WO2020215681A1 - Procédé et appareil de génération d'informations d'indication, terminal et support de stockage - Google Patents

Procédé et appareil de génération d'informations d'indication, terminal et support de stockage Download PDF

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Publication number
WO2020215681A1
WO2020215681A1 PCT/CN2019/117602 CN2019117602W WO2020215681A1 WO 2020215681 A1 WO2020215681 A1 WO 2020215681A1 CN 2019117602 W CN2019117602 W CN 2019117602W WO 2020215681 A1 WO2020215681 A1 WO 2020215681A1
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Prior art keywords
information
target user
target
self
user
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PCT/CN2019/117602
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English (en)
Chinese (zh)
Inventor
王保军
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平安科技（深圳）有限公司
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Publication of WO2020215681A1 publication Critical patent/WO2020215681A1/fr

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/44—Arrangements for executing specific programs
    • G06F9/451—Execution arrangements for user interfaces
    • G06F9/453—Help systems
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/045—Combinations of networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION 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
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"

Definitions

  • This application relates to the field of data analysis technology, and in particular to a method, device, terminal and storage medium for generating indication information.
  • This application provides a method, device, terminal and storage medium for generating instruction information to solve the problem that the existing process guidance instructions are relatively fixed, and it is difficult to provide a flexible operation guidance according to the needs of users.
  • the intelligent guidance effect is poor, resulting in business Deal with inefficient issues.
  • This application provides a method for generating indication information, including the following steps:
  • the node data includes at least the relevance of each historical operation information, user information, to-do business information, and certificate information
  • An indication information generating device provided by this application includes:
  • the obtaining module is used to obtain multiple operation information performed by the target user on the business item information displayed on the interface of the self-service business terminal;
  • the generating module is used to obtain the historical operation information of the user in each self-service business terminal from the background server, and generate node data from the historical operation information;
  • the analysis module is used to use the node data to train the convolutional neural network model until it converges to obtain an indication model; wherein the node data includes the relevance of each historical operation information, user information, to-do business information, At least one of the credential information; input the operation information of the target user into the indication model, and analyze the operation information using the indication model to predict and analyze the next operation of the target user to determine the target The predicted probability of the user performing each next operation;
  • the selection module is configured to select the next operation with the largest predicted probability according to the predicted probability, obtain the target operation, and generate the instruction information of the target operation, and display the instruction information on the interface of the self-service terminal.
  • the present application provides a terminal including a memory and a processor.
  • the memory stores computer-readable instructions.
  • the processor is caused to perform the following steps:
  • the node data includes at least the relevance of each historical operation information, user information, to-do business information, and certificate information
  • the present application provides a storage medium on which computer-readable instructions are stored.
  • the computer-readable instructions are executed by a processor, the following steps are implemented:
  • the node data includes at least the relevance of each historical operation information, user information, to-do business information, and certificate information
  • the instruction information generating method, device, terminal and storage medium provided in this application obtain multiple operation information performed by the target user on the business item information displayed on the interface of the self-service terminal; and obtain each self-service terminal from the back-end server According to the historical operation information of the user in the historical operation information, node data is generated from the historical operation information; then the next step operation of the target user is predicted and analyzed according to the node data and operation information, and the next operation of the target user is determined Finally, the next operation with the largest predicted probability is selected according to the predicted probability, and the target operation is obtained, and the instruction information of the target operation is generated, and the instruction information is displayed on the interface of the self-service terminal.
  • This application predicts and analyzes the next operation of the target user based on the operation information of the target user, and displays the instruction information of the next operation, so that the target user can perform subsequent operations according to the instruction information, thereby providing a flexible operation guidance and realizing intelligent guidance. Improve the guidance effect of self-service business terminals, thereby improving business processing efficiency.
  • Fig. 1 is an implementation environment diagram of a method for generating indication information provided in an embodiment of this application
  • FIG. 2 is a flowchart of an embodiment of a method for generating indication information of an application
  • Fig. 3 is a block diagram of an embodiment of an application indication information generating device
  • Fig. 4 is a block diagram of the internal structure of a terminal in an embodiment of the application.
  • FIG. 1 is a diagram of an implementation environment of a method for generating instruction information provided in an embodiment.
  • the implementation environment includes a server 110 and a self-service business terminal 120.
  • the self-service terminal 120 is connected to the server 110 through the network.
  • the self-service terminal 120 is equipped with a client or browser.
  • the user can self-service related services through the self-service terminal 120, such as processing credit card applications and lending on a bank self-service terminal.
