CN110968291A - Method and device for adjusting application program function menu based on optimal tree - Google Patents
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Abstract
The embodiment of the invention discloses a method and a device for adjusting an application program function menu based on an optimal tree. And calculating comprehensive weight capable of reflecting the importance of each preset function for the target group by the optimal tree corresponding to each target user in the target group, and readjusting the menu level of each preset function in the preset application program through the comprehensive weight, so that the setting of each preset function in the menu of the preset application program meets the requirements of the user, and the user can use the menu conveniently. According to the method, the result reflecting the real use condition of the application program by the user can be quickly obtained through the binary tree, so that the menu of the application program adjusted according to the result accords with the use habit of the user, and the operation of the user is facilitated.
Description
Technical Field
The embodiment of the invention relates to the technical field of application program development, in particular to a method and a device for adjusting an application program function menu based on an optimal tree.
Background
With the rapid advance of the development market of the mobile internet and the APP application, the mobile APP has become the mainstream of the mobile internet; the development of APP applications via mobile terminals has become an indispensable part of people's daily life and work. Wherein the functions provided in the APP and the design of the functions are directly related to the use value of the APP. The current App functional design mainly has the following modes: the design is carried out by a top-down method, and the organization of the functions is also designed and placed by a designed fixed menu; the functional modules are configured and adjusted by the user according to the preference. However, the existing process for setting the APP function menu for the APP has the following disadvantages: (1) the value and the criticality of each function in the system to a user cannot be evaluated quickly and accurately; (2) the inability to reasonably generate customized menus based on the user's usage habits in the system; (3) the existing functional items in the system cannot be managed, organized and applied efficiently.
Most of the functions of the target application program are in default settings in the function menu, the default settings generally cannot reflect the real requirements of the user, and the default settings cannot be changed according to the requirements of the user and cannot adapt to the use requirements of the user in time. For example, a certain function is frequently used by a user, but the function is set in a menu level behind an APP by default, and the user needs to perform multiple operations each time to trigger the function, which is very inconvenient.
In the process of implementing the embodiment of the invention, the inventor finds that most of the functions of the existing application program are default settings in the function menu, and the default settings often cannot reflect the real requirements of users, so that the operation of the application program is inconvenient in the use process.
Disclosure of Invention
The invention aims to solve the technical problem of how to solve the problem that most of the functions of the existing application program are default settings in a function menu, and the default settings often cannot reflect the real requirements of a user, so that the operation of the application program is inconvenient in the using process.
In view of the above technical problems, an embodiment of the present invention provides a method for adjusting an application function menu based on an optimal tree, including:
for each target user in a target group, acquiring user behavior data of the target user for operating a preset application program, and obtaining an evaluation parameter representing the importance of each preset function in the preset application program to the target user according to the user behavior data;
acquiring binary trees with different structures, calculating the weighted path length of each binary tree according to the evaluation parameter corresponding to each preset function and the depth, determined by the evaluation parameter, corresponding to each preset function in the binary tree, of each binary tree, and taking the binary tree with the minimum weighted path length as the optimal tree corresponding to the target user;
and calculating the comprehensive weight of each preset function for the optimal tree corresponding to each target user in the target group according to the depth of each preset function in each optimal tree and the preset weight corresponding to the menus of different levels in the preset application program, and adjusting the level of the menu to which each preset function in the preset application program belongs according to the comprehensive weight corresponding to each preset function.
In a second aspect, the present embodiment provides an apparatus for adjusting an application function menu based on an optimal tree, including:
the system comprises an acquisition module, a judgment module and a display module, wherein the acquisition module is used for acquiring user behavior data of each target user in a target group for operating a preset application program by the target user and obtaining an evaluation parameter representing the importance of each preset function in the preset application program to the target user according to the user behavior data;
the calculation module is used for acquiring binary trees with different structures, calculating the weighted path length of each binary tree according to the evaluation parameter corresponding to each preset function and the depth, determined by the evaluation parameter, corresponding to each preset function in the binary tree, and taking the binary tree with the minimum weighted path length as the optimal tree corresponding to the target user;
and the adjusting module is used for calculating the comprehensive weight of each preset function according to the depth of each preset function in each optimal tree and preset weights corresponding to menus of different levels in the preset application program for the optimal tree corresponding to each target user in the target group, and adjusting the level of the menu to which each preset function in the preset application program belongs according to the comprehensive weight corresponding to each preset function.
