CN109240787A - Personalized facilitation adaptive multi-layer grade interaction area Optimal Configuration Method - Google Patents
Personalized facilitation adaptive multi-layer grade interaction area Optimal Configuration Method Download PDFInfo
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- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
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Abstract
The present invention is personalized facilitation adaptive multi-layer grade interaction area Optimal Configuration Method, it is combined after personalization, facilitation, adaptive and multi-layer four aspect modelings, according to the handedness of user, hand exercise range clicks the position that length of time determines user using multilayer interaction area, the adaptive approach of interaction area size, position is provided according to age and use habit afterwards, priority ranking finally is carried out to interaction area with interlayer in layer, keeps user easy to use quickly；Invention belongs to the crossing domain of graph image and soft project.
Description
Technical field
The present invention is personalized facilitation adaptive multi-layer grade interaction area Optimal Configuration Method, and the invention belongs to graphic diagrams
Picture and soft project crossing domain.
Background technique
While intelligent equipment of today is brought convenience to everybody, some worries are also brought, such as when using mobile phone, no
Application needed for user can be positioned rapidly；Smart machine of today is all that first downloading is sorted to the setting of the interaction areas such as interaction area
Preceding, rear downloading sequence is rear, and the individualized section being related to is also required to user and takes action on one's own arranging desktop, and user can expend thus
Time；And the folders section being related to also is set by user in person, is clicked and is opened into after file, checks the friendship in file
Mutual region can only left cunning or right cunning, into the circulation applied needed for user cannot be positioned rapidly；The present invention is personalized convenient
Change adaptive multi-layer grade interaction area Optimal Configuration Method, from personalization, facilitation, it is adaptive and multi-layer four in terms of modeling
After combine, according to the handedness of user, hand exercise range clicks length of time and determines user using multilayer interaction area
Position, after according to age and use habit provide the adaptive approach of interaction area size, position, finally in layer and interlayer pair
Interaction area carries out priority ranking, keeps user easy to use quickly；What invention belonged to graph image and soft project intersects neck
Domain.
Summary of the invention
Architecture
It is personalized:
As shown in Figure 1, the handedness (Ha) of sensor perception user, left example hand (HL), right example hand (HR), Ha=HL │ HR；
What sensor also perceived user simultaneously uses hand region (DIS), upper (DU), under (DD), left (DL), right (DR), DIS=DU&
DD&DL&DR；
It clicks time (ClickDuration) to be customized by the user, clicks the number of plies that the time is different, in the multilayered structure of opening
It is different；
Facilitation:
After Ha and DIS has been determined, in order to keep user easy to use, interaction area is scheduled on the region within the scope of DIS close to Ha
It is interior；Fig. 3 is a specific example, it is assumed that user HR, finger movement range a length of d that sensor measures, width l are set at this time
It sets interaction area and focuses on position shown in dotted line frame, close to the right hand, and a length of d in region, width l, interactive areas when the user clicks
Domain P2Afterwards, it may appear that multilayer interaction area；ClickDuration=1s then enters L0, ClickDuration=2s then enters
L1……
As shown in figure 4, working as Icon1And Icon2Simultaneously in use, preceding state is set as M, the latter state is set as N, exists
Once the case where several conversions:
M(Left) → N(Right │ Up │ Down): work as Icon1In left in use, Icon2Should appear in right, top or
Lower section；
M(Right) → N(Left │ Up │ Down): work as Icon1In right in use, Icon2Should appear in left, top or under
Side；
M(Up) → N(Left │ Right │ Down): work as Icon1Above in use, Icon2Should appear in left, right or under
Side；
M(Down) → N(Left │ Right │ Up): work as Icon1In lower section in use, Icon2Should appear in left, right or on
Side；
It is adaptive:
The interaction area size of each layer of placement determines that SureSize=(Age, SL) is made of two algorithms, specific as follows:
(1) Age(Fac) → d: age effects function Age under the auxiliary of interface Fac, determine the side length d, d of each interaction area
To be most suitable for the best interaction area side length that the user of the age bracket uses；
(2) SL(w, l) → d │ d ': layer size contrast function SL after the long l and high w of input layer, size ratio is carried out with d
