CN105760428B - Knowledge map mapping generation method - Google Patents
Knowledge map mapping generation method Download PDFInfo
- Publication number
- CN105760428B CN105760428B CN201610063529.7A CN201610063529A CN105760428B CN 105760428 B CN105760428 B CN 105760428B CN 201610063529 A CN201610063529 A CN 201610063529A CN 105760428 B CN105760428 B CN 105760428B
- Authority
- CN
- China
- Prior art keywords
- knowledge
- grid
- calculated
- map
- blocks
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/904—Browsing; Visualisation therefor
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/901—Indexing; Data structures therefor; Storage structures
Landscapes
- Engineering & Computer Science (AREA)
- Databases & Information Systems (AREA)
- Theoretical Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Software Systems (AREA)
- Image Generation (AREA)
Abstract
The invention discloses a knowledge map mapping generation method. The method comprises the steps that hierarchical relationship and association relationship attributes of knowledge serve as input parameters, and coordinates of the knowledge mapped to a two-dimensional plane map are obtained; a knowledge type attribute serves as an input parameter, a graph element parameter definition and fractal calculation are utilized, and geometric graph shapes of knowledge units mapped to a two-dimensional plane are generated; information quantity of the knowledge serves as an input parameter, the projected area ratio of the information quantity and the two-dimensional map area is calculated, the size of an outer boundary box of the knowledge units mapped to the two-dimensional map area is calculated through the area ratio, and the sizes of graphs in the knowledge units are controlled through a largest external rectangle algorithm; a knowledge map with a proper proportion is generated by taking the knowledge attributes and user preferences as input parameters. According to the knowledge map mapping generation method, information of the hierarchical relationship and the association relationship of the knowledge, the knowledge type and the knowledge information quantity is comprehensively considered, the spatial mapping method of the knowledge is established, and a foundation base map is established for cognition and display of subject knowledge and platform application based on the knowledge.
Description
Technical field
The invention belongs to IT application in education sector technical field, more particularly, to a kind of Knowledge Map mapping generating method.
Background technology
With the progress and the development of IT application in education sector technology of education cognitive theory, Knowledge Map is increasingly subject to the pass of people
Note, with the Internet+development, urgently need the knowledge organization platform of an autonomous knowledge based map, and knowledge ground
Map generalization method and basis and core that bandwagon effect is then Knowledge Map.At present, China to the research of Knowledge Map with should
With being scarcely out of swaddling-clothes, many technologies are all simply to absorb external existing knowledge to lead the expression such as figure and exhibiting method.
Carry out finding when educational resource tissue is applied with profound level, figure shows that stereovision is unclear, and resource polymerization shows slightly mixed and disorderly, uses
When node carries out knowledge representation with side, the incidence relation between knowledge is focused on too much, and ignores the level of knowledge, knowledge
Inherent knowledge quantity and personal characteristics.
The mapping generating method of Knowledge Map feature to a certain extent for studied knowledge type, simplifies general knowledge
Between all types of relation, it is established that the expression of level, relatedness, type and knowledge quantity attribute, foundation are mapped to class generation
The two dimensional surface of boundary's map, realizes, from knowledge space to the Mapping and Converting of map Cognitive Spaces, visually reducing cognitive threshold, building
The resource organization framework of vertical similar map display platform.
The content of the invention
For the disadvantages described above or Improvement requirement of prior art, the invention provides a kind of Knowledge Map mapping generation side
Method, for the feature of studied knowledge type, simplifies relations all types of between general knowledge, it is established that level, relatedness, class
The expression of type and knowledge quantity attribute, sets up the similar expression of similar two-dimensional world map, realizes that knowledge space is empty with map
Between mapping, the expression for knowledge provides new vivid method.
