third," and the like in the description of the present specification and in the appended claims, are used for distinguishing between descriptions and not necessarily for indicating or implying a relative importance.
Reference in the specification to "one embodiment" or "some embodiments" or the like means that a particular feature, structure, or characteristic described in connection with the embodiment is included in one or more embodiments of the application. Thus, appearances of the phrases "in one embodiment," "in some embodiments," "in other embodiments," and the like in the specification are not necessarily all referring to the same embodiment, but mean "one or more but not all embodiments" unless expressly specified otherwise. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless expressly specified otherwise.
In order to illustrate the technical scheme of the application, the following description is made by specific examples.
Referring to fig. 1, fig. 1 is a flowchart of a method for determining a resource allocation policy according to an embodiment of the present application.
In this embodiment, there is a possible application scenario in which in investment financial management, there are some users lacking basic financial and investment financial management knowledge, so risk evaluation is performed when investment financial management is performed, and the evaluation range mainly covers static information such as age, income, marital status, investment experience, etc., but because the risk bearing capacity, risk preference, etc. which change with the user while the user is aged are not considered, that is, the scene of investment is single, the obtained user portrait is relatively single and static, so that when investment financial management products are selected, the investment financial management allocation policy obtained based on the user portrait cannot be well adapted to the user in different application scenarios and investment requirements, and good allocation of resource products is realized. Therefore, it is required to more comprehensively and finely describe the user portrait of the user so as to obtain a better resource allocation strategy of the resource product based on the user portrait after the accurate description, so as to better fit the requirements of the user.
In this embodiment, the method for determining a resource allocation policy is used to determine, when a resource product is allocated, a resource allocation policy of a user for the resource product, where an execution body of the resource allocation policy is a terminal device.
The method for determining a resource allocation policy as shown in fig. 1 comprises the steps of:
S11: and acquiring a user portrait of the user.
In step S11, a user portrait is used to describe the relevant situation of the user, and the user portrait includes data information of the user corresponding to the user and allocation data information of the user to the resource product when the resource product is allocated.
For example, the user portrait includes at least one of basic information such as name and sex of the user, financial information of the user, investment information of the user, preference information of the user and industry information of the user, and information related to the resource product of the user can be known in detail by acquiring the user portrait.
It is understood that the image of the user may include at least one of current data information, historical data information of the user, and at least one of current allocation data information, historical allocation data information of the user for the resource product.
In this embodiment, when a user wants to allocate resource products, a user portrait of the user is obtained through the terminal device, and because the user portrait can be used to describe details of the user, the user portrait of the user is obtained, that is, user data of the user when allocating resource products is obtained, so that a resource allocation policy conforming to the user can be better formed on the basis of considering details of the user, and when allocating resource products based on the resource allocation policy, the user can also accurately configure the resource allocation policy most conforming to the needs of the user. As to when to obtain a user representation of a user, the following two scenarios may be included, but are not limited to.
Scene 1: if the resource allocation request input by the user is detected before the resource allocation, the user portrait of the user is acquired through the terminal equipment.
For example, when a user's request to inventory is detected, a user representation of the user is obtained by the user terminal device. For example, sample data such as user basic information, user financial information, user investment information, user preference information, user industry information and the like of the user is obtained, and an evaluation data set is extracted based on the sample data, so that a user portrait of the user is generated, and the related situation of the user and the resource product, such as the name and the sex of the user, the user is in the science and technology industry, the user likes investment science and technology and the like, is described through the user portrait.
Scene 2: if the additional resource allocation request of the user is detected in order to better allocate the resource products in the resource allocation process, the user portrait of the user is acquired through the terminal equipment.
After the operation of the financial product is performed by one user, in order to better throw own property into the corresponding financial product, a better investment combination is obtained, the user inputs a resource allocation request through the terminal device, the terminal device responds to and obtains a user portrait of the user, namely, data information of the user and allocation data information of the financial product are obtained, so that analysis can be better performed based on the user portrait in the follow-up process, and a better resource allocation strategy is obtained.
It should be understood that in practical application, in order to facilitate better determining the resource allocation policy of the resource product according to the user portrait, the resource allocation policy may be stored in advance in the storage area of the terminal device after the user portrait of the user is acquired, so that the subsequent terminal device obtains the better resource allocation policy according to the stored user portrait.