Compared with if d≤min(w, l), it is determined that d is side length, and otherwise taking side length is d '=α × d, and α is that external source data mining obtains, 0 < α < 1；
Determination SurePosition=(Sure of interaction area positionn, Place)
(1) Suren(SureSize, q) → n: every layer interaction area can accommodate maximum quantity function SurenIn SureSize function
After d has been determined, the beautiful of age of user section is obtained according to interface Fac and appreciates parameter q, q reflects interaction area and interaction area
The distance between, as shown in figure 4, determining the quantity n of interaction area using the relationship of q, layer size and d；
(2) Place(Suren) → (middlenode): central point determines function Place, is determining that every layer of interaction area can hold
After the maximum quantity n received, the central point middlenode of n interaction area is determined；
Multi-layer:
In layer: single interaction area (Icon): diagonally being sat on each layer of interaction area with one group of plane right-angle coordinate
Mark expression, Icon={ (xi,yi), (xi+1,yi+1), as shown in figure 4, figure grey area is an interaction area, (x1, y1)
For the point coordinate in the interaction area upper right corner, (x2, y2) be the interaction area lower left corner point coordinate determine one by the two coordinates
The position of a interaction area.The side length d of interaction area=；
Single layer (L): L={ (x, y, z), w, l }, (x, y, z) are the central point of L on three-dimensional coordinate, and w is height, and l is length, width
It ignores；
Wrap (P): P={ (xi,yi), (xi+1,yi+1), as shown in figure 4, figure grey area is an interaction area, (x4, y4)
For the point coordinate in the interaction area upper right corner, (x3, y3) be the interaction area lower left corner point coordinate determine one by the two coordinates
The position of a interaction area；
Interlayer: multilayer is according to priority successively stacked L, i.e., when that is, the quantity of L is greater than 1 from L0It puts to Lk；
Priority algorithm: a priority algorithm PA=(FlowCharticon, Package, PL, PAIcon, PAL), include five calculations
Method, specific as follows:
(1) FlowCharticon(icon, ClickDuration, t) → fre): input interaction area icon, record user click
The quantity click of this icon and time t of click exports the frequency of use fre curve graph FlowChart of icon；According to RNN
The frequency fre and trend that each interaction area uses can be obtained by practising FlowChart；
(2) Package(Fac) → Pi: similar interaction area function Package is used under the cooperation of interface Fac according to most of
Similar interaction area is put into P in the same packet by the use habit at familyi；
(3) PL(Ha, fre) → P: packet priority function PL after obtaining the sequence of fre, by the sequence of Ha by interaction area one by one
It is corresponding to place, such as the user of HL, the higher packet of priority is more turned left and is put, and finally obtains the position P individually wrapped；
(4) PAIcon(Ha, fre) → Icon: pri function PA in layerIconIt, will by the sequence of Ha after obtaining the sequence of fre
Interaction area, which corresponds, places, such as the user of HL, the higher interaction area of priority is more turned left and put, finally
Obtain the position Icon of single interaction area；
(5) PAL(PAIcon, n) and → Li: interlayer pri function PALObtaining PAIconAfterwards, as quantity≤n of interaction area,
Interaction area is placed on L0, otherwise toward L1Put, and so on until discharging similar interaction area；
The utility model has the advantages that
The present invention is personalized facilitation adaptive multi-layer grade interaction area Optimal Configuration Method, from personalization, facilitation, adaptive
It is combined after should being modeled with four aspects of multi-layer, according to the handedness of user, hand exercise range, click length of time are determined
User uses the position of multilayer interaction area, after according to age and use habit provide interaction area size, position it is adaptive
Method finally carries out priority ranking to interaction area with interlayer in layer, keeps user easy to use quickly；With following excellent
Point:
1) it the present invention provides personalized and facilitation method, is mentioned according to the handedness of user and hands movement region for user
For individual operation region, it is convenient for the user to use；
2) the present invention provides adaptive approach, can be provided suitably according to the age and layer size of user for user
Interaction area size, the interaction area position further according to user's frequency of use, after priority ranking is provided for user；
3) the present invention provides multi-layer interaction area methods, can be to use according to the click length of time and priority of user
Family provides interaction area sequence and final position, and user is capable of the position of rapid the target icon, and easy to use.
