CN116385126A - Information processing method, information processing device, storage medium and computer equipment - Google Patents

Information processing method, information processing device, storage medium and computer equipment Download PDF

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CN116385126A
CN116385126A CN202310377501.0A CN202310377501A CN116385126A CN 116385126 A CN116385126 A CN 116385126A CN 202310377501 A CN202310377501 A CN 202310377501A CN 116385126 A CN116385126 A CN 116385126A
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information
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information processing
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姚从飞
吴淮恩
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Ping An International Financial Leasing Co Ltd
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Abstract

The invention discloses an information processing method, an information processing device, a storage medium and computer equipment, relates to the technical field of information and financial science and technology, and mainly aims to improve information changing efficiency and changing accuracy and improve user experience. The method comprises the following steps: receiving an information processing instruction corresponding to information to be processed, wherein the information processing instruction carries an information identifier corresponding to the information to be processed; based on the information identification, determining an information type to which the information to be processed belongs, and determining an information processing template corresponding to the information type; acquiring change demand data corresponding to the information to be processed based on the information processing template; inputting the change demand data into a preset value prediction model to perform conversion value prediction, and obtaining a change value prediction parameter corresponding to the information to be processed; and changing the information to be processed based on the change value prediction parameter. The invention is suitable for changing information.

Description

Information processing method, information processing device, storage medium and computer equipment
Technical Field
The present invention relates to the field of information technologies, and in particular, to an information processing method, an information processing device, a storage medium, and a computer device.
Background
Information change is an important part of assets of a financial company, and is a problem that enterprises need to face for information change, and it is important that users cannot directly change certain information simply and effectively.
Currently, a user usually verbally presents a change requirement to a worker, and the worker directly changes information according to the change requirement of the user. However, this way requires the user to arrive at the scene personally or express the requirement with the staff, which results in lower efficiency of information change, and meanwhile, this way also results in the situation that the staff understand the error to the change requirement of the user, which results in lower accuracy of information change, and in addition, the user cannot know in advance whether the information after change is better than the information before change, which reduces the experience of the user.
Disclosure of Invention
The invention provides an information processing method, an information processing device, a storage medium and computer equipment, which mainly aim to improve the efficiency and the accuracy of information change and improve the experience of a user.
According to a first aspect of the present invention, there is provided an information processing method comprising:
receiving an information processing instruction corresponding to information to be processed, wherein the information processing instruction carries an information identifier corresponding to the information to be processed;
based on the information identification, determining an information type to which the information to be processed belongs, and determining an information processing template corresponding to the information type;
acquiring change demand data corresponding to the information to be processed based on the information processing template;
inputting the change demand data into a preset value prediction model to perform conversion value prediction, and obtaining a change value prediction parameter corresponding to the information to be processed;
and changing the information to be processed based on the change value prediction parameter.
Preferably, before said determining an information processing template corresponding to said information type, the method further comprises:
determining each group of change demand data corresponding to different types of information;
storing the groups of change demand data into a demand database corresponding to the different types of information;
and constructing information processing templates corresponding to the different types of information, and building mapping relations between the different information processing templates and different requirement databases.
Preferably, the obtaining, based on the information processing template, change requirement data corresponding to the information to be processed includes:
determining a target demand database corresponding to the information processing template based on the mapping relation between different information processing templates and different demand databases;
and acquiring change demand data selected by a user from the target demand database aiming at the information to be processed.
Preferably, the obtaining the change requirement data selected by the user from the target requirement database for the information to be processed includes:
and acquiring the change starting time, the change ending time and the change type selected by the user from the target demand database aiming at the information to be processed.
Preferably, before the changing requirement data is input into a preset value prediction model to perform conversion value prediction, and the changing value prediction parameters corresponding to the information to be processed are obtained, the method further includes:
constructing at least one preset initial value prediction model;
collecting sample change demand data corresponding to sample information, and acquiring actual change value parameters corresponding to the sample change demand data;
training each preset initial value prediction model based on the sample change demand data and the corresponding actual change value parameters thereof to obtain training results;
and determining a preset value prediction model according to the training result.