S12: an event simulation environment is determined based on the user profile, the event simulation environment containing simulated events for at least one resource product.
In step S12, after determining the event simulation environment as sample data of the event simulation environment based on the user portrait, a virtual environment generated based on the sample data is simulated by using a preset electronic device, and the user may enter the virtual environment based on the electronic device or a device connected to the electronic device.
It will be appreciated that the sample data corresponding to the event simulation environments is pre-arranged and stored, so that when a user profile of a user is obtained, the corresponding event simulation environment can be determined based on the user profile, and there can be a plurality of determined event simulation environments. The sample data corresponding to the event simulation environment comprises at least one of sample data of a certain social event, a family event, an economic event, a political event and a natural event.
The resource product may be a product that allocates resources such as public offering funds, bonds, stocks, bank financing, trust, insurance or privately recruited funds products.
A simulated event is a simulated event in which a resource product automatically evolves based on an event simulation environment to exist in the event simulation environment. For example, when a large infection outbreak occurs and the catering industry encounters a cold burst, the corresponding simulated event for the resource product stock is a dip.
It can be appreciated that the corresponding event simulation environment is determined based on the user's data information recorded in the user profile and the user's allocation data information for the resource product.
S13: pushing the event simulation environment to the user, and acquiring the biological characteristic information of the user in the event simulation environment.
In step S13, the biometric information is biometric data information that describes what the user has for the simulated event of the resource product.
In this embodiment, after determining an event simulation environment according to a user portrait, the terminal device generates a control instruction for pushing the event simulation environment to the user, and sends the control instruction to the terminal device operated by the user or connects with other electronic devices, and the user receives the pushed event simulation environment through the terminal device or other electronic devices, so that the user can be in the event simulation environment based on the terminal device or other electronic devices, and thus can see a simulation event of a resource product that exists correspondingly when in the event simulation environment.
The control instruction is used for indicating the terminal equipment or connecting other electronic equipment with the terminal equipment to simulate and generate the event simulation environment according to sample data of the event simulation environment, such as simulating and generating financial crisis and large-scale infectious disease outbreaks, so that catering industry suffers from explosion and coldness and the like.
In some embodiments, the terminal device sends the data image of the event simulation environment to the user account, and when the user logs in the user account, the user uses the terminal device to connect with other electronic devices of the terminal device to receive the data image, so that the user can be in the event simulation environment to see the simulation event of the resource product correspondingly existing in the event simulation environment.
It will be appreciated that, because the user is exposed to the event simulation environment based on the terminal device or other electronic device, the user can view the corresponding simulated event of the resource product and there will be a corresponding change in the biometric features.
It should be noted that the biometric information of the user may be obtained based on detection in the terminal device or other electronic devices. For example, heartbeat information of the user is detected by a heartbeat sensor.
For example, when a certain simulation event is seen, the user does not extend hands, heart beat is quickened or pupils are contracted inwards independently, so that the attention or deflection of the user to the certain simulation event can be known by acquiring the biological characteristic information of the user in the event simulation environment, the truest allocation requirement condition of the user is reflected, and finally the resource allocation strategy closest to the resource product allocation requirement of the user can be obtained based on the biological characteristic information.
For example, sample data of an event simulation environment is determined to be sample data of the catering industry based on user portraits, and a user views that a consumption stock held by the user falls down by wearing visual equipment such as AR, VR and the like, so that the pupil of the user contracts inwards, the heartbeat is accelerated, and hands do not independently want to operate to sell the consumption stock.
In some embodiments, a simulated event corresponding to a resource product is obtained, and biometric information of a user corresponding to the simulated event is obtained.
In some embodiments, a simulated event corresponding to a plurality of resource products, biometric information of a user corresponding to the simulated event is obtained once.
S14: and updating the user portrait according to the biological characteristic information.
In step S14, updating of the target data in the user data portion recorded in the user portrait is completed by using the biometric information, that is, the target data recorded in the user portrait is confirmed based on the biometric information, and then updating of the target data is completed based on the biometric information. The target data is used for describing situations such as bearing capacity, risk preference and the like of risks of a user during resource product distribution.
