CN112506406B

CN112506406B - Target control method and system based on user habit self-learning control

Info

Publication number: CN112506406B
Application number: CN202011396955.5A
Authority: CN
Inventors: 李国臣; 徐惠勇; 赵轩; 邢廷炎; 张强; 路林千
Original assignee: China University of Geosciences Beijing
Current assignee: China University of Geosciences Beijing
Priority date: 2020-12-03
Filing date: 2020-12-03
Publication date: 2021-08-17
Anticipated expiration: 2040-12-03
Also published as: CN112506406A

Abstract

The invention provides a target control method and a target control system based on user habit self-learning control. The user attribute database stores user names and user grades of authorized operation users, and the local user habit database stores first target operation data; the global user habit database stores second target operation data; the target recommending module determines at least one recommended sub-object based on the first target operation data and/or the second target operation data; the target feedback module is used for receiving the current user feedback parameters. The invention also discloses a system implementation method and a computer readable storage medium for implementing the method. The technical scheme of the invention can recommend the corresponding sub-object presentation by combining the use habits of the local user and the global user, thereby ensuring the accuracy of self-learning control.

Description

Target control method and system based on user habit self-learning control

Technical Field

The invention belongs to the technical field of automatic learning and control, and particularly relates to a target control system and method based on user habit self-learning control and a computer readable storage medium for realizing the method.

Background

With the rapid development of science and technology, the era of electronic informatization has come, the living and working modes of people have changed day by day, various intelligent devices and intelligent applications emerge endlessly, and great convenience is brought to the living and working of people. The continuous development of various computer technologies, database technologies and network technologies also provides the possibility of developing intelligent systems with strong functionality, high speed, low cost and better quality.

In the aspect of intelligent equipment, smart homes have gone into thousands of households. The existing household environment control equipment comprises an air conditioning system, a floor heating system, a fresh air system, an air purifier system and the like, usually, the household environment control equipment is controlled locally or remotely through a control panel, a mobile terminal or an intelligent household system, if the household environment control equipment is opened or closed, parameters are adjusted and the like, the intelligent household equipment can realize information exchange through a wireless communication technology, even intelligent equipment capable of learning autonomously, convenient and effective service can be provided for a user, and the labor amount of the user is reduced. The smart home devices may include smart sockets, smart door locks, smart lights, smart fans, smart air conditioners, smart curtains, and the like.

In the aspect of intelligent application, multifunctional interactive Applications (APP), particularly various life type APPs realized by using a mobile terminal human-computer interface, can realize the control of a specific object according to the habit or target operation of a user through the interaction with the surrounding environment; or, based on the user's mind, as many services as possible are provided. For example, the smart home control APP can realize remote control of different smart devices, and the integrated life service APP can provide a wide range of life exploration entrances, such as nearby banks, takeouts, movie theaters, navigation, current news hotspots, and the like.

In this regard, the chinese patent application cn201910245789.x provides a method, related apparatus, and system for displaying a device control page. In the method, the electronic device can display the control page of the intelligent household device before the user and the intelligent household device successfully establish the dependency relationship, so that the user can be familiar with the control method of the intelligent household device in advance through the control page to know various functions of the intelligent household device. Therefore, the habit of the user is better met, and the user experience is also improved.

Further, chinese patent application CN202010452013.8 discloses a business operation method, apparatus, computer device and storage medium. The method comprises the following steps: receiving a service operation request in a page, wherein the service operation request carries a user identifier; searching an operation model corresponding to the user identifier, wherein the operation model is obtained by performing data modeling according to historical business operation data of the user; acquiring an active cursor corresponding to a current business operation process; extracting guide pages related to the movable cursor and operation duration corresponding to each guide page from the operation model; and continuously displaying a guide page in a preset area in the page within the time corresponding to the operation duration, wherein the guide page is used for guiding the user to execute the business operation at the position of the active cursor. The method can effectively improve the efficiency of business operation.

However, as the functions of intelligent devices and intelligent Applications (APPs) are more and more, and the types of the applications are more and more complete, how to get familiar with the functions of the applications comprehensively and accurately, and how to perform autonomous operation gradually becomes a prominent problem. Especially for new users who never contact intelligent devices and intelligent Applications (APP), a great deal of time is needed to understand the functions of the new users; some elderly users often do not have the right to do with the techniques and operations of the latest devices.