  • instruction information will be displayed on the interface of the self-service business terminal 120 to guide users to process and improve business processing efficiency.
  • the aforementioned network may include the Internet, 2G/3G/4G, wifi, and so on.
  • the server 110 may be an independent physical server or terminal, or a server cluster composed of multiple physical servers, and may be a cloud server that provides basic cloud computing services such as cloud servers, cloud databases, cloud storage, and CDN.
  • This application provides a method for generating instruction information, which can be applied to banks, hospitals, insurance, securities,
  • the guiding concept is introduced into the self-service business terminals to provide a flexible operation guidance according to the needs of users, improve the effect of intelligent guidance, and thereby improve the efficiency of business processing.
  • the indication information generation method includes the following steps:
  • the total business item information when the user uses the self-service terminal, the total business item information will be displayed on the homepage of the self-service terminal.
  • the user selects the corresponding total business item information according to the business to be handled, and the interface will display the total business item information Other business item information under the branch.
  • multiple operation information of the target user will be generated, such as the selected business item information, the relevance of each business item information, and the information entered on each business item information Wait.
  • the business item information may be a self-service business type displayed on a self-service business terminal. Taking a self-service banking terminal as an example, the business item information may include "bank card service", “transfer”, “lending”, “financial Services” and other banking business item information.
  • the operation information is user operation data generated when operating the business item information.
  • This embodiment can collect the historical operation information of users in each self-service business terminal, filter the historical operation information, remove invalid information, to generate node data and save it in the database, so as to maintain single-node data and facilitate the user’s history Save and recall operation information.
  • the deep learning model can be used to perform next-step operation predictive analysis on the historical operation information of each user in the node data and the current multiple operation information of the target user to obtain the predicted probability of the target user to perform each next operation. For example, when the target user selects the business item information of the transfer, the next operation performed may be the input of the payee account.
  • the next operation with the largest predicted probability is selected to obtain the target operation of the target user, and the instruction information for the target operation is generated.
  • the instruction information is displayed on the interface of the self-service terminal to prompt the target user of the next operation that may be required to improve the guidance effect of the self-service terminal.
  • the instruction information can be displayed in the form of text or icon, and when displayed, it can be displayed at the business item information corresponding to the next operation.
  • the instruction information generation method provided in this application obtains multiple operation information performed by the target user on the business item information displayed on the interface of the self-service business terminal; and obtains the historical operation information of the user in each self-service business terminal from the back-end server , Generate node data from the historical operation information; then perform predictive analysis on the target user’s next operation based on the node data and operation information, and determine the predicted probability of the target user to perform each next operation; The predicted probability selects the next operation with the largest predicted probability, obtains the target operation, generates the instruction information of the target operation, and displays the instruction information on the interface of the self-service terminal.
  • This application predicts and analyzes the next operation of the target user based on the operation information of the target user, and displays the instruction information of the next operation, so that the target user can perform subsequent operations according to the instruction information, thereby providing a flexible operation guidance and realizing intelligent guidance. Improve the guidance effect of self-service business terminals, thereby improving business processing efficiency.
  • step S23 the step of predicting and analyzing the next operation of the target user according to the node data and operation information may specifically include:
  • A1 Use the node data to train the convolutional neural network model until it converges to obtain an indication model; wherein, the node data includes the relevance of each historical operation information, user information, to-do business information, and certificate information. At least one of
  • the deep learning model in this embodiment is a convolutional neural network model.
  • the node data can be used to train the convolutional neural network model until convergence , That is, when the training result meets the preset requirements, a qualified instruction model is obtained; in this training process, the more the amount of node data, the better the training effect.
  • A2 Input the operation information of the target user into the instruction model, and use the instruction model to predict and analyze the next operation of the target user.
  • the operation information of the target user is input into a trained instruction model, and the instruction model is used to predict and analyze the next operation of the target user, thereby automatically obtaining the next operation that the target user may perform.
  • step A2 the step of using the indicator model to predict and analyze the next operation of the target user may specifically include:
  • A21 Extract the operation content and operation time from each operation information of the target user
  • A22 Analyze the correlation between the operation information according to the operation time and operation content
  • the correlation between various operation information can be analyzed according to the sequence of the operation time and the operation content.
  • bank card processing when the target user clicks "bank card service”, “card application”, “information filling”, “card activation” and other business item information on the self-service bank terminal, they can click according to the time of clicking
  • the sequence and the content of each operation are related to the corresponding operation information of "bank card service", “card application”, “information filling”, and “card activation”.
  • the operation of "bank card service” needs to be in “card application” Before “application”, “fill in information” should be operated after “application for card”.
