CN110968291B - Method and device for adjusting function menu of application program based on optimal tree - Google Patents
Method and device for adjusting function menu of application program based on optimal tree Download PDFInfo
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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 weights which can reflect the importance of each preset function for the target group according to 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 weights so that the setting of each preset function in the menu of the preset application program meets the requirements of the user and is convenient for the user to use. According to the method, the result of reflecting the actual use condition of the application program of the user can be obtained quickly 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 user operation 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 progress of mobile internet and APP application development markets, mobile APP has become the mainstream of mobile internet; the development of APP applications by means of mobile terminals has become an integral 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 functional design of the current App mainly comprises the following modes: designing by a top-down method, and designing and placing functional organizations by a designed fixed menu; the function modules are configured and adjusted by the user according to the preference. However, the existing process of setting an APP function menu for an APP has the following disadvantages: (1) The value and the criticality of each function in the system to the user cannot be evaluated quickly and accurately; (2) The method can not reasonably generate a customized menu based on the use habit of the user in the system; (3) The existing functional items in the application system cannot be efficiently managed, organized and applied.
The functions of the target application program are often default settings in the function menu, the default settings generally cannot reflect the real demands of the users, and the default settings cannot be changed according to the demands of the users, so that the default settings cannot be adapted to the use demands of the users in time. For example, a certain function is frequently used by a user, but the default setting sets the function in a menu hierarchy behind the APP, and the user needs to operate multiple times each time to trigger the function, so that the operation is very inconvenient.
In the process of implementing the embodiment of the invention, the inventor finds that the layout of the functions of the existing application program in the function menu is often a default setting, and the default setting often cannot reflect the real requirements of the user, so that the operation is inconvenient in the use process of the application program.
Disclosure of Invention
The technical problem to be solved by the invention is how to solve the problem that the operation is inconvenient in the application using process because the default setting is often unable to reflect the real demands of users because the functions of the existing application are arranged in the function menu.
Aiming at the technical problems, the embodiment of the invention provides a method for adjusting an application program function menu based on an optimal tree, which comprises the following steps:
for each target user in a target group, acquiring user behavior data of the target user for operating a preset application program, and acquiring 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 corresponding to each preset function in the binary tree determined by the evaluation parameter, 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 according to the depth of each preset function in each optimal tree and the preset weights corresponding to the menus of different levels in the preset application program, and adjusting the level of the menu of each preset function in the preset application program by the comprehensive weight corresponding to each preset function.
In a second aspect, the present embodiment provides an apparatus for adjusting a function menu of an application program based on an optimal tree, including:
the acquisition module is used for acquiring user behavior data of each target user in a target group, wherein the user behavior data are operated by the target user on a preset application program, and the evaluation parameters which represent the importance of each preset function in the preset application program on the target user are obtained according to the user behavior data;
the computing module is used for acquiring binary trees with different structures, computing the weighted path length of the binary tree according to the evaluation parameter corresponding to each preset function and the depth corresponding to each preset function in the binary tree determined by the evaluation parameter, and taking the binary tree with the minimum weighted path length as the optimal tree corresponding to the target user;
the adjustment 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 the preset weights corresponding to the menus of different levels in the preset application program, and adjusting the level of the menu of each preset function in the preset application program according to the comprehensive weight corresponding to each preset function.
The present embodiment provides an electronic device, including:
at least one processor, at least one memory, a communication interface, and a bus; wherein, the liquid crystal display device comprises a liquid crystal display device,
the processor, the memory and the communication interface complete the communication with each other 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 invokes the program instructions to perform the method described above.