For example, when the heartbeat frequency corresponding to a simulated event of a high-risk stock in an event simulation environment is accelerated by a user and the hand is not independently expected to sell the biological feature information of the stock, namely, the user does not deviate to the high risk and the financial wind direction bearing capacity is low, so that based on the information such as the acquired biological feature information update, the bearing capacity of the user for the financial risk recorded in the user portrait, the risk preference and the like, for example, the description of the bearing capacity is low based on the biological feature information update, or the B grade, the risk preference is C grade, the subsequent determination of a low-risk resource allocation strategy based on the updated user image is facilitated, and the user can carry out investment of the financial product based on the low-risk resource allocation strategy to acquire low-risk benefits.
S15: and determining a resource allocation strategy for the resource product according to the updated user portrait.
In step S15, the resource allocation policy is a logical process or means describing the allocation of resource products.
The resource product is a financial product, the resource allocation policy is an investment combination policy describing the allocation investment of the financial product, and when the updated user portrait is obtained, the investment combination policy of the financial product is matched according to the information recorded by the user portrait.
In this embodiment, a resource allocation policy of a resource product with the highest matching degree with the user is determined according to the data information of the user and the allocation data information of the user to the resource product recorded in the updated user portrait.
In some embodiments, the resource allocation policy may be pre-established and stored in the terminal device or an electronic device connected to the terminal device, and after determining the updated user profile, the updated user profile is used to match the stored resource allocation policy, so as to determine the resource allocation policy for the resource product.
The method for determining the resource allocation policy provided by the application is characterized in that firstly, a user portrait is obtained so as to be convenient for knowing the condition of the user approximately through the user portrait, then, an event simulation environment containing simulation events for at least one resource product is determined according to the user portrait, the event simulation environment is pushed to the user, and the biological characteristic information of the user reflected in the event simulation environment is obtained so as to be convenient for knowing the preference of the user to one resource product through the biological characteristic information expressed by the user. Then, updating the user portrait according to the biological characteristic information, namely, the user portrait for describing the user is more accurate, and a resource allocation strategy for the resource product is determined according to the updated user portrait, so that the customization requirement of the user can be better met, and the matching degree of the resource allocation strategy and the user is higher. In one embodiment of the present application, obtaining a user image includes:
user basic data is acquired, and an initial user portrait is generated based on the user basic data.
First selection data of a user in at least one simulation scene is acquired.
And matching the first selection data with the target selection data, and updating the initial user portrait according to the matching result to obtain the user portrait.
In this embodiment, the user basic data is data describing the basic situation of the user, from which the rough situation of the user can be known. For example, at least one of basic information such as a user's name, sex, etc., user financial information, user investment information, user preference information, and user industry information.
The manner of acquiring the user basic data includes, but is not limited to: 1) Filling out a questionnaire form, namely acquiring user data in multiple aspects according to basic questions manually set in advance, including filling-in questions, selecting questions, multiple selecting questions and the like; 2) The robot dialogue mode, namely, the robot collects user data through a language model, a probability graph model, a word segmentation algorithm, part-of-speech tagging, dependency statement analysis, semantic role word segmentation, named entity recognition, semantic tree algorithm and technology and decision tree type or free question-answer interaction flow of the robot; 3) The external data channel, i.e. access and retrieve the user data stored in the memory area.
The simulation scene is a virtual environment generated by simulating the terminal equipment or the electronic equipment connected with the terminal equipment based on sample data of a preset simulation scene. For example, the terminal device or the electronic device connected to the terminal device generates a simulation scene based on sample data of life scenes such as life, education, work, home, investment financial, etc., in which a user can select allocation of operation resource products such as various investments in operation financial products.
The first selection data is used to describe the user's operation of resource product allocation in the simulated scenario. For example, the user selects data for the investment in the simulation scenario.
The target selection data is used for describing the selection operation of other users for resource product allocation in the simulation scene, and the selection data corresponding to each user in the scene simulation is obtained after deep learning based on user portraits of a plurality of other users.
In this embodiment, since the first selection data and the target selection data may both describe the operation of allocating the resource product in the simulation scenario, the first selection data and the target selection data may be matched to determine where the first selection data is different from the target selection data, that is, the matching result, so that the first selection data in the initial user representation may be modified by using the target selection data according to the matching result, so that the user representation of the user may be described more accurately, and the resource allocation policy may be determined more accurately later.
