CN110602322A - Method and device for layout of application icons and mobile terminal - Google Patents
Method and device for layout of application icons and mobile terminal Download PDFInfo
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- CN110602322A CN110602322A CN201910861769.5A CN201910861769A CN110602322A CN 110602322 A CN110602322 A CN 110602322A CN 201910861769 A CN201910861769 A CN 201910861769A CN 110602322 A CN110602322 A CN 110602322A
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- 238000012163 sequencing technique Methods 0.000 claims abstract description 24
- 230000008451 emotion Effects 0.000 claims description 11
- 230000009466 transformation Effects 0.000 claims description 5
- 230000008569 process Effects 0.000 claims description 3
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M1/00—Substation equipment, e.g. for use by subscribers
- H04M1/72—Mobile telephones; Cordless telephones, i.e. devices for establishing wireless links to base stations without route selection
- H04M1/724—User interfaces specially adapted for cordless or mobile telephones
- H04M1/72469—User interfaces specially adapted for cordless or mobile telephones for operating the device by selecting functions from two or more displayed items, e.g. menus or icons
- H04M1/72472—User interfaces specially adapted for cordless or mobile telephones for operating the device by selecting functions from two or more displayed items, e.g. menus or icons wherein the items are sorted according to specific criteria, e.g. frequency of use
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Abstract
The application discloses a method, a device and a mobile terminal for application icon layout, wherein the method comprises the following steps: acquiring an application operation log of a user; generating a user use habit label according to an application operation log of a user, wherein the user use habit label comprises an application searching difficulty label; sequencing the applications according to the use habit tags of the users; and laying out the application icons according to the sequencing result. According to the technical scheme, the using habits of the user on the mobile phone are collected, the difficulty level label of the user when the user searches the APP is obtained according to the screen sliding operation of the user, the personalized recommendation of the user is perfected by utilizing the label, and the personalized mobile phone using experience of the user is improved and enriched.
Description
Technical Field
The present application relates to the field of mobile devices, and in particular, to a method and an apparatus for layout of application icons, and a mobile terminal.
Background
With the development of the internet, mobile terminals are on a trend to replace PCs in daily life. In terms of internet applications, the browser/server architecture of the PC era gradually evolved to the client/server architecture. More and more service and application providers are offering services to users by providing Applications (APPs) on mobile terminals, which can save costs while improving user stickiness, in particular avoiding the cost of delivering advertisements to search engines.
With the continuous evolution of services, more and more APPs are used by mobile terminals. According to the statistics of Ministry of industry and belief, at the end of 5 months in 2018, 415 ten thousand mobile Applications (APP) are monitored in the market of China. Such numerous APP applications are struggling for the location on the user's mobile phone desktop, which is a result of congestion. A typical user has hundreds of APP applications on a mobile phone desktop, and when the user uses a mobile phone, application icons are generally tiled on the desktop in a grid manner. At this time, the user needs to turn the screen page by page to search for a certain APP application, which is time-consuming and inconvenient.
In order to solve the above problems, the prior art also provides some solutions. For example, the patent "method and system for desktop application icon layout" (application number: 201410161315.4) improves the efficiency of viewing application icons by creating a first icon display area and a second icon display area on the desktop, and displaying the application icons of the acquired recommended applications directly on the first icon display area. Also, for example, in the patent "icon layout method, computer-readable storage medium, and terminal device" (application No. 201810921158.0), the use frequency of an application is obtained by specifying a history use record of the application, and the icon is displayed according to the use frequency and the priority of the icon display area, so that the user can conveniently find the icon of a sub-application that is used conventionally, and the operation efficiency of the user is improved.
However, in the related art, icons are basically all placed from left to right and from top to bottom according to the usage frequency of the application, and usage habit information other than the usage frequency of the application is not considered.
Disclosure of Invention
In view of this, the present application provides a method and an apparatus for layout of application icons, and a mobile terminal, so as to complete personalized layout of application icons.
According to an aspect of the present application, a method of applying an icon layout is proposed, the method comprising:
acquiring an application operation log of a user;
generating a user use habit label according to an application operation log of a user, wherein the user use habit label comprises an application searching difficulty label;
sequencing the applications according to the use habit tags of the users;
and laying out the application icons according to the sequencing result.
Preferably, the application search ease level tab is determined according to the number and direction of screen strokes during opening of the application.