Preferably, the training each preset initial value prediction model based on the sample change demand data and the corresponding actual change value parameter to obtain a training result includes:
inputting the sample change demand data into a corresponding preset initial value prediction model to perform conversion value prediction, so as to obtain a predicted change value parameter;
determining a backtracking value corresponding to each preset initial value prediction model based on an actual change value parameter and a predicted change value parameter corresponding to the same sample change demand data, wherein the backtracking value is used for representing a prediction error of the corresponding preset initial value prediction model;
the determining a preset value prediction model according to the training result comprises the following steps:
and filtering each preset initial value prediction model according to the backtracking value to obtain the preset value prediction model.
Preferably, the changing the information to be processed based on the change value prediction parameter includes:
judging whether the change value prediction parameter is larger than a preset threshold value or not;
if the information to be processed is larger than the preset threshold value, changing the information to be processed;
and if the information is smaller than or equal to the preset threshold, displaying the alarm information so that a user can determine whether to continue to change the information to be processed based on the alarm information.
According to a second aspect of the present invention, there is provided an information processing apparatus comprising:
the receiving unit is used for receiving an information processing instruction corresponding to the information to be processed, wherein the information processing instruction carries an information identifier corresponding to the information to be processed;
the determining unit is used for determining the information type of the information to be processed based on the information identifier and determining an information processing template corresponding to the information type;
the acquisition unit is used for acquiring the change demand data corresponding to the information to be processed based on the information processing template;
the prediction unit is used for inputting the change demand data into a preset value prediction model to perform conversion value prediction, so as to obtain a change value prediction parameter corresponding to the information to be processed;
and the changing unit is used for changing the information to be processed based on the change value prediction parameter.
According to a third aspect of the present invention, there is provided a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the above information processing method.
According to a fourth aspect of the present invention, there is provided a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the above information processing method when executing the program.
According to the information processing method, the device, the storage medium and the computer equipment provided by the invention, compared with the mode that a user orally submits a change requirement to a worker at present and the worker changes information according to the change requirement of the user, the information processing method and the device provided by the invention have the advantages that the information processing instruction corresponding to the information to be processed is received, wherein the information processing instruction carries the information identifier corresponding to the information to be processed; based on the information identification, determining an information type to which the information to be processed belongs, and determining an information processing template corresponding to the information type; acquiring change demand data corresponding to the information to be processed based on the information processing template; inputting the change demand data into a preset value prediction model to perform conversion value prediction, and obtaining a change value prediction parameter corresponding to the information to be processed; and changing the information to be processed based on the change value prediction parameter. Therefore, through determining the information processing template corresponding to the information to be processed, a user selects various change demand data in the information processing template, the communication time between the user and staff can be reduced, the information processing efficiency is improved, meanwhile, the situation that the staff understands errors to the change demand of the user can be avoided, the information changing accuracy is improved, then the conversion value of the change demand data is predicted by using a preset value prediction model, change value prediction parameters are obtained, whether the changed information can bring benefits to the user or not is judged according to the value change prediction parameters, the experience of the user can be improved, and loss of the user is avoided.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiments of the invention and together with the description serve to explain the invention and do not constitute a limitation on the invention. In the drawings:
FIG. 1 shows a flow chart of an information processing method provided by an embodiment of the invention;
FIG. 2 is a flowchart of another information processing method according to an embodiment of the present invention;
fig. 3 is a schematic diagram showing a structure of an information processing apparatus according to an embodiment of the present invention;
fig. 4 is a schematic diagram showing the structure of another information processing apparatus provided by an embodiment of the present invention;
fig. 5 shows a schematic physical structure of a computer device according to an embodiment of the present invention.
Detailed Description
The invention will be described in detail hereinafter with reference to the drawings in conjunction with embodiments. It should be noted that, in the case of no conflict, the embodiments and features in the embodiments may be combined with each other.
At present, a user verbally presents a change requirement to a staff, and the staff changes the information according to the change requirement of the user, so that the efficiency of information change is low and the accuracy of the change is low.
In order to solve the above problems, an embodiment of the present invention provides an information processing method, as shown in fig. 1, including:
101. and receiving an information processing instruction corresponding to the information to be processed, wherein the information processing instruction carries an information identifier corresponding to the information to be processed.
The message to be processed can be a lease plan, a loan repayment plan and the like in the financial field. The information identifier may be an icon identifier or a character identifier, so long as the message to be processed can be uniquely determined through the information identifier, the form of the information identifier is not particularly limited in the embodiment of the present invention.