In some embodiments, the initial user representation is updated based on the first selection data, the target selection data, and the collaborative filtering algorithm to obtain a user representation.
In one embodiment of the present application, before determining the event simulation environment according to the user portrait, the method further comprises:
Processing the user basic data and/or the first selection data through a preset data analysis model to obtain at least one reference variable;
At least one reference variable is processed through the quantization model to determine at least one resource product.
In this embodiment, a pre-trained preset data analysis model is pre-stored in the terminal device. The preset data analysis model is obtained by training an initial data analysis model based on a sample training set by using a machine learning algorithm.
It can be understood that the data analysis model may be trained by the terminal device in advance, or files corresponding to the data analysis model may be transplanted to the terminal device after being trained by other devices in advance. That is, the execution subject for training the data analysis model may be the same as or different from the execution subject for performing data analysis using the data analysis model. For example, when the initial data analysis model is trained by other equipment, after the training of the initial data analysis model is finished by the other equipment, fixing model parameters of the initial data analysis model to obtain a file corresponding to the data analysis model. The file is then migrated to the terminal device.
The reference variables are used to describe the user's matching degree to the resource product, and the tendency to assign the resource product. For example, based on the reference variable, the risk cognition capability of the financial product of the user is insufficient, the investment risk preference is high, the risk bearing capability is high, and the like can be known.
The quantization model processes at least one reference variable, so that a resource product with high matching degree or high interest degree with a user is determined through the reference variable, and a resource allocation strategy with high matching degree can be formulated for the user conveniently and subsequently around the resource product.
In some embodiments, the quantization model includes a makewise mean variance optimization Model (MVO), a brisk one Li Teman (Black Li terman) model, a risk flat model, a hidden markov chain model, a linear time series model, a conditional heteroscedastic model nonlinear model, a continuous time model, extremum theory, quantile estimation and risk values, a multivariate time series analysis, principal component analysis and factor model, a multivariate volatility model, a state space model and kalman filtering, a markov chain monte carlo method.
For example, the data analysis model is used for analyzing and processing the user basic data, and the information such as financial expertise, financial capability investment preference, risk bearing capability, risk cognition capability and the like of the user recorded in the first selection data, and quantifying the information into at least one reference variable, so that the financial expertise, risk bearing capability and risk cognition capability of the user can be determined through the reference variable. Further, the reference variable is processed through a quantization model, so that different risk preferences, different industry types and different product types of financial products are configured for the user.
In an embodiment, the user basic data and the first selection data are processed through a preset data analysis algorithm to obtain at least one reference variable.
For example, the user base data, the first selection data are classified, regression analyzed, clustered, associated planning or feature analyzed by a machine learning algorithm to obtain at least one reference variable.
In one embodiment of the present application, determining at least one resource product by processing at least one reference variable through a quantization model comprises:
and acquiring resource product configuration information input by a user.
At least one resource product parameter is configured according to the resource product configuration information.
At least one resource product is determined by processing the at least one reference variable and the at least one resource product parameter through the quantization model.
In this embodiment, the resource product configuration information describes the evaluation requirement of the user when the resource product is allocated. For example, the user inputs the set investment period, return rate, and price factor, value factor, scale factor, etc. of the stock at the time of financing.
In one embodiment of the present application, the biometric information includes at least one of static feature information and dynamic feature information.
Updating the representation of the user based on the biometric information, comprising: and updating the user portrait according to the static characteristic information and/or the dynamic characteristic information.
In this embodiment, static characteristic information is used to describe the internal body biometric characteristics of the user while in a stationary state. Such as heart beat, pupil changes.
The dynamic characteristic information is used for describing physical extrinsic action of the user. Such as shaking of the body, involuntary shaking of the hands.
In this embodiment, after the static feature information or the dynamic feature information is obtained, the static feature information or the dynamic feature information is used to determine target data recorded in the user portrait and describing the static feature information or the dynamic feature information, and then the static feature information or the dynamic feature information is used to update the corresponding target data in the user portrait.