The present embodiment provides a non-transitory computer-readable storage medium storing computer instructions that cause the computer to perform the above-described method
The embodiment of the invention provides a method and a device for adjusting an application program function menu based on an optimal tree, aiming at a target group using a certain preset application program, the method collects user behavior data of each target user in the target group for operating the preset application program, and according to the user behavior data, the optimal tree of importance of each preset function of the application program to the target user can be reflected through a binary tree. And calculating comprehensive weights which can reflect the importance of each preset function for the target group according to 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 weights so that the setting of each preset function in the menu of the preset application program meets the requirements of the user and is convenient for the user to use. According to the method, the result of reflecting the actual use condition of the application program of the user can be obtained quickly 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, the requirement of the user is met, and the user operation is facilitated.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a method for adjusting an application function menu based on an optimal tree according to one embodiment of the present invention;
FIG. 2 is a schematic diagram of a method for adjusting an application function menu based on an optimal tree according to another embodiment of the present invention;
FIG. 3 is a schematic diagram showing an operation frequency record of 4 functions of the APP 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 from data operated on 4 functions in an APP by user A, 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 user A, user B, user C, and user D according to another embodiment of the present invention;
FIG. 6 is a schematic diagram of the number of preset functions corresponding to the menu of each level of the optimal tree statistics 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 of an apparatus for adapting a menu of application functions based on an optimal tree according to another embodiment of the present invention;
fig. 9 is a block diagram showing the structure of an electronic apparatus provided in the present embodiment.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Fig. 1 is a flowchart of a method for adjusting an application function menu based on an optimal tree according to the present 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 acquiring 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 corresponding to each preset function in the binary tree determined by the evaluation parameter, 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 according to the depth of each preset function in each optimal tree and the preset weights corresponding to the menus of different levels in the preset application program, and adjusting the level of the menu of each preset function in the preset application program by the comprehensive weight corresponding to each preset function.
The method provided by the embodiment is generally executed by a server, the comprehensive weights of all preset functions of the user demands of a certain group are reflected by the server according to the user behavior data, and the belonging levels of all preset functions in the menu of the preset application program are adjusted by the comprehensive weights corresponding to all preset functions. When a user opens the preset application program through the terminal, the menu page with the hierarchy of each preset function being adjusted can be loaded through the server, and the user can conveniently and rapidly find the preset function to be triggered through the menu page.
The target group is a user using the preset application program. When it is necessary to set a menu of the preset application for a specific group, a user having a certain attribute may be selected as a target group, for example, a user having a sex of female and using the preset application may be selected as a target group. The evaluation parameter characterizes 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 in a certain period of time, or the frequency of the user operating the preset function in a unit of time, which is not particularly limited in this embodiment.
The embodiment provides a method for adjusting an application function menu based on an optimal tree, which aims at a target group using a certain preset application, collects user behavior data of each target user in the target group for operating the preset application, and according to the user behavior data, reflects the optimal tree of importance of each preset function of the application to the target user through a binary tree. And calculating comprehensive weights which can reflect the importance of each preset function for the target group according to 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 weights so that the setting of each preset function in the menu of the preset application program meets the requirements of the user and is convenient for the user to use. According to the method, the result of reflecting the actual use condition of the application program of the user can be obtained quickly 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, the requirement of the user is met, and the user operation is facilitated.
Specifically, fig. 2 is a schematic diagram of a method for adjusting a function menu of an application program based on an optimal tree according to the present embodiment, referring to fig. 2, in the process of using a system (a system corresponding to a preset application program) by a user, the method provided by the present embodiment records a behavior of the user operating in the system, and the recorded content is stored in a user behavior data center; in the center of the behavior model, outputting data models with different dimensionalities mainly according to different user sets; and the algorithm processing module is used for efficiently providing the most suitable function organization architecture for the user by taking the optimal tree algorithm as a core.
As shown in fig. 2, (1) user behavior data center: recording the operation behaviors of a user system, wherein the operation behaviors of the system of a single user are mainly recorded from two dimensions, and the operation behaviors of the system of the single user are recorded for a long time in the individual dimension; in the group dimension, the operation behaviors of users in different areas, age structures, gender characteristics and the like are recorded.