Specifically, the information processing system is downloaded and installed in a corporate network, the information processing system main interface is displayed when the information processing system is opened by double clicking, the information type options in the information processing system main interface are clicked, the drop-down menus corresponding to different information types appear, the information types of the information to be processed are selected in the drop-down menus, at the moment, the information processing instruction corresponding to the information to be processed is triggered, the information processing instruction carries the information identification corresponding to the information to be processed, the exclusive information processing template corresponding to the information types is displayed based on the information identification, and then the change demand data corresponding to the information to be processed is determined based on the information processing template. Therefore, the change demand data is obtained through the information processing template, and the information to be processed is changed according to the change data, so that the information changing efficiency can be improved, and meanwhile, communication errors generated during artificial communication can be avoided, so that the information changing accuracy is improved.
102. Based on the information identification, determining the information type of the information to be processed, and determining an information processing template corresponding to the information type.
The information types comprise a rent type, a house credit type, a car credit type and the like; different information types correspond to different information processing templates.
For the embodiment of the invention, after the information processing instruction is received, the information type of the information to be processed is determined based on the information identifier carried in the information processing instruction, and because different information types correspond to different information processing templates, the information processing template corresponding to the information type can be determined based on the information type, the change demand data is selected in the information processing template, and finally the information is changed based on the change demand data, so that the change demand data is acquired through the information processing template, normalized change demand data can be acquired, the situation that a change person understands the change demand orally stated by a user in error can be avoided, and the change accuracy of the information is improved.
103. And acquiring change demand data corresponding to the information to be processed based on the information processing template.
The change demand data comprises change starting time, change ending time and change type, and the change type comprises exhibition period, slow renting and the like.
For the embodiment of the invention, various drop-down option menus corresponding to the change requirements exist in the information processing template, drop-down menu identifiers corresponding to the change requirement title items in the information processing template are clicked, drop-down menus corresponding to various change requirements corresponding to the information processing template can be displayed, change requirement data corresponding to the information to be processed is selected in the drop-down menus, for example, the user selects the change start time of 2022 to 11 months and the change end time of 2032 to 11 months in the drop-down menus corresponding to the change start time title items, and accordingly, the change requirement data corresponding to the information to be processed is obtained through the information processing template, the situation that the user carries out change requirement according to own language logic, and staff understand the change requirement for errors is avoided.
104. And inputting the change demand data into a preset value prediction model to perform conversion value prediction, and obtaining change value prediction parameters corresponding to the information to be processed.
The change value prediction parameter refers to the income amount which can be brought to the user after the information is changed.
For the embodiment of the invention, after the change demand data of the user is obtained, the change demand data is input into the pre-trained preset value prediction model to carry out conversion value prediction, after the prediction is finished, the preset value prediction model outputs the change value prediction parameters corresponding to the information to be processed, and finally, whether the information to be processed needs to be changed or not is judged according to the change value prediction parameters, so that the benefit brought by the change can be predicted for the user, and the user can judge whether the information to be processed is continuously changed or not according to the benefit condition, so that the experience of the user can be improved, and the loss brought by the change information of the user is avoided.
105. And changing the information to be processed based on the change value prediction parameter.
For the embodiment of the invention, after the change value prediction parameters corresponding to the information to be processed are obtained, the change value prediction parameters can be displayed to the user, the user can judge whether the information to be processed is continuously changed according to the change value prediction parameters, if the information to be processed is continuously changed, a determination button in the information processing template is clicked, if the information to be processed is not changed, a cancel button in the information processing template is clicked, meanwhile, if the change value prediction parameters are larger than a preset threshold, the information processing system can automatically change the information to be processed, and if the change value prediction parameters are smaller than or equal to the preset threshold, the user selects whether the information to be processed is changed, so that the economic loss of the user can be avoided by calculating the change value prediction parameters corresponding to the information to be processed and determining whether the information to be processed is changed according to the change value prediction parameters, and the experience of the user is improved.