Therefore, there is a need for a technique capable of autonomous learning and automatic target control oriented to different user habits.

Disclosure of Invention

In order to solve the technical problems, the invention provides a target control method and a system based on user habit self-learning control. The user attribute database stores user names and user grades of authorized operation users, and the local user habit database stores first target operation data; the global user habit database stores second target operation data; the target recommending module determines at least one recommended sub-object based on the first target operation data and/or the second target operation data; the target feedback module is used for receiving the current user feedback parameters. The invention also discloses a system implementation method and a computer readable storage medium for implementing the method.

The technical scheme of the invention can recommend the corresponding sub-object presentation by combining the use habits of the local user and the global user, thereby ensuring the accuracy of self-learning control.

In a first aspect of the invention, a target control system based on user habit self-learning control is provided, the target control system comprising a local user habit database, a global user habit database, a user attribute acquisition module, a target recommendation module and a target feedback module,

the user attribute acquisition module is used for acquiring user attribute data of a user operation target object;

the local user habit database is used for storing first target operation data which are generated when all users corresponding to the user attribute data operate the target object within a first preset time period;

the global user habit database is used for storing second target operation data generated when all users operate the target object within a second preset time period;

the target object comprises a plurality of sub-objects;

the target recommending module determines at least one recommended sub-object from a plurality of sub-objects of the target object based on the first target operation data and/or the second target operation data;

and the target feedback module is used for receiving the feedback parameters of the current user to the recommended sub-object determined by the target recommendation module.

The target control system further comprises a user attribute database;

the user attribute database is used for storing the user name and the user grade of the authorized operation user of the target object.

The system also includes a sub-object preloading module;

and the sub-object preloading module preloads the recommended sub-object determined by the target recommending module every preset period based on second target operation data or first target operation data generated when the target object is operated by a user.

In a second aspect of the invention, a target control method based on user habit self learning control is provided for controlling a target object comprising a plurality of different sub objects.

In a specific implementation, the method comprises the steps of:

s100: acquiring a user name used when the current user operates the target object;

s200: judging whether the user name can be found in a user attribute database;

if yes, obtaining a user grade corresponding to the user name;

otherwise, prompting that the user name is wrong, and returning to the step S100;

s300: judging whether first target operation data generated when other users corresponding to the user grades operate the target object can be found in a local user habit database;

if yes, go to step S500;

if not, the step S400 is entered;

s400: searching second target operation data in a global user habit database, wherein the second target operation data corresponds to the current position and/or the current time of a current user;

s500: taking the first target operation data and/or the second target operation data as recommendation basic data;

s600: determining at least one recommended sub-object from a plurality of sub-objects of the target object based on the recommendation basic data;

s700: prompting the current user to input a user password corresponding to the user name;

s800: judging whether the user password is correct or not;

if yes, go to step S900;

if not, prompting that the password is wrong, and returning to the step S800;

s900: and displaying the recommended sub-object.

The method of the invention can be realized in the form of computer program instructions on the remote terminal equipment after the collected data and the execution processing are communicated with the centralized control platform based on the data transmission middleware. Thus, in a third aspect of the present invention, a computer-readable storage medium is provided, having stored thereon computer-executable program instructions for execution by a processor for carrying out the aforementioned method steps S100-S900.

The technical scheme of the invention includes that first target operation data of a current interface of a target object, which has the same level as that of a current user, is searched by utilizing a local user habit database, and at least one target sub-object presentation is recommended to the user for next display or interface switching; if the target object cannot be found, the global user habit database is used for searching for second target operation data, corresponding to the current user attributes (including current time, current position and the like) of the current user, of the current interface of the target object, and at least one target sub-object presentation is recommended to the user for next display or interface switching, so that the self-learning target control at any time can be close to the requirements of the current user.

Further advantages of the invention will be apparent in the detailed description section in conjunction with the drawings attached hereto.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.

