CN106484754A - Based on hierarchical data and the knowledge forest layout method of diagram data visualization technique - Google Patents
Based on hierarchical data and the knowledge forest layout method of diagram data visualization technique Download PDFInfo
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Abstract
The present invention relates to a kind of knowledge forest layout method based on hierarchical data and diagram data visualization technique, the data of knowledget opic facet tree and the data of knowledge fragment of instantiation are obtained first, using the data, the drafting of the knowledget opic facet tree of instantiation is realized by the knowledget opic facet tree rendering algorithm of the instantiation based on Bezier；By abstract for the knowledget opic facet tree of the instantiation that draws for node v, by abstract for the cognitive relation between knowledget opic for side e, by abstract for knowledge forest for figure G (V, E), wherein, G represents knowledge forest, and V represents the set of v, and E represents the set of e；Realize the integral layout of knowledge forest G and show community structure, complete the knowledge forest layout with diagram data visualization technique based on hierarchical data.Binding hierarchy data of the present invention and diagram data topology, realize the layout of knowledget opic facet tree and the layout of knowledge forest of instantiation, while supporting the visualization of knowledget opic facet tree and cognitive relation.
Description
【Technical field】
The present invention relates to data visualization field, more particularly to a kind of based on hierarchical data and diagram data visualization technique
Knowledge forest layout method.
【Background technology】
The high speed development of science and technology causes knowledge explosion phenomenon increasingly serious, and multi-source, unilateral, unordered knowledge fragment add
The acute cognitive overload problem of the mankind and study are got lost problem.Knowledge forest is a kind of brand-new knowledge polymerizing pattern, can be by
Knowledge fragment aggregates into the form for meeting human cognitive feature, alleviates the problems referred to above.But the huge and structure of knowledge forest data volume
Complexity, user are difficult to directly understanding, need application data visualization correlation technique to realize its visual presentation.
Knowledge forest had both included a large amount of knowledget opic facet trees, and again comprising a large amount of cognition relations, the former has hierarchical data
Architectural feature, the latter has the architectural feature of diagram data.In existing research, the layout method of hierarchical data mainly include with
Lower three classes：Node link method, space completion method and tree-model；The visual form of first two technology is not the form of tree, no
Method is applied in the visualization of knowledget opic facet tree, and the development of tree-model is also and immature, is not suitable for knowledget opic and is divided
The method of face tree layout.The layout of diagram data mainly includes the layout of non-directed graph and the layout of digraph, and the former applies more wide
General technology is power guiding model, and it is hierarchical layout algorithm that the latter is more popular.
Do not support due to prior art or the visualization of knowledget opic facet tree or do not support the visual of cognitive relation
Change, be all difficult to be applied directly in the middle of the visualization of knowledge forest.Need binding hierarchy data layout and two class of diagram data layout
Technology, realizes the visualization of knowledge forest.For hierarchical data and the layout method of diagram data, applicant is new by looking into, retrieval
To 1 patent of invention related to the present invention：
A kind of method for visualizing of hierarchical data and equipment, number of patent application：2013100171509；The patent proposes
A kind of method for visualizing of hierarchical data and equipment, including：Tree data is generated according to its detail analysis relation to data set HD
Structure；Each node in level in the tree data structure that will be generated less than Node B threshold, is calculated with adaptive radiation ring
Method generates sector structure；Each node in level in the tree data structure that will be generated greater than or equal to Node B threshold, adopts
With interactive mode, son radiation ring, i.e. item chain link is generated with item chain link algorithm；Described putting is drawn and is shown on display plane
Penetrate ring and item chain link.
In the art solutions of above-mentioned hierarchical data method for visualizing, visualization result is radiation annular, is not certainly
The form that so sets in boundary, it is impossible to each level element for showing knowledget opic facet tree directly perceived.And general hierarchical data visualization
As a result or be node connection figure, or be space blank map, cannot all realize the visualization of knowledget opic facet tree.
【Content of the invention】
It is an object of the invention to overcoming problems of the prior art, one kind is proposed based on hierarchical data and diagram data
The knowledge forest layout method of visualization technique, can support the visualization of knowledget opic facet tree and cognitive relation simultaneously.
For reaching object above, the present invention is adopted the following technical scheme that and is achieved：
Comprise the following steps：
Step one：Obtain the data of knowledget opic facet tree and the data of knowledge fragment of instantiation；
Step 2：The knowledget opic facet tree of the instantiation obtained using step one and knowledge crumb data, by being based on
The knowledget opic facet tree rendering algorithm of the instantiation of Bezier realizes the drafting of the knowledget opic facet tree of instantiation；
Step 3：The knowledget opic facet tree of the instantiation that step 2 is drawn is abstract for node v, by between knowledget opic
Cognitive relation abstract for side e, in order to scheme G (V, E), wherein, G represents knowledge forest, and V represents the set of v by abstract for knowledge forest,
E represents the set of e；
Step 4：Realize the integral layout of knowledge forest G and show community structure, complete based on hierarchical data and diagram data
The knowledge forest layout of visualization technique.