(2) Behavior model center: user behavior analysis modeling can be performed for a single user, or the same attribute features can be possessed, such as: user area dimension: "users in a certain city"; user rights dimension: "all agents"; user gender dimension: "all female users"; user age dimension: and users with ages of 30-45 years old, and the like, support independent features or combined features to be grouped into a user group with a specific label, and analyze the user behavior of the users of the specific user group so as to generate data models of different clients, different groups and different dimensions and store the data models in a model center.
(3) The algorithm processing module: and constructing binary trees with different structures for the behavior model of the user by taking an optimal tree algorithm as a core, and taking the frequency used by each function in the behavior model as the weight of the leaf node to obtain the weighted path length of the behavior model.
The structure of the tree is understood to be the function menu organization structure which is most suitable for the user, the root node can be understood to be the first page, the weight is understood to be the operation frequency, and the function item with higher operation frequency is closer to the first page, so that the organization design of functions and the effective and reasonable placement of menus 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 function items as dimensions, the hierarchy of each function in a user menu is displayed, the weight of each function is defined for the menu hierarchy position (determining whether the function is important for the user) of each function in each user menu, the number of times the function appears in each menu is multiplied by the sum of the weight scores of each level, namely the weight of each function node in the optimal tree of the user group, and then the function optimal architecture of the user group is obtained according to the weight.
Further, on the basis of the foregoing embodiment, the obtaining, for each target user in the target group, user behavior data of the target user operating on 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:
obtaining user behavior data of the target users operating a preset application program for each target user in a target group, and respectively counting the frequency of the target users operating each preset function in 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.
The preset time period, for example, three months forward from the current time point. The evaluation parameter corresponding to a certain preset function in the embodiment is the number of times that the user operates the preset function in a preset time period.
The embodiment provides a method for adjusting a function menu of an application program based on an optimal tree, which takes the number of times of a user operating a certain preset function in a preset time period as an evaluation parameter, and can conveniently and rapidly determine the evaluation parameter.
Further, on the basis of the foregoing embodiments, the obtaining binary trees with different structures, for each binary tree, calculates a weighted path length of the binary tree according to an evaluation parameter corresponding to each preset function and a depth corresponding to each preset function in the binary tree determined by the evaluation parameter, and uses a binary tree with the smallest weighted path length as an optimal tree corresponding to the target user, where the method includes:
acquiring binary trees with different structures, and determining the depth of a preset function in the binary tree according to the rule that the frequency corresponding to the preset function with larger depth in the binary tree is smaller than the frequency corresponding to the preset function with smaller depth in the binary tree for each binary tree by the frequency corresponding to each preset function;
according to formula L N ＝∑(W i *n i ) 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 is N For the weighted path length, W, corresponding to the Nth binary tree i Representing the evaluation parameter corresponding to the ith preset function in the Nth binary tree, N i Representing the depth of the ith preset function in the nth binary tree.
For example, an APP has 4 functions, namely, order, fund claim, group visit, bill of lading, respectively. Fig. 3 is a schematic diagram of an operation frequency record of 4 functions of the APP by a user recorded in a user behavior data center, and referring to fig. 3, the frequency of use of each function by each user is very different due to different factors such as service usage scenarios, personal usage habits, regional service development situations, and the like.