FIG. 1 is an overall schematic diagram of a target control system based on user habit self-learning control according to an embodiment of the present invention

FIG. 2 is a schematic diagram of an interface flow for implementing target control by the system of FIG. 1

FIG. 3 is a flow chart illustrating a method for implementing target control based on the system of FIG. 1

FIG. 4 is a more general operational schematic diagram of the target object control implemented by the system of FIG. 1

Detailed Description

The invention is further described with reference to the following drawings and detailed description.

Referring to fig. 1, an overall schematic diagram of a target control system based on user habit self-learning control according to an embodiment of the present invention is shown.

In fig. 1, the target control system includes a user attribute database, a local user habit database, a global user habit database, a user attribute obtaining module, a target recommending module, and a target feedback module.

The target object includes a plurality of sub-objects.

As a non-limiting example, the target object may be a multifunctional APP, or may also be an automated office system software, or may also be a terminal device with a human-computer interaction interface.

In the above target object, there may be a plurality of different interfaces, which are presented sequentially in different processes or according to the selection of the user, and on each different interface, there are different operation sub-objects, such as menus, buttons, options, etc., as sub-objects of the target object.

the user attribute data comprises one or a combination of the following:

and the user name, the user level, the current position, the current time and the current operation data are used when the user operates the target object.

as an example, the user attribute data is a user rating, and thus, the local user habit database stores first target operation data generated when all users corresponding to the user rating operate the target object within the last 10 days;

as a more preferable example, the global user habit database class stores second target operation data, which is generated when the target object is operated within the past 7 days, corresponding to users at different locations and at different times.

Obviously, the priority of the first target operation data is relatively higher than that of the first target operation data, and therefore, in the present embodiment, the length of the first predetermined time period is longer than that of the second predetermined time period.

Preferably, the local user habit database stores first target operation data of the users of different grades in a first predetermined time period, and the first target operation data has different weights varying with time.

For example, among the login operation data in the first predetermined time period, the login operation data closer to the current time node is weighted more heavily; conversely, the smaller the weight.

Preferably, the second target operation data or the first target operation data generated when the target object is operated includes:

and after the user operates the current sub-object, the next sub-object loaded by the target object.

In order to further improve the display efficiency of the system, the system further comprises a sub-object preloading module;

On the basis of fig. 1, referring to fig. 2, take the multifunctional APP with the target object being the terminal device with the human-computer interaction interface as an example.

In fig. 2, the multifunctional APP includes a login interface.

The login interface provides at least two input boxes for inputting a user ID (also called a user name) and a user password.

In this embodiment, a process (thread) where the user name input box is located is connected to the user attribute acquisition module through a unidirectional data pipe (data-pipeline), and after the user name is input, the user ID is read from the user name input box and is searched in the user attribute database.

And if the user ID is not found in the user attribute database, returning an error prompt.

The method is different from the prior art that correct or incorrect response can be made only after the user name and the user password are input.

If the user ID is found, obtaining a user grade corresponding to the user ID, then entering a local user habit database, and searching first target operation data of a user corresponding to the user grade in the local user habit database;

if not found (e.g., a brand-new APP or a brand-new level of users), then go to the global user habit database;

if the target object is found, the target recommending module determines at least one recommended sub-object from a plurality of sub-objects of the target object based on the first target operation data;

next, the sub-object preloading module preloads the recommended sub-objects determined by the target recommending module every other preset period;

then prompting to input a password; and displaying the recommended sub-object after the user inputs the password corresponding to the user ID.

The above process can be further embodied as steps S100 to S900 of the method described in fig. 3, and each step is specifically implemented as follows:

s200: judging whether the user name can be found in a user attribute database;

if yes, obtaining a user grade corresponding to the user name;

if yes, go to step S500;

if not, the step S400 is entered;

s800: judging whether the user password is correct or not;

if yes, go to step S900;

if not, prompting that the password is wrong, and returning to the step S800;

s900: and displaying the recommended sub-object.

In the above embodiment, the second target operation data is user habit data generated when all users operate the target object, and the user habit data includes operation time, operation position, and specific operation parameters.

The target object is a multifunctional application, the multifunctional application comprises a plurality of different pages, and each different page comprises a plurality of the sub-objects.

Of course, the above embodiments are embodied in the process control and self-learning process of the user logging in the target object.