Detailed description of the invention
Fig. 1 is the illustraton of model of personalized facilitation adaptive multi-layer grade interaction area Optimal Configuration Method personalization；
Fig. 2 is the adaptive illustraton of model of personalized facilitation adaptive multi-layer grade interaction area Optimal Configuration Method；
Fig. 3 is one specific embodiment of personalized facilitation adaptive multi-layer grade interaction area Optimal Configuration Method；
Fig. 4 is one specific embodiment of personalized facilitation adaptive multi-layer grade interaction area Optimal Configuration Method；
Fig. 5 is personalized facilitation adaptive multi-layer grade interaction area Optimal Configuration Method specific implementation flow chart.
Specific embodiment
The detailed process of personalized facilitation adaptive multi-layer grade interaction area Optimal Configuration Method is as follows:
Shown in 001 in step 1) corresponding diagram 5, input interaction area (Icon): with flat square on each layer of interaction area
One group of diagonal coordinate representation of coordinate system, Icon={ (xi,yi), (xi+1,yi+1), as shown in figure 4, figure grey area is one
A interaction area, (x1, y1) be the interaction area upper right corner point coordinate, (x2, y2) be the interaction area lower left corner point coordinate, lead to
The two coordinates are crossed, determine the position of an interaction area.The side length d of interaction area=；
Single layer (L): L={ (x, y, z), w, l }, (x, y, z) are the central point of L on three-dimensional coordinate, and w is height, and l is length, width
It ignores；
Wrap (P): P={ (xi,yi), (xi+1,yi+1), as shown in figure 4, figure grey area is an interaction area, (x4, y4)
For the point coordinate in the interaction area upper right corner, (x3, y3) be the interaction area lower left corner point coordinate determine one by the two coordinates
The position of a interaction area；
Shown in 002 in step 2 corresponding diagram 5, into personality module；As shown in Figure 1, the handedness of sensor perception user
(Ha), left example hand (HL), right example hand (HR), Ha=HL │ HR；
What sensor also perceived user simultaneously uses hand region (DIS), upper (DU), under (DD), left (DL), right (DR), DIS=DU&
DD&DL&DR；
It clicks time (ClickDuration) to be customized by the user, clicks the number of plies that the time is different, in the multilayered structure of opening
It is different；
Shown in 003 in step 3) corresponding diagram 5, into facilitation module, after Ha and DIS has been determined, in order to make user using just
Interaction area is scheduled within the scope of DIS in the region of Ha by victory；Fig. 3 is a specific example, it is assumed that user HR, sensing
Finger movement range a length of d, the width l that device measures are arranged interaction area and focus on position shown in dotted line frame, at this time close to right
Hand, and a length of d in region, width l, when the user clicks interaction area P2Afterwards, it may appear that multilayer interaction area；ClickDuration=
1s then enters L0, ClickDuration=2s, then into L1……
As shown in figure 4, working as Icon1And Icon2Simultaneously in use, preceding state is set as M, the latter state is set as N, exists
Once the case where several conversions:
M(Left) → N(Right │ Up │ Down): work as Icon1In left in use, Icon2Should appear in right, top or
Lower section；
M(Right) → N(Left │ Up │ Down): work as Icon1In right in use, Icon2Should appear in left, top or under
Side；
M(Up) → N(Left │ Right │ Down): work as Icon1Above in use, Icon2Should appear in left, right or under
Side；
M(Down) → N(Left │ Right │ Up): work as Icon1In lower section in use, Icon2Should appear in left, right or on
Side；
Shown in 004 in step 4) corresponding diagram 5, into adaptation module；The interaction area size of each layer of placement determines
SureSize=(Age, SL) is made of two algorithms, specific as follows:
(1) Age(Fac) → d: age effects function Age under the auxiliary of interface Fac, determine the side length d, d of each interaction area
To be most suitable for the best interaction area side length that the user of the age bracket uses；
(2) SL(w, l) → d │ d ': layer size contrast function SL after the long l and high w of input layer, size ratio is carried out with d
Compared with if d≤min(w, l), it is determined that d is side length, and otherwise taking side length is d '=α × d, and α is that external source data mining obtains, 0 < α < 1；
Determination SurePosition=(Sure of interaction area positionn, Place)
(1) Suren(SureSize, q) → n: every layer interaction area can accommodate maximum quantity function SurenIn SureSize function