Fig. 4 shows a schematic diagram of a binary tree generated according to data of 4 functions in the APP by the user a, referring to fig. 4, taking the user a as an example, a behavior model is used to construct a plurality of binary trees with different structures (e.g. the binary trees with the numbers (a), (b), (c), (d) and (e) in fig. 4, for example, in the diagram with the number (a), the frequency corresponding to "fund claim" is 50, the frequency corresponding to "bill" is 150, the frequency corresponding to "order" is 200, the frequency corresponding to "group visit" is 300), and the frequency used by each function in the behavior model is taken as the weight of the leaf node. According to formula L N ＝∑(W i *n i ) Calculating the weight of each binary treePath lengths of (L) 1 Corresponding binary tree numbered (a), L 2 Corresponding binary tree numbered (b), L 3 Corresponding binary tree numbered (c), L 4 Corresponding binary tree numbered (d), L 5 Binary tree corresponding to number (e):
L 1 ＝50×2+150×2+200×2+300×2＝1400
L 2 ＝50×3+150×3+200×2+300×1＝1300
L 3 ＝50×2+150×3+200×3+300×1＝1450
L 4 ＝300×3+200×3+150×2+50×1＝1850
L 5 ＝300×1+200×2+150×3+50×3＝1300
the binary tree with the lowest weighted path length is the optimal tree corresponding to the user A, and the binary tree with the reference number (b) is known to be the optimal tree through the calculation, namely the behavior model (b), the behavior model (b) and the behavior model (c) are both binary trees with the lowest weighted path length, and the binary tree corresponding to the behavior model (b) is randomly selected to be the optimal tree. The optimal tree is understood to be the function menu organization structure most suitable for user a.
The user A, the user B, the user C and the user D are a user group with the same characteristics, the optimal tree corresponding to each user in the user group is calculated through the method, and 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 is provided in fig. 5.
The embodiment provides a method for adjusting function menus of an application program based on optimal trees, which is characterized in that the optimal tree corresponding to each target user in a target group is determined through weighted path length, and then a function menu organization structure which is most suitable for the group is analyzed according to the optimal tree corresponding to each user.
Further, on the basis of the foregoing embodiments, the calculating, for the optimal tree corresponding to each target user in the target group, the comprehensive weight of each preset function according to the 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, by the comprehensive weight corresponding to each preset function, the level of the menu to which each preset function in the preset application program belongs, includes:
acquiring the 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 the preset application program, counting the number of each preset function positioned at the depth corresponding to the level in all optimal trees according to the corresponding relation for each level in the preset application program, and obtaining 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 formulaCalculating the comprehensive weight of each preset function;
according to the rule that the comprehensive weight corresponding to the preset function in the menu with smaller hierarchy is greater than the comprehensive weight corresponding to the preset function in the menu with larger hierarchy, adjusting the hierarchy of the menu to which the preset function belongs;
wherein M is i The comprehensive weight corresponding to the ith preset function, m j Representing the number of the ith preset functions corresponding to in the menu of the jth hierarchy,and representing the preset weight corresponding to the menu of the j-th level.
For example, the menu in the preset application program has 3 levels, and the correspondence relationship in this embodiment is: the first-level menu corresponds to a preset function at a position with depth of 1 in the optimal tree, the second-level menu corresponds to a preset function at a position with depth of 2 in the optimal tree, and the third-level menu corresponds to a preset function at a position with depth of 3 in the optimal tree. Fig. 6 shows a schematic diagram of the number of preset functions corresponding to the menus of the levels according to the optimum tree statistics in fig. 5, referring to fig. 6, in the first-level menu, the number of times that "group visit" appears in the binary tree of depth 1 in fig. 5 is 1, the number of times that "fund claim" appears in the binary tree of depth 1 in fig. 5 is 2, the number of times that "order" appears in the binary tree of depth 1 in fig. 5 is 1, and the number of times that "bill" appears in the binary tree of depth 1 in fig. 5 is 0. FIG. 6 builds a model with function items as dimensions, showing the hierarchy of functions in the user menu.