In an embodiment of the present application, pushing an event simulation environment to a user and acquiring biometric information of the user in the event simulation environment includes:
pushing the event simulation environment to the user, and acquiring second selection data of the user in the event simulation environment;
Updating the representation of the user based on the biometric information, comprising:
And updating the user portrait according to the second selection data.
In this embodiment, the second selection data is used to describe the operation of the user for resource product allocation in the simulation scenario. For example, the user selects data for the investment in the simulation scenario.
In one embodiment of the present application, after determining the resource allocation policy for the resource product according to the updated user representation, the method further includes:
Acquiring feedback data of a user;
And updating the resource allocation strategy according to the feedback data of the user to obtain a new resource allocation strategy.
In this embodiment, the feedback data is used to describe the user's demand for product allocation of the resource allocation policy. For example, after a user obtains an analysis report of own investment and a corresponding investment combination strategy, the user determines that a fund manager is unsuitable in the investment combination strategy, and can contact a restaurant company for the reason of own work, so that the company is subjectively approved according to own personal experiences, and the user wants to invest more weight, and feeds own opinion back to the system for quantification, thereby facilitating the follow-up modification of the investment combination strategy based on feedback data.
In this embodiment, after user feedback data is obtained, the updated user portrait is updated again based on the feedback data, and the resource allocation policy of the resource product is determined to be modified based on the updated user portrait, so as to obtain a new resource allocation policy.
It should be understood that the sequence number of each step in the foregoing embodiment does not mean that the execution sequence of each process should be determined by the function and the internal logic, and should not limit the implementation process of the embodiment of the present application.
Corresponding to the method described in the above embodiments, fig. 2 shows a block diagram of an apparatus for determining a resource allocation policy according to an embodiment of the present application, and for convenience of explanation, only a portion related to the embodiment of the present application is shown.
Referring to fig. 2, the apparatus 100 includes:
an acquisition module 101, configured to acquire a user image of a user;
a simulation module 102 for determining an event simulation environment based on the user profile, the event simulation environment comprising simulation events for at least one resource product;
A pushing module 103, configured to push the event simulation environment to the user, and obtain biometric information of the user in the event simulation environment;
an updating module 104, configured to update the user portrait according to the biometric information;
A determining module 105, configured to determine a resource allocation policy for the resource product according to the updated user representation.
Optionally, the acquiring module 101 is further configured to acquire user basic data, and generate an initial user portrait based on the user basic data; acquiring selection data of the user in at least one simulation scene; and matching the selection data with target selection data, and updating the initial user portrait according to a matching result to obtain the user portrait.
Optionally, the apparatus 100 further includes a first processing module and a second processing module.
The first processing module is used for processing the user basic data and the first selection data through a preset data analysis model to obtain at least one reference variable;
And the second processing module is used for processing the at least one reference variable through a quantization model and determining at least one resource product.
Optionally, the second processing module is further configured to obtain resource product configuration information input by the user; configuring at least one resource product parameter according to the resource product configuration information; and processing the at least one reference variable and the at least one resource product parameter through the quantization model to determine at least one resource product.
Optionally, the biometric information includes at least one of static feature information and dynamic feature information.
The updating module 104 is further configured to enrich the user portrait according to the static feature information and/or the dynamic feature information.
Optionally, the updating module 104 is further configured to determine a static risk variable according to the static feature information; enriching the user portraits according to the static risk variables; or, determining a dynamic risk variable according to the dynamic characteristic information; enriching the user portrait according to the dynamic risk variable.
Optionally, an updating module 104, configured to obtain feedback data of the user; and updating the resource allocation strategy according to the feedback data of the user to obtain a new resource allocation strategy.
Fig. 3 is a schematic structural diagram of a terminal device according to an embodiment of the present application. As shown in fig. 3, the terminal device 3 of this embodiment includes: at least one processor 30 (only one processor is shown in fig. 3), a memory 31 and a computer program 32 stored in the memory 31 and executable on the at least one processor 30, the processor 30 executing the computer program 32 implementing the steps in any of the various method embodiments for determining a resource allocation policy described above.
The terminal device 3 may be a computing device such as a desktop computer, a notebook computer, a palm computer, a cloud server, etc. The terminal device may include, but is not limited to, a processor 30, a memory 31. It will be appreciated by those skilled in the art that fig. 3 is merely an example of the terminal device 3 and does not constitute a limitation of the terminal device 3, and may include more or less components than illustrated, or may combine certain components, or different components, such as may also include input-output devices, network access devices, etc.
