CN114968028A - Method, apparatus, and medium for dynamically changing menu layout based on user behavior analysis - Google Patents
Method, apparatus, and medium for dynamically changing menu layout based on user behavior analysis Download PDFInfo
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- CN114968028A CN114968028A CN202210568262.2A CN202210568262A CN114968028A CN 114968028 A CN114968028 A CN 114968028A CN 202210568262 A CN202210568262 A CN 202210568262A CN 114968028 A CN114968028 A CN 114968028A
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
- G06F3/048—Interaction techniques based on graphical user interfaces [GUI]
- G06F3/0481—Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance
- G06F3/0482—Interaction with lists of selectable items, e.g. menus
Abstract
The application discloses a method, equipment and a medium for dynamically changing menu layout based on user behavior analysis, which are used for solving the technical problems that the menu layout cannot be dynamically modified according to user requirements in the conventional menu layout, and user experience is reduced. The method comprises the following steps: acquiring user behavior data of a user accessing a menu application, storing the user behavior data into a user behavior log, preprocessing the user behavior data, and determining the accumulated click times, the accumulated use duration and the use frequency of the menu application in the user behavior data; according to the weight coefficients corresponding to the accumulated click times, the accumulated use duration and the use frequency determined by the preset rule, carrying out weighted summation on the accumulated click times, the accumulated use duration and the use frequency of the menu application so as to determine the priority corresponding to each menu application; according to the priority of the menu application, the menu applications are sequentially arranged at the corresponding initial positions, so that the dynamic change of the menu arrangement is realized, the user operation is facilitated, and the user experience is improved.
Description
Technical Field
The present application relates to the field of big data technologies, and in particular, to a method, an apparatus, and a medium for dynamically changing a menu layout based on user behavior analysis.
Background
With the rapid development of the internet and big data technology, more and more enterprises carry out digital transformation. The corresponding system and cloud service are inevitably induced by digital transformation, and a great deal of time is occupied by the use of various systems and complicated functions. The dynamic layout of the menu has the advantages of flexibility and humanization, and the priority of the menu frequently used by the user can be calculated according to an algorithm, so that the menu most possibly used by the user is displayed to a position with higher priority.
However, the menu layout in the prior art is static, and the menu layout cannot be dynamically modified according to the actual requirements of the user, so that the use experience of the user is reduced.
Disclosure of Invention
The embodiment of the application provides a method, equipment and a medium for dynamically changing menu layout based on user behavior analysis, and aims to solve the technical problems that the existing menu layout is static, the menu layout cannot be dynamically modified according to the actual requirements of a user, and the use experience of the user is reduced.
In one aspect, an embodiment of the present application provides a method for dynamically changing a menu layout based on user behavior analysis, including:
acquiring user behavior data of a user accessing a menu application through a log collection system according to a preset time interval; the user behavior data comprises the accumulated use times, the accumulated use duration and the use frequency of the menu application;
storing the user behavior data into a user behavior log, preprocessing the user behavior data in the user behavior log, and determining the cumulative click times, the cumulative use duration and the use frequency of the menu application in the user behavior data;
determining weight coefficients corresponding to the accumulated click times, the accumulated use time and the use frequency according to a preset rule, and performing weighted summation on the accumulated click times, the accumulated use time and the use frequency of the menu applications according to the corresponding weight coefficients to determine the priority corresponding to each menu application;
sequencing the menu applications based on the priorities of the menu applications, and sequentially laying out the menu applications at corresponding initial positions according to the priority order of the menu applications; and the priority of the initial position corresponds to the priority of the menu application one by one.
In an implementation manner of the present application, the sequentially laying out each of the menu applications before the corresponding initial position according to the priority order of each of the menu applications, where the method further includes:
acquiring historical behavior data of the user from a Hadoop distributed file system, and determining the cumulative click times of the user on each menu application according to the historical behavior data;
determining the clicking habit of the user according to the accumulated clicking times corresponding to the menu applications, and determining the significant value of the initial position corresponding to the menu applications according to the clicking habit of the user;
and sequencing the initial positions of the menu applications according to the descending order of the significance values of the initial positions of the menu applications to obtain the priority of the initial positions.