The embodiment provides an electronic device, including:
at least one processor, at least one memory, a communication interface, and a bus; wherein,
the processor, the memory and the communication interface complete mutual communication through the bus;
the communication interface is used for information transmission between the electronic equipment and the communication equipment of the terminal equipment;
the memory stores program instructions executable by the processor, which when called by the processor are capable of performing the methods described above.
The present embodiments provide a non-transitory computer-readable storage medium storing computer instructions that cause the computer to perform the method described above
The embodiment of the invention provides a method and a device for adjusting an application program function menu based on an optimal tree. And calculating comprehensive weight capable of reflecting the importance of each preset function for the target group by the optimal tree corresponding to each target user in the target group, and readjusting the menu level of each preset function in the preset application program through the comprehensive weight, so that the setting of each preset function in the menu of the preset application program meets the requirements of the user, and the user can use the menu conveniently. According to the method, the result reflecting the real use condition of the application program by the user can be quickly obtained through the binary tree, so that the menu of the application program adjusted according to the result conforms to the use habit of the user, the requirement of the user is met, and the operation of the user is facilitated.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
FIG. 1 is a flowchart illustrating a method for adjusting an application menu based on an optimal tree according to an embodiment of the present invention;
FIG. 2 is a schematic diagram illustrating a method for adjusting a menu of application functions based on an optimal tree according to another embodiment of the present invention;
fig. 3 is a schematic diagram illustrating how many records of operation frequency of 4 functions of the APP are performed by a user recorded in a user behavior data center according to another embodiment of the present invention;
FIG. 4 is a schematic diagram of a binary tree generated according to data operated by user A for 4 functions in APP, according to another embodiment of the present invention;
FIG. 5 is a schematic diagram of an optimal tree corresponding to each user in a user group consisting of a user A, a user B, a user C, and a user D according to another embodiment of the present invention;
FIG. 6 is a diagram illustrating the number of preset functions corresponding to the menus of each level according to the optimal tree statistics shown in FIG. 5 according to another embodiment of the present invention;
FIG. 7 is a schematic diagram of a target binary tree generated for 4 preset functions of an APP according to another embodiment of the present invention;
FIG. 8 is a block diagram illustrating an apparatus for adjusting a menu of functions of an application based on an optimal tree according to another embodiment of the present invention;
fig. 9 is a block diagram showing the structure of the electronic apparatus provided in the present embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 is a schematic flowchart of a method for adjusting an application function menu based on an optimal tree according to this embodiment, and referring to fig. 1, the method includes:
101: for each target user in a target group, acquiring user behavior data of the target user for operating a preset application program, and obtaining an evaluation parameter representing the importance of each preset function in the preset application program to the target user according to the user behavior data;
102: acquiring binary trees with different structures, calculating the weighted path length of each binary tree according to the evaluation parameter corresponding to each preset function and the depth, determined by the evaluation parameter, corresponding to each preset function in the binary tree, of each binary tree, and taking the binary tree with the minimum weighted path length as the optimal tree corresponding to the target user;
103: and calculating the comprehensive weight of each preset function for the optimal tree corresponding to each target user in the target group according to the depth of each preset function in each optimal tree and the preset weight corresponding to the menus of different levels in the preset application program, and adjusting the level of the menu to which each preset function in the preset application program belongs according to the comprehensive weight corresponding to each preset function.
The method provided by this embodiment is usually executed by a server, where the server reflects the comprehensive weight of each preset function required by a user of a certain group according to user behavior data, and adjusts the hierarchy of each preset function in the menu of the preset application program according to the comprehensive weight corresponding to each preset function. When a user opens the preset application program through the terminal, the menu page with the hierarchy to which each preset function belongs can be loaded and adjusted through the server, and the user can conveniently and quickly find the preset function to be triggered through the menu page.
The target group is users using the preset application program. When it is necessary to set the menu of the preset application program for a specific group, a user having a certain specific attribute may be selected as the target group, for example, a user whose gender is female and who uses the preset application program may be selected as the target group. The evaluation parameter represents the importance of the preset function to the user, for example, the evaluation parameter of a certain preset function may be the frequency of the user operating the preset function within a certain period of time, or the frequency of the user operating the preset function within unit time, and the like, which is not limited in this embodiment.