The preset weight of the function items of the primary menu is set to be 5, the preset of the function items of the secondary menu is set to be 3, and the preset of the function items of the tertiary menu is set to be 2. According to the formulaThe comprehensive weight corresponding to each preset function is calculated as follows:
group visit: m is M 1 ＝1*5+2*3+1*2＝13
Funding claim: m is M 2 ＝2*5+0*3+2*2＝14
And (3) list: m is M 3 ＝1*5+1*3+2*2＝12
Bill of lading: m is M 4 ＝0*5+1*3+2*3＝9
According to the comprehensive weights, the levels of menus to which each preset function belongs are adjusted, for example, the comprehensive weights corresponding to 'fund claim' and 'group visit' are larger, the 'fund claim' and the 'group visit' can be arranged on a primary menu (for example, a first page of an APP), the 'order' corresponding to the comprehensive weights are repeated, the 'order' can be arranged on a secondary menu, the comprehensive weights corresponding to the 'order' are minimum, and the 'order' can be arranged on a tertiary menu.
The embodiment provides a method for adjusting the function menu of an application program based on an optimal tree, which realizes the representation of the importance of different functions to a certain user group through comprehensive weights and facilitates the 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, a target binary tree is generated according to the comprehensive weight corresponding to each preset function, and according to the rule that the comprehensive weight corresponding to the preset function with larger depth in the target binary tree is smaller than the comprehensive weight corresponding to the preset function with smaller depth in the target binary tree, nodes corresponding to each preset function are marked in the target binary tree, so that a group optimal tree suitable for the target group is obtained, and the group optimal tree is displayed;
the depth of the target binary tree is equal to the total number of the levels of the menu in the preset application program.
In order to clearly show the function menu organization relationship applicable to the user group, the comprehensive weight can be obtained again to generate a target binary tree, 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 a function menu of an application program based on an optimal tree, which is convenient and visual to know a preset function organization relation applicable to a certain group through a target binary tree.
In a second aspect, the present embodiment provides a method for adjusting preset functions in a menu for a single user, where the method for adjusting a function menu of an application program based on an optimal tree includes:
user behavior data of a target user operating a preset application program is obtained, evaluation parameters representing importance of each preset function in the preset application program to the target user are obtained according to the user behavior data, and the level of a menu to which each preset function in the preset application program belongs is adjusted according to the evaluation parameters.
The embodiment provides a method for adjusting function menus of an application program based on an optimal tree, which aims at an individual user to directly analyze the importance of each preset function relative to the individual user according to user behavior data of the individual user, and then rearrange the preset functions according to the analyzed importance so as to meet the user requirements.
Further, on the basis of the above embodiment, the method further includes:
and obtaining binary trees with different structures, calculating the weighted path length of the binary tree according to the evaluation parameters corresponding to each preset function and the depth corresponding to each preset function in the binary tree determined by the evaluation parameters, using 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 convenient and visual to know a preset function organization relation applicable to a certain user through a binary tree.
The method provided by the embodiment is based on the optimal tree collection and constructs a data modeling method used by a user for the APP function, and can be used for carrying out a mechanism of a certain dynamic adjustment on the function organization and individuation of the APP. Based on the optimal tree, dynamic evaluation and adjustment of system function organization are realized by taking user experience and improvement of system use efficiency as cores, so that the system function organization has pertinence and customization. According to the using habit of the user, an algorithm is realized by taking the optimal tree as a core, and a system function structure menu which is most suitable for the operating habit of the user is dynamically and efficiently organized for the user.
In the method provided by the implementation, user behavior information is introduced in the process of user demand understanding, existing knowledge and previous memories are fused similar to human thinking, behaviors are modeled, an optimal tree algorithm is introduced, and a system function structure is dynamically organized according to daily operation habits of users, so that the users can operate more quickly and conveniently, the user experience is improved to a great extent while the work efficiency of the users is improved, and the method has the following summarizing advantages: (1) The proposal takes the optimal tree as an algorithm core, can dynamically present the most 'gastrostomy' function menu for the user in real time. (2) The proposal is based on the operation behavior of the user to carry out specific algorithm processing, thereby having more rationality. (3) According to the proposal, the function menu is divided into layers according to different dimensions, so that the service efficiency of the system is greatly improved. (4) And the manager can monitor the actual service conditions of the service through the weight configuration and the optimal tree with different dimensions, reasonably presents a function menu for the user, plays a certain guiding role for the user, is more convenient for service supervision, promotes the development of guiding the service and ensures the high efficiency of the service.