In an implementation manner of the present application, before determining the weight coefficients corresponding to the cumulative click number, the cumulative usage duration, and the usage frequency according to a preset rule, the method further includes:
respectively determining the corresponding proportions of the accumulated click times, the accumulated use duration and the use frequency according to the influence degrees of the accumulated click times, the accumulated use duration and the use frequency on the use of the menu application by the user;
and determining a weight coefficient setting rule of the accumulated click times, the accumulated use time and the use frequency according to the corresponding proportion.
In an implementation manner of the present application, the preprocessing the user behavior data in the user behavior log to determine the cumulative click times, the cumulative use duration, and the use frequency of the menu application in the user behavior data specifically includes:
writing the user behavior log into a Hadoop distributed file system, and based on a preset MapReduce model, segmenting user behavior data in the user behavior log so as to divide the user behavior data into the cumulative click times, the cumulative use duration and the use frequency of menu application.
In an implementation manner of the present application, before performing weighted summation on the cumulative click times, the cumulative usage duration, and the usage frequency of the menu applications according to the corresponding weight coefficients to determine the priorities corresponding to the menu applications, the method further includes:
respectively determining a first weight, a second weight and a third weight corresponding to the menu application; the first weight is a weight corresponding to the accumulated click times of the menu application, the second weight is a weight corresponding to the accumulated service duration of the menu application, and the third weight is a weight corresponding to the service frequency of the menu application.
In an implementation manner of the present application, the weighting and summing the cumulative number of clicks, the cumulative duration of use, and the frequency of use of the menu application according to the weight coefficient to obtain a priority corresponding to each menu application specifically includes:
according to the first weight corresponding to the accumulated clicking times, the second weight corresponding to the accumulated using time length, the third weight corresponding to the using frequency and the weight coefficients corresponding to the accumulated clicking times, the accumulated using time length and the using frequency respectively, carrying out weighted summation on the accumulated clicking times, the accumulated using time length and the using frequency of the menu application to obtain the weighted value corresponding to the menu application;
and determining the priority corresponding to each menu application according to the weighted value corresponding to each menu application.
In an implementation manner of the present application, after the obtaining, by the log collection system and according to a preset time interval, user behavior data of a user accessing the menu application, the method further includes:
determining whether null values and repeated values exist in the user behavior data or not based on a preset function, and if so, filling null values and filtering repeated values in the user behavior data;
and converting the filtered user behavior data into a preset format to obtain the user behavior data to be used.
In an implementation manner of the present application, the sorting the menu applications based on the priorities corresponding to the menu applications specifically includes:
acquiring the priority corresponding to each menu application, and sequencing the menu applications according to a preset sequencing mode on the basis of the priority corresponding to each menu application;
wherein, the preset sequencing mode comprises: according to the sequence of the priority from large to small or according to the sequence of the priority from small to large.
On the other hand, an embodiment of the present application further provides an apparatus for dynamically changing a menu layout based on user behavior analysis, where the apparatus includes:
at least one processor;
and a memory communicatively coupled to the at least one processor;
wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to:
a method of dynamically changing the layout of a menu based on analysis of user behavior as described above is performed.
In another aspect, an embodiment of the present application further provides a non-volatile computer storage medium storing computer-executable instructions, where the computer-executable instructions are configured to:
such as the method of dynamically changing menu layout based on user behavior analysis described above.