The embodiment provides a method for adjusting an application program function menu based on an optimal tree, which is characterized in that aiming at a target group using a certain preset application program, user behavior data of each target user in the target group operating on the preset application program are collected, and according to the user behavior data, the optimal tree which can reflect the importance of each preset function of the application program to the target user can be reflected through a binary tree. And calculating comprehensive weight capable of reflecting the importance of each preset function for the target group by the optimal tree corresponding to each target user in the target group, and readjusting the menu level of each preset function in the preset application program through the comprehensive weight, so that the setting of each preset function in the menu of the preset application program meets the requirements of the user, and the user can use the menu conveniently. According to the method, the result reflecting the real use condition of the application program by the user can be quickly obtained through the binary tree, so that the menu of the application program adjusted according to the result conforms to the use habit of the user, the requirement of the user is met, and the operation of the user is facilitated.
Specifically, fig. 2 shows a schematic diagram of a method for adjusting an application function menu based on an optimal tree according to this embodiment, and referring to fig. 2, in a process that a user uses a system (a system corresponding to a preset application), the method according to this embodiment records behaviors of the user operating in the system, and the recorded contents are stored in a user behavior data center; in a behavior model center, outputting data models with different dimensions mainly according to different user sets; and the algorithm processing module takes the optimal tree algorithm as a core and efficiently provides the most appropriate function organization structure for the user.
As shown in FIG. 2, ① the user behavior data center records the user system operation behavior, mainly from two dimensions, in individual dimension, records the system operation behavior of a single user for a long period of time, and in group dimension, records the user operation behaviors of different areas, age structures, gender characteristics, and the like.
② behavior model center, which can analyze and model the user behavior aiming at a single user, and also can analyze the user behavior of the users with the same attribute characteristics, such as user area dimension, 'users in a certain city', user authority dimension, 'all agents', user gender dimension, 'all female users', user age dimension, 'users between 30 and 45 years of age' and the like, supporting independent characteristics or combined characteristics to be integrated into a user group with a specific label, and analyzing the user behavior of the users of the specific user group to generate data models of different clients, different groups and different dimensions to be stored in the model center.
③ algorithm processing module, which takes the optimal tree algorithm as the core to construct binary trees with different structures for the behavior model of the user, and takes the frequency of each function in the behavior model as the weight of the leaf node to obtain the weighted path length of the behavior model.
The path with the weight has the minimum length, namely the optimal binary tree, the structure of the tree is understood as the most suitable function menu organization structure for the user, the root node can be understood as the home page, the weight is understood as the operation frequency, and the function items with higher operation frequency are closer to the home page, so that the function organization design and the effective and reasonable menu placement from top to bottom according to the actual operation condition of the user are realized.
For a user group with the same characteristics, each user in the user group has a corresponding optimal tree, so that a model is constructed by taking a function item as a dimension, the hierarchy of each function in a user menu is displayed, the weight of each function is defined according to the menu hierarchy position of each function in each user menu (whether the function is important to the user is determined), the frequency of the function appearing in each level of menu is multiplied by the sum of the weight scores of each level, the weight of each function node in the optimal tree of the user group is obtained, and the function optimal architecture of the user group is obtained by judging according to the weight.
Further, on the basis of the above embodiment, the obtaining, for each target user in the target group, user behavior data of the target user operating a preset application program, and obtaining, according to the user behavior data, an evaluation parameter indicating importance of each preset function in the preset application program to the target user includes:
for each target user in a target group, acquiring user behavior data of the target user for operating a preset application program, and respectively counting the frequency of the target user for operating each preset function within a preset time period according to the user behavior data to serve as an evaluation parameter for representing the importance of each preset function to the target user;
wherein the target group is a group consisting of users having the same attribute.
For a preset period of time, for example, within three months from the current time point onward. In this embodiment, the evaluation parameter corresponding to a certain preset function is the number of times that a user operates the preset function within a preset time period.
The embodiment provides a method for adjusting an application program function menu based on an optimal tree, which takes the times of operating a certain preset function by a user in a preset time period as an evaluation parameter, and can conveniently and quickly determine the evaluation parameter.
Further, on the basis of the foregoing embodiments, the acquiring binary trees with different structures, for each binary tree, calculating a weighted path length of the binary tree according to an evaluation parameter corresponding to each preset function and a depth, determined by the evaluation parameter, corresponding to each preset function in the binary tree, and taking the binary tree with the smallest weighted path length as the optimal tree corresponding to the target user includes:
acquiring binary trees with different structures, and determining the depth of a preset function in each binary tree by using the frequency count corresponding to each preset function according to the rule that the frequency count corresponding to the preset function with larger depth in the binary tree is smaller than the frequency count corresponding to the preset function with smaller depth in the binary tree;
according to the formula LN＝∑(Wi*ni) Calculating the weighted path length corresponding to each binary tree, and taking the binary tree with the minimum weighted path length as the optimal tree corresponding to the target user;
wherein L isNFor the length of the weighted path corresponding to the Nth binary tree, WiThe evaluation parameter, N, corresponding to the ith preset function in the Nth binary tree is showniIndicating the depth of the ith preset function in the nth binary tree.