  • A23 Generate the operation flow of the target user according to the relevance, and query the historical operation flow matching the operation flow from the database according to the operation flow to obtain the target operation flow; wherein, all users are stored in the database Historical operation process;
  • the operation flow of the target user is generated according to the relevance of the operation information, and the operation flow is matched with the historical operation flow of each user in the database, and the matching historical operation flow is filtered out to obtain multiple target operation flows.
  • the historical operation process is the entire operation process performed by the user to successfully handle the business. Specifically, when the user clicks on the four operations of "bank card service”, “card application”, “information filling”, and “card activation”, the operation process of the target user is generated: bank card service-card application Application-information filling-card activation, filter the historical operation process that exactly matches the target user's operation process, that is, the operation content and operation time are also completely matched.
  • A24 Analyze the predicted probability of the target user performing each next operation according to the target operation process.
  • the historical operation flow that completely matches the target user's operation flow is obtained.
  • the next operation that the target user may need to perform is obtained according to the target operation flow, and the predicted probability of the target user performing each next operation is calculated .
  • the A24 step may specifically include:
  • A241. Obtain the current operation of the target user from the operation information of the target user;
  • A242. Predict the next operation of the target user from each target operation process according to the current operation
  • A245. Calculate the proportion of the next operation of each target operation process in all next operations according to the classified statistical results, and obtain the predicted probability of the target user to perform each next operation.
  • the target user when the target user performs the four operations of "bank card service”, “card application”, “information filling”, and “card activation”, the target user's current operation is "open Card activation", according to the operation of "card activation”, query the next operation corresponding to the operation from each target operation process, so as to predict the next operation of the target user, and then classify and count the next operation of each target operation process , Divide the same next step into the same category, and count the number of next steps in the same category, and calculate the proportion of the next step of each target operation process to all next steps based on the classification statistics, and get the target user’s execution of each The predicted probability of the next operation.
  • step A1 after training the convolutional neural network model using the node data, the method may further include:
  • each base layer of the convolutional neural network model includes several nodes, the nodes between the base layer and the base layer are in a fully connected state, and the connection between the nodes usually has a weight parameter.
  • the weight parameter between nodes is a parameter value set at will.
  • the optimal weight parameter of the connection between the two generates a convolutional neural network model corresponding to the optimal weight parameter, and uses it as an indicator model.
  • the indication information generating method may further include:
  • the historical data of the target user is obtained from the historical database, and the historical data can be saved when the target user has already processed other services on the self-service business terminal
  • the data may include user name, gender, contact information, hometown, home address, bank card number and other information.
  • the corresponding information point can be extracted from the historical database according to the information to be filled in the task item to be filled, and the information point can be filled in the corresponding task item to be filled, thereby further improving the business processing efficiency.
  • the gender information point is extracted from the target user’s historical data, and the Information points are automatically filled in the task to be filled in gender, thereby further improving the efficiency of business processing.
  • the indication information generating method further includes:
  • the target user when the target user is using the self-service terminal for business, when the interface currently displayed by the self-service terminal exits abnormally, such as when the self-service terminal has a black screen or the current interface contains a task item to be filled out and exits, then Automatically save the business information entered by the user on the interface before the user exits abnormally, and collect the face image of the target user by starting the camera to obtain the target face image and save it in the database.
  • the filled service information may include information such as user name, gender, contact information, and address.
  • the face image is compared with the target face image pre-stored in the database, and after the comparison is passed, the filled business information of the target user is obtained and displayed on the interface.
  • the face image of the target user is collected by restarting the camera of the self-service terminal, and the face image is combined with the target face image pre-stored in the database.
  • the filled-in business information before the abnormal exit of the target user is obtained, and the filled-in business information is displayed on the interface, so as to prevent the user from re-entering and improve the efficiency of business processing.
  • an embodiment of the present application also provides an indication information generation device.
  • it includes an acquisition module 31, a generation module 32, an analysis module 33, and a selection module 34. among them,
  • the obtaining module 31 is configured to obtain multiple operation information performed by the target user on the business item information displayed on the interface of the self-service business terminal;
  • the total business item information when the user uses the self-service terminal, the total business item information will be displayed on the homepage of the self-service terminal.
  • the user selects the corresponding total business item information according to the business to be handled, and the interface will display the total business item information Other business item information under the branch.
  • multiple operation information of the target user will be generated, such as the selected business item information, the relevance of each business item information, and the information entered on each business item information Wait.
  • the business item information may be a self-service business type displayed on a self-service business terminal. Taking a self-service banking terminal as an example, the business item information may include "bank card service", “transfer”, “lending”, “financial Services” and other banking business item information.