According to the information processing method, compared with the mode that a user orally submits a change requirement to a worker at present and the worker changes information according to the change requirement of the user, the information processing method is characterized in that an information processing instruction corresponding to information to be processed is received, wherein the information processing instruction carries an information identifier corresponding to the information to be processed; based on the information identification, determining an information type to which the information to be processed belongs, and determining an information processing template corresponding to the information type; acquiring change demand data corresponding to the information to be processed based on the information processing template; inputting the change demand data into a preset value prediction model to perform conversion value prediction, and obtaining a change value prediction parameter corresponding to the information to be processed; and changing the information to be processed based on the change value prediction parameter. Therefore, through determining the information processing template corresponding to the information to be processed, a user selects various change demand data in the information processing template, the communication time between the user and staff can be reduced, the information processing efficiency is improved, meanwhile, the situation that the staff understands errors to the change demand of the user can be avoided, the information changing accuracy is improved, then the conversion value of the change demand data is predicted by using a preset value prediction model, change value prediction parameters are obtained, whether the changed information can bring benefits to the user or not is judged according to the value change prediction parameters, the experience of the user can be improved, and loss of the user is avoided.
Further, in order to better illustrate the above process of changing information, as a refinement and extension of the above embodiment, an embodiment of the present invention provides another information processing method, as shown in fig. 2, where the method includes:
201. and receiving an information processing instruction corresponding to the information to be processed, wherein the information processing instruction carries an information identifier corresponding to the information to be processed.
Specifically, the information processing system is opened, the information type is selected in a pull-down menu of the information processing system, namely, an information processing instruction is triggered, and the information processing instruction carries an information identifier corresponding to information to be processed.
202. Based on the information identification, determining the information type of the information to be processed, and determining an information processing template corresponding to the information type.
For the embodiment of the invention, after receiving the information processing instruction, the information type of the information to be processed can be determined based on the information identifier carried in the information processing instruction, and then in order to determine the information processing template corresponding to the information type, the information processing template needs to be constructed first, and based on the information processing instruction, the method comprises the following steps: determining each group of change demand data corresponding to different types of information; storing the groups of change demand data into a demand database corresponding to the different types of information; and constructing information processing templates corresponding to the different types of information, and building mapping relations between the different information processing templates and different requirement databases.
Specifically, because the same change requirement exists in the information of the same type, in order to avoid that the same change requirement data needs to be repeatedly filled in each time when the information to be processed is changed, firstly, a requirement database corresponding to the information of different types can be constructed in advance, the same change requirement data can be stored in the corresponding requirement database, meanwhile, an information processing template corresponding to the different information types is constructed again, and in order to select a target information processing template, the requirement database corresponding to the target information processing template is automatically linked, and the mapping relation between the different information processing templates and the different requirement databases needs to be established.
Further, after the information processing template is built and the mapping relation between the information processing template and the demand database is built, based on the information identifier corresponding to the information to be processed, checking which type of information the information to be processed belongs to, and determining the information processing template corresponding to the information type based on the information type corresponding to the information to be processed, namely determining the information processing template corresponding to the information to be processed, for example, the information identifier corresponding to the loan development period, so that the information processing template corresponding to the loan information can be determined by the information processing template corresponding to the loan information type.
203. And acquiring change demand data corresponding to the information to be processed based on the information processing template.
For the embodiment of the present invention, after determining the information processing template corresponding to the information to be processed, a plurality of transformation requirement data required for the information to be processed need to be obtained based on the information processing template, based on which step 203 specifically includes: determining a target demand database corresponding to the information processing template based on the mapping relation between different information processing templates and different demand databases; and acquiring change demand data selected by a user from the target demand database aiming at the information to be processed. .
Specifically, based on the mapping relation between different information processing templates and different requirement databases, determining a target and requirement database corresponding to the information processing templates, wherein each piece of change data required for changing the type of information is stored in the target and requirement database, a user clicks a drop-down menu identifier on a change requirement data title item corresponding to the information processing templates, each piece of change requirement data corresponding to the type of information is displayed in the drop-down menu, and the user selects a plurality of pieces of change requirement data required for the information to be processed from each piece of change requirement data, for example, the user can select information change starting time, information change ending time and information change type aiming at the information to be processed from the change requirement database.
204. At least one preset initial value prediction model is constructed.
The preset initial value prediction model is a numerical prediction model constructed based on a neural network. After each preset initial value prediction model is constructed, the preset value prediction model finally used for predicting the change value parameter is determined by training each preset initial value prediction model, so that the prediction accuracy of the preset value prediction model can be improved.
205. And collecting sample change demand data corresponding to the sample information, and acquiring actual change value parameters corresponding to the sample change demand data.
206. Based on the sample change demand data and the corresponding actual change value parameters, training each preset initial value prediction model to obtain training results.