For example, an APP has 4 functions, which are placing an order, asking for funds, visiting a group, and taking an order. Fig. 3 is a schematic diagram illustrating how frequently the user performs operations on 4 functions of the APP recorded in the user behavior data center, and referring to fig. 3, the frequency of each user using each function is greatly different due to different factors in various aspects such as service use scenarios, personal use habits, regional service development conditions, and the like.
FIG. 4 shows the pairing of 4 of APPs according to user AReferring to fig. 4, taking user a as an example, a behavior model of user a is used to construct a plurality of binary trees with different structures (for example, in the binary tree with numbers (a), (b), (c), (d), and (e) in fig. 4, for example, in the diagram with number (a), the frequency count corresponding to "fund claim" is 50, the frequency count corresponding to "bill raising" is 150, the frequency count corresponding to "order placing" is 200, and the frequency count corresponding to "group visit" is 300), and the frequency used by each function in the behavior model is used as the weight of a leaf node. According to the formula LN＝∑(Wi*ni) The weighted path length corresponding to each binary tree is calculated and is (L)1Corresponding to binary tree numbered (a), L2Corresponding to binary tree numbered (b), L3Corresponding to binary tree numbered (c), L4Corresponding to binary tree numbered (d), L5Corresponding binary tree numbered (e):
L1＝50×2+150×2+200×2+300×2＝1400
L2＝50×3+150×3+200×2+300×1＝1300
L3＝50×2+150×3+200×3+300×1＝1450
L4＝300×3+200×3+150×2+50×1＝1850
L5＝300×1+200×2+150×3+50×3＝1300
the minimum weighted path length is the optimal tree corresponding to the user a, and it can be known from the above calculation that the binary tree labeled as (b) is the optimal tree, (i.e., the behavior model (b) and the behavior model (c) are both binary trees with the minimum weighted path length, and the binary tree corresponding to the behavior model (b) is randomly selected as the optimal tree in this embodiment). The optimal tree is understood as the organization of the menu of functions that is most suitable for user a.
The user a, the user B, the user C, and the user D are a "user group" having the same characteristics, the optimal tree corresponding to each user in the user group is calculated by the above method, and fig. 5 provides a schematic diagram of the optimal tree corresponding to each user in the user group consisting of the user a, the user B, the user C, and the user D.
The embodiment provides a method for adjusting an application function menu based on an optimal tree, which determines the optimal tree corresponding to each target user in a target group through a weighted path length, and then analyzes a function menu organization structure most suitable for the group according to the optimal tree corresponding to each user.
Further, on the basis of the foregoing embodiments, the calculating, according to the depth of each preset function in each optimal tree and preset weights corresponding to menus of different levels in the preset application program, an integrated weight of each preset function for the optimal tree corresponding to each target user in the target group, and adjusting, by the integrated weight corresponding to each preset function, the level of the menu to which each preset function in the preset application program belongs, includes:
acquiring a corresponding relation between the depth of a preset function in an optimal tree and the level of a menu to which the preset function belongs in a preset application program, and counting the number of each preset function at the depth corresponding to the level in all the optimal trees for each level in the preset application program according to the corresponding relation to obtain the number corresponding to each preset function in the menu of each level;
acquiring preset weights corresponding to menus of different levels in the preset application program, and according to a formula
Calculating the comprehensive weight of each preset function;
adjusting the level of the menu to which the preset function belongs according to a rule that the comprehensive weight corresponding to the preset function in the menu with a smaller level is greater than the comprehensive weight corresponding to the preset function in the menu with a larger level;
wherein M isiFor the integral weight, m, corresponding to the ith preset functionjIndicating the number corresponding to the ith preset function in the j hierarchy menu,
corresponding to the menu representing the jth hierarchical levelThe weight is preset.
For example, the menu in the preset application program has 3 levels, and the corresponding relationship in this embodiment is: the first level menu corresponds to a preset function located at the position with the depth of 1 in the optimal tree, the second level menu corresponds to a preset function located at the position with the depth of 2 in the optimal tree, and the third level menu corresponds to a preset function located at the position with the depth of 3 in the optimal tree. Fig. 6 is a diagram showing the number of preset functions corresponding to the menus of each level according to the optimal tree statistics in fig. 5, and referring to fig. 6, in the menu of one level, "clique visit" occurs 1 times in the binary tree with depth 1 in fig. 5, "fund claim" occurs 2 times in the binary tree with depth 1 in fig. 5, "order placement" occurs 1 times in the binary tree with depth 1 in fig. 5, and "bill picking" occurs 0 times in the binary tree with depth 1 in fig. 5. FIG. 6 is a diagram illustrating the hierarchy of functions in a user menu, with function items as dimensions, and a model constructed.