  • the operation information is user operation data generated when operating the business item information.
  • the generating module 32 is configured to obtain historical operation information of users in each self-service business terminal from the back-end server, and generate node data from the historical operation information;
  • This embodiment can collect the historical operation information of users in each self-service business terminal, filter the historical operation information, remove invalid information, to generate node data and save it in the database, so as to maintain single-node data and facilitate the user’s history Save and recall operation information.
  • the analysis module 33 is configured to perform predictive analysis on the next operation of the target user according to the node data and operation information, and determine the predicted probability of the target user to perform each next operation;
  • the deep learning model can be used to perform next-step operation predictive analysis on the historical operation information of each user in the node data and the current multiple operation information of the target user to obtain the predicted probability of the target user to perform each next operation. For example, when the target user selects the business item information of the transfer, the next operation performed may be the input of the payee account.
  • the selection module 34 is configured to select the next operation with the largest predicted probability according to the predicted probability, obtain the target operation, and generate instruction information of the target operation, and display the instruction information on the interface of the self-service terminal.
  • the next operation with the largest predicted probability is selected to obtain the target operation of the target user, and the instruction information for the target operation is generated.
  • the instruction information is displayed on the interface of the self-service terminal to prompt the target user of the next operation that may be required to improve the guidance effect of the self-service terminal.
  • the instruction information can be displayed in the form of text or icon, and when displayed, it can be displayed at the business item information corresponding to the next operation.
  • the instruction information generating device obtaineds multiple operation information performed by the target user on the business item information displayed on the interface of the self-service business terminal; and obtains the historical operation information of the user in each self-service business terminal from the background server , Generate node data from the historical operation information; then perform predictive analysis on the target user’s next operation based on the node data and operation information, and determine the predicted probability of the target user to perform each next operation; The predicted probability selects the next operation with the largest predicted probability, obtains the target operation, generates the instruction information of the target operation, and displays the instruction information on the interface of the self-service terminal.
  • This application predicts and analyzes the next operation of the target user based on the operation information of the target user, and displays the instruction information of the next operation, so that the target user can perform subsequent operations according to the instruction information, thereby providing a flexible operation guidance and realizing intelligent guidance. Improve the guidance effect of self-service business terminals, thereby improving business processing efficiency.
  • the analysis module 33 is further configured to:
  • the node data includes at least the relevance of each historical operation information, user information, to-do business information, and certificate information
  • the operation information of the target user is input into the instruction model, the operation information is analyzed by the instruction model, and the next operation of the target user is used for predictive analysis.
  • the analysis module 33 is further configured to:
  • the analysis module 33 is further configured to:
  • the analysis module 33 is further configured to:
  • the convolutional neural network model is used as an indicator model.
  • the instruction information generating device further includes:
  • the extraction module is used to extract historical data of the target user from the database when the interface displayed by the self-service business terminal contains task items to be filled;
  • the filling module is used to extract information points from the historical data of the target user, and fill the information points into the corresponding task items to be filled.
  • the instruction information generating device further includes:
  • the saving module is used to save the filled business information entered by the user on the current interface when it is detected that the target user exits the interface displayed by the self-service terminal abnormally;
  • the collection module is used to start the camera of the self-service terminal to collect the face image of the target user when it is detected that the self-service terminal redisplays the interface before exit;
  • the comparison module is used to compare the face image with the target face image pre-stored in the database, and after the comparison is passed, obtain the filled business information of the target user and display it on the interface.
  • a terminal provided by the present application includes a memory and a processor.
  • the memory stores computer-readable instructions.
  • the processor executes the instructions as described above. The steps of the information generation method.
  • the terminal is a computer device, as shown in FIG. 4.
  • the computer equipment described in this embodiment may be equipment such as servers, personal computers, and network equipment.
  • the computer equipment includes a processor 402, a memory 403, an input unit 404, a display unit 405 and other devices.
  • the memory 403 may be used to store a computer program 401 (or referred to as computer-readable instructions) and various functional modules, and the processor 402 runs the computer program 401 stored in the memory 403 to execute various functional applications and data processing of the device.
  • the memory may be internal memory or external memory, or include both internal memory and external memory.
  • the internal memory may include read only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), flash memory, or random access memory.
  • ROM read only memory
  • PROM programmable ROM
  • EPROM electrically programmable ROM
  • EEPROM electrically erasable programmable ROM
  • flash memory or random access memory.
  • External storage can include hard disks, floppy disks, ZIP disks, U disks, tapes, etc.