The embodiment of the application provides a method, equipment and a medium for dynamically changing menu layout based on user behavior analysis, and the method, the equipment and the medium at least have the following beneficial effects: the menu application frequently used by the user can be determined by acquiring the user behavior data when the user accesses the menu application, so that the menu application most probably used by the user is displayed to the most obvious menu position, the time consumed by the user for searching for the corresponding menu application in various functions can be saved, and the system use experience of the user is improved. According to the method and the device, the menu layout of the system is dynamically changed based on the user behaviors in the user behavior data, so that the menu layout has more flexibility and practicability, and the user operation is facilitated.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
fig. 1 is a schematic flowchart of a method for dynamically changing a menu layout based on user behavior analysis according to an embodiment of the present application;
fig. 2 is a schematic diagram of an internal structure of a device for dynamically changing a menu layout based on user behavior analysis according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be described in detail and completely with reference to the following specific embodiments of the present application and the accompanying drawings. It should be apparent that the described embodiments are only some of the embodiments of the present application, and not all of the embodiments. 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 application.
The embodiment of the application provides a method, equipment and a medium for dynamically changing menu layout based on user behavior analysis, and the menu application commonly used by a user can be determined by acquiring user behavior data when the user accesses the menu application, so that the menu application most probably used by the user is displayed to the most prominent menu position, the time consumed by the user for searching for the corresponding menu application in various functions can be saved, and the system use experience of the user is improved. According to the method and the device, the menu layout of the system is dynamically changed based on the user behaviors in the user behavior data, so that the menu layout has more flexibility and practicability, and the user operation is facilitated. The technical problems that the existing menu layout is static, dynamic modification can not be carried out on the menu layout according to the actual requirements of a user, and the use experience of the user is reduced are solved.
Fig. 1 is a schematic flowchart of a method for dynamically changing a menu layout based on user behavior analysis according to an embodiment of the present application. As shown in fig. 1, the method for dynamically changing a menu layout based on user behavior analysis according to the embodiment of the present application may mainly include the following steps:
step 101: and acquiring user behavior data of the user accessing the menu application according to a preset time interval through a log collection system.
At present, digital wave wind and cloud surge, whether in the Internet industry or the traditional manufacturing industry, strive to be digitally transformed platoon soldiers. Although digital transformation brings convenience, the system with complex functions is also headache for many users.
The server regularly acquires user behavior data of the menu application accessed by the user according to a preset time interval through a log collection system flash, so that the data of the menu application used by the user in the current time interval can be known.
It should be noted that, the user behavior data in the embodiment of the present application at least includes: the user uses the accumulated number of times of use, the accumulated time of use, and the frequency of use of the menu application.
In an embodiment of the application, after acquiring user behavior data of a user access menu application according to a preset time interval through a log collection system, a server determines whether null values and repetition values exist in the user behavior data based on a preset function, if so, performs null value filling and repetition value filtering on the user behavior data, and then converts the filtered user behavior data into a preset format, so as to obtain the user behavior data to be used. Therefore, the acquired user behavior data can meet the use standard, and the subsequent direct acquisition and use are facilitated.
Step 102: and storing the user behavior data into a user behavior log, preprocessing the user behavior data in the user behavior log, and determining the cumulative click times, the cumulative use duration and the use frequency of the menu application in the user behavior data.
The server adds the user behavior log in the system menu, stores the obtained user behavior data into the user behavior log, can facilitate the subsequent direct obtaining of the user behavior data from the user behavior log, and analyzes the user behavior data. And the server preprocesses the user behavior data in the user behavior log so as to determine the accumulated click times, the accumulated use time and the use frequency of each menu application by the user in the user behavior data.
Specifically, the server writes the user behavior log into the Hadoop distributed file system so as to store the user behavior data through the Hadoop distributed file system, and follow-up data can be conveniently found. The server acquires user behavior data from the Hadoop distributed file system, and divides the user behavior data based on a preset MapReduce model in the Hadoop distributed file system, so that the user behavior data is divided into the accumulated click times, the accumulated use duration and the use frequency of the menu applications, and the actual use data corresponding to each menu application used by the user is determined.
According to the method and the device, a storage function is provided for the user behavior data through the HDFS in the Hadoop distributed file system, a processing and analyzing function is provided for the user behavior data through a preset MapReduce model in the Hadoop distributed file system, the user behavior data are classified and collected, and the flexibility and the expandability of the menu layout are high.