For achieving the above object, the invention provides a kind of Knowledge Map mapping generating method, it is characterised in that include：
(1) with the hierarchical relationship of knowledge and incidence relation attribute as |input paramete, filled out by spatial level subdivision and curve
Calculating is filled, and Knowledge Mapping is obtained to the coordinate of two dimensional surface map；
Further include following steps：
(1-1) total number of plies L of hierarchical relationship is counted, wherein, i-th layer of blocks of knowledge collection is combined into Xi, i=1,2 ..., L, Xi
={ KDDj| j=1,2 ..., Ni, KDDjFor i-th layer of j-th blocks of knowledge, NiFor the number of blocks of knowledge in i-th layer；
(1-2) plane coordinates for defining blocks of knowledge is the function related to hierarchical relationship value h and incidence relation value r；
(1-3) all layers are traveled through, the sub- lattice network parameters of each layer are calculated；
Wherein, i-th layer of sub- lattice network parameters
(1-4) the sub- lattice network parameters according to each layer, carry out the division of grid space to the corresponding plane domain of each layer, and build
Vertical space filling curve, calculates the length of space filling curve；
(1-5) the incidence relation value sum of all blocks of knowledge in each layer is calculated, and then it is corresponding with this layer flat to calculate which
The space filling curve length ratio in face region；
(1-6) position of each blocks of knowledge on the space filling curve of this layer of corresponding plane domain in each layer is calculated, is entered
And the plane coordinates of each blocks of knowledge is back-calculated to obtain by curve segmentation algorithm；
(2) with knowledge type attribute as |input paramete, defined using pel parameter and fractal calculation, generate blocks of knowledge and reflect
It is mapped to the geometric figure shape of two dimensional surface；
(3) quantity of information with knowledge calculates quantity of information and two-dimensional map region projection area ratio, by face as |input paramete
Product is mapped to the outer bounding box size in two-dimensional map region than calculation knowledge unit, controls knowledge using maximum bounding rectangle algorithms
The feature size of unit；
(4) with knowledge attribute and user preference as |input paramete, optimize map graphics shape and pattern coloring, generate ratio
The Knowledge Map of appropriateness.
Preferably, in the step (1-4), space filling curve length Len of i-th layer of corresponding plane domainiBy as follows
Method is calculated：
(A1) i-th layer of corresponding plane domain is divided intoIndividual grid；
(A2) by s rows t arrange grid ticks be (s, t), with 2 × 2 grid as unit, selection (s, t), (s, t+1),
(s+1, t+1) and (central point of this four grid is connected into line by s+1, t) four grid successively；
(A3) successively will (s+2, t), (s+2, t+1), (s+3, t+1) and (s+3, t) central point of four grid connect into
Line；
(A4) by (s+1, t+1) and (s+2, central point t) connect into line；
(A5) successively the central point of (s, t+2), (s, t+3), (s+1, t+3) and (s+1, t+2) four grid is connected into
Line；
(A6) central point of (s+1, t+1) and (s, t+2) is connected into into line；
(A7) successively will (s+2, t), (s+2, t+1), (s+3, t+1) and (s+3, t) central point of four grid connect into
Line；
(A8) by (s+1, t+3) and (s+2, central point t) connect into line；
(A9) the line total length that calculation procedure (A2)～(A8) is obtained, obtains the filling of i-th layer of corresponding plane domain
Length of curve Leni。
Preferably, the step (1-6) further includes following steps：
(1-6-1) incidence relation value r according to blocks of knowledge, from the space filling curve head of its corresponding plane domain of place layer
Begin stepping through, obtain the point P that starting point distance is r；
(1-6-2) the long dx of grid and grid width dy of calculation knowledge unit place layer；
(1-6-3) calculate and be not less thanMinimum positive integer Li, the ranks number of P places grid are calculated according to Li；
(1-6-4) calculate the middle point coordinates (x of P places grid0,y0)；
(1-6-5) calculate P point coordinates.
Preferably, the step (1-6-3) further includes following steps：
(1-6-3-1) according to space filling curve rule, calculate the line number of 2 × 2 grid units that P is located
(1-6-3-2) calculate the length Δ l=Li (dx+dy) of space filling curve from starting point to P in 2 × 2 grid units-
r；
(1-6-3-3) existWhen, judge P in the lower-left grid of 2 × 2 grid units；When, judge P in the upper left grid of 2 × 2 grid units；
When, judge P in the upper right grid of 2 × 2 grid units；When, judge P 2 × 2
In the bottom right grid of grid unit；
(1-6-3-4) position according to P places grid in 2 × 2 grid units, calculates line number s of P places gridxWith
Row number tx。
Preferably, the step (1-6-5) is specially：When P is in the lower-left grid of 2 × 2 grid units, P is calculated
Point coordinates isWhen P is in the upper left grid of 2 × 2 grid units, in Δ l ＜ dx, P is calculated
Point coordinates is (x0+Δl-dx,y0), in Δ l ＞ dx, P point coordinates is calculated for (x0,y0+Δl-dx)；P is in 2 × 2 grid
When in the upper right grid of unit, in Δ l ＜ dx+dy, P point coordinates is calculated for (x0,y0+ Δ l-dx-dy), in Δ l ＞ dx
During+dy, being calculated P point coordinates isWhen P is in the bottom right grid of 2 × 2 grid units,
In Δ l ＜ 2dx+dy, P point coordinates is calculated for (x0+Δl-2dx+dy,y0), in Δ l ＞ 2dx+dy, it is calculated P
Point coordinates is (x0,y0+Δl-2dx-dy)。
Preferably, the step (2) further includes following steps：
(2-1) define blocks of knowledge be mapped to two dimensional surface geometric figure be shaped as and knowledge type attribute T-phase close
Function；
(2-2) analysis knowledge type attribute T, defines fundamental type component base (T), wherein, base (T) takes different values
The different basic geometric figure of correspondence；
(2-3) analysis knowledge type attribute T, defines subtype component factal (T), wherein, factal (T) takes different
The different basic geometric figure of value correspondence；
(2-4) v=factal (T) is defined, each edge of basic geometric figure is entered with Koch curve calculation Method of Fractal
V time point of shape refinement of row, obtains new figure.