207. And determining a preset value prediction model according to the training result.
Specifically, a plurality of preset initial value prediction models are pre-built, sample change requirement data of sample information are obtained, actual change value parameters corresponding to the sample change requirement data are obtained, the data are determined to be training sets, the training sets are divided into a plurality of groups of training data and a plurality of groups of test data according to the number of the models, the preset initial value prediction models corresponding to the plurality of groups of training data are trained to obtain each trained preset initial value prediction model, the corresponding preset initial value prediction models are tested by the test sets, finally, a preset value prediction model for changing value parameter prediction is determined according to test results, and based on the fact, the method for determining the preset value prediction model for changing value parameter prediction specifically according to the test results comprises the following steps: inputting the sample change demand data into a corresponding preset initial value prediction model to perform conversion value prediction, so as to obtain a predicted change value parameter; determining a backtracking value corresponding to each preset initial value prediction model based on an actual change value parameter and a predicted change value parameter corresponding to the same sample change demand data, wherein the backtracking value is used for representing a prediction error of the corresponding preset initial value prediction model; and filtering each preset initial value prediction model according to the backtracking value to obtain the preset value prediction model.
The backtracking value is an absolute difference value between an actual change value parameter and a predicted change value parameter corresponding to the same change demand data. Specifically, sample change demand data is input into a corresponding preset initial value prediction model to perform conversion value prediction, a predicted change value parameter is obtained, then an absolute difference value between an actual change value parameter corresponding to the same sample change demand data and the predicted change value parameter is determined, and the absolute difference value is determined to be a backtracking value corresponding to the corresponding preset initial value prediction model. Further, after determining the backtracking value corresponding to each preset initial value prediction model, determining the minimum backtracking value in each backtracking value, determining the preset initial value prediction model corresponding to the minimum backtracking value as a preset value prediction model, and predicting the change value parameter corresponding to the change demand data by using the established preset value prediction model.
208. And inputting the change demand data into a preset value prediction model to perform conversion value prediction, and obtaining change value prediction parameters corresponding to the information to be processed.
The preset value prediction model can be a multi-layer perceptron, and the multi-layer perceptron is a neural network model and comprises an input layer, a hidden layer and an output layer.
For the embodiment of the present invention, after determining the change requirement data corresponding to the information to be processed, the change requirement data may be input into a preset value prediction model to perform change value parameter prediction, based on which step 208 specifically includes: inputting the change demand data to the multi-layer perceptron, and extracting the characteristics output by the last full-connection layer in the multi-layer perceptron; and inputting the characteristics output by the last full-connection layer into a softmax layer in the multi-layer sensor to obtain the change value prediction parameters corresponding to the information to be processed.
Specifically, the change demand data is input to the hidden layer through the input layer of the multi-layer sensor model, and the result output through the hidden layer is:
f(W 1 x+b 1 )
wherein the output result is the feature that the change demand data is output after the full connection of the preset value prediction model, x is the change demand data, and w 1 B, as the weight of the hidden layer, is also the connection coefficient of the multi-layer sensor 1 For the bias factor of the hidden layer, the f-function may generally be a sigmoid function or a tanh function, as follows:
sigmoid(x)＝1/(1+e -x )
tanh(x)＝(e x -e -x )/(e 1 +e -x )
further, after the change demand data is input to the hidden layer through the input layer of the multi-layer perceptron model to obtain the result output by the hidden layer, the result is input to the output layer, namely the softmax layer of the multi-layer perceptron, and the change value parameter is predicted through the output layer, so that the obtained prediction result is as follows:
softmax(W 2 f(W 1 x+b 1 )+b 2 )
wherein W is 2 B is the weight coefficient of the output layer 2 And as the bias coefficient of the output layer, the output layer of the multi-layer perceptron model can output the change value prediction parameters corresponding to the information to be processed.
209. And changing the information to be processed based on the change value prediction parameter.
For the embodiment of the present invention, after predicting the change value prediction parameter corresponding to the information to be processed by using the preset value parameter prediction model, it is required to determine whether the change processing needs to be performed on the information to be processed according to the change value prediction parameter, based on this, step 209 specifically includes: judging whether the change value prediction parameter is larger than a preset threshold value or not; if the information to be processed is larger than the preset threshold value, changing the information to be processed; and if the information is smaller than or equal to the preset threshold, displaying the alarm information so that a user can determine whether to continue to change the information to be processed based on the alarm information.