Preferably, the application search difficulty level tag is the sum of the application search difficulty scores/the number of times of application use, and the application search difficulty level tag is α 1+ α 2 + α 3+ the number of times of stroking transformation, where α 1, α 2, and α 3 are preset coefficients.
Preferably, the user usage habit tag further comprises at least one of an application type, an application open time tag, an application usage habit tag, an application average usage duration tag, an application search difficulty level tag, and a key time period user emotion index tag.
Preferably, the sorting the applications according to the user usage habit tags comprises:
and scoring the applications according to the habit tags used by the user and a preset calculation rule, and sequencing the applications according to a scoring result.
Preferably, the calculation rule comprises giving a weight to each tag.
Preferably, the laying out the application icons according to the sorting result includes:
the first N icons are laid out in the middle of the screen, and/or the first M icons are laid out in the middle of the recommendation area, M, N being a positive integer.
Preferably, the laying out the application icons according to the sorting result includes:
according to the sorting result, the application is laid out on the screen or the recommended area according to the following rules:
the middle is prior to the two sides, the inner circle is prior to the outer circle, the left side is prior to the right side, and the upper side is prior to the lower side.
The application provides a device of application icon overall arrangement, the device includes:
the acquisition module is used for acquiring an application operation log of a user;
the generating module is used for generating a user use habit label according to the application operation log of the user, wherein the user use habit label comprises an application searching difficulty label;
the sequencing module is used for sequencing the applications according to the use habit tags of the users;
and the layout module is used for laying out the application icons according to the sequencing result.
Preferably, the generating module is further configured to determine the application search difficulty level tag according to the number and the direction of the screen strokes in the process of opening the application.
Preferably, the application search difficulty level tag is the sum of the application search difficulty scores/the number of times of application use, and the application search difficulty level tag is α 1+ α 2 + α 3+ the number of times of stroking transformation, where α 1, α 2, and α 3 are preset coefficients.
Preferably, the user usage habit tag further comprises at least one of an application type, an application open time tag, an application usage habit tag, an application average usage duration tag, an application search difficulty level tag, and a key time period user emotion index tag.
Preferably, the ranking module is further configured to score the applications according to the habit tags used by the user and a preset calculation rule, and rank the applications according to a scoring result.
Preferably, the calculation rule comprises giving a weight to each tag.
Preferably, the application module is further configured to layout the first N icons in the middle of the screen, and/or layout the first M icons in the middle of the recommendation area, M, N being a positive integer.
Preferably, the application module is further configured to, according to the sorting result, lay out the application on the screen or the recommended area according to the following rule:
the middle is prior to the two sides, the inner circle is prior to the outer circle, the left side is prior to the right side, and the upper side is prior to the lower side.
The application provides a mobile terminal, which comprises a memory and a processor;
a memory for storing a program;
a processor for executing a program to perform the steps of:
acquiring an application operation log of a user;
generating a user use habit label according to an application operation log of a user, wherein the user use habit label comprises an application searching difficulty label;
sequencing the applications according to the use habit tags of the users;
and laying out the application icons according to the sequencing result.
According to the technical scheme, the using habits of the user on the mobile phone are collected, the difficulty level label of the user when the user searches the APP is obtained according to the screen sliding operation of the user, the personalized recommendation of the user is perfected by utilizing the label, and the personalized mobile phone using experience of the user is improved and enriched.
Additional features and advantages of the present application will be described in detail in the detailed description which follows.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate an embodiment of the invention and, together with the description, serve to explain the invention. In the drawings:
fig. 1 is a schematic diagram of an application icon layout method provided in the present application;
FIGS. 2A-2B are schematic diagrams of screens with recommended fields;
3A-3C are schematic diagrams of application icon layouts provided by embodiments of the present application;
FIG. 4 is a schematic diagram of an application icon apparatus provided herein;
fig. 5 is a schematic diagram of a mobile terminal provided in the present application.
Detailed Description
In addition, the features of the embodiments and the respective embodiments in the present application may be combined with each other without conflict.
The present application will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
The method aims to deeply dig the historical use habits of APP such as screen sliding behaviors and the like in the process that a user uses a mobile phone, so that the layout of the desktop icons of the user is recommended in an individualized mode, the recommended result is presented on an independent recommended column, or the layout sequence of the multi-screen desktop icons is optimized by utilizing the recommended result.