Preferably, the step (2-4) further includes following steps：
(2-4-1) cycle-index k=0 is set；
(2-4-2) two end points of basic geometric figure a line are labeled as into P1 and P5；
(2-4-3) with P1 as starting point, P2, labelling at line segment P1P5 2/3rds will at line segment P1P5 1/3rd, be labeled as
For P4；
(2-4-4) with P2 as axle center, by 60 ° of P4 rotate counterclockwises, P3 points are obtained；
(2-4-5) P1, P2, P3, P4 and P5 point coordinates is calculated, generates line segment P1P2, P2P3, P3P4, P4P5, complete wall scroll
The fractal calculation on side；
(2-4-6) according to step (2-4-2) to (2-4-5), traversal completes the fractal calculation on all sides of basic geometric figure,
Obtain new geometric figure；
(2-4-7) cycle-index k=k+1 is made, judges k<Whether v sets up, and is then using new geometric figure as substantially several
What figure, return to step (2-4-2) continue fractal calculation, otherwise complete a point shape, obtain new polygon.
Preferably, the step (3) further includes following steps：
(3-1) the knowledge information amount for counting total isWherein, N is blocks of knowledge quantity, and E is each blocks of knowledge
Quantity of information, according to the planning of formation zone, the area of calculation knowledge unit is σ, and then is calculated shared by unit information amount
Area
(3-2) the quantity of information E according to each blocks of knowledge, calculates each blocks of knowledge occupied area for S=ρ * E；
(3-3) according to each blocks of knowledge occupied area S, with reference to basic geometric figure shape (such as equilateral triangle, positive four side
Shape, regular pentagon or regular hexagon) calculate the size of its boundary rectangle；
(3-4) according to basic geometric figure shape and its size of boundary rectangle, calculate the length of side of basic geometric figure；
(3-5) point centered on the position coordinateses of basic geometric figure, according to basic geometric figure form and dimension, generates
Geometric figure.
Preferably, in the step (3-4), when basic geometric figure is equilateral triangle, it is calculated equilateral triangle
The length of sideWhen basic geometric figure is square, the length of side of square is calculated
When basic geometric figure is regular pentagon, the length of side of regular pentagon is calculatedIn basic geometric figure it is
During regular hexagon, the orthohexagonal length of side is calculated
Preferably, the step (4) further includes following steps：
(4-1) according to knowledge domain knowledge quantity size and the scope of two-dimensional map, it is determined that generating the ratio of map；
(4-2) when there is knowledge attribute file or user preference is arranged, relevant parameter is read, each is set accordingly and is known
Know the color of unit；When there is no knowledge attribute file and user preference is arranged, using trichromatism to each knowledge list
Unit's coloring；
(4-3) ratio according to the map, carries out random round and smooth process to segmenting pel of the level more than three layers；
(4-4) Knowledge Map is generated, and map file is saved as with reference format.
In general, by the contemplated above technical scheme of the present invention compared with prior art, with following beneficial effect
Really：
(1) set up from knowledge space to the mapping method of traditional map Cognitive Spaces, using the map cognition of shape, reduce
The cognitive difficulty of knowledge space.
(2) set up knowledge multielement set, and belonged to controlling the generation of final graphics by each element component in set
Inventive process.
(3) propose first to set up the hardware and software platform expression of Knowledge Map, set up the new resource organizer based on locus
Formula.
Description of the drawings
Fig. 1 is the Knowledge Map mapping generating method flow chart of the embodiment of the present invention；
Fig. 2 is to calculate space filling line and length of curve calculating flow process using level and relating attribute；
Fig. 3 is that grid decomposes numbering and space filling curve generation method flow process；
Fig. 4 is that space filling curve calculates space coordinatess flow process；
Fig. 5 is that knowledge type generates figure fractal algorithm flow process；
Fig. 6 is the exemplary method of single edge fractal calculation；
Fig. 7 calculates the flow process of feature size by knowledge information amount；
Fig. 8 carries out the flow process of figure color matching by user preference.