Setting the preset weight of the function item of the first-level menu as 5, the preset weight of the function item of the second-level menu as 3, and the preset weight of the function item of the third-level menu as 2. According to the formula
The comprehensive weight corresponding to each preset function is calculated as follows:
group visit: m1＝1*5+2*3+1*2＝13
And (4) fund claiming: m2＝2*5+0*3+2*2＝14
Ordering: m3＝1*5+1*3+2*2＝12
And (4) bill extraction: m4＝0*5+1*3+2*3＝9
The level of the menu to which each preset function belongs is adjusted according to the comprehensive weight, for example, the comprehensive weight corresponding to capital claim and group visit is large, the capital claim and the group visit can be set in the first-level menu (for example, the first page of APP), the comprehensive weight corresponding to order placement can be set in the second-level menu, the comprehensive weight corresponding to order picking is minimum, and the order picking can be set in the third-level menu.
The embodiment provides a method for adjusting an application program function menu based on an optimal tree, which realizes representation of importance of different functions to a certain user group through comprehensive weights, and facilitates adjustment of the menu according to the comprehensive weights.
Further, on the basis of the above embodiments, the method further includes:
after the comprehensive weight of each preset function is calculated, generating a target binary tree according to the comprehensive weight corresponding to each preset function, marking nodes corresponding to each preset function in the target binary tree according to a rule that the comprehensive weight corresponding to the preset function with the larger depth in the target binary tree is smaller than the comprehensive weight corresponding to the preset function with the smaller depth in the target binary tree, obtaining a group optimal tree suitable for the target group, and displaying the group optimal tree;
and the depth of the target binary tree is equal to the total number of the levels of the menus in the preset application program.
In order to clearly show the organization relationship of the function menus applicable to the user group, and after obtaining the comprehensive weight, a target binary tree may be generated, and fig. 7 is a schematic diagram of the target binary tree generated for the 4 preset functions of the APP.
The embodiment provides a method for adjusting an application program function menu based on an optimal tree, and a preset function organization relation suitable for a certain group is conveniently and visually known through a target binary tree.
In a second aspect, the present embodiment provides a method for adjusting a preset function in a menu for a single user, where the method for adjusting an application function menu based on an optimal tree includes:
the method comprises the steps of obtaining user behavior data of a target user in operation on a preset application program, obtaining an evaluation parameter representing the importance of each preset function in the preset application program on the target user according to the user behavior data, and adjusting the level of a menu to which each preset function in the preset application program belongs according to the evaluation parameter.
The embodiment provides a method for adjusting an application program function menu based on an optimal tree, which is characterized in that the importance of each preset function relative to an individual user can be directly analyzed according to user behavior data of the individual user aiming at the individual user, and then the preset functions are rearranged according to the analyzed importance so as to meet the requirements of the user.
Further, on the basis of the above embodiment, the method further includes:
acquiring binary trees with different structures, calculating the weighted path length of each binary tree according to the evaluation parameter corresponding to each preset function and the depth, determined by the evaluation parameter, corresponding to each preset function in the binary tree, of each binary tree, taking the binary tree with the minimum weighted path length as the optimal tree corresponding to the target user, marking the node corresponding to each preset function in the optimal tree corresponding to the target user, obtaining the optimal tree suitable for the target user, and displaying the optimal tree corresponding to the target user.
The embodiment provides a method for adjusting an application program function menu based on an optimal tree, which is used for conveniently and intuitively knowing a preset function organization relation suitable for a certain user through a binary tree.
The method provided by the embodiment collects and constructs a data modeling method used by a user for the APP function based on the optimal tree, and can perform a certain dynamic adjustment mechanism for the APP function organization and personalization. The dynamic evaluation and adjustment of system function organization are realized based on the optimal tree by taking user experience and improvement of system use efficiency as the core, so that the system has pertinence and customizability. And according to the use habits of the users, the algorithm is realized by taking the optimal tree as a core, and a system function structure menu which most accords with the operation habits of the users is dynamically and efficiently organized for the users.