If the target object does not need to be logged in, or the target object does not need to be logged in for the first time, namely the target object directly enters a login picture behind a certain default function interface, the scheme of the invention can automatically recommend and load the next target sub-object after detecting that the user has the intention of switching the interface based on the real-time operation data of the user on the current interface.

See, in particular, fig. 4.

When the operation intention of a user for switching an interface is detected, searching target operation data related to the interface operation data in the global user operation habit database based on the interface operation data;

and the target recommendation module determines a recommended sub-object and automatically loads and switches to an interface of the recommended sub-object.

Preferably, the detecting of the operation intention of the user to switch the interface specifically includes detecting one or a combination of the following operations:

a user executes a search operation on a current interface;

the user executes sliding operation on the current interface;

and the user performs page turning operation on the current interface.

In the above example, a target feedback module is further provided, and is configured to receive a feedback parameter of the current user to the recommended sub-object determined by the target recommendation module.

The feedback parameters comprise satisfaction feedback of the current user to the automatically loaded recommended sub-objects;

and if the feedback data is unsatisfactory, not saving the current interface switching data as the operation data of the login user.

If the dissatisfaction frequency of a certain recommended sub-object reaches a threshold value, determining at least one recommended sub-object from a plurality of sub-objects of the target object in the next target sub-object recommending process by combining the current first target operation data and the second target operation data.

Obviously, in the above process, the technical solution of the present invention can automatically preload the next function interface or function module to be displayed for the user based on the current login user level and the existing recorded operation data stored in the local user habit database and the global user habit database, thereby avoiding the user from finding or spending time to know the transaction to be processed in the current time period; due to the fact that different users and operation data in different time periods are fully considered, the technical scheme of the invention can greatly improve the target control efficiency.

Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.

Claims

1. A target control system based on user habit self-learning control comprises a user attribute acquisition module, a target recommendation module and a target feedback module,

the target object comprises a plurality of sub-objects;

the target recommending module determines at least one recommended sub-object from a plurality of sub-objects of the target object based on first target operation data and/or second target operation data;

the target feedback module is used for receiving the feedback parameters of the current user to the recommended sub-object determined by the target recommendation module;

the method is characterized in that:

the target control system comprises a local user habit database and a global user habit database;

the first target operation data is operation data generated when all users corresponding to the user attribute data operate the target object within a first preset time period;

the local user habit database is used for the first target operation data;

the second target operation data is target operation data generated when all users operate the target object within a second preset time period;

the global user habit database is used for the second target operation data;

and the length of the first predetermined period of time is greater than the length of the second predetermined period of time;

the system also includes a sub-object preloading module;

2. The system of claim 1, wherein the target control system is based on user habit self learning control, and comprises:

the user attribute data comprises one or a combination of the following:

3. The system of claim 1, wherein the target control system is based on user habit self learning control, and comprises:

the target control system further comprises a user attribute database;

4. The system of claim 1, wherein the target control system is based on user habit self learning control, and comprises:

the second target operation data or the first target operation data generated when the target object is operated comprises:

5. A target control method based on user habit self learning control, the method is used for controlling a target object comprising a plurality of different sub objects, and the method is characterized by comprising the following steps:

s200: judging whether the user name can be found in a user attribute database;

if yes, obtaining a user grade corresponding to the user name;

s300: judging whether the first target operation data can be found in the local user habit database or not;

if yes, go to step S500;

if not, the step S400 is entered;

s500: taking the first target operation data and/or the second target operation data as recommendation basic data; s600: determining at least one recommended sub-object from a plurality of sub-objects of the target object based on the recommendation basic data;

s800: judging whether the user password is correct or not;

if yes, go to step S900;

if not, prompting that the password is wrong, and returning to the step S800;

s900: displaying the recommended sub-object;

the first target operation data is operation data generated when all users corresponding to the user level operate the target object within a first preset time period;

the length of the first predetermined period of time is greater than the length of the second predetermined period of time.

6. The object control method according to claim 5, characterized in that:

the second target operation data is user habit data generated when all users operate the target object, and the user habit data comprises operation time, operation positions and specific operation parameters.

7. The object control method according to claim 6, characterized in that:

8. A computer-readable storage medium having stored thereon computer-executable program instructions that are executed by a terminal device comprising a memory and a processor for implementing the method of any one of claims 5-7.