The preset threshold is a value set according to the changing requirement, and the embodiment of the invention does not specifically limit the preset threshold.
Specifically, after the change value prediction parameter corresponding to the information to be processed is predicted, if the change value prediction parameter is greater than the preset threshold, the information to be processed is determined to be changed, and then benefits are brought to the user, so that the information to be processed can be directly changed according to the change demand data, if the change value prediction parameter is less than or equal to the preset threshold, the information to be processed is determined to be changed, and then loss is brought to the user, so that warning information needs to be displayed to the user, the warning information can comprise information such as loss amount, the user can select to cancel the change after seeing the warning information, the information to be processed is not changed after selecting but changing the table, and if the user selects to continue the change, the system continues to change the information to be processed according to the change demand data.
According to the other information processing method, compared with the mode that a user orally submits a change requirement to a worker at present and the worker changes information according to the change requirement of the user, the information processing method is characterized in that an information processing instruction corresponding to information to be processed is received, wherein the information processing instruction carries an information identifier corresponding to the information to be processed; based on the information identification, determining an information type to which the information to be processed belongs, and determining an information processing template corresponding to the information type; acquiring change demand data corresponding to the information to be processed based on the information processing template; inputting the change demand data into a preset value prediction model to perform conversion value prediction, and obtaining a change value prediction parameter corresponding to the information to be processed; and changing the information to be processed based on the change value prediction parameter. Therefore, through determining the information processing template corresponding to the information to be processed, a user selects various change demand data in the information processing template, the communication time between the user and staff can be reduced, the information processing efficiency is improved, meanwhile, the situation that the staff understands errors to the change demand of the user can be avoided, the information changing accuracy is improved, then the conversion value of the change demand data is predicted by using a preset value prediction model, change value prediction parameters are obtained, whether the changed information can bring benefits to the user or not is judged according to the value change prediction parameters, the experience of the user can be improved, and loss of the user is avoided.
Further, as a specific implementation of fig. 1, an embodiment of the present invention provides an information processing apparatus, as shown in fig. 3, including: a receiving unit 31, a determining unit 32, an acquiring unit 33, a predicting unit 34 and a changing unit 35.
The receiving unit 31 may be configured to receive an information processing instruction corresponding to the information to be processed, where the information processing instruction carries an information identifier corresponding to the information to be processed.
The determining unit 32 may be configured to determine, based on the information identifier, an information type to which the information to be processed belongs, and determine an information processing template corresponding to the information type.
The obtaining unit 33 may be configured to obtain, based on the information processing template, change requirement data corresponding to the information to be processed.
The prediction unit 34 may be configured to input the change demand data into a preset value prediction model to perform conversion value prediction, so as to obtain a change value prediction parameter corresponding to the information to be processed.
The changing unit 35 may be configured to change the information to be processed based on the change value prediction parameter.
In a specific application scenario, in order to establish a mapping relationship between different information processing templates and different requirement databases, as shown in fig. 4, the apparatus further includes: a storage unit 36 and a construction unit 37.
The determining unit 32 may be further configured to determine each set of change requirement data corresponding to different types of information.
The storage unit 36 may be configured to store the sets of change requirement data into a requirement database corresponding to the different types of information.
The construction unit 37 may be configured to construct information processing templates corresponding to the different types of information, and establish mapping relationships between the different information processing templates and different databases of requirements.
In a specific application scenario, in order to obtain the change requirement data corresponding to the information to be processed, the obtaining unit 33 includes a first determining module 331 and an obtaining module 332.
The first determining module 331 may be configured to determine a target requirement database corresponding to the information processing template based on a mapping relationship between different information processing templates and different requirement databases.
The obtaining module 332 may be configured to obtain change requirement data selected by a user from the target requirement database for the information to be processed.
In a specific application scenario, in order to obtain the change requirement data, the obtaining module 332 may be specifically configured to obtain a change start time, a change end time, and a change type selected by a user from the target requirement database for the information to be processed.
In a specific application scenario, in order to construct the preset value prediction model, the apparatus further includes: training unit 38.
The construction unit 37 may also be configured to construct at least one pre-set initial value prediction model.
The obtaining unit 33 may be further configured to collect sample change requirement data corresponding to sample information, and obtain an actual change value parameter corresponding to the sample change requirement data.