According to the method provided by the implementation, in the process of user demand understanding, user behavior information is introduced, similar human thinking fuses existing knowledge and past memory, modeling is performed on behaviors, an optimal tree algorithm is introduced, a system function structure is dynamically organized according to daily operation habits of users, the users can operate more quickly and conveniently, the user experience is improved to a great extent while the working efficiency of the users is improved, and the advantages are summarized as follows: (1) and the optimal tree is taken as an algorithm core in the proposal, so that a function menu most aiming at the appetite can be dynamically presented to the user in real time. (2) And the method has reasonableness, and the proposal carries out specific algorithm processing on the basis of user operation behaviors, thereby having more reasonableness. (3) The method has the advantages that the function menu is divided into levels according to different dimensions, so that the service efficiency of the system is improved to a great extent. (4) Guiding, managers can monitor the actual service condition of the service through the optimal trees of different dimensions through weight configuration, and reasonably present a function menu for the user, so that the guiding effect of a certain degree is played for the user, the service supervision is more convenient, the development of guiding service is promoted, and the efficiency of the service is ensured.
Fig. 8 is a block diagram of an apparatus for adjusting an application function menu based on an optimal tree according to the present embodiment, referring to fig. 8, the apparatus includes an obtaining module 801, a calculating module 802, and an adjusting module 803, wherein,
an obtaining module 801, configured to obtain, for each target user in a target group, user behavior data of the target user for operating a preset application program, and obtain, according to the user behavior data, an evaluation parameter indicating importance of each preset function in the preset application program to the target user;
a calculating module 802, configured to obtain binary trees with different structures, calculate, for each binary tree, a weighted path length of the binary tree according to an evaluation parameter corresponding to each preset function and a depth, determined by the evaluation parameter, corresponding to each preset function in the binary tree, and use the binary tree with the smallest weighted path length as an optimal tree corresponding to the target user;
an adjusting module 803, configured to calculate, for the optimal tree corresponding to each target user in the target group, a comprehensive weight of each preset function according to the depth of each preset function in each optimal tree and preset weights corresponding to menus of different levels in the preset application program, and adjust, by the comprehensive weight corresponding to each preset function, a level of a menu to which each preset function in the preset application program belongs.
The apparatus for adjusting an application function menu based on an optimal tree provided in this embodiment is suitable for the method for adjusting an application function menu based on an optimal tree provided in the foregoing embodiment, and is not described herein again.
The embodiment provides a device for adjusting an application program function menu based on an optimal tree, which is used for collecting user behavior data of each target user operating a preset application program in a target group using a certain preset application program, and according to the user behavior data, the optimal tree which can reflect the importance of each preset function of the application program to the target user most through a binary tree. And calculating comprehensive weight capable of reflecting the importance of each preset function for the target group by the optimal tree corresponding to each target user in the target group, and readjusting the menu level of each preset function in the preset application program through the comprehensive weight, so that the setting of each preset function in the menu of the preset application program meets the requirements of the user, and the user can use the menu conveniently. The device can quickly obtain the result reflecting the real use condition of the application program by the user through the binary tree, so that the menu of the application program adjusted according to the result conforms to the use habit of the user, the requirement of the user is met, and the operation of the user is facilitated.
Fig. 9 is a block diagram showing the structure of the electronic apparatus provided in the present embodiment.
Referring to fig. 9, the electronic device includes: a processor (processor)901, a memory (memory)902, a communication Interface (Communications Interface)903, and a bus 904;
wherein,
the processor 901, the memory 902 and the communication interface 903 complete mutual communication through the bus 904;
the communication interface 903 is used for information transmission between the electronic device and a communication device of the terminal device;
the processor 901 is configured to call program instructions in the memory 902 to perform the methods provided by the above-mentioned method embodiments, for example, including: for each target user in a target group, acquiring user behavior data of the target user for operating a preset application program, and obtaining an evaluation parameter representing the importance of each preset function in the preset application program to the target user according to the user behavior data; acquiring binary trees with different structures, calculating the weighted path length of each binary tree according to the evaluation parameter corresponding to each preset function and the depth, determined by the evaluation parameter, corresponding to each preset function in the binary tree, of each binary tree, and taking the binary tree with the minimum weighted path length as the optimal tree corresponding to the target user; and calculating the comprehensive weight of each preset function for the optimal tree corresponding to each target user in the target group according to the depth of each preset function in each optimal tree and the preset weight corresponding to the menus of different levels in the preset application program, and adjusting the level of the menu to which each preset function in the preset application program belongs according to the comprehensive weight corresponding to each preset function.