User usage habits as used herein include, but are not limited to: the method comprises the following steps of screen-sliding direction of the mobile phone, screen-sliding time of the mobile phone, APP name, APP type, APP opening time, APP closing time and current APP icon position (several screens). Further, the application generates a user use habit tag for each application according to the user use habit, such as an APP name, an APP current position, APP opening times, an APP common period, an APP average use duration, an APP search difficulty degree, a key period user emotion index and the like. As shown in table 1:
TABLE 1 user APP usage habit Tab
APP 1-APP N represent N applications.
The APP type represents the type of the APP, such as tourism, entertainment, reading, games, education, office work and the like, can be combined with the conventional period of the APP, analyzes the APP theme type opened by the habit of a user in a certain special period, and can prepare for theme recommendation in subsequent divided periods.
The APP current position represents the position where the APP is currently located, and may be generally represented as screen row, column, for example, "1 st screen row, 3 rd column" may represent "< 1, 3, 3 >". If the APPs are grouped, the APP icon at the "1 st screen row 3 column 2 row 2 column" position under the 1 st screen row 3 column directory can be expressed as "< 1, 3, 3, <1, 2, 2> >".
The APP turn-on times and APP use times have the same meaning.
The conventional APP time period is divided into an "office peak period (7: 00-9: 00)", "morning (9: 00-12: 00)", "noon (12: 00-14: 00)", "afternoon (14: 00-18: 00)", "night (18: 00-22: 00)", and "late night (22: 00-2: 00) in the next day. The APP average usage duration ═ Σ (APP off-time-APP on-time)/number of APP uses.
The APP searching difficulty degree is ═ Sigma APP searching difficulty score/APP using times, and the APP searching difficulty score is ═ alpha 1 left stroke times + alpha 2 right stroke times + alpha 3 stroke transformation times. α 1, α 2, α 3 may be determined according to the actual stroking situation. The APP lookup difficulty level may be calculated according to a certain statistical period, for example, 10 is turned on as a statistical period. The stroke calculation and division rule is that whether the stroke is left (one screen is advanced to the right) or right (one screen is retracted to the left), one division is added once every stroke, and the stroke direction is changed by one division. According to the above-mentioned arithmetic rule, α 1 ═ α 2 ═ 1, and α 3 ═ 3. For example, the APP icon to be searched is on line 3, column 3 of screen 3, but the sequence of events before the user finds APP open from screen 1 is: "draw 5 times left, 4 times right, 1 time left, open", then APP finds the difficulty score 5+4+1+3+ 3-16.
And calculating the emotion index of the user in the key period according to the invalid sliding operation and the opening operation of the user, specifically, the user does not immediately open the APP after sliding the screen and regards the APP as the invalid sliding operation, and the user immediately closes the operation which does not use the APP and regards the APP as the invalid opening APP after opening the APP. If the invalid operation is 0, the user is busy, and the mobile phone is operated in no time. The emotion index of the user in the key time interval is sigma of invalid stroke operation in the key time interval and sigma of invalid opening operation in the key time interval. The index can count the operation condition in a month, so that interval segmentation is carried out according to the specific value, and the emotion index of the user in a key time period is defined as index values of three gears of low, medium and high. The key time interval is defined according to specific requirements, for example, for white-collar workers, we can define the key time interval as "peak working hours" and "night".
Based on the above description, the present application provides a method of applying an icon layout as shown in fig. 1, the method including:
step 101, acquiring an application operation log of a user; the user operation log can be acquired through a log recording tool of the operating system, and can also be acquired through installing software of a third party; in order to facilitate layout adjustment, a period for acquiring the application operation log may be set, for example, the operation log is acquired once per worship or once per month; the period of the operation log may be 10 days, 15 days, or 1 month.
102, generating a user use habit label according to an application operation log of a user, wherein the user use habit label comprises; as described above, the usage habit tag may include at least one of an application type, an application open number tag, an application usage period tag, an application average usage duration tag, an application search difficulty level tag, and a key period user emotion index tag, in addition to the user application search difficulty level tag; the user using habit tags can be increased, decreased and changed by the technicians in the field according to the actual needs.
103, sequencing the applications according to the use habit tags of the users; in order to sort the applications, some tags need to be processed to make them easy to participate in the computation. For example, the APP type tag, the APP familiar period tag, the key period user emotion index and the like need to be converted into numbers to facilitate calculation, and preferably, normalization processing can be performed on APP open times, APP average use duration, APP search difficulty and the like.