Step 103: and determining the weight coefficients corresponding to the accumulated clicking times, the accumulated using time and the using frequency according to a preset rule, and performing weighted summation on the accumulated clicking times, the accumulated using time and the using frequency of the menu application according to the corresponding weight coefficients to determine the priority corresponding to each menu application.
The server respectively determines corresponding weight coefficients for the accumulated click times, the accumulated use time and the use frequency according to a predetermined weight coefficient setting rule, and then respectively performs weighted summation on the accumulated click times, the accumulated use time and the use frequency of each menu application according to the corresponding weight coefficients, so as to determine the corresponding priority of each menu application.
In an embodiment of the application, before determining the weight coefficients corresponding to the accumulated click times, the accumulated use time and the use frequency according to a preset rule, the server determines the corresponding proportions of the accumulated click times, the accumulated use time and the use frequency according to the influence degree of the accumulated click times, the accumulated use time and the use frequency in the user behavior data on the use menu application of the user, and then determines the weight coefficient setting rule of the accumulated click times, the accumulated use time and the use frequency according to the determined corresponding proportions.
It should be noted that, in the embodiment of the present application, the accumulated number of clicks may be based on a click habit of a user on a menu page, and a menu application at a specified position is clicked each time, so that the click habit of the user may be determined according to the accumulated number of clicks. The accumulated time duration can indicate that the user needs to continuously use the specified menu application, so that the use needs of the user can be determined. The frequency of use enables the most common menu application for the user to be determined.
In an embodiment of the application, before the server performs weighted summation on the accumulated click times, the accumulated usage duration, and the usage frequency of the menu applications according to the corresponding weight coefficients to determine the priorities corresponding to the menu applications, it is required to determine a first weight, a second weight, and a third weight corresponding to each menu application.
It should be noted that, in this embodiment of the application, the first weight is a weight corresponding to an accumulated number of clicks of a menu application, the second weight is a weight corresponding to an accumulated usage duration of the menu application, and the third weight is a weight corresponding to a usage frequency of the menu application.
Specifically, the server performs weighted summation on the accumulated click times, the accumulated use duration and the use frequency of each menu application according to a first weight corresponding to the accumulated click times, a second weight corresponding to the accumulated use duration, a third weight corresponding to the use frequency and weight coefficients corresponding to the accumulated click times, the accumulated use duration and the use frequency respectively, so as to obtain a weighted value corresponding to the menu application, and then determines a priority corresponding to each menu application according to the weighted value corresponding to each menu application.
Step 104: and sequencing the menu applications based on the priorities corresponding to the menu applications, and sequentially laying out the menu applications at the corresponding initial positions according to the priority sequence of the menu applications.
The server obtains the priority corresponding to each determined menu application, then sorts the menu applications according to the corresponding priority, and sequentially arranges each menu application at the corresponding initial position according to the priority sequence of each menu application. Therefore, the menu application which is most likely to be frequently used by the user can be placed at the most obvious position of the menu, the searching time of the user is saved, and the user experience is improved.
Specifically, the server obtains the priority corresponding to each menu application, and then sorts each menu application according to a preset sorting mode based on the priority corresponding to each menu application. It should be noted that the preset ordering manner in the embodiment of the present application includes: and sorting according to the sequence of the priorities from big to small or according to the sequence of the priorities from small to big.
In an embodiment of the application, the server needs to obtain historical behavior data of a user from a Hadoop distributed file system before sequentially laying out the menu applications at corresponding initial positions according to priority sequences of the menu applications, determines cumulative click times of the user on the menu applications according to the historical behavior data, determines click habits of the user according to the cumulative click times corresponding to the menu applications, determines significant values of the initial positions corresponding to the menu applications according to the click habits of the user, and can sequence the initial positions of the menu applications according to the sequence of the significant values of the initial positions corresponding to the menu applications from large to small to obtain the priority of the initial positions. Therefore, the menu applications commonly used by the user can be sequentially displayed at the most obvious menu positions.