The present embodiments provide a non-transitory computer-readable storage medium storing computer instructions that cause the computer to perform the methods provided by the above method embodiments, for example, including: for each target user in a target group, acquiring user behavior data of the target user for operating a preset application program, and obtaining an evaluation parameter representing the importance of each preset function in the preset application program to the target user according to the user behavior data; acquiring binary trees with different structures, calculating the weighted path length of each binary tree according to the evaluation parameter corresponding to each preset function and the depth, determined by the evaluation parameter, corresponding to each preset function in the binary tree, of each binary tree, and taking the binary tree with the minimum weighted path length as the optimal tree corresponding to the target user; and calculating the comprehensive weight of each preset function for the optimal tree corresponding to each target user in the target group according to the depth of each preset function in each optimal tree and the preset weight corresponding to the menus of different levels in the preset application program, and adjusting the level of the menu to which each preset function in the preset application program belongs according to the comprehensive weight corresponding to each preset function.
The present embodiments disclose a computer program product comprising a computer program stored on a non-transitory computer readable storage medium, the computer program comprising program instructions which, when executed by a computer, enable the computer to perform the methods provided by the above-described method embodiments, for example, comprising: for each target user in a target group, acquiring user behavior data of the target user for operating a preset application program, and obtaining an evaluation parameter representing the importance of each preset function in the preset application program to the target user according to the user behavior data; acquiring binary trees with different structures, calculating the weighted path length of each binary tree according to the evaluation parameter corresponding to each preset function and the depth, determined by the evaluation parameter, corresponding to each preset function in the binary tree, of each binary tree, and taking the binary tree with the minimum weighted path length as the optimal tree corresponding to the target user; and calculating the comprehensive weight of each preset function for the optimal tree corresponding to each target user in the target group according to the depth of each preset function in each optimal tree and the preset weight corresponding to the menus of different levels in the preset application program, and adjusting the level of the menu to which each preset function in the preset application program belongs according to the comprehensive weight corresponding to each preset function.
Those of ordinary skill in the art will understand that: all or part of the steps for implementing the method embodiments may be implemented by hardware related to program instructions, and the program may be stored in a computer readable storage medium, and when executed, the program performs the steps including the method embodiments; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.
The above-described embodiments of the electronic device and the like are merely illustrative, where the units described as separate parts may or may not be physically separate, and the parts displayed as units may or may not be physical units, may be located in one place, or may also be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
Finally, it should be noted that: the above embodiments are only used for illustrating the technical solutions of the embodiments of the present invention, and are not limited thereto; although embodiments of the present invention have been described in detail with reference to the foregoing embodiments, those skilled in the art will understand that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. A method for adjusting an application menu based on an optimal tree, comprising:
for each target user in a target group, acquiring user behavior data of the target user for operating a preset application program, and obtaining an evaluation parameter representing the importance of each preset function in the preset application program to the target user according to the user behavior data;
acquiring binary trees with different structures, calculating the weighted path length of each binary tree according to the evaluation parameter corresponding to each preset function and the depth, determined by the evaluation parameter, corresponding to each preset function in the binary tree, of each binary tree, and taking the binary tree with the minimum weighted path length as the optimal tree corresponding to the target user;
and calculating the comprehensive weight of each preset function for the optimal tree corresponding to each target user in the target group according to the depth of each preset function in each optimal tree and the preset weight corresponding to the menus of different levels in the preset application program, and adjusting the level of the menu to which each preset function in the preset application program belongs according to the comprehensive weight corresponding to each preset function.
2. The method according to claim 1, wherein the step of obtaining, for each target user in a target group, user behavior data of the target user operating a preset application program, and obtaining an evaluation parameter indicating importance of each preset function in the preset application program to the target user according to the user behavior data comprises:
for each target user in a target group, acquiring user behavior data of the target user for operating a preset application program, and respectively counting the frequency of the target user for operating each preset function within a preset time period according to the user behavior data to serve as an evaluation parameter for representing the importance of each preset function to the target user;
wherein the target group is a group consisting of users having the same attribute.
3. The method according to claim 2, wherein the obtaining binary trees with different structures, for each binary tree, calculating a weighted path length of the binary tree according to an evaluation parameter corresponding to each preset function and a depth, determined by the evaluation parameter, corresponding to each preset function in the binary tree, and taking the binary tree with the smallest weighted path length as the optimal tree corresponding to the target user includes:
acquiring binary trees with different structures, and determining the depth of a preset function in each binary tree by using the frequency count corresponding to each preset function according to the rule that the frequency count corresponding to the preset function with larger depth in the binary tree is smaller than the frequency count corresponding to the preset function with smaller depth in the binary tree;
according to the formula LN＝∑(Wi*ni) Calculating the weighted path length corresponding to each binary tree, and taking the binary tree with the minimum weighted path length as the optimal tree corresponding to the target user;
wherein L isNFor the length of the weighted path corresponding to the Nth binary tree, WiThe evaluation parameter, N, corresponding to the ith preset function in the Nth binary tree is showniIndicating the depth of the ith preset function in the nth binary tree.