The Processor 30 may be a central processing unit (Central Processing Unit, CPU), the Processor 30 may also be other general purpose processors, digital signal processors (DIGITAL SIGNAL processors, DSP), application SPECIFIC INTEGRATED Circuit (ASIC), off-the-shelf Programmable gate array (Field-Programmable GATE ARRAY, FPGA) or other Programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 31 may in some embodiments be an internal storage unit of the terminal device 3, such as a hard disk or a memory of the terminal device 3. The memory 31 may in other embodiments also be an external storage device of the terminal device 3, such as a plug-in hard disk provided on the terminal device 3, a smart memory card (SMART MEDIA CARD, SMC), a Secure Digital (SD) card, a flash memory card (FLASH CARD) or the like. Further, the memory 31 may also include both an internal storage unit and an external storage device of the terminal device 3. The memory 31 is used for storing an operating system, application programs, boot loader (BootLoader), data, other programs etc., such as program codes of the computer program etc. The memory 31 may also be used for temporarily storing data that has been output or is to be output.
It should be noted that, because the content of information interaction and execution process between the above devices/units is based on the same concept as the method embodiment of the present application, specific functions and technical effects thereof may be referred to in the method embodiment section, and will not be described herein.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions. The functional units and modules in the embodiment may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit, where the integrated units may be implemented in a form of hardware or a form of a software functional unit. In addition, the specific names of the functional units and modules are only for distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working process of the units and modules in the above system may refer to the corresponding process in the foregoing method embodiment, which is not described herein again.
Embodiments of the present application also provide a computer readable storage medium storing a computer program which, when executed by a processor, implements steps for implementing the various method embodiments described above.
Embodiments of the present application provide a computer program product enabling a terminal device to carry out the steps of the method embodiments described above when the computer program product is run on the terminal device.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the present application may implement all or part of the flow of the method of the above embodiments, and may be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, and when the computer program is executed by a processor, the computer program may implement the steps of each of the method embodiments described above. Wherein the computer program comprises computer program code which may be in source code form, object code form, executable file or some intermediate form etc. The computer readable medium may include at least: any entity or device capable of carrying computer program code to a photographing device/terminal apparatus, recording medium, computer Memory, read-Only Memory (ROM), random access Memory (RAM, random Access Memory), electrical carrier signals, telecommunications signals, and software distribution media. Such as a U-disk, removable hard disk, magnetic or optical disk, etc. In some jurisdictions, computer readable media may not be electrical carrier signals and telecommunications signals in accordance with legislation and patent practice.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and in part, not described or illustrated in any particular embodiment, reference is made to the related descriptions of other embodiments.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus/network device and method may be implemented in other manners. For example, the apparatus/network device embodiments described above are merely illustrative, e.g., the division of the modules or units is merely a logical functional division, and there may be additional divisions in actual implementation, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other forms.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
The above embodiments are only for illustrating the technical solution of the present application, and not for limiting the same; although the application has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present application, and are intended to be included in the scope of the present application.

Claims (10)

1. A method of determining a resource allocation policy, comprising:
acquiring a user portrait of a user;
Determining an event simulation environment according to the user portrait, wherein the event simulation environment comprises simulation events aiming at least one resource product, the event simulation environment is a virtual environment generated by simulating a preset electronic device based on sample data after determining the sample data of the event simulation environment based on the user portrait, and a user can enter the virtual environment based on the electronic device or a device connected with the electronic device; the sample data corresponding to the event simulation environment comprises at least one of sample data of a social event, a family event, an economic event, a political event and a natural event;
Pushing the event simulation environment to the user, and acquiring biological characteristic information of the user in the event simulation environment, wherein the biological characteristic data is biological response data information describing a simulation event of the user on the resource product;
Updating the user portrait according to the biological characteristic information;
and determining a resource allocation strategy for the resource product according to the updated user portrait.
2. The method of claim 1, wherein the obtaining the representation of the user comprises:
acquiring user basic data, and generating an initial user portrait based on the user basic data;
Acquiring first selection data of the user in at least one simulation scene;
And matching the first selection data with target selection data, and updating the initial user portrait according to a matching result to obtain the user portrait.