After d has been determined, the beautiful of age of user section is obtained according to interface Fac and appreciates parameter q, q reflects interaction area and interaction area
The distance between, as shown in figure 4, determining the quantity n of interaction area using the relationship of q, layer size and d；
(2) Place(Suren) → (middlenode): central point determines function Place, is determining that every layer of interaction area can hold
After the maximum quantity n received, the central point middlenode of n interaction area is determined；
Shown in 005 in step 5) corresponding diagram 5, into multi-layer module；
Interlayer: multilayer is according to priority successively stacked L, i.e., when that is, the quantity of L is greater than 1 from L0It puts to Lk；
Priority algorithm: a priority algorithm PA=(FlowCharticon, Package, PL, PAIcon, PAL), include five calculations
Method, specific as follows:
(1) FlowCharticon(icon, ClickDuration, t) → fre): input interaction area icon, record user click
The quantity click of this icon and time t of click exports the frequency of use fre curve graph FlowChart of icon；According to RNN
The frequency fre and trend that each interaction area uses can be obtained by practising FlowChart；
(2) Package(Fac) → Pi: similar interaction area function Package is used under the cooperation of interface Fac according to most of
Similar interaction area is put into P in the same packet by the use habit at familyi；
(3) PL(Ha, fre) → P: packet priority function PL after obtaining the sequence of fre, by the sequence of Ha by interaction area one by one
It is corresponding to place, such as the user of HL, the higher packet of priority is more turned left and is put, and finally obtains the position P individually wrapped；
(4) PAIcon(Ha, fre) → Icon: pri function PA in layerIconIt, will by the sequence of Ha after obtaining the sequence of fre
Interaction area, which corresponds, places, such as the user of HL, the higher interaction area of priority is more turned left and put, finally
Obtain the position Icon of single interaction area；
(5) PAL(PAIcon, n) and → Li: interlayer pri function PALObtaining PAIconAfterwards, as quantity≤n of interaction area,
Interaction area is placed on L0, otherwise toward L1Put, and so on until discharging similar interaction area；
Shown in 006 in step 6) corresponding diagram 5, personalized facilitation adaptive multi-layer grade is exported treated interaction area.
Claims (1)
1. the present invention is personalized facilitation adaptive multi-layer grade interaction area Optimal Configuration Method, from personalization, facilitation, from
It adapts to combine with after four aspect modelings of multi-layer, according to the handedness of user, hand exercise range, click length of time are true
Determine the position that user uses multilayer interaction area, after according to age and use habit provide interaction area size, position it is adaptive
Induction method finally carries out priority ranking to interaction area with interlayer in layer, keeps user easy to use quickly；It is personalized convenient
The detailed process for changing adaptive multi-layer grade interaction area Optimal Configuration Method is as follows:
Step 1) input interaction area (Icon): it is diagonally sat on each layer of interaction area with one group of plane right-angle coordinate
Mark expression, Icon={ (xi,yi), (xi+1,yi+1), as shown in figure 4, figure grey area is an interaction area, (x1, y1)
For the point coordinate in the interaction area upper right corner, (x2, y2) be the interaction area lower left corner point coordinate determine one by the two coordinates
The position of a interaction area；The side length d of interaction area=；
Single layer (L): L={ (x, y, z), w, l }, (x, y, z) are the central point of L on three-dimensional coordinate, and w is height, and l is length, width
It ignores；
Wrap (P): P={ (xi,yi), (xi+1,yi+1), as shown in figure 4, figure grey area is an interaction area, (x4, y4) be
The point coordinate in the interaction area upper right corner, (x3, y3) be the interaction area lower left corner point coordinate determine one by the two coordinates
The position of interaction area；
Step 2 enters personality module；As shown in Figure 1, the handedness (Ha) of sensor perception user, left example hand (HL) are right
Example hand (HR), Ha=HL │ HR；
What sensor also perceived user simultaneously uses hand region (DIS), upper (DU), under (DD), left (DL), right (DR), DIS=DU&
DD&DL&DR；
It clicks time (ClickDuration) to be customized by the user, clicks the number of plies that the time is different, in the multilayered structure of opening
It is different；
Step 3) enters facilitation module, and after Ha and DIS has been determined, in order to keep user easy to use, interaction area is scheduled on