4. The method according to claim 2, wherein for the optimal tree corresponding to each target user in the target group, calculating a comprehensive weight of each preset function according to a depth of each preset function in each optimal tree and preset weights corresponding to different levels of menus in the preset application program, and adjusting a level of a menu to which each preset function in the preset application program belongs according to the comprehensive weight corresponding to each preset function comprises:
acquiring a corresponding relation between the depth of a preset function in an optimal tree and the level of a menu to which the preset function belongs in a preset application program, and counting the number of each preset function at the depth corresponding to the level in all the optimal trees for each level in the preset application program according to the corresponding relation to obtain the number corresponding to each preset function in the menu of each level;
acquiring preset weights corresponding to menus of different levels in the preset application program, and according to a formula
Calculating the comprehensive weight of each preset function;
adjusting the level of the menu to which the preset function belongs according to a rule that the comprehensive weight corresponding to the preset function in the menu with a smaller level is greater than the comprehensive weight corresponding to the preset function in the menu with a larger level;
wherein M isiFor the integral weight, m, corresponding to the ith preset functionjIndicating the number corresponding to the ith preset function in the j hierarchy menu,
and representing the preset weight corresponding to the menu of the jth level.
5. The method of claim 1, further comprising:
after the comprehensive weight of each preset function is calculated, generating a target binary tree according to the comprehensive weight corresponding to each preset function, marking nodes corresponding to each preset function in the target binary tree according to a rule that the comprehensive weight corresponding to the preset function with the larger depth in the target binary tree is smaller than the comprehensive weight corresponding to the preset function with the smaller depth in the target binary tree, obtaining a group optimal tree suitable for the target group, and displaying the group optimal tree;
and the depth of the target binary tree is equal to the total number of the levels of the menus in the preset application program.
6. A method for adjusting an application menu based on an optimal tree, comprising:
the method comprises the steps of obtaining user behavior data of a target user in operation on a preset application program, obtaining an evaluation parameter representing the importance of each preset function in the preset application program on the target user according to the user behavior data, and adjusting the level of a menu to which each preset function in the preset application program belongs according to the evaluation parameter.
7. The method of claim 6, further comprising:
acquiring binary trees with different structures, calculating the weighted path length of each binary tree according to the evaluation parameter corresponding to each preset function and the depth, determined by the evaluation parameter, corresponding to each preset function in the binary tree, of each binary tree, taking the binary tree with the minimum weighted path length as the optimal tree corresponding to the target user, marking the node corresponding to each preset function in the optimal tree corresponding to the target user, obtaining the optimal tree suitable for the target user, and displaying the optimal tree corresponding to the target user.
8. An apparatus for adjusting an application menu based on an optimal tree, comprising:
the system comprises an acquisition module, a judgment module and a display module, wherein the acquisition module is used for acquiring user behavior data of each target user in a target group for operating a preset application program by the target user and obtaining an evaluation parameter representing the importance of each preset function in the preset application program to the target user according to the user behavior data;
the calculation module is used for acquiring binary trees with different structures, calculating the weighted path length of each binary tree according to the evaluation parameter corresponding to each preset function and the depth, determined by the evaluation parameter, corresponding to each preset function in the binary tree, and taking the binary tree with the minimum weighted path length as the optimal tree corresponding to the target user;
and the adjusting module is used for calculating the comprehensive weight of each preset function according to the depth of each preset function in each optimal tree and preset weights corresponding to menus of different levels in the preset application program for the optimal tree corresponding to each target user in the target group, and adjusting the level of the menu to which each preset function in the preset application program belongs according to the comprehensive weight corresponding to each preset function.
9. An electronic device, comprising:
at least one processor, at least one memory, a communication interface, and a bus; wherein,
the processor, the memory and the communication interface complete mutual communication through the bus;
the communication interface is used for information transmission between the electronic equipment and the communication equipment of the terminal equipment;
the memory stores program instructions executable by the processor, the processor invoking the program instructions to perform the method of any of claims 1-5.
10. A non-transitory computer-readable storage medium storing computer instructions that cause a computer to perform the method of any one of claims 1 to 5.
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