3. The method of claim 2, wherein prior to determining an event simulation environment from the user representation, further comprising:
processing the user basic data and/or the first selection data through a preset data analysis model to obtain at least one reference variable;
Processing the at least one reference variable through a quantization model to determine at least one of the resource products.
4. A method according to claim 3, wherein said processing said at least one reference variable by a quantization model to determine at least one of said resource products comprises:
Acquiring resource product configuration information input by the user;
Configuring at least one resource product parameter according to the resource product configuration information;
And processing the at least one reference variable and the at least one resource product parameter through the quantization model to determine at least one resource product.
5. The method of claim 1, wherein the biometric information comprises at least one of static feature information, dynamic feature information;
the updating of the user portrait according to the biometric information comprises:
And updating the user portrait according to the static characteristic information and/or the dynamic characteristic information.
6. The method of claim 1, wherein pushing the event simulation environment to the user and obtaining biometric information of the user in the event simulation environment comprises:
pushing the event simulation environment to the user, and acquiring second selection data of the user in the event simulation environment;
the updating of the user portrait according to the biometric information comprises:
And updating the user portrait according to the second selection data.
7. The method of claim 1, wherein after determining the resource allocation policy for the resource product based on the updated representation of the user, further comprising:
Acquiring feedback data of a user;
and updating the resource allocation strategy according to the feedback data of the user.
8. An apparatus for determining a resource allocation policy, the apparatus comprising:
The acquisition module is used for acquiring a user image of a user;
The simulation module is used for determining an event simulation environment according to the user portrait, wherein the event simulation environment comprises simulation events aiming at least one resource product, the event simulation environment is a virtual environment which is generated by simulating the sample data by using preset electronic equipment after determining the sample data of the event simulation environment based on the user portrait, and a user can enter the virtual environment based on the electronic equipment or equipment connected with the electronic equipment; the sample data corresponding to the event simulation environment comprises at least one of sample data of a social event, a family event, an economic event, a political event and a natural event;
The pushing module is used for pushing the event simulation environment to the user and acquiring the biological characteristic information of the user in the event simulation environment, wherein the biological characteristic data is biological response data information describing the simulation event of the user on the resource product;
The updating module is used for updating the user portrait according to the biological characteristic information;
and the determining module is used for determining a resource allocation strategy for the resource product according to the updated user portrait.
9. A terminal device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the method according to any one of claims 1 to 7 when executing the computer program.
10. A computer readable storage medium, characterized in that the computer readable storage medium stores a computer program which, when executed by a processor, implements the method according to any of claims 1 to 7.
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Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107203939A (en) * 2017-05-26 2017-09-26 阿里巴巴集团控股有限公司 Determine method and device, the computer equipment of consumer's risk grade
CN107526433A (en) * 2016-06-21 2017-12-29 宏达国际电子股份有限公司 To provide the method for customized information and simulation system in simulated environment
CN107798607A (en) * 2017-07-25 2018-03-13 上海壹账通金融科技有限公司 Asset Allocation strategy acquisition methods, device, computer equipment and storage medium
CN108985638A (en) * 2018-07-25 2018-12-11 腾讯科技(深圳)有限公司 A kind of customer investment methods of risk assessment and device and storage medium
CN110992190A (en) * 2019-12-19 2020-04-10 中国建设银行股份有限公司 Asset configuration method and device based on user portrait

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107526433A (en) * 2016-06-21 2017-12-29 宏达国际电子股份有限公司 To provide the method for customized information and simulation system in simulated environment
CN107203939A (en) * 2017-05-26 2017-09-26 阿里巴巴集团控股有限公司 Determine method and device, the computer equipment of consumer's risk grade
CN107798607A (en) * 2017-07-25 2018-03-13 上海壹账通金融科技有限公司 Asset Allocation strategy acquisition methods, device, computer equipment and storage medium
CN108985638A (en) * 2018-07-25 2018-12-11 腾讯科技(深圳)有限公司 A kind of customer investment methods of risk assessment and device and storage medium
CN110992190A (en) * 2019-12-19 2020-04-10 中国建设银行股份有限公司 Asset configuration method and device based on user portrait

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