The training unit 38 may be configured to train each of the preset initial value prediction models based on the sample change requirement data and the corresponding actual change value parameter, so as to obtain a training result.
The determining unit 32 may be further configured to determine a preset value prediction model according to the training result.
In a specific application scenario, in order to train each preset initial value prediction model to obtain a training result, the training unit 38 includes a value prediction module 381 and a second determination module 382.
The value prediction module 381 may be configured to input the sample change requirement data into a corresponding preset initial value prediction model to perform conversion value prediction, so as to obtain a predicted change value parameter.
The second determining module 382 may be configured to determine a backtracking value corresponding to each preset initial value prediction model based on an actual change value parameter and a predicted change value parameter corresponding to the same sample change requirement data, where the backtracking value is used to characterize a prediction error of the corresponding preset initial value prediction model.
The determining unit 32 may be further configured to filter each of the preset initial value prediction models according to the backtracking value to obtain the preset value prediction model.
In a specific application scenario, in order to change the information to be processed, the changing unit 35 includes a determining module 351, a changing module 352, and a displaying module 353.
The determining module 351 may be configured to determine whether the change value prediction parameter is greater than a preset threshold.
The change module 352 may be configured to perform change processing on the information to be processed if the change module is greater than the preset threshold.
The display module 353 may be configured to display the alarm information if the alarm information is less than or equal to the preset threshold, so that the user determines whether to continue to change the information to be processed based on the alarm information.
It should be noted that, for other corresponding descriptions of each functional module related to the information processing apparatus provided in the embodiment of the present invention, reference may be made to corresponding descriptions of the method shown in fig. 1, which are not repeated herein.
Based on the above method as shown in fig. 1, correspondingly, the embodiment of the present invention further provides a computer readable storage medium, on which a computer program is stored, which when being executed by a processor, implements the following steps: receiving an information processing instruction corresponding to information to be processed, wherein the information processing instruction carries an information identifier corresponding to the information to be processed; based on the information identification, determining an information type to which the information to be processed belongs, and determining an information processing template corresponding to the information type; acquiring change demand data corresponding to the information to be processed based on the information processing template; inputting the change demand data into a preset value prediction model to perform conversion value prediction, and obtaining a change value prediction parameter corresponding to the information to be processed; and changing the information to be processed based on the change value prediction parameter.
Based on the embodiment of the method shown in fig. 1 and the device shown in fig. 3, the embodiment of the invention further provides a physical structure diagram of a computer device, as shown in fig. 5, where the computer device includes: a processor 41, a memory 42, and a computer program stored on the memory 42 and executable on the processor, wherein the memory 42 and the processor 41 are both arranged on a bus 43, the processor 41 performing the following steps when said program is executed: receiving an information processing instruction corresponding to information to be processed, wherein the information processing instruction carries an information identifier corresponding to the information to be processed; based on the information identification, determining an information type to which the information to be processed belongs, and determining an information processing template corresponding to the information type; acquiring change demand data corresponding to the information to be processed based on the information processing template; inputting the change demand data into a preset value prediction model to perform conversion value prediction, and obtaining a change value prediction parameter corresponding to the information to be processed; and changing the information to be processed based on the change value prediction parameter.
According to the technical scheme, the information processing instruction corresponding to the information to be processed is received, wherein the information processing instruction carries the information identifier corresponding to the information to be processed; based on the information identification, determining an information type to which the information to be processed belongs, and determining an information processing template corresponding to the information type; acquiring change demand data corresponding to the information to be processed based on the information processing template; inputting the change demand data into a preset value prediction model to perform conversion value prediction, and obtaining a change value prediction parameter corresponding to the information to be processed; and changing the information to be processed based on the change value prediction parameter. Therefore, through determining the information processing template corresponding to the information to be processed, a user selects various change demand data in the information processing template, the communication time between the user and staff can be reduced, the information processing efficiency is improved, meanwhile, the situation that the staff understands errors to the change demand of the user can be avoided, the information changing accuracy is improved, then the conversion value of the change demand data is predicted by using a preset value prediction model, change value prediction parameters are obtained, whether the changed information can bring benefits to the user or not is judged according to the value change prediction parameters, the experience of the user can be improved, and loss of the user is avoided.