The above is a method embodiment proposed in the present application. Based on the same inventive concept, the embodiment of the present application further provides a device for dynamically changing a menu layout based on user behavior analysis, and the structure of the device is shown in fig. 2.
Fig. 2 is a schematic diagram of an internal structure of a device for dynamically changing a menu layout based on user behavior analysis according to an embodiment of the present application. As shown in fig. 2, the apparatus includes:
at least one processor;
and a memory communicatively coupled to the at least one processor;
wherein the memory stores instructions executable by the at least one processor to cause the at least one processor to:
acquiring user behavior data of a user accessing a menu application according to a preset time interval through a log collection system; the user behavior data comprises the accumulated use times, the accumulated use duration and the use frequency of the menu application;
storing the user behavior data into a user behavior log, preprocessing the user behavior data in the user behavior log, and determining the cumulative click times, the cumulative use duration and the use frequency of the menu application in the user behavior data;
determining the weight coefficients corresponding to the accumulated click times, the accumulated use time and the use frequency according to a preset rule, and performing weighted summation on the accumulated click times, the accumulated use time and the use frequency of the menu application according to the corresponding weight coefficients to determine the priority corresponding to each menu application;
sequencing the menu applications based on the priorities corresponding to the menu applications, and sequentially laying out the menu applications at corresponding initial positions according to the priority sequence; wherein, the priority of the initial position corresponds to the priority of the menu application one by one.
An embodiment of the present application further provides a non-volatile computer storage medium, in which computer-executable instructions are stored, and the computer-executable instructions are configured to:
acquiring user behavior data of a user accessing a menu application according to a preset time interval through a log collection system; the user behavior data comprises the accumulated use times, the accumulated use duration and the use frequency of the menu application;
storing the user behavior data into a user behavior log, preprocessing the user behavior data in the user behavior log, and determining the cumulative click times, the cumulative use duration and the use frequency of the menu application in the user behavior data;
determining the weight coefficients corresponding to the accumulated clicking times, the accumulated using time and the using frequency according to a preset rule, and performing weighted summation on the accumulated clicking times, the accumulated using time and the using frequency of the menu application according to the corresponding weight coefficients to determine the priority corresponding to each menu application;
sequencing the menu applications based on the priorities corresponding to the menu applications, and sequentially laying out the menu applications at corresponding initial positions according to the priority sequence; wherein, the priority of the initial position corresponds to the priority of the menu application one by one.
The embodiments in the present application are described in a progressive manner, and the same and similar parts among the embodiments can be referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the device and media embodiments, the description is relatively simple as it is substantially similar to the method embodiments, and reference may be made to some descriptions of the method embodiments for relevant points.
The device and the medium provided by the embodiment of the application correspond to the method one to one, so the device and the medium also have the similar beneficial technical effects as the corresponding method, and the beneficial technical effects of the method are explained in detail above, so the beneficial technical effects of the device and the medium are not repeated herein.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The above description is only an example of the present application and is not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (10)
1. A method for dynamically changing a menu layout based on user behavior analysis, the method comprising:
acquiring user behavior data of a user accessing a menu application according to a preset time interval through a log collection system; the user behavior data comprises the accumulated use times, the accumulated use duration and the use frequency of the menu application;
storing the user behavior data into a user behavior log, preprocessing the user behavior data in the user behavior log, and determining the cumulative click times, the cumulative use duration and the use frequency of the menu application in the user behavior data;
determining weight coefficients corresponding to the accumulated click times, the accumulated use time and the use frequency according to a preset rule, and performing weighted summation on the accumulated click times, the accumulated use time and the use frequency of the menu applications according to the corresponding weight coefficients to determine the priority corresponding to each menu application;
sequencing the menu applications based on the priorities of the menu applications, and sequentially laying out the menu applications at corresponding initial positions according to the priority order of the menu applications; and the priority of the initial position corresponds to the priority of the menu application one by one.