Within the scope of DIS in the region of Ha；Fig. 3 is a specific example, it is assumed that user HR, the finger movement model that sensor measures
Girth is d, width l, and interaction area is arranged at this time and focuses on position shown in dotted line frame, the close right hand, and a length of d in region, wide
For l, interaction area P when the user clicks2Afterwards, it may appear that multilayer interaction area；ClickDuration=1s then enters L0,
ClickDuration=2s then enters L1……
As shown in figure 4, working as Icon1And Icon2Simultaneously in use, preceding state is set as M, the latter state is set as N, exists
Once the case where several conversions:
M(Left) → N(Right │ Up │ Down): work as Icon1In left in use, Icon2Should appear in right, top or under
Side；
M(Right) → N(Left │ Up │ Down): work as Icon1In right in use, Icon2Should appear in left, top or under
Side；
M(Up) → N(Left │ Right │ Down): work as Icon1Above in use, Icon2Should appear in left, right or under
Side；
M(Down) → N(Left │ Right │ Up): work as Icon1In lower section in use, Icon2Should appear in left, right or on
Side；
Step 4) enters adaptation module；The interaction area size of each layer of placement determines SureSize=(Age, SL) by two
Algorithm composition, specific as follows:
(1) Age(Fac) → d: age effects function Age under the auxiliary of interface Fac, determine the side length d, d of each interaction area
To be most suitable for the best interaction area side length that the user of the age bracket uses；
(2) SL(w, l) → d │ d ': layer size contrast function SL after the long l and high w of input layer, size ratio is carried out with d
Compared with if d≤min(w, l), it is determined that d is side length, and otherwise taking side length is d '=α × d, and α is that external source data mining obtains, 0 < α < 1；
Determination SurePosition=(Sure of interaction area positionn, Place)
(1) Suren(SureSize, q) → n: every layer interaction area can accommodate maximum quantity function SurenIn SureSize function
After d has been determined, the beautiful of age of user section is obtained according to interface Fac and appreciates parameter q, q reflects interaction area and interaction area
The distance between, as shown in figure 4, determining the quantity n of interaction area using the relationship of q, layer size and d；
(2) Place(Suren) → (middlenode): central point determines function Place, is determining that every layer of interaction area can accommodate
Maximum quantity n after, the central point middlenode of n interaction area is determined；
Step 5) enters multi-layer module；
Interlayer: multilayer is according to priority successively stacked L, i.e., when that is, the quantity of L is greater than 1 from L0It puts to Lk；
Priority algorithm: a priority algorithm PA=(FlowCharticon, Package, PL, PAIcon, PAL), include five calculations
Method, specific as follows:
(1) FlowCharticon(icon, ClickDuration, t) → fre): input interaction area icon, record user click
The quantity click of this icon and time t of click exports the frequency of use fre curve graph FlowChart of icon；According to RNN
The frequency fre and trend that each interaction area uses can be obtained by practising FlowChart；
(2) Package(Fac) → Pi: similar interaction area function Package is used under the cooperation of interface Fac according to most of
Similar interaction area is put into P in the same packet by the use habit at familyi；
(3) PL(Ha, fre) → P: packet priority function PL after obtaining the sequence of fre, by the sequence of Ha by interaction area one by one
It is corresponding to place, such as the user of HL, the higher packet of priority is more turned left and is put, and finally obtains the position P individually wrapped；
(4) PAIcon(Ha, fre) → Icon: pri function PA in layerIconAfter obtaining the sequence of fre, it will be handed over by the sequence of Ha
Mutual region, which corresponds, places, such as the user of HL, the higher interaction area of priority is more turned left and put, finally
To the position Icon of single interaction area；
(5) PAL(PAIcon, n) and → Li: interlayer pri function PALObtaining PAIconIt afterwards, will as quantity≤n of interaction area
Interaction area is placed on L0, otherwise toward L1Put, and so on until discharging similar interaction area.
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| CN102541352A (en) * | 2011-12-19 | 2012-07-04 | 深圳桑菲消费通信有限公司 | Method capable of enabling cell phone to adapt to user touch control habits |
| US20180210640A1 (en) * | 2017-01-26 | 2018-07-26 | International Business Machines Corporation | Methods for repositioning icons on touch displays based on characteristics of touch gestures and related program products |
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