The application score is β 1 × APP type tag + β 2 × APP open time tag + β 3 × APP used period tag + β 4 × APP average used time tag + β 5 × APP search difficulty level tag + β 6 × key period user emotion index tag, where β 1, β 2, β 3, β 4, and β 5 are weight coefficients, and may be adjusted according to actual needs, for example, in order to highlight APP search difficulty level tag, the value of β 5 may be increased. Optionally, the APP average usage duration label may also be increased to highlight the effect of average usage duration.
After the scores of the applications are obtained, the applications can be sorted according to the size of the score value so as to be recommended or laid out.
And 104, laying out the application icons according to the sequencing result. And performing application recommendation or layout according to the sequencing result, wherein the application recommendation or layout can be performed after the user agrees, or can be performed directly and automatically. Preferably, one, two or several of the top ranked results may be selected for layout or recommendation. There may be a plurality of recommendation fields (recommendation areas), which are named and distinguished by different functionalities, such as "easy forgetting recommendation area", "frequent recommendation area", "mood recommendation area", and so on. The recommendation columns can be placed on the first screen and the negative screen according to the understanding of manufacturers and tool providers, even grouping can be carried out, and recommendation information is placed under a grouping directory. FIG. 2A shows a screen that may have one recommendation field and FIG. 2B shows a screen that has two recommendation fields.
In the layout, the frequently used or focused APP icons can be placed in the middle, and the overall principle of "the middle is prior to the two sides, the inner circle is prior to the outer circle, the left is prior to the right, and the upper side is prior to the lower side" is followed, instead of being placed from left to right and from top to bottom. Fig. 3A to 3C show the layout of the application icons according to the sorting result.
When the layout is carried out, only one, two or a plurality of application icons which are ranked the most top can be selected for layout, and when one or two application icons are selected, the one or two icons can be laid out in the middle of the screen or the recommendation field, so that the application icons can be observed by the user more easily.
Further, the present application provides an apparatus for applying an icon layout, as shown in fig. 4, the apparatus including: the device comprises an acquisition module, a generation module, a sorting module and a layout module; the acquisition module is used for acquiring an application operation log of a user; the generating module is used for generating a user use habit label according to the application operation log of the user, wherein the user use habit label comprises an application searching difficulty label; the sequencing module is used for sequencing the applications according to the use habit tags of the users; and the layout module is used for laying out the application icons according to the sequencing result. For the functions that can be realized by each module, please refer to the above detailed description, which is not repeated herein.
Accordingly, the present application provides a mobile terminal, as shown in fig. 5, including a processor and a memory, where the memory may be used to store a program, and the processor may execute the program to implement the method provided in the present application.
The technical scheme who this application provided, both taken into account user's operation, taken into account user's vision custom again, still taken into account user's use custom, move the reference factor of operation as the application overall arrangement with the user, when realizing the application overall arrangement, can make the result that the application overall arrangement appears more be favorable to the user to use, the user of being convenient for will be difficult for the application of seeking to arrange the user and change the discovery to the user, thereby make the user experience at terminal intelligent, improve user's experience, increase user's viscosity.
The above description is only for the purpose of illustrating the preferred embodiments of the present application and is not to be construed as limiting the present application, and any modifications, equivalents, improvements, etc. made within the spirit and principle of the present application should be included in the scope of the present application.
Claims (10)
1. A method for applying icon layout, the method comprising:
acquiring an application operation log of a user;
generating a user use habit label according to an application operation log of a user, wherein the user use habit label comprises an application searching difficulty label;
sequencing the applications according to the use habit tags of the users;
and laying out the application icons according to the sequencing result.
2. The method of claim 1, wherein the application find ease label is determined by the number and direction of screen strokes during opening of the application;
preferably, the application search difficulty level tag is the sum of the application search difficulty scores/the number of times of application use, and the application search difficulty level tag is α 1+ α 2 + α 3+ the number of times of stroking transformation, where α 1, α 2, and α 3 are preset coefficients.
3. The method of claim 1, wherein the user usage habit tags further comprise at least one of an application type, an application open times tag, an application usage habit period tag, an application average usage duration tag, an application search ease degree tag, and a key period user emotion indicator tag;
preferably, the sorting the applications according to the user usage habit tags comprises:
scoring the applications according to the habit tags used by the user and a preset calculation rule, and sequencing the applications according to a scoring result;
preferably, the calculation rule comprises giving a weight to each tag.