Further, the data of the knowledget opic facet tree for being related to instantiate and knowledge fragment are converted in step one
Json form.
Further, the data of the knowledget opic facet tree of instantiation include branch amount evidence, and branch data structure includes 8
Parameter：The number of direct subordinate's branch of the total tbn of Branches of Different Orders, branch on maximum level depth tbl of branch, branch
On bn, branch leafed number tln, data c of lowest-rank element, the unique identifier ti of branch, branch title na with
And type tp of the Branches of Different Orders in the knowledget opic facet tree of instantiation, the wherein element of c includes under leaf or nesting
Level branch；
The leaf data of the knowledget opic facet tree of the data composition instantiation of knowledge fragment, leaf data structure include 4
Individual parameter：Web page address u, content ct of knowledge fragment, the id identifier fi of knowledge fragment and knowledge that knowledge fragment is located
Type tp ' of the fragment in the knowledget opic facet tree of instantiation.
Further, step 2 is specifically included：
201st, layout control parameter is initialized, the node for calculating Beziers at different levels in conjunction with layout control parameter is sat
Mark；
202nd, control branch presses the growth of self-adaptive growth order：
The succession of branch is Bl1,Bl2,...,Bli-1,Bli,Bli+1,...,Blm-1,Blm,Brn,Brn-1,...,Brj+1,
Brj,Brj-1,...,Br2,Br1, wherein BliAnd BrjKnowledget opic facet tree left side and the branch on right side that generation, table was instantiated respectively, m
The quantity of left side and right side branch is represented with n respectively；
On branch, the quantity of leaf meets following rule：|Bl1|≤|Bl2|≤...≤|Bli-1|≤|Bli|≥|Bli+1|
≥...≥|Blm-1|≥|Blm| and | Brn|≤|Brn-1|≤...≤|Brj+1|≤|Brj|≥|Brj-1|≥...≥|Br2|≥|Br1
|, | Bli| and | Brj| represent B respectivelyliAnd BrjThe quantity of upper leaf；
203rd, according to the coordinate (x of root node0, y0) and branch total quantity nb, the starting point seat of trunk is calculated by below equation
Mark：The terminal point coordinate of trunk is calculated by below equation：Wherein xi1And xi2Trunk T is represented respectivelyiTerminal abscissa；yi1And yi2Point
Trunk T is not representediThe ordinate of terminal；Wt represents the linear width of trunk；Bht is to determine that branch starts determining for growth position
Value parameter；Lc represents the abscissa of trunk in an intermediate position, lc=x0+wt×M×nb/2；Level represents trunk growth
Height, if i<(nb/2), then level=i+1, otherwise level=nb-i；
204th, following operation is executed to each branch：Depth-first traversal, higher level's branch as the father node of subordinate's branch,
The terminal point coordinate of wherein trunk is calculated by below equation and represents three shellfishes of Branches of Different Orders as the starting point coordinate of one-level branch
The starting point of Sai Er curve, terminal and two control point coordinates：If wherein (xi1, yi1) generation
During the coordinate of table starting point, first control point or second control point, corresponding：(xi2, yi2) represent first control point,
Two control points or terminal point coordinate；L represents lst1, lst2 or lst3, and as represents ast1, ast2 or ast3；Wherein, lst1 represents
One-level branch length, lst2 represent second branch length, and lst3 represents three-level branch length, lst1 ＞ lst2 ＞ lst3；ast1
Represent one-level crotch angle, ast2 represents second branch angle, and ast3 represents three-level crotch angle, ast1, ast2 and ast3's
Span is between 0.6 to 0.8；
205th, using final stage branch as leaf father node, formula according to step 204 calculates and represents the three of leaf
The starting point of secondary Bezier, terminal and control point coordinates, if wherein (xi1, yi1) represent starting point, first control point or second
During the coordinate at individual control point, corresponding：(xi2, yi2) represent first control point, second control point or terminal point coordinate；L is represented
Lsl1, lsl2 or lsl3, as represent asl1, asl2 or asl3；Wherein, lsl1 represents the Leaf length of one-level branch, lsl2 table
Show the Leaf length of second branch, lsl3 represents the Leaf length of three-level branch, lsl1 ＞ lsl2 ＞ lsl3；Asl1 represents one-level
The leaf angle of branch, asl2 represent the leaf angle of second branch, and asl3 represents the leaf angle of three-level branch, asl1,
The span of asl2 and asl3 is between 0.6 to 1.6；
206th, trunk is drawn according to the coordinate that step 203 to step 205 is calculated and represents three times of Branches of Different Orders and leaf
Bezier, and add corresponding text message, complete the drafting of the knowledget opic facet tree of instantiation.
Further, 41 parameters are had in step 201.
Further, the text message for adding in step 206 includes that knowledget opic, the facet of the knowledget opic and knowledge are broken
Piece, adds knowledget opic in trunk position, adds each facet of the knowledget opic in Branches of Different Orders position, in the leaf of branch
The knowledge fragment under corresponding facet is added in position.
Further, step 4 is specifically included：
401st, for each node v in G, the geometric distance between calculate node v and another arbitrary node u：Wherein vxAnd uxRepresent the x-axis coordinate of node v and u, v respectivelyyAnd uyDifference table
Show the y-axis coordinate of node v and u；
402nd, repulsive force between v and u is calculated：fr(v, u)=k2/(α×dist(v,u))；Wherein α is parameter, and in node
When v and u belong to same corporations, α value is 1, and when node v and u are not belonging to same corporations, α value is 6；
403rd, attraction between v and u is calculated：fa(v, u)=(dist (v, u))2/k；
404th, by the coordinate (v of node vx, vy) it is updated to (vx', vy'), wherein vx'=max (0, min (W, vx)), vy'=
max(0,min(H,vy)), W and H is the width of viewable area and height；
405th, final, by continuous iteration, until the coordinate of each node v determines constant, stable state is reached, is realized
The integral layout of knowledge forest.
Further, also include step 5：Using the Sugiyama algorithm in layout of directed graph, calculate each node v's
Coordinate, obtains position of each node v in viewable area, realizes the layout in corporations.
Further, step 5 is specifically included：
501st, directed loop is eliminated：If G has ring, the side for having ring is reversed, eliminated directed loop；
502nd, by Node distribution in each layer：Each node level number is specified, determines the ordinate of node, if ＜ u, v ＞ category
In E, then level number of the level number of node u less than node v；The step can introduce intermediate node in long side；
503rd, cross edge is minimized：One number of times is specified to every node layer, makes cross edge minimum number；
504th, the minimum principle of the number of bends that introduces by the total length on side and by intermediate node gives each node coordinate, complete
Become the layout in corporations.
Compared with prior art, the present invention has following beneficial technique effect：
In the present invention for knowledget opic facet tree layout, it is proposed that the knowledge master based on the instantiation of Bezier
Topic facet tree rendering algorithm, solves imbalance and the staggered leaf overlap of branch of the knowledget opic facet tree of instantiation etc. and asks
Topic；For the layout of forest, the layout of whole forest is achieved by improved FR algorithm and shows community structure.The present invention is tied
Hierarchical data and diagram data topology is closed, the layout of knowledget opic facet tree and the layout of knowledge forest of instantiation is realized,
While supporting the visualization of knowledget opic facet tree and cognitive relation.
Further, branch growth direction and growth angle self adaptation are controlled by layout parameter in the present invention, solves
The knowledget opic facet tree that the leaf quantity gap of the more and different branches of knowledget opic facet leaf quantum count is larger and causes
The problem that easily uneven and branch interlocks, leaf is overlapped.
Further, layout parameter up to 41 in the present invention, can control the knowledget opic facet of instantiation well
The display effect of tree so as to meet the growth rhythm that sets in nature, is conducive to user learning to use.
Further, pass through Sugiyama algorithm in the present invention, it is achieved that knowledget opic facet root vertex in corporations
Layout, for the community structure in whole knowledge forest, more intuitively shows between each corporations' interior nodes
Cognitive relation, facilitate user learning and use.
【Description of the drawings】
Fig. 1 is the flow chart of the present invention.
Fig. 2 is the knowledget opic facet tree rendering algorithm flow process of the instantiation based on Bezier proposed by the invention
Figure.
Fig. 3 is the instance graph of the knowledget opic facet drawn by Fig. 2.
Fig. 4 is the instance graph of knowledge forest community structure realized when α value is by 6 in the present invention.
Fig. 5 is the instance graph of knowledge forest community structure realized when α value is by 1 in the present invention.
【Specific embodiment】
Below in conjunction with the drawings and the specific embodiments, the present invention is described in further detail.Be given in the present invention first
The term definition being related to.
Knowledge forest：It is a kind of brand-new fragmentation knowledge polymerizing pattern, fragmentation knowledge polymerizing process is regarded as and " is known
Know theme facet tree generations-fragmentation knowledge and assemble-cognition relation excavation " triphasic knowledge forest generating process, can be by
The such as Chinese and English text of multi-source, unilateral, unordered fragmentation knowledge and the multimedia resource such as picture, video are aggregated into and meet people
The pattern of the features such as class cognitive learning multi-dimensional nature, relevance, conformability.
Knowledget opic facet tree：Refer to the hierarchical structure tree of a certain knowledget opic institutional framework of description, knowledget opic facet tree
Data mainly include branch data.
Instantiation knowledget opic facet tree：Refer to comprising the knowledget opic facet for describing all knowledge fragments of a certain knowledget opic
Tree, i.e., the leaf data for also including in branch data, the content of leaf data are exactly the data of knowledge fragment.
Cognitive relation：Refer to the dependence formed between knowledget opic in learning process due to cognitive needs.
Corporations refer in knowledge forest that a part of knowledget opic is gathered into a cluster due to cognitive relation, form a society
Group.
Knowledge forest initializes：Knowledge forest is expressed as two tuples KF=(FT, LD), wherein FT represents knowing for instantiation
Know the set of theme facet tree, LD represents the cognitive set of relationship between knowledget opic, i.e.,The knowledge of instantiation
Theme facet tree can be further represented as triple KTI=(KFT, KFS, MP), and wherein KFT is expressed as knowledget opic facet tree collection
Close, KFS represents knowledge set of patches, and MP represents between knowledget opic facet leaf child node Leaf (KFT) and knowledge fragment
Mapping relations set, i.e.,Knowledget opic facet tree be represented by triple KT=(ku, FR,
R), wherein root node ku represents a knowledget opic, such as " linear list ".Intermediate node set FR represents the facet collection of knowledget opic
Close, for example, for " linear list ", its facet includes " definition ", " storage organization " etc..It is dividing for knowledget opic
There is hyponymy between semantic relation set between face, such as " storage organization " and " sequential core-pulling ".
Knowledge forest layout method of the present invention based on hierarchical data and diagram data visualization technique, by being based on Bezier
The knowledget opic facet tree rendering algorithm of curve realizes the layout of knowledget opic facet tree, by FR algorithm and Sugiyama algorithm
The layout of forest and theme corporations is realized, as shown in figure 1, comprising the following steps that：
Step one：Execute following initialization operation：
101st, data prediction：According to the demand of drafting, respectively will be broken to the knowledget opic facet tree for being related to instantiate and knowledge
The data of piece are converted to specific json form, are subsequently to carry out drafting in a browser to prepare.Wherein, the knowledge of instantiation
The branch data structure of theme facet tree includes 8 parameters：Tbl represents the maximum level depth of the branch；Tbn refers on the branch
The sum of Branches of Different Orders, Branches of Different Orders refer to direct subordinate's branch on the branch to final stage branch；Bn refers to the direct of the branch
The number of subordinate's branch；Tln refers to the leafed number of institute on the branch；The element of c refers to the data of lowest-rank element, can be leaf
Data or nesting subordinate's branch data；Ti refers to the unique identifier of the branch；Na refers to the title of the branch；Tp refers to respectively
Type of the level branch in the knowledget opic facet tree of instantiation.
The leaf data of the knowledget opic facet tree of instantiation are made up of the data of knowledge fragment, and leaf data structure includes
4 parameters：U represents the web page address that the knowledge fragment is located；Ct refers to the content of the knowledge fragment, and most is content of text, also
Can be the multimedia resources such as picture or video；Fi represents the id identifier of the knowledge fragment；Tp ' refers to the knowledge fragment in reality
Type in the knowledget opic facet tree of exampleization.
Step 2：Instantiation is realized by the knowledget opic facet tree rendering algorithm of the instantiation based on Bezier
The drafting of knowledget opic facet tree, solves imbalance and the staggered leaf overlap of branch of the knowledget opic facet tree of instantiation etc.
Problem；The knowledge of instantiation of the knowledget opic facet tree of the instantiation that completes including obtaining after pretreatment in step one
Theme facet tree and the data file of knowledge fragment, the coordinate (x of the knowledget opic facet root vertex of instantiation0, y0), and
Control parameter M of the knowledget opic facet tree display level of control instantiation.Arthmetic statement is as follows：
The input of algorithm is the data file that obtains after pretreatment, and output is that the knowledget opic of the instantiation that draws divides
Face tree simultaneously shows in a browser.Referring to Fig. 2, the concrete steps of algorithm include following 6 step：
201st, the layout control parameter of 41 trunk, branch and leaves is initialized：Parameter is related to length, width, angle, face
5 aspect such as color, control parameter, the parameter for being related to angle therein and part control parameter cause the direction of growth of branch adaptive
Should, the node coordinate of Beziers at different levels is calculated in conjunction with these parameters.Wherein, length parameter 12, width parameter 7,
Angle parameter 6, color parameter 6, control parameter 10.Length parameter includes and certain branch length or its subordinate's branch length
5 relevant parameters 5 parameter, beam length and the text sizes relevant with the Leaf length on multistage branch, wherein, five
Individual branch length at least includes one-level branch length, second branch length and three-level branch length, and Leaf length at least includes one
The Leaf length of the level Leaf length of branch, the Leaf length of second branch and three-level branch, rest parameter can be as needed
Set, such as increase branch series etc.；Text size refers to click on certain leaf, the prompting text size of explicit knowledge's fragment；
Width parameter includes trunk width, one-level branch width, second branch width, the Leaf width of one-level branch, second branch
Leaf width, highlighted Leaf width and textwidth；Angle parameter includes one-level crotch angle, second branch angle, three fractions
Branch angle, the leaf angle of one-level branch, the leaf angle of second branch, the leaf angle of three-level branch；Color parameter includes
Trunk color, one-level branch color, second branch color, leaf color, highlighted branch color, highlighted leaf color；Control ginseng
Number includes to control knowledget opic facet tree display level, the width for controlling whole layout, the height for controlling whole layout, control point
Branch clearance spaces position, control leaf locus, control need to show the length of text, control trunk space, control branch
Space, the x coordinate of control text and y-coordinate.By this 41 parameters, the knowledget opic facet of instantiation can be controlled well
The display effect of tree so as to meet the growth rhythm that sets in nature, is conducive to user learning to use.
202nd, control branch growth order self adaptation, be described as follows example：
By taking certain knowledget opic for instantiating facet tree as an example, before processing to data, the number of leaf on each branch
Mesh is random, and the knowledget opic facet tree of the instantiation that now draws is likely to be unbalance；Divide after sequence is processed
The succession of branch is Bl1,Bl2,...,Bli-1,Bli,Bli+1,...,Blm-1,Blm,Brn,Brn-1,...,Brj+1,Brj,
Brj-1,...,Br2,Br1, wherein Bli、BrjThe branch of the knowledget opic facet tree left and right side of difference representative instance, m and n difference
The quantity of left and right side branch is represented, | Bli|、|Brj| represent B respectivelyli、BrjThe quantity of upper leaf；
On branch, the quantity of leaf meets following rule：|Bl1|≤|Bl2|≤...≤|Bli-1|≤|Bli|≥|Bli+1|
≥...≥|Blm-1|≥|Blm| and | Brn|≤|Brn-1|≤...≤|Brj+1|≤|Brj|≥|Brj-1|≥...≥|Br2|≥|Br1
|, the knowledget opic facet tree left and right for now instantiating is in a basic balance, and mid portion leaf quantity is at most, to upper and lower both sides leaf
Subnumber mesh respectively successively decreases, and meets the growth rhythm of trees in nature.
203rd, according to (x0, y0) and branch total quantity nb, the starting point coordinate of trunk is calculated by below equation：(x0, y0) represent root node coordinate；The terminal point coordinate of trunk is calculated by below equation：Wherein xi1And xi2The trunk T of the theme facet tree of i-th instantiation is represented respectivelyi
Terminal abscissa, yi1And yi2Trunk T is represented respectivelyiThe ordinate of terminal, wt represent the linear width of trunk, and bht is
Definite value parameter, determines that branch starts the position for growing.Lc represents the abscissa of trunk in an intermediate position, according to trunk starting point
Coordinate and trunk are highly calculating the abscissa in trunk centre position：Lc=x0+ wt × M × nb/2, level represent trunk growth
Height, the ordinate of trunk terminal can be determined, its computing formula is：If i<(nb/2), then level=i+1, otherwise
Level=nb-.i
204th, following operation is executed to each branch：Depth-first traversal, higher level's branch is used as the father node of subordinate's branch
(wherein trunk terminal point coordinate as one-level branch starting point coordinate), calculated by below equation and represent for three times of Branches of Different Orders
The starting point of Bezier, terminal and two control point coordinates：If wherein (xi1, yi1)
Represent starting point, first control point or second control point coordinate when, corresponding：(xi2, yi2) represent first control point,
Second control point or terminal point coordinate；L represents lst1, lst2 or lst3, and as represents ast1, ast2 or ast3.Wherein, lst1 table
Show one-level branch length, lst2 represents second branch length, lst3 represents three-level branch length, their value foundation is lst1
＞ lst2 ＞ lst3；Ast1 represents one-level crotch angle, and ast2 represents second branch angle, and ast3 represents three-level crotch angle,
Their span be between 0.6 to 0.8.
205th, using final stage branch as leaf father node, formula according to step 204 calculates and represents the three of leaf
The starting point of secondary Bezier, terminal and control point coordinates, if wherein (xi1, yi1) represent starting point, first control point or second
During the coordinate at individual control point, corresponding：(xi2, yi2) represent first control point, second control point or terminal point coordinate；L is represented
Lsl1, lsl2 or lsl3, as represent asl1, asl2 or asl3.Wherein, lsl1 represents the Leaf length of one-level branch, lsl2 table
Show that the Leaf length of second branch, lsl3 represent the Leaf length of three-level branch, their value foundation is lsl1 ＞ lsl2 ＞
lsl3；Asl1 represents that the leaf angle of one-level branch, asl2 represent that the leaf angle of second branch, asl3 represent three-level branch
Leaf angle, their span be between 0.6 to 1.6.
206th, trunk is drawn according to the coordinate that step 203 to step 205 is calculated and represents three times of Branches of Different Orders and leaf
Bezier, and add corresponding text message, text message mainly includes knowledget opic, facet and knowledge fragment, is leading
Knowledget opic is added in dry position, adds each facet of the knowledget opic in Branches of Different Orders, adds in the leaf of certain branch and corresponds to
Knowledge fragment under facet.
Referring to Fig. 3, the knowledget opic facet tree of this instantiation is made up of trunk, branch, leaf, the coordinate at these positions
It is calculated by the algorithm of step 2, which is meant that：Trunk corresponds to knowledget opic；Branch corresponds to each point of knowledget opic
Face, second branch are the sub- branches of one-level branch, refer to the sub- facet of certain facet；Leaf on branch is under the facet
Knowledge fragment.
Step 3：Execute following operation：By abstract for knowledge forest for scheming G (V, E), the instantiation for wherein being produced by step 2
Knowledget opic facet tree be conceptualized as node v, cognitive relation is conceptualized as side e；G represents knowledge forest, and V represents the set of v,
E represents the set of e.
Step 4：FR algorithm is improved, is realized the integral layout of knowledge forest G and shows community structure.Knowledge forest whole
Body layout refers to calculate the coordinate of all knowledget opics and shows all knowledget opics and its cognitive relation, moreover it is possible to embody corporations
Structure.Community structure refers to that the connection in knowledge forest between a part of knowledget opic point is denser, is gathered into a cluster, shape
Become corporations.It is described in detail below：By new parameter alpha is introduced, increase the repulsive force between the node for belonging to different corporations,
Repulsive force formula between node v and u is by fr(v, u)=k2/ dist (v, u) is changed to fr(v, u)=k2/(α*dist(v,
u)).In formula, if node v and u belong to same corporations, α value is 1；If node v and u are not belonging to same corporations, α value is
According to circumstances can be adjusted, by Experimental comparison, when in the layout of knowledge forest, α value is 6, layout effect is preferable.
Being described as follows of algorithm：
For each node v in G, by calculating the repulsive force between two arbitrary nodes, so as to any to the two
Node is laid out, specific as follows：
401st, the geometric distance between calculate node v and another arbitrary node u：Wherein vx、uxRepresent the x-axis coordinate of node v and u, vy、uyRepresent node v and u
Y-axis coordinate.
402nd, repulsive force between v and u is calculated：fr(v, u)=k2/(α×dist(v,u))；
403rd, attraction between v and u is calculated：fa(v, u)=(dist (v, u))2/k；
404th, by the coordinate (v of node vx, vy) it is updated to (vx', vy'), wherein vx'=max (0, min (W, vx)), vy'=
max(0,min(H,vy)), W and H is the width of viewing area and height；Viewing area is the display model of the viewable area such as browser
Enclose；
405th, final, by continuous iteration, until the coordinate of each node v determines constant, stable state is reached, is realized
The integral layout of knowledge forest.
Referring to Fig. 4, the integral layout of the figure explicit knowledge forest and community structure, the node of in figure represents knowing for instantiation
Know theme facet tree, the side of in figure represents the cognitive relation between node.In figure has four corporations, shows as four node clusters.
Fig. 4 is the knowledge forest layout effect that the parameter alpha value in step 4 is 6, and it is 1 know that Fig. 5 is the parameter alpha value in step 4
Know forest layout effect, it can be seen that Fig. 5 can not clearly display community structure.
Step 5：Using the Sugiyama algorithm in layout of directed graph, the coordinate of each node v is calculated, as knowledge is gloomy
The node of woods is all the root node of the knowledget opic facet tree of instantiation, therefore obtains the root of the knowledget opic facet tree of instantiation
Position of the node in viewable area, realizes the layout in corporations, and viewable area is exactly the viewing area of browser；Relative
For the community structure in the whole knowledge forest of step 4, recognizing between each corporations' interior nodes is more intuitively shown
MS system, facilitates user learning and use.Arthmetic statement is as follows：
501st, directed loop is eliminated：If G has ring, the side for having ring is reversed, eliminated directed loop.Ring be due to scheme G in
Exist the node can be returned to from certain node through other node and be formed.Specifically included in ring is node, node
Refer to knowledget opic.Because the cognitive relation in the present invention is oriented, corresponding side is oriented, so the ring for being formed
And it is oriented.
502nd, node v is distributed in each layer：Each node level number is specified, in order to determine the ordinate of node, it is therefore an objective to
The flow direction of each edge is made to be essentially from top to bottom, if ＜ u, v ＞ belongs to E, then the level number of node u is less than the level of node v
Number.The step can introduce intermediate node in long side.
503rd, cross edge is minimized：One number of times is specified to every node layer so that cross edge quantity is as far as possible few.
504th, each node coordinate is given：The total length for making side and the number of bends introduced by intermediate node minimum.
505th, figure G is returned, and eliminates intermediate node.
The invention discloses a kind of knowledge forest layout method based on hierarchical data and diagram data visualization technique, crucial
Step includes：(1) knowledget opic of instantiation, by the knowledget opic facet tree rendering algorithm based on Bezier, is solved
The uneven and branch of facet tree is staggered, leaf overlap problem；(2) the FR algorithm in non-directed graph layout is improved, is increased and belongs to not
With the repulsive force between the knowledget opic facet tree instantiated between corporations, the layout of forest is realized, show community structure；(3)
The layout in theme corporations is realized with the Sugiyama algorithm in layout of directed graph.The present invention proposes complete knowledge forest
Layout method, is that the interaction design for realizing knowledge forest is laid a good foundation with visual navigation.
Claims (9)
1. a kind of knowledge forest layout method based on hierarchical data and diagram data visualization technique, it is characterised in that：Including with
Lower step：
Step one：Obtain the data of knowledget opic facet tree and the data of knowledge fragment of instantiation；
Step 2：The knowledget opic facet tree of the instantiation obtained using step one and knowledge crumb data, by being based on shellfish plug
The knowledget opic facet tree rendering algorithm of the instantiation of your curve realizes the drafting of the knowledget opic facet tree of instantiation；
Step 3：The knowledget opic facet tree of the instantiation that step 2 is drawn is abstract for node v, by recognizing between knowledget opic
MS system is abstract for side e, and by abstract for knowledge forest for scheming G (V, E), wherein, G represents knowledge forest, and V represents the set of v, E generation
The set of table e；
Step 4：Realize the integral layout of knowledge forest G and show community structure, complete visual with diagram data based on hierarchical data
The knowledge forest layout of change technology.
2. a kind of knowledge forest layout side based on hierarchical data and diagram data visualization technique according to claim 1
Method, it is characterised in that：The data of the knowledget opic facet tree for being related to instantiate and knowledge fragment are converted to json in step one
Form.
3. a kind of knowledge forest layout side based on hierarchical data and diagram data visualization technique according to claim 1
Method, it is characterised in that：The data of the knowledget opic facet tree of instantiation include branch amount evidence, and branch data structure is joined comprising 8
Number：The number bn of direct subordinate's branch of the total tbn of Branches of Different Orders, branch on maximum level depth tbl of branch, branch,
On branch leafed number tln, data c of lowest-rank element, the unique identifier ti of branch, title na of branch and each
Type tp of the level branch in the knowledget opic facet tree of instantiation, the wherein element of c include the lower fraction of leaf or nesting
Branch；
The leaf data of the knowledget opic facet tree of the data composition instantiation of knowledge fragment, leaf data structure are joined comprising 4
Number：Web page address u, content ct of knowledge fragment, the id identifier fi of knowledge fragment and knowledge fragment that knowledge fragment is located
Type tp ' in the knowledget opic facet tree of instantiation.
4. a kind of knowledge forest layout side based on hierarchical data and diagram data visualization technique according to claim 3
Method, it is characterised in that：Step 2 is specifically included：
201st, layout control parameter is initialized, the node coordinate of Beziers at different levels is calculated in conjunction with layout control parameter；
202nd, control branch presses the growth of self-adaptive growth order：
The succession of branch is Bl1,Bl2,...,Bli-1,Bli,Bli+1,...,Blm-1,Blm,Brn,Brn-1,...,Brj+1,Brj,
Brj-1,...,Br2,Br1, wherein BliAnd BrjKnowledget opic facet tree left side and the branch on right side that generation, table was instantiated respectively, m and n
The quantity of left side and right side branch is represented respectively；
On branch, the quantity of leaf meets following rule：|Bl1|≤|Bl2|≤...≤|Bli-1|≤|Bli|≥|Bli+1|≥...≥
|Blm-1|≥|Blm| and | Brn|≤|Brn-1|≤...≤|Brj+1|≤|Brj|≥|Brj-1|≥...≥|Br2|≥|Br1|, | Bli|
With | Brj| represent B respectivelyliAnd BrjThe quantity of upper leaf；
203rd, according to the coordinate (x of root node0, y0) and branch total quantity nb, the starting point coordinate of trunk is calculated by below equation：The terminal point coordinate of trunk is calculated by below equation：
Wherein xi1And xi2Trunk T is represented respectivelyiTerminal abscissa；yi1And yi2Trunk T is represented respectivelyiThe ordinate of terminal；wt
Represent the linear width of trunk；Bht is to determine that branch starts the definite value parameter of growth position；Lc represents master in an intermediate position
Dry abscissa, lc=x0+wt×M×nb/2；Level represents the height of trunk growth, if i<(nb/2), then level=i+
1, otherwise level=nb-i；M represents the control parameter of the knowledget opic facet tree display level of control instantiation；
204th, following operation is executed to each branch：Depth-first traversal, higher level's branch as the father node of subordinate's branch, wherein
The terminal point coordinate of trunk calculates, as the starting point coordinate of one-level branch, three Bezier for representing Branches of Different Orders by below equation
The starting point of curve, terminal and two control point coordinates：If wherein (xi1, yi1) represent
During the coordinate of point, first control point or second control point, corresponding：(xi2, yi2) represent first control point, second
Control point or terminal point coordinate；L represents lst1, lst2 or lst3, and as represents ast1, ast2 or ast3；Wherein, lst1 represents one-level
Branch length, lst2 represent second branch length, and lst3 represents three-level branch length, lst1 ＞ lst2 ＞ lst3；Ast1 represents
One-level crotch angle, ast2 represent second branch angle, and ast3 represents three-level crotch angle, the value of ast1, ast2 and ast3
Scope is between 0.6 to 0.8；
205th, using final stage branch as leaf father node, formula according to step 204 calculates three shellfishes for representing leaf
The starting point of Sai Er curve, terminal and control point coordinates, if wherein (xi1, yi1) represent starting point, first control point or second control
During the coordinate of system point, corresponding：(xi2, yi2) represent first control point, second control point or terminal point coordinate；L is represented
Lsl1, lsl2 or lsl3, as represent asl1, asl2 or asl3；Wherein, lsl1 represents the Leaf length of one-level branch, lsl2 table
Show the Leaf length of second branch, lsl3 represents the Leaf length of three-level branch, lsl1 ＞ lsl2 ＞ lsl3；Asl1 represents one-level
The leaf angle of branch, asl2 represent the leaf angle of second branch, and asl3 represents the leaf angle of three-level branch, asl1,
The span of asl2 and asl3 is between 0.6 to 1.6；
206th, trunk is drawn according to the coordinate that step 203 to step 205 is calculated and represents three shellfish plugs of Branches of Different Orders and leaf
That curve, and add corresponding text message, complete the drafting of the knowledget opic facet tree of instantiation.
5. a kind of knowledge forest layout side based on hierarchical data and diagram data visualization technique according to claim 4
Method, it is characterised in that：41 parameters are had in step 201.
6. a kind of knowledge forest layout side based on hierarchical data and diagram data visualization technique according to claim 4
Method, it is characterised in that：The text message added in step 206 includes knowledget opic, the facet of the knowledget opic and knowledge fragment,
Add knowledget opic in trunk position, add each facet of the knowledget opic in Branches of Different Orders position, in the leaf position of branch
Put the knowledge fragment added under corresponding facet.
7. a kind of knowledge forest layout side based on hierarchical data and diagram data visualization technique according to claim 1
Method, it is characterised in that：Step 4 is specifically included：
401st, for each node v in G, the geometric distance between calculate node v and another arbitrary node u：Wherein vxAnd uxRepresent the x-axis coordinate of node v and u, v respectivelyyAnd uyDifference table
Show the y-axis coordinate of node v and u；
402nd, repulsive force between v and u is calculated：fr(v, u)=k2/(α×dist(v,u))；Wherein α is parameter, and in node v and u
When belonging to same corporations, α value is 1, and when node v and u are not belonging to same corporations, α value is 6；
403rd, attraction between v and u is calculated：fa(v, u)=(dist (v, u))2/k；
404th, by the coordinate (v of node vx, vy) it is updated to (vx', vy'), wherein vx'=max (0, min (W, vx)), vy'=max
(0,min(H,vy)), W and H is the width of viewable area and height；
405th, final, by continuous iteration, until the coordinate of each node v determines constant, stable state is reached, realizes knowledge
The integral layout of forest.
8. a kind of knowledge forest layout side based on hierarchical data and diagram data visualization technique according to claim 1
Method, it is characterised in that：Also include step 5：Using the Sugiyama algorithm in layout of directed graph, the seat of each node v is calculated
Mark, obtains position of each node v in viewable area, realizes the layout in corporations.
9. a kind of knowledge forest layout side based on hierarchical data and diagram data visualization technique according to claim 8
Method, it is characterised in that：Step 5 is specifically included：
501st, directed loop is eliminated：If G has ring, the side for having ring is reversed, eliminated directed loop；
502nd, by Node distribution in each layer：Each node level number is specified, determines the ordinate of node, if ＜ u, v ＞ belongs to E,
Then the level number of node u is less than the level number of node v；The step can introduce intermediate node in long side；
503rd, cross edge is minimized：One number of times is specified to every node layer, makes cross edge minimum number；
504th, the minimum principle of the number of bends that introduces by the total length on side and by intermediate node gives each node coordinate, completes society
Layout in group.
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