Specific embodiment
In order that the objects, technical solutions and advantages of the present invention become more apparent, it is below in conjunction with drawings and Examples, right
The present invention is further elaborated.It should be appreciated that specific embodiment described herein is only to explain the present invention, and
It is not used in the restriction present invention.As long as additionally, technical characteristic involved in invention described below each embodiment
Do not constitute conflict each other can just be mutually combined.
As shown in figure 1, the Knowledge Map mapping generating method of the embodiment of the present invention comprises the steps：
(1) with the hierarchical relationship of knowledge and incidence relation attribute as |input paramete, filled out by spatial level subdivision and curve
Calculating is filled, and Knowledge Mapping is obtained to the coordinate of two dimensional surface map；
As shown in Fig. 2 further including following steps：
(1-1) total number of plies L of hierarchical relationship is counted, wherein, i-th layer of blocks of knowledge collection is combined into Xi, i=1,2 ..., L, Xi
={ KDDj| j=1,2 ..., Ni, KDDjFor i-th layer of j-th blocks of knowledge, NiFor the number of blocks of knowledge in i-th layer；
(1-2) plane coordinates for defining blocks of knowledge is the function related to hierarchical relationship value h and incidence relation value r；
(1-3) all layers are traveled through, the sub- lattice network parameters of each layer are calculated；
Wherein, i-th layer of sub- lattice network parameters
(1-4) the sub- lattice network parameters according to each layer, carry out the division of grid space to the corresponding plane domain of each layer, and build
Vertical space filling curve, calculates the length of space filling curve；
As shown in figure 3, space filling curve length Len of i-th layer of corresponding plane domainiIt is calculated by the following method：
(A1) i-th layer of corresponding plane domain is divided intoIndividual grid；
(A2) by s rows t arrange grid ticks be (s, t), with 2 × 2 grid as unit, selection (s, t), (s, t+1),
(s+1, t+1) and (central point of this four grid is connected into line by s+1, t) four grid successively；
(A3) successively will (s+2, t), (s+2, t+1), (s+3, t+1) and (s+3, t) central point of four grid connect into
Line；
(A4) by (s+1, t+1) and (s+2, central point t) connect into line；
(A5) successively the central point of (s, t+2), (s, t+3), (s+1, t+3) and (s+1, t+2) four grid is connected into
Line；
(A6) central point of (s+1, t+1) and (s, t+2) is connected into into line；
(A7) successively will (s+2, t), (s+2, t+1), (s+3, t+1) and (s+3, t) central point of four grid connect into
Line；
(A8) by (s+1, t+3) and (s+2, central point t) connect into line；
(A9) the line total length that calculation procedure (A2)～(A8) is obtained, obtains the filling of i-th layer of corresponding plane domain
Length of curve Leni。
(1-5) the incidence relation value sum of all blocks of knowledge in each layer is calculated, and then it is corresponding with this layer flat to calculate which
The space filling curve length ratio in face region；
Wherein, incidence relation value sum τ of i-th layer of all blocks of knowledgeiThe filling of plane domain corresponding with i-th layer is bent
Line length LeniRatio
(1-6) position of each blocks of knowledge on the space filling curve of this layer of corresponding plane domain in each layer is calculated, is entered
And the plane coordinates of each blocks of knowledge is back-calculated to obtain by curve segmentation algorithm.
As shown in figure 4, further including following steps：
(1-6-1) incidence relation value r according to blocks of knowledge, from the space filling curve head of its corresponding plane domain of place layer
Begin stepping through, obtain the point P that starting point distance is r；
(1-6-2) the long dx of grid and grid width dy of calculation knowledge unit place layer；
Wherein, blocks of knowledge is at i-th layer,
(1-6-3) calculate and be not less thanMinimum positive integer Li, the ranks number of P places grid are calculated according to Li；
Further include following steps：
(1-6-3-1) according to space filling curve rule, calculate the line number of 2 × 2 grid units that P is located
(1-6-3-2) calculate the length Δ l=Li (dx+dy) of space filling curve from starting point to P in 2 × 2 grid units-
r；
(1-6-3-3) existWhen, judge P in the lower-left grid of 2 × 2 grid units；When, judge P in the upper left grid of 2 × 2 grid units；
When, judge P in the upper right grid of 2 × 2 grid units；When, judge P 2 × 2
In the bottom right grid of grid unit；
(1-6-3-4) position according to P places grid in 2 × 2 grid units, calculates line number s of P places gridxWith
Row number tx。
(1-6-4) calculate the middle point coordinates (x of P places grid0,y0)；
Wherein,
(1-6-5) calculate P point coordinates.