4. The method of claim 1, wherein laying out application icons according to the ranking results comprises:
the first N icons are arranged in the middle of the screen, and/or the first M icons are arranged in the middle of the recommendation area, and M, N is a positive integer;
preferably, the laying out the application icons according to the sorting result includes:
according to the sorting result, the application is laid out on the screen or the recommended area according to the following rules:
the middle is prior to the two sides, the inner circle is prior to the outer circle, the left side is prior to the right side, and the upper side is prior to the lower side.
5. An apparatus for applying icon layout, the apparatus comprising:
the acquisition module is used for acquiring an application operation log of a user;
the generating module is used for generating a user use habit label according to the application operation log of the user, wherein the user use habit label comprises an application searching difficulty label;
the sequencing module is used for sequencing the applications according to the use habit tags of the users;
and the layout module is used for laying out the application icons according to the sequencing result.
6. The apparatus of claim 5, wherein the generating module is further configured to determine the application search difficulty level tag according to the number and the direction of screen strokes in the process of opening the application;
preferably, the application search difficulty level tag is the sum of the application search difficulty scores/the number of times of application use, and the application search difficulty level tag is α 1+ α 2 + α 3+ the number of times of stroking transformation, where α 1, α 2, and α 3 are preset coefficients.
7. The apparatus of claim 5, wherein the user usage habit tags further comprise at least one of an application type, an application open times tag, an application usage habit period tag, an application average usage duration tag, an application search ease degree tag, and a key period user emotion indicator tag;
preferably, the ranking module is further configured to score the applications according to the habit tags used by the user and a preset calculation rule, and rank the applications according to a scoring result;
preferably, the calculation rule comprises giving a weight to each tag.
8. The device of claim 5, wherein the application module is further configured to layout the first N icons in the middle of the screen, and/or layout the first M icons in the middle of the recommendation area, and M, N is a positive integer.
9. The device of claim 5, wherein the application module is further configured to, according to the sorting result, lay out the application on the screen or the recommended area according to the following rules:
the middle is prior to the two sides, the inner circle is prior to the outer circle, the left side is prior to the right side, and the upper side is prior to the lower side.
10. A mobile terminal, characterized in that the mobile terminal comprises a memory and a processor;
a memory for storing a program;
a processor for executing a program to perform the steps of:
acquiring an application operation log of a user;
generating a user use habit label according to an application operation log of a user, wherein the user use habit label comprises an application searching difficulty label;
sequencing the applications according to the use habit tags of the users;
and laying out the application icons according to the sequencing result.
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| CN111158699A (en) * | 2019-12-31 | 2020-05-15 | 青岛海尔科技有限公司 | Application optimization method and device based on Apriori algorithm and intelligent equipment |
| CN111813292A (en) * | 2020-05-26 | 2020-10-23 | 北京达佳互联信息技术有限公司 | Application interaction method, device, system, equipment and storage medium based on group chat |
| CN112269513A (en) * | 2020-10-30 | 2021-01-26 | 维沃移动通信有限公司 | Interface display method and device and electronic equipment |
| CN112882617A (en) * | 2021-02-07 | 2021-06-01 | 惠州Tcl移动通信有限公司 | Mobile terminal application setting method and system, intelligent terminal and storage medium |
| CN113419665A (en) * | 2021-08-25 | 2021-09-21 | 腾讯科技（深圳）有限公司 | Application display method, related device and equipment |
| CN114374953A (en) * | 2022-01-06 | 2022-04-19 | 西安交通大学 | APP usage prediction method and system under multi-source feature conversion base station based on Hadoop and RAPIDS |
| CN114374953B (en) * | 2022-01-06 | 2023-09-05 | 西安交通大学 | APP usage prediction method and system based on Hadoop and RAPIDS multi-source feature conversion base station |
| CN117767802A (en) * | 2023-12-19 | 2024-03-26 | 淮阴工学院 | Control system and method for permanent magnet synchronous motor |
| CN118409685A (en) * | 2024-04-25 | 2024-07-30 | 中国第一汽车股份有限公司 | Display method, device, electronic equipment, vehicle and storage medium for vehicle interface |
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