Fig. 8 is a block diagram of the 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 acquisition module 801, a calculation module 802, and an adjustment 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 operating on 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 on 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 corresponding to each preset function in the binary tree determined by the evaluation parameter, and use a binary tree with a minimum weighted path length as an optimal tree corresponding to the target user;
the adjustment module 803 is configured to calculate, for an optimal tree corresponding to each target user in the target group, a comprehensive weight of each preset function according to a 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 device for adjusting the application function menu based on the optimal tree provided in this embodiment is applicable to the method for adjusting the application function menu based on the optimal tree provided in the above embodiment, and will not be described herein.
The embodiment provides a device for adjusting an application program function menu based on an optimal tree, which aims at a target group using a certain preset application program, collects user behavior data of each target user in the target group for operating the preset application program, and according to the user behavior data, reflects the optimal tree of importance of each preset function of the application program to the target user through a binary tree. And calculating comprehensive weights which can reflect the importance of each preset function for the target group according to 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 weights so that the setting of each preset function in the menu of the preset application program meets the requirements of the user and is convenient for the user to use. The device can quickly obtain the result of 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 accords with the use habit of the user, meets the requirement of the user, and is convenient for the user to operate.
Fig. 9 is a block diagram showing the structure of an electronic apparatus provided in the present embodiment.
Referring to fig. 9, the electronic apparatus includes: a processor (processor) 901, a memory (memory) 902, a communication interface (Communications Interface) 903, and a bus 904;
wherein, the liquid crystal display device comprises a liquid crystal display device,
the processor 901, the memory 902, the communication interface 903, and the bus 904 complete the communication therebetween;
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 the program instructions in the memory 902 to perform the methods provided in 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 acquiring 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 corresponding to each preset function in the binary tree determined by the evaluation parameter, 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 according to the depth of each preset function in each optimal tree and the preset weights corresponding to the menus of different levels in the preset application program, and adjusting the level of the menu of each preset function in the preset application program by the comprehensive weight corresponding to each preset function.
The present embodiment provides a non-transitory computer-readable storage medium storing computer instructions that cause a computer to perform the methods provided by the above-described 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 acquiring 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 corresponding to each preset function in the binary tree determined by the evaluation parameter, 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 according to the depth of each preset function in each optimal tree and the preset weights corresponding to the menus of different levels in the preset application program, and adjusting the level of the menu of each preset function in the preset application program by the comprehensive weight corresponding to each preset function.
The present embodiment discloses 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, are capable of performing 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 acquiring 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 corresponding to each preset function in the binary tree determined by the evaluation parameter, 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 according to the depth of each preset function in each optimal tree and the preset weights corresponding to the menus of different levels in the preset application program, and adjusting the level of the menu of each preset function in the preset application program by the comprehensive weight corresponding to each preset function.
Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the above method embodiments may be implemented by hardware associated with program instructions, where the foregoing program may be stored in a computer readable storage medium, and when executed, the program performs steps including the above method embodiments; and the aforementioned storage medium includes: various media that can store program code, such as ROM, RAM, magnetic or optical disks.
The above-described embodiments of electronic devices and the like are merely illustrative, wherein the elements described as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. Based on this understanding, the foregoing technical solution may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method described in the respective embodiments or some parts of the embodiments.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution 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, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present invention.
Claims (7)
1. A method for adjusting a menu of functions of an application 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 acquiring 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 corresponding to each preset function in the binary tree determined by the evaluation parameter, and taking the binary tree with the minimum weighted path length as the optimal tree corresponding to the target user;
acquiring the 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 the preset application program, counting the number of each preset function positioned at the depth corresponding to the level in all optimal trees according to the corresponding relation for each level in the preset application program, and obtaining 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 formulaCalculating the comprehensive weight of each preset function;
according to the rule that the comprehensive weight corresponding to the preset function in the menu with smaller hierarchy is greater than the comprehensive weight corresponding to the preset function in the menu with larger hierarchy, adjusting the hierarchy of the menu to which the preset function belongs;
wherein M is i The comprehensive weight corresponding to the ith preset function, m j Representing the number of the ith preset functions corresponding to in the menu of the jth hierarchy,and representing the preset weight corresponding to the menu of the j-th level.