Specifically, when P is in the lower-left grid of 2 × 2 grid units, being calculated P point coordinates isWhen P is in the upper left grid of 2 × 2 grid units, in Δ l ＜ dx, being calculated P point coordinates is
(x0+Δl-dx,y0), in Δ l ＞ dx, P point coordinates is calculated for (x0,y0+Δl-dx)；P is on the right side of 2 × 2 grid units
When in upper grid, in Δ l ＜ dx+dy, P point coordinates is calculated for (x0,y0+ Δ l-dx-dy), in Δ l ＞ dx+dy, meter
Calculation obtains P point coordinatesWhen P is in the bottom right grid of 2 × 2 grid units, in Δ l ＜
During 2dx+dy, P point coordinates is calculated for (x0+Δl-2dx+dy,y0), in Δ l ＞ 2dx+dy, being calculated P point coordinates is
(x0,y0+Δl-2dx-dy)。
(2) with knowledge type attribute as |input paramete, defined using pel parameter and fractal calculation, generate blocks of knowledge and reflect
It is mapped to the geometric figure shape of two dimensional surface；
As shown in figure 5, further including following steps：
(2-1) define blocks of knowledge be mapped to two dimensional surface geometric figure be shaped as and knowledge type attribute T-phase close
Function；
(2-2) analysis knowledge type attribute T, defines fundamental type component base (T), wherein, base (T) takes different values
The different basic geometric figure of correspondence；
Specifically,
(2-3) analysis knowledge type attribute T, defines subtype component factal (T), wherein, factal (T) takes different
The different basic geometric figure of value correspondence；
Specifically,
(2-4) v=factal (T) is defined, each edge of basic geometric figure is entered with Koch curve calculation Method of Fractal
V time point of shape refinement of row, obtains new figure.
Further include following steps：
(2-4-1) cycle-index k=0 is set；
(2-4-2) two end points of basic geometric figure a line are labeled as into P1 and P5；
(2-4-3) with P1 as starting point, P2, labelling at line segment P1P5 2/3rds will at line segment P1P5 1/3rd, be labeled as
For P4；
(2-4-4) with P2 as axle center, by 60 ° of P4 rotate counterclockwises, P3 points are obtained；
Specifically used equation below：
(2-4-5) P1, P2, P3, P4 and P5 point coordinates is calculated, generates line segment P1P2, P2P3, P3P4, P4P5, complete wall scroll
The fractal calculation on side；
(2-4-6) according to step (2-4-2) to (2-4-5), traversal completes the fractal calculation on all sides of basic geometric figure,
Obtain new geometric figure；
(2-4-7) cycle-index k=k+1 is made, judges k<Whether v sets up, and is then using new geometric figure as substantially several
What figure, return to step (2-4-2) continue fractal calculation, otherwise complete a point shape, obtain new polygon.
(3) quantity of information with knowledge calculates quantity of information and two-dimensional map region projection area ratio, by face as |input paramete
Product is mapped to the outer bounding box size in two-dimensional map region than calculation knowledge unit, controls knowledge using maximum bounding rectangle algorithms
The feature size of unit；
As shown in fig. 7, further including following steps：
(3-1) the knowledge information amount for counting total isWherein, N is blocks of knowledge quantity, and E is each blocks of knowledge
Quantity of information, according to the planning of formation zone, the area of calculation knowledge unit is σ, and then is calculated shared by unit information amount
Area
(3-2) the quantity of information E according to each blocks of knowledge, calculates each blocks of knowledge occupied area for S=ρ * E；
(3-3) according to each blocks of knowledge occupied area S, with reference to basic geometric figure shape (such as equilateral triangle, positive four side
Shape, regular pentagon or regular hexagon) calculate the size of its boundary rectangle；
(3-4) according to basic geometric figure shape and its size of boundary rectangle, calculate the length of side of basic geometric figure；
Specifically, when basic geometric figure is equilateral triangle, it is calculated the length of side of equilateral triangleWhen basic geometric figure is square, the length of side of square is calculatedIn base
When this geometric figure is regular pentagon, the length of side of regular pentagon is calculatedIn basic geometric figure for just
During hexagon, the orthohexagonal length of side is calculated
(3-5) point centered on the position coordinateses of basic geometric figure, according to basic geometric figure form and dimension, generates
Geometric figure.
(4) with knowledge attribute and user preference as |input paramete, optimize map graphics shape and pattern coloring, generate ratio
The Knowledge Map of appropriateness.
Further include following steps：
(4-1) according to knowledge domain knowledge quantity size and the scope of two-dimensional map, it is determined that generating the ratio of map；
(4-2) when there is knowledge attribute file or user preference is arranged, relevant parameter is read, each is set accordingly and is known
Know the color of unit；When there is no knowledge attribute file and user preference is arranged, using trichromatism to each knowledge list
Unit's coloring；
(4-3) ratio according to the map, carries out random round and smooth process to segmenting pel of the level more than three layers；
(4-4) Knowledge Map is generated, and map file is saved as with reference format.