It will be appreciated by those skilled in the art that the modules or steps of the invention described above may be implemented in a general purpose computing device, they may be concentrated on a single computing device, or distributed across a network of computing devices, they may alternatively be implemented in program code executable by computing devices, so that they may be stored in a memory device for execution by computing devices, and in some cases, the steps shown or described may be performed in a different order than that shown or described, or they may be separately fabricated into individual integrated circuit modules, or multiple modules or steps within them may be fabricated into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.
The above description is only of the preferred embodiments of the present invention and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (10)

1. An information processing method, characterized by comprising:
receiving an information processing instruction corresponding to information to be processed, wherein the information processing instruction carries an information identifier corresponding to the information to be processed;
based on the information identification, determining an information type to which the information to be processed belongs, and determining an information processing template corresponding to the information type;
acquiring change demand data corresponding to the information to be processed based on the information processing template;
inputting the change demand data into a preset value prediction model to perform conversion value prediction, and obtaining a change value prediction parameter corresponding to the information to be processed;
and changing the information to be processed based on the change value prediction parameter.
2. The method of claim 1, wherein prior to said determining an information processing template corresponding to said information type, the method further comprises:
determining each group of change demand data corresponding to different types of information;
storing the groups of change demand data into a demand database corresponding to the different types of information;
and constructing information processing templates corresponding to the different types of information, and building mapping relations between the different information processing templates and different requirement databases.
3. The method according to claim 1, wherein the obtaining, based on the information processing template, change requirement data corresponding to the information to be processed includes:
determining a target demand database corresponding to the information processing template based on the mapping relation between different information processing templates and different demand databases;
and acquiring change demand data selected by a user from the target demand database aiming at the information to be processed.
4. A method according to claim 3, wherein said obtaining change demand data selected by a user from said target demand database for said information to be processed comprises:
and acquiring the change starting time, the change ending time and the change type selected by the user from the target demand database aiming at the information to be processed.
5. The method according to claim 1, wherein before the changing requirement data is input into a preset value prediction model to perform conversion value prediction, and a changing value prediction parameter corresponding to the information to be processed is obtained, the method further includes:
constructing at least one preset initial value prediction model;
collecting sample change demand data corresponding to sample information, and acquiring actual change value parameters corresponding to the sample change demand data;
training each preset initial value prediction model based on the sample change demand data and the corresponding actual change value parameters thereof to obtain training results;
and determining a preset value prediction model according to the training result.
6. The method according to claim 1, wherein the training each of the preset initial value prediction models based on the sample change demand data and the corresponding actual change value parameter to obtain a training result includes:
inputting the sample change demand data into a corresponding preset initial value prediction model to perform conversion value prediction, so as to obtain a predicted change value parameter;
determining a backtracking value corresponding to each preset initial value prediction model based on an actual change value parameter and a predicted change value parameter corresponding to the same sample change demand data, wherein the backtracking value is used for representing a prediction error of the corresponding preset initial value prediction model;
the determining a preset value prediction model according to the training result comprises the following steps:
and filtering each preset initial value prediction model according to the backtracking value to obtain the preset value prediction model.
7. The method of claim 1, wherein the altering the information to be processed based on the altering value prediction parameter comprises:
judging whether the change value prediction parameter is larger than a preset threshold value or not;
if the information to be processed is larger than the preset threshold value, changing the information to be processed;
and if the information is smaller than or equal to the preset threshold, displaying the alarm information so that a user can determine whether to continue to change the information to be processed based on the alarm information.
8. An information processing apparatus, characterized by comprising:
the receiving unit is used for receiving an information processing instruction corresponding to the information to be processed, wherein the information processing instruction carries an information identifier corresponding to the information to be processed;
the determining unit is used for determining the information type of the information to be processed based on the information identifier and determining an information processing template corresponding to the information type;
the acquisition unit is used for acquiring the change demand data corresponding to the information to be processed based on the information processing template;
the prediction unit is used for inputting the change demand data into a preset value prediction model to perform conversion value prediction, so as to obtain a change value prediction parameter corresponding to the information to be processed;
and the changing unit is used for changing the information to be processed based on the change value prediction parameter.
9. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 7.
10. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the computer program when executed by the processor implements the steps of the method according to any one of claims 1 to 7.
CN202310377501.0A 2023-04-10 2023-04-10 Information processing method, information processing device, storage medium and computer equipment Pending CN116385126A (en)

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CN116385126A true CN116385126A (en) 2023-07-04

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