2. The method of claim 1, wherein the menu applications are sequentially laid out before corresponding initial positions according to the priority order of the menu applications, and the method further comprises:
acquiring historical behavior data of the user from a Hadoop distributed file system, and determining the cumulative click times of the user on each menu application according to the historical behavior data;
determining the clicking habit of the user according to the accumulated clicking times corresponding to the menu applications, and determining the significant value of the initial position corresponding to the menu applications according to the clicking habit of the user;
and sequencing the initial positions of the menu applications according to the descending order of the significance values of the initial positions of the menu applications to obtain the priority of the initial positions.
3. The method of claim 1, wherein before determining the weighting coefficients corresponding to the cumulative number of clicks, the cumulative duration of use, and the frequency of use according to the predetermined rule, the method further comprises:
respectively determining the corresponding proportions of the accumulated click times, the accumulated use duration and the use frequency according to the influence degrees of the accumulated click times, the accumulated use duration and the use frequency on the use of the menu application by the user;
and determining a weight coefficient setting rule of the accumulated click times, the accumulated use duration and the use frequency according to the corresponding proportion.
4. The method of claim 1, wherein the preprocessing is performed on the user behavior data in the user behavior log to determine the cumulative number of clicks, cumulative duration of use, and frequency of use of the menu application in the user behavior data, and specifically comprises:
writing the user behavior log into a Hadoop distributed file system, and based on a preset MapReduce model, segmenting user behavior data in the user behavior log so as to divide the user behavior data into the cumulative click times, the cumulative use duration and the use frequency of menu application.
5. The method of claim 1, wherein before performing a weighted summation of the cumulative number of clicks, the cumulative duration of use, and the frequency of use of the menu applications according to the corresponding weighting factors to determine the priority corresponding to each of the menu applications, the method further comprises:
respectively determining a first weight, a second weight and a third weight corresponding to the menu application; the first weight is a weight corresponding to the accumulated click times of the menu application, the second weight is a weight corresponding to the accumulated service duration of the menu application, and the third weight is a weight corresponding to the service frequency of the menu application.
6. The method of claim 1, wherein the step of performing a weighted summation on the cumulative number of clicks, the cumulative duration of use, and the frequency of use of the menu applications according to the weighting coefficients to obtain the priority corresponding to each menu application comprises:
according to the first weight corresponding to the accumulated clicking times, the second weight corresponding to the accumulated using time length, the third weight corresponding to the using frequency and the weight coefficients corresponding to the accumulated clicking times, the accumulated using time length and the using frequency respectively, carrying out weighted summation on the accumulated clicking times, the accumulated using time length and the using frequency of the menu application to obtain the weighted value corresponding to the menu application;
and determining the priority corresponding to each menu application according to the weighted value corresponding to each menu application.
7. The method of claim 1, wherein after the obtaining of the user behavior data of the user accessing the menu application by the log collection system at the preset time interval, the method further comprises:
determining whether null values and repeated values exist in the user behavior data or not based on a preset function, and if so, filling null values and filtering repeated values in the user behavior data;
and converting the filtered user behavior data into a preset format to obtain the user behavior data to be used.
8. The method as claimed in claim 1, wherein the step of ranking each of the menu applications based on the priority level corresponding to each of the menu applications comprises:
acquiring the priority corresponding to each menu application, and sequencing the menu applications according to a preset sequencing mode on the basis of the priority corresponding to each menu application;
wherein, the preset sequencing mode comprises: according to the sequence of the priority from large to small or according to the sequence of the priority from small to large.
9. Apparatus for dynamically changing a menu layout based on user behavior analysis, the apparatus comprising:
at least one processor;
and a memory communicatively coupled to the at least one processor;
wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to:
a method of dynamically changing a menu layout based on user behavior analysis according to any of claims 1-8 is performed.
10. A non-transitory computer storage medium storing computer-executable instructions, the computer-executable instructions configured to:
a method of dynamically changing a menu layout based on user behavior analysis according to any of claims 1-8.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116382558A (en) * | 2023-06-07 | 2023-07-04 | 深圳市欣威智能有限公司 | Writing effect determining method and device, electronic pen, computer equipment and medium |
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