As it will be easily appreciated by one skilled in the art that the foregoing is only presently preferred embodiments of the present invention, not to
The present invention, all any modification, equivalent and improvement made within the spirit and principles in the present invention etc. are limited, all should be included
Within protection scope of the present invention.
Claims (10)
1. a kind of Knowledge Map mapping generating method, it is characterised in that include：
(1) with the hierarchical relationship of knowledge and incidence relation attribute as |input paramete, by spatial level subdivision and fitting a curve meter
Calculate, Knowledge Mapping is obtained to the coordinate of two dimensional surface map；
Further include following steps：
(1-1) total number of plies L of hierarchical relationship is counted, wherein, i-th layer of blocks of knowledge collection is combined into Xi, i=1,2 ..., L, Xi=
{KDDj| j=1,2 ..., Ni, KDDjFor i-th layer of j-th blocks of knowledge, NiFor the number of blocks of knowledge in i-th layer；
(1-2) plane coordinates for defining blocks of knowledge is the function related to hierarchical relationship value h and incidence relation value r；
(1-3) all layers are traveled through, the sub- lattice network parameters of each layer are calculated；
Wherein, i-th layer of sub- lattice network parameters
(1-4) the sub- lattice network parameters according to each layer, carry out the division of grid space to the corresponding plane domain of each layer, and foundation is filled out
Curve is filled, the length of space filling curve is calculated；
(1-5) the incidence relation value sum of all blocks of knowledge in each layer is calculated, and then calculates its plane area corresponding with this layer
The space filling curve length ratio in domain；
(1-6) position of each blocks of knowledge on the space filling curve of this layer of corresponding plane domain in each layer, Jin Eryou are calculated
Curve segmentation algorithm is back-calculated to obtain the plane coordinates of each blocks of knowledge；
(2) with knowledge type attribute as |input paramete, defined using pel parameter and fractal calculation, generate blocks of knowledge and be mapped to
The geometric figure shape of two dimensional surface；
(3) quantity of information with knowledge calculates quantity of information and two-dimensional map region projection area ratio, by area ratio as |input paramete
Calculation knowledge unit is mapped to the outer bounding box size in two-dimensional map region, controls blocks of knowledge using maximum bounding rectangle algorithms
Feature size；
(4) with knowledge attribute and user preference as |input paramete, optimize map graphics shape and pattern coloring, generate suitable scale
Knowledge Map.
2. Knowledge Map mapping generating method as claimed in claim 1, it is characterised in that in the step (1-4), i-th layer
Space filling curve length Len of corresponding plane domainiIt is calculated by the following method：
(A1) i-th layer of corresponding plane domain is divided intoIndividual grid；
(A2) grid ticks for arranging s rows t is (s, t), with 2 × 2 grid as unit, chooses (s, t), (s, t+1), (s+
1, t+1) and (central point of this four grid is connected into line by s+1, t) four grid successively；
(A3) successively will (s+2, t), (s+2, t+1), (s+3, t+1) and (s+3, t) central point of four grid connect into line；
(A4) by (s+1, t+1) and (s+2, central point t) connect into line；
(A5) central point of (s, t+2), (s, t+3), (s+1, t+3) and (s+1, t+2) four grid is connected into into line successively；
(A6) central point of (s+1, t+1) and (s, t+2) is connected into into line；
(A7) successively will (s+2, t), (s+2, t+1), (s+3, t+1) and (s+3, t) central point of four grid connect into line；
(A8) by (s+1, t+3) and (s+2, central point t) connect into line；
(A9) the line total length that calculation procedure (A2)～(A8) is obtained, obtains the space filling curve of i-th layer of corresponding plane domain
Length Leni。
3. Knowledge Map mapping generating method as claimed in claim 1, it is characterised in that the step (1-6) is further wrapped
Include following steps：
(1-6-1) incidence relation value r according to blocks of knowledge, from the beginning of the space filling curve head of its corresponding plane domain of place layer
Traversal, obtains the point P that starting point distance is r；
(1-6-2) the long dx of grid and grid width dy of calculation knowledge unit place layer；
(1-6-3) calculate and be not less thanMinimum positive integer Li, the ranks number of P places grid are calculated according to Li；
(1-6-4) calculate the middle point coordinates (x of P places grid0,y0)；
(1-6-5) calculate P point coordinates.