2. The method according to claim 1, wherein the obtaining, for each target user in the target group, user behavior data of the target user operating on 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:
obtaining user behavior data of the target users operating a preset application program for each target user in a target group, and respectively counting the frequency of the target users operating each preset function in 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, calculates a weighted path length of the binary tree according to an evaluation parameter corresponding to each preset function and a depth corresponding to each preset function in the binary tree determined by the evaluation parameter, and uses a 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 the binary tree according to the rule that the frequency corresponding to the preset function with larger depth in the binary tree is smaller than the frequency corresponding to the preset function with smaller depth in the binary tree for each binary tree by the frequency corresponding to each preset function;
according to formula L N ＝∑(W i *n i ) 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 is N For the weighted path length, W, corresponding to the Nth binary tree i Representing the evaluation parameter corresponding to the ith preset function in the Nth binary tree, N i Representing the depth of the ith preset function in the nth binary tree.
4. The method as recited in claim 1, further comprising:
after the comprehensive weight of each preset function is calculated, a target binary tree is generated according to the comprehensive weight corresponding to each preset function, and according to the rule that the comprehensive weight corresponding to the preset function with larger depth in the target binary tree is smaller than the comprehensive weight corresponding to the preset function with smaller depth in the target binary tree, nodes corresponding to each preset function are marked in the target binary tree, so that a group optimal tree suitable for the target group is obtained, and the group optimal tree is displayed;
the depth of the target binary tree is equal to the total number of the levels of the menu in the preset application program.
5. An apparatus for adjusting a menu of functions of an application based on an optimal tree, comprising:
the acquisition module is used for acquiring user behavior data of each target user in a target group, wherein the user behavior data are operated by the target user on a preset application program, and the evaluation parameters which represent the importance of each preset function in the preset application program on the target user are obtained according to the user behavior data;
the computing module is used for acquiring binary trees with different structures, computing the weighted path length of the binary tree according to the evaluation parameter corresponding to each preset function and the depth corresponding to each preset function in the binary tree determined by the evaluation parameter, and taking the binary tree with the minimum weighted path length as the optimal tree corresponding to the target user;
the corresponding relation acquisition module is used for acquiring the corresponding relation between the depth of the preset function in the optimal tree and the level of the menu to which the preset function belongs in the preset application program, counting the number of each preset function positioned at the depth corresponding to the level in all the optimal tree according to the corresponding relation in each level in the preset application program, and obtaining the number corresponding to each preset function in the menu of each level;
the preset weight acquisition module is used for acquiring preset weights corresponding to menus of different levels in the preset application program and according to a formulaCalculating the comprehensive weight of each preset function;
the menu level adjusting module is used for adjusting the level of the menu to which the preset function belongs according to the rule that the comprehensive weight corresponding to the preset function in the menu with smaller level is greater than the comprehensive weight corresponding to the preset function in the menu with larger level;
wherein M is i The comprehensive weight corresponding to the ith preset function, m j Representing the number of the ith preset functions corresponding to in the menu of the jth hierarchy,and representing the preset weight corresponding to the menu of the j-th level.
6. An electronic device, comprising:
at least one processor, at least one memory, a communication interface, and a bus; wherein, the liquid crystal display device comprises a liquid crystal display device,
the processor, the memory and the communication interface complete the communication with each other 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 1-4.
7. A non-transitory computer readable storage medium storing computer instructions that cause the computer to perform the method of any one of claims 1 to 4.
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