  • the memory disclosed in this application includes but is not limited to these types of memory.
  • the memory disclosed in this application is only an example and not a limitation.
  • the input unit 404 is used for receiving input of signals and receiving keywords input by the user.
  • the input unit 404 may include a touch panel and other input devices.
  • the touch panel can collect the user's touch operations on or near it (for example, the user uses any suitable objects or accessories such as fingers, stylus, etc., to operate on the touch panel or near the touch panel), and according to the preset
  • the program drives the corresponding connection device; other input devices may include, but are not limited to, one or more of a physical keyboard, function keys (such as playback control buttons, switch buttons, etc.), trackball, mouse, and joystick.
  • the display unit 405 can be used to display information input by the user or information provided to the user and various menus of the computer device.
  • the display unit 405 can take the form of a liquid crystal display, an organic light emitting diode, or the like.
  • the processor 402 is the control center of the computer equipment. It uses various interfaces and lines to connect the various parts of the entire computer. It executes by running or executing the software programs and/or modules stored in the memory 402 and calling the data stored in the memory. Various functions and processing data.
  • the computer device includes: one or more processors 402, a memory 403, and one or more computer programs 401, wherein the one or more computer programs 401 are stored in the memory 403 and configured to Executed by the one or more processors 402, the one or more computer programs 401 are configured to execute the instruction information generation method described in the above embodiments.
  • this application also proposes a storage medium storing computer-readable instructions; the storage medium may be a non-volatile readable storage medium; the computer-readable instructions are executed by one or more processors At this time, one or more processors are caused to execute the foregoing instruction information generation method.
  • the storage medium may be ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, optical data storage device, etc.
  • the aforementioned storage medium may be a magnetic disk, an optical disk, a read-only storage memory (Read-Only Non-volatile storage media such as Memory, ROM, or Random Access Memory (RAM), etc.
  • the instruction information generating method, device, terminal and storage medium provided in this application obtain multiple operation information performed by the target user on the business item information displayed on the interface of the self-service terminal; and obtain each self-service terminal from the back-end server According to the historical operation information of the user in the historical operation information, node data is generated from the historical operation information; then the next step operation of the target user is predicted and analyzed according to the node data and operation information, and the next operation of the target user is determined Finally, the next operation with the largest predicted probability is selected according to the predicted probability, and the target operation is obtained, and the instruction information of the target operation is generated, and the instruction information is displayed on the interface of the self-service terminal.
  • This application predicts and analyzes the next operation of the target user based on the operation information of the target user, and displays the instruction information of the next operation, so that the target user can perform subsequent operations according to the instruction information, thereby providing a flexible operation guidance and realizing intelligent guidance. Improve the guidance effect of self-service business terminals, thereby improving business processing efficiency.

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Abstract

L'invention concerne un procédé et un appareil de génération d'informations d'indication, un terminal et un support de stockage. Le procédé de génération d'informations d'indication consiste à : obtenir une pluralité d'éléments d'informations d'opération exécutées par un utilisateur cible pour des informations de projet de service affichées sur des interfaces de terminaux en libre-service (S21) ; obtenir des informations d'opération historiques d'utilisateurs dans les terminaux en libre-service auprès d'un serveur dorsal, et générer des données de nœud à partir de celles-ci (S22) ; réaliser, en fonction des données de nœud et des informations d'opération, une analyse prédictive sur des opérations suivantes de l'utilisateur cible, et déterminer la probabilité prédictive que l'utilisateur cible exécute les opérations suivantes (S23) ; et sélectionner l'opération suivante ayant la probabilité prédictive maximale en fonction de la probabilité prédictive pour obtenir une opération cible, générer des informations d'indication de l'opération cible, et les afficher sur l'interface du terminal en libre-service (S24). La solution procure un guide d'opération flexible pour obtenir un guide intelligent, améliorant ainsi l'effet d'indication du terminal en libre-service.
PCT/CN2019/117602 2019-04-26 2019-11-12 Procédé et appareil de génération d'informations d'indication, terminal et support de stockage WO2020215681A1 (fr)

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CN112799762A (zh) * 2021-01-27 2021-05-14 北京嘀嘀无限科技发展有限公司 信息展示方法、装置、电子设备、计算机可读存储介质
CN113553159A (zh) * 2021-07-29 2021-10-26 共达地创新技术(深圳)有限公司 基于可视化的模型调度方法、设备和存储介质
CN113591443A (zh) * 2021-08-03 2021-11-02 中国银行股份有限公司 表单填单方法、装置、服务器、介质及产品
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