4. Knowledge Map mapping generating method as claimed in claim 3, it is characterised in that the step (1-6-3) is further
Comprise the steps：
(1-6-3-1) according to space filling curve rule, calculate the line number of 2 × 2 grid units that P is located
(1-6-3-2) calculate length Δ l=Li (dx+dy)-r of the space filling curve from starting point to P in 2 × 2 grid units；
(1-6-3-3) existWhen, judge P in the lower-left grid of 2 × 2 grid units；
When, judge P in the upper left grid of 2 × 2 grid units；When, judge P in 2 × 2 grid
In the upper right grid of unit；When, judge bottom right grid of the P in 2 × 2 grid units
It is interior；
(1-6-3-4) position according to P places grid in 2 × 2 grid units, calculates line number s of P places gridxAnd row number
tx。
5. Knowledge Map mapping generating method as claimed in claim 4, it is characterised in that the step (1-6-5) is specially：
When P is in the lower-left grid of 2 × 2 grid units, being calculated P point coordinates isP is in 2 × 2 grid
When in the upper left grid of unit, in Δ l ＜ dx, P point coordinates is calculated for (x0+Δl-dx,y0), in Δ l ＞ dx, meter
Calculation obtains P point coordinates for (x0,y0+Δl-dx)；When P is in the upper right grid of 2 × 2 grid units, in Δ l ＜ dx+dy, meter
Calculation obtains P point coordinates for (x0,y0+ Δ l-dx-dy), in Δ l ＞ dx+dy, being calculated P point coordinates isWhen P is in the bottom right grid of 2 × 2 grid units, in Δ l ＜ 2dx+dy, calculate
It is (x to P point coordinates0+Δl-2dx+dy,y0), in Δ l ＞ 2dx+dy, P point coordinates is calculated for (x0,y0+Δl-2dx-
dy)。
6. the Knowledge Map mapping generating method as any one of claim 1 to 5, it is characterised in that the step (2)
Further include following steps：
(2-1) define blocks of knowledge be mapped to two dimensional surface geometric figure be shaped as with knowledge type attribute T-phase close function；
(2-2) analysis knowledge type attribute T, defines fundamental type component base (T), wherein, base (T) takes different value correspondences
Different basic geometric figures；
(2-3) analysis knowledge type attribute T, defines subtype component factal (T), wherein, factal (T) takes different values pair
Answer different basic geometric figures；
(2-4) v=factal (T) is defined, each edge of basic geometric figure is carried out v time with Koch curves calculation Method of Fractal
Divide shape refinement, obtain new figure.
7. Knowledge Map mapping generating method as claimed in claim 6, it is characterised in that the step (2-4) is further wrapped
Include following steps：
(2-4-1) cycle-index k=0 is set；
(2-4-2) two end points of basic geometric figure a line are labeled as into P1 and P5；
(2-4-3) with P1 as starting point, P2 will be labeled as at line segment P1P5 1/3rd, be labeled as at line segment P1P5 2/3rds
P4；
(2-4-4) with P2 as axle center, by 60 ° of P4 rotate counterclockwises, P3 points are obtained；
(2-4-5) P1, P2, P3, P4 and P5 point coordinates is calculated, generates line segment P1P2, P2P3, P3P4, P4P5, complete single edge
Fractal calculation；
(2-4-6) according to step (2-4-2) to (2-4-5), traversal completes the fractal calculation on all sides of basic geometric figure, obtains
New geometric figure；
(2-4-7) cycle-index k=k+1 is made, judges k<Whether v sets up, and is then using new geometric figure as basic geometric graph
Shape, return to step (2-4-2) continue fractal calculation, otherwise complete a point shape, obtain new polygon.
8. Knowledge Map mapping generating method as claimed in claim 7, it is characterised in that the step (3) further includes
Following steps：
(3-1) the knowledge information amount for counting total isWherein, N is blocks of knowledge quantity, and E is the letter of each blocks of knowledge
Breath amount, according to the planning of formation zone, the area of calculation knowledge unit is σ, and then the face being calculated shared by unit information amount
Product
(3-2) the quantity of information E according to each blocks of knowledge, calculates each blocks of knowledge occupied area for S=ρ * E；
(3-3) according to each blocks of knowledge occupied area S, the size of its boundary rectangle is calculated with reference to basic geometric figure shape；
(3-4) according to basic geometric figure shape and its size of boundary rectangle, calculate the length of side of basic geometric figure；
(3-5) point centered on the position coordinateses of basic geometric figure, according to basic geometric figure form and dimension, generates geometry
Figure.
9. Knowledge Map mapping generating method as claimed in claim 8, it is characterised in that in the step (3-4), basic
When geometric figure is equilateral triangle, the length of side of equilateral triangle is calculatedIt is positive four in basic geometric figure
During the shape of side, the length of side of square is calculatedWhen basic geometric figure is regular pentagon, positive five are calculated
The length of side of side shapeWhen basic geometric figure is regular hexagon, the orthohexagonal length of side is calculated
10. Knowledge Map mapping generating method as claimed in claim 9, it is characterised in that the step (4) further includes
Following steps：
(4-1) according to knowledge domain knowledge quantity size and the scope of two-dimensional map, it is determined that generating the ratio of map；
(4-2) when there is knowledge attribute file or user preference is arranged, relevant parameter is read, each knowledge list is set accordingly
The color of unit；When there is no knowledge attribute file and user preference is arranged, each blocks of knowledge using trichromatism
Color；
(4-3) ratio according to the map, carries out random round and smooth process to segmenting pel of the level more than three layers；
(4-4) Knowledge Map is generated, and map file is saved as with reference format.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610063529.7A CN105760428B (en) | 2016-01-29 | 2016-01-29 | Knowledge map mapping generation method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610063529.7A CN105760428B (en) | 2016-01-29 | 2016-01-29 | Knowledge map mapping generation method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN105760428A CN105760428A (en) | 2016-07-13 |
| CN105760428B true CN105760428B (en) | 2017-04-26 |
Family
ID=56342731
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610063529.7A Active CN105760428B (en) | 2016-01-29 | 2016-01-29 | Knowledge map mapping generation method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105760428B (en) |
Families Citing this family (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108319733B (en) * | 2018-03-29 | 2020-08-25 | 华中师范大学 | Map-based education big data analysis method and system |
| CN112836060B (en) * | 2019-11-25 | 2023-11-24 | 中国科学技术信息研究所 | Atlas construction method and apparatus for technological innovation data |
| CN113157977A (en) * | 2020-12-28 | 2021-07-23 | 北京力诺达信息技术有限公司 | Quick-checking guide picture and its making method |
| CN113220773B (en) * | 2021-05-28 | 2023-09-01 | 华中师范大学 | Map visualization method and system for student evaluation data image |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20140081982A1 (en) * | 2012-09-18 | 2014-03-20 | Jiun Hung | Method and Computer for Indexing and Searching Structures |
| CN103744846B (en) * | 2013-08-13 | 2016-12-28 | 北京航空航天大学 | A kind of multidimensional dynamic local knowledge map and construction method thereof |
| CN103605706B (en) * | 2013-11-11 | 2016-06-15 | 华中师范大学 | A kind of resource retrieval method of knowledge based map |
-
2016
- 2016-01-29 CN CN201610063529.7A patent/CN105760428B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN105760428A (en) | 2016-07-13 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105760428B (en) | Knowledge map mapping generation method | |
| CN105513114B (en) | The method and apparatus of three-dimensional animation generation | |
| CN104183016B (en) | A kind of construction method of quick 2.5 dimension building model | |
| CN100562895C (en) | A kind of method of the 3 D face animation based on Region Segmentation and speced learning | |
| CN109711018A (en) | A kind of Size Dwelling Design method of 2 d-to-3 d | |
| CN103489224B (en) | A kind of interactive three-dimensional point cloud color edit methods | |
| CN105931298B (en) | A kind of basse-taille position automatic selecting method of view-based access control model conspicuousness | |
| CN105069751B (en) | A kind of interpolation method of depth image missing data | |
| CN106295170A (en) | Tooth modeling method based on corona Yu root of the tooth feature | |
| CN112099627B (en) | City design virtual reality instant interaction platform based on artificial intelligence | |
| CN107145928A (en) | It is improved towards 3D printing self-definition model stereoscopic two-dimensional code generating method and system | |
| CN109544687B (en) | Directional layered household graph expansion method | |
| CN106600684A (en) | Oblique model organization construction method | |
| CN108986221A (en) | A kind of three-dimensional face grid texture method lack of standardization approached based on template face | |
| CN104732592A (en) | Real-time three-dimensional data generation method based on two-dimensional LED rotating screen | |
| CN108510562A (en) | Digital camouflage method for generating pattern based on image fractal texture | |
| Xie et al. | Balloonfab: Digital fabrication of large-scale balloon art | |
| CN105894551A (en) | Image drawing method and device | |
| CN110176053A (en) | A kind of three-dimensional whole even color method of extensive outdoor scene | |
| CN103366402A (en) | Fast attitude synchronization method of three-dimensional virtual clothing | |
| CN107346408A (en) | Age recognition methods based on face feature | |
| US9875555B2 (en) | Partitioning an image | |
| CN110443872A (en) | A kind of countenance synthesis method having dynamic texture details | |
| CN109509254B (en) | Three-dimensional map construction method, device and storage medium | |
| CN108898679A (en) | A kind of method of component serial number automatic marking |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |