CN106021836A - Method and system for generating disciplinary knowledge map based on disciplinary logic knowledge relation - Google Patents
Method and system for generating disciplinary knowledge map based on disciplinary logic knowledge relation Download PDFInfo
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Abstract
The invention discloses a method and a system for generating a disciplinary knowledge map based on disciplinary logic knowledge relations. The method comprises a step of automatically generating knowledge points and connecting lines and a step of automatically generating knowledge relation lines. The step of automatically generating knowledge points and connecting lines further comprises: a substep of knowledge point configuration, used to generate chapter spatial data and configuration files; a substep of knowledge point connecting line generation, used to generate knowledge point connecting lines; and a substep of knowledge point spatial data generation, used to generate knowledge point spatial data. The step of automatically generating knowledge relation lines further comprises: a substep of knowledge relation configuration, used to generate logic knowledge relation configuration files; and a substep of knowledge relation line generation, used to generate knowledge relation spatial data. The method generates a disciplinary knowledge map meeting map characteristics according to logic description of knowledge structure and based on a geographic element spatial simulation technology, so as to provide convenience for a user to understand subject knowledge structure and visualization query.
Description
Technical field
The present invention relates to geographical science graphics field, particularly relate to a kind of raw based on subject logic knowledge relation
Become the method and system of Knowledge Map.
Background technology
" asking of Qian Xuesen " and " two Conferences " representative " are lightened the burden " to shout loudly and are received the extensive concern of public opinion, as
On the premise of not affecting quality of instruction, alleviate the overweight schoolwork burden of student and irrational psychology is born
Load, is that China educates the urgent task faced.
" national medium-term and long-term educational reform and development planning outline (2010-2020) " explicitly points out " information
Technology has revolutionary impact to educational development, it is necessary to paid much attention to ".IT application in education sector is placed in one
Individual unprecedented height, exploitation application high-quality digital education resource, build Learning in Information and teaching environment
Deng, become the guiding theory of new ten years " planning ".Idea of Creative Education, Modern Education Technology are taught with China
The combination educating practice has important practical significance and using value.
Traditional educational mode is for logic knowledge relation tree, shortage iconicity and difficulty by abstract for learning content
In memory；Existing teaching platform knowledge has moved classroom to screen, is still unavoidable from subject logic knowledge
Point and the visualization expression problem of knowledge relation.Additionally, current national curricular standard and existing educational resource tool
There is area differentiation, how to build with knowledge classification as standard, standardized data system based on knowledge relation
Also it is a bottleneck facing of traditional logic knowledge relation.
So, under this background, a Knowledge Map new, natural sciences length of schooling figure thought in combination
Construction method, make Knowledge Map become Dynamic and Multi dimensional, meet reader's vision and read, ground that can be mutual
Figure message form, for promoting problem demanding prompt solution in the change learning thinking.
Summary of the invention
The technical problem to be solved is to provide a kind of generation based on subject logic knowledge relation to learn
The method and system of section's Knowledge Map, are used for solving tradition subject logic knowledge relation and lack visualization table directly perceived
Reach method, the problem that user is not easy mnemonic learning.
The present invention solves further, introduces geographic information system technology (Geographic Information
System, GIS) improve Knowledge Map drawing efficiency and Map Expression Specialization.
For reaching above-mentioned purpose, what the present invention provided generates Knowledge Map based on subject logic knowledge relation
Method, the step that the step automatically generated including knowledge point and line and knowledge relation line automatically generate, its
It is characterised by,
The step that this knowledge point and line automatically generate farther includes:
One knowledge point configuration sub-step, for the chapters and sections graphic hotsopt chapters and sections space number according to picture format
According to and generate logic knowledge point configuration file according to knowledge point form；
One knowledge point line generates sub-step, for closing according to chapters and sections shape, knowledge point quantity and level
System generates knowledge point line and records knowledge point position coordinates；
One knowledge point spatial data generates sub-step, for knowing according to locus, knowledge point Coordinate generation
Know space of points data and attribute data.
The step that this knowledge relation line automatically generates farther includes:
One knowledge relation configuration sub-step, for generating the configuration of logic knowledge relation with knowledge relation form
File, and obtain knowledge point space coordinates；
One knowledge relation line generates sub-step, for according to shortest path principle, generates knowledge relation line
Shape data and attribute data.
The above-mentioned method generating Knowledge Map based on subject logic knowledge relation, it is characterised in that described
Knowledge point configuration sub-step farther includes:
Step S101, according to the chapters and sections graphic hotsopt chapters and sections spatial data of picture format；
Step S102, generates logic knowledge point configuration file with knowledge point form.
Configuration file is expressed in xml format, and content includes knowledge point coding, knowledge point title, knowledge point
Classification, education resource mark, by structurized data representation, it is simple to system reads data genaration knowledge point
And line.
The above-mentioned method generating Knowledge Map based on subject logic knowledge relation, it is characterised in that described
Knowledge point line generates in sub-step, calculates abstract knowledge point outsourcing figure according to chapters and sections shape, according to knowing
Know point from left to right, from top to bottom and the equidistant distribution rule in knowledge point at the same level, in conjunction with knowledge point quantity and layer
Secondary relation, uses geographic element space automatic imitation generation technique generate knowledge point line and record position, knowledge point
Put coordinate.
The above-mentioned method generating Knowledge Map based on subject logic knowledge relation, it is characterised in that described
Knowledge point spatial data generates in sub-step, according to the Coordinate generation knowledge point, locus, knowledge point calculated
Spatial data, by the knowledge point coding in configuration file, knowledge point title, knowledge point classification, education resource
Mark data are converted into the attribute data of knowledge point, and store with vector file format.
The above-mentioned method generating Knowledge Map based on subject logic knowledge relation, it is characterised in that described
Knowledge relation configuration sub-step farther includes:
Step S201, generates logic knowledge relation configuration file with knowledge relation form；
Configuration file is expressed in xml format, and content includes knowledge relation coding, knowledge relation title, knows
Know point set, education resource mark.Knowledge relation coding is encoded to prefix with initial knowledge point, knows with identical
The ordinal number knowing the knowledge relation appearance that point is starting point is suffix, separates with underscore and constitutes knowledge relation coding.
Knowledge point set comprise this knowledge relation the coding of all knowledge points of process, each coding is split with underscore.
By structurized data representation, it is simple to system reads data genaration knowledge relation line.
Step S202, according to the knowledge point set in knowledge relation configuration file, in conjunction with knowledge point spatial data,
Obtain knowledge point space coordinates；
Step S203, first knowledge point keeping knowledge relation is starting point, with shortest path for optimizing
Principle, the order that rearrangement knowledge point occurs in knowledge relation；
Step S204, according to the knowledge point of rearrangement, utilizes Bezier generating algorithm to generate knowledge
Relation line connects each knowledge point, according to the description content to knowledge relation comprised in knowledge relation configuration file,
Knowledge relation coding in configuration file, knowledge relation title, knowledge point set, education resource mark are converted
For the attribute data of knowledge relation, and with vector file format stored knowledge relation line data；
The above-mentioned method generating Knowledge Map based on subject logic knowledge relation, it is characterised in that one draws
Enter geographic information system technology (Geographic Information System, GIS) and improve subject knowledge ground
Figure drawing efficiency and map specialization are expressed.
Further, present invention also offers a kind of system realizing said method, it is characterised in that including:
One knowledge point and line automatically generate subsystem, for configuring literary composition according to chapters and sections spatial data and knowledge point
Part, generates knowledge point line and knowledge point spatial data；
One knowledge relation line automatically generates subsystem, for according to knowledge relation configuration file, in conjunction with knowledge point
Spatial data, utilizes Bezier generating algorithm to generate knowledge relation data；
One Knowledge Map visual subsystem, for according to the knowledge point generated and line, knowledge relation line
With chapters and sections spatial data, in conjunction with the specialized Map-making technology of GIS, Visualization Knowledge Map.
Said system, it is characterised in that described knowledge point and line automatically generate subsystem and farther include:
One chapters and sections shape space unit, for being converted to the chapters and sections figure of picture format with geographical space
The chapters and sections geometric space data of the vector form of coordinate；
One knowledge point dispensing unit, for generating the logic knowledge point configuration of XML format with knowledge point form
File；
One line signal generating unit, for calculating abstract knowledge point outsourcing figure according to chapters and sections shape, according to knowing
Know point from left to right, from top to bottom and the equidistant distribution rule in knowledge point at the same level, in conjunction with knowledge point quantity and layer
Secondary relation, uses geographic element space automatic imitation generation technique generate knowledge point line and record position, knowledge point
Put coordinate；
One knowledge point signal generating unit, for empty according to the Coordinate generation knowledge point, locus, knowledge point calculated
Between data, and with vector file format store.
Said system, it is characterised in that described knowledge relation line automatically generates subsystem and farther includes:
One knowledge relation dispensing unit, closes for generating the logic knowledge of XML format with knowledge relation form
It it is configuration file；
One knowledge point coordinate acquiring unit, for according to the knowledge point coding obtained in knowledge relation configuration file
From extracting data locus, knowledge point coordinate；
One knowledge point sequencing unit, for first knowledge point of knowledge relation as starting point, according to the shortest
Path optimization's principle, the order that rearrangement knowledge point occurs in knowledge relation；
One knowledge relation line signal generating unit, for the knowledge point according to rearrangement, utilizes Bezier
Generating algorithm generates knowledge relation line.
Said system, it is characterised in that described Knowledge Map visual subsystem farther includes:
One Map Expression unit, for logical to knowledge point and line, knowledge relation line and chapters and sections spatial data
Cross color, shape, symbol carry out drawing and express；
One map visualization unit, for expressing knowledge point and line, knowledge relation line and chapters and sections drawing
Result Overlapping display is a secondary complete Knowledge Map.
Compared with prior art, the Advantageous Effects of the present invention is:
(1) expressed by the spatial visualization of knowledge point and line and knowledge relation line so that knowledge point it
Between level and logical relation clearer, it is simple to the understanding to knowledge structure；
(2) utilize the Map Expression technology under GIS technology support, attractive in appearance representing can be become apparent from and know
Know point and the locus of knowledge relation, by spatial data structure, knowledge point and knowledge relation organized,
The more convenient user quick search to knowledge.
Accompanying drawing explanation
Fig. 1 is that a kind of of the present invention generates knowing of Knowledge Map method based on subject logic knowledge relation
Know point and line automatically generates embodiment flow chart；
Fig. 2 is that a kind of of the present invention generates knowing of Knowledge Map method based on subject logic knowledge relation
Know relation line and automatically generate embodiment flow chart；
Fig. 3 is a kind of knot generating Knowledge Map system based on subject logic knowledge relation of the present invention
Structure frame diagram；
Fig. 4 is a kind of reality generating Knowledge Map method based on subject logic knowledge relation of the present invention
Execute example flow chart.
Detailed description of the invention
The present invention is described in detail with embodiment below in conjunction with the accompanying drawings, to further appreciate that the mesh of the present invention
, scheme and effect.
A kind of based on subject logic knowledge relation generation Knowledge Map the method that the present invention provides includes
Knowledge point and line automatically generate and automatically generate two relatively independent processes with knowledge relation line.
Knowledge point and line automatically generate the basic thought of process: according to the chapters and sections graphic hotsopt of picture format
Chapters and sections spatial data；Logic knowledge point configuration file is generated with knowledge point form；According to Distribution of knowledge gists rule,
Geographic element space automatic imitation generation technique is used to generate knowledge point line；Empty according to the knowledge point calculated
Between Coordinate generation knowledge point, position spatial data.
Fig. 1 shows that the one of the present invention generates Knowledge Map method based on subject logic knowledge relation
Knowledge point and line automatically generate embodiment flow chart.With reference to Fig. 1, the present invention is a kind of based on subject logic
Knowledge relation generates in Knowledge Map method, and the process that knowledge point and line automatically generate farther includes
Following steps:
Step S101, according to the chapters and sections graphic hotsopt chapters and sections spatial data of picture format.
Chapters and sections shape directly limit the space layout form of knowledge point, is changed by the chapters and sections figure of picture format
For the spatial data of the vector format with geospatial coordinates system, close as knowledge point and line and knowledge
The basis that anchor line (string) generates.
Step S102, generates logic knowledge point configuration file with knowledge point form.
Configuration file is organized in xml format, utilizes label, attribute and three kinds of elements of value to knowledge point data
Expressing, content includes knowledge point coding, knowledge point title, knowledge point classification, education resource mark,
By structurized data representation, it is simple to system reads data genaration knowledge point and line.
Step S103, according to chapters and sections shape, according to Distribution of knowledge gists principle, uses geographic element space automatic
Simulation generation technique generates knowledge point line.
Knowledge point line automatically generates to be followed from left to right, from top to bottom and the equidistant distribution rule in knowledge point at the same level
Then, each knowledge point and subordinate's knowledge are distributed according to the quantity of knowledge point at the same level and the complexity of subordinate knowledge point
Area of space shared by Dian.Geographic element space automatic imitation generation technique is used to generate knowledge point line and remember
Record the space coordinates of each knowledge point.
Step S104, comprises knowing of attribute data according to locus, calculated knowledge point Coordinate generation
Know space of points data.
Fig. 2 shows that the one of the present invention generates Knowledge Map method based on subject logic knowledge relation
Knowledge relation line automatically generate embodiment flow chart.With reference to Fig. 2, present invention one is known based on subject logic
Knowledge relation generates in Knowledge Map method, and the process that knowledge relation line automatically generates farther includes following
Step:
Step 201, generates logic knowledge relation configuration file with knowledge relation form.
Configuration file is organized in xml format, utilizes label, attribute and three kinds of elements of value to knowledge relation number
According to expressing, content includes knowledge relation coding, knowledge relation title, knowledge point set, education resource mark
Know.Knowledge relation coding is encoded to prefix with initial knowledge point, and the knowledge with identical knowledge point as starting point is closed
The ordinal number that system occurs is suffix, separates with underscore and constitutes knowledge relation coding.Knowledge point set comprises this and knows
Knowledge relation the coding of all knowledge points of process, each coding is split with underscore.By structurized data
Express, it is simple to system reads data genaration knowledge relation line.
Step S202, according to the knowledge point set in knowledge relation configuration file, in conjunction with knowledge point spatial data,
Obtain knowledge point space coordinates；
Knowledge relation space coordinates through knowledge point be that knowledge relation line provides node, at knowledge relation
Knowledge point is concentrated, and storage has the coding through knowledge point, inquires about according to coding and know in the spatial data of knowledge point
Know the space coordinates of point.
Step S203, with shortest path as optimization principles, rearrangement knowledge point occurs in knowledge relation
Order；
The knowledge point constituting knowledge relation is tactic according to chapters and sections, when knowledge point is converted to spatial data
After, each knowledge point has fixing locus, in order to knowledge relation line is expressed more attractive in appearance, keeps
First knowledge point of knowledge relation is starting point, with shortest path as optimization principles, and knowledge point of resequencing
The order occurred in knowledge relation.
Step S204, knowledge relation line generates.
According to the knowledge point of rearrangement, utilize Bezier generating algorithm to generate knowledge relation line and connect each
Knowledge point, according to the description content to knowledge relation comprised in knowledge relation configuration file, by configuration file
In knowledge relation coding, knowledge relation title, knowledge point set, education resource mark be converted into knowledge relation
Attribute data, and with vector file format stored knowledge relation line data；
ArcGIS is utilized to realize generating the knowledge point of Knowledge Map method based on subject logic knowledge relation
And line automatically generates and automatically generates with knowledge relation line, and by result with the exhibition of the formal intuition of map image
Show to user.
With reference to Fig. 3, it is shown that the one of the present invention generates Knowledge Map based on subject logic knowledge relation
The structural framing figure of system, it is automatic that system is divided into knowledge point and line to automatically generate subsystem, knowledge relation line
Generate subsystem and map visualization subsystem.
Knowledge point and line automatically generate subsystem 301 and include: chapters and sections shape space unit 3011, know
Know some dispensing unit 3012, line signal generating unit 3013 and knowledge point signal generating unit 3014.
Chapters and sections shape space unit 3011 is by the chapters and sections figure geographic registration of picture format, data binaryzation
The rear chapters and sections geometry utilizing space automatic scanning technology to be converted to the vector form with geospatial coordinates
Spatial data.Chapters and sections shape space unit 3011 is present in knowledge point and line automatically generates subsystem,
Chapters and sections shape space result is automatically generated subsystem by knowledge relation line simultaneously and shares.
Knowledge point dispensing unit 3012 generates the logic knowledge point configuration literary composition of XML format with knowledge point form
Part, structured organization knowledge point data, it is simple to system program digital independent and analysis.
Line signal generating unit 3013 calculates abstract knowledge point outsourcing figure according to chapters and sections shape, according to knowledge
Point from left to right, from top to bottom and the equidistant distribution rule in knowledge point at the same level, in conjunction with knowledge point quantity and level
Relation, uses geographic element space automatic imitation generation technique generate knowledge point line and record position, knowledge point
Coordinate, its premise is chapters and sections shape space data and knowledge point configuration file has generated.
Knowledge point signal generating unit 3014 is according to the space, Coordinate generation knowledge point, locus, knowledge point calculated
Data, and store with vector file format.
Knowledge relation line automatically generates subsystem 302 and includes: knowledge relation dispensing unit 3021, knowledge point
Coordinate acquiring unit 3022, knowledge point sequencing unit 3023 and knowledge relation line signal generating unit 3024.
Knowledge relation dispensing unit 3021 generates the logic knowledge relation of XML format with knowledge relation form
Configuration file, content includes knowledge relation coding, knowledge relation title, knowledge point set, education resource mark.
Knowledge relation coding is encoded to prefix with initial knowledge point, and the knowledge relation with identical knowledge point as starting point goes out
Existing ordinal number is suffix, separates with underscore and constitutes knowledge relation coding.Knowledge point set comprises this knowledge and closes
System the coding of all knowledge points of process, each coding is split with underscore.
Knowledge point coordinate acquiring unit 3022 is according to the knowledge point set in knowledge relation configuration file, and acquisition is known
The knowledge point coding of knowledge relation storage, empty from the knowledge point that knowledge point signal generating unit 3014 generates according to coding
Between data are inquired about the space coordinates of knowledge point.
Knowledge point sequencing unit 3023 is expressed more attractive in appearance for knowledge relation line, keeps the of knowledge relation
One knowledge point is starting point, and with shortest path as optimization principles, rearrangement knowledge point is in knowledge relation
The order occurred；
Knowledge relation line signal generating unit 3024, according to the knowledge point of rearrangement, utilizes Bezier raw
Become algorithm generate knowledge relation line connect each knowledge point, according to knowledge relation configuration file comprises to knowledge
The description content of relation, by the knowledge relation coding in configuration file, knowledge relation title, knowledge point set,
Education resource mark is converted into the attribute data of knowledge relation, and with vector file format stored knowledge relation line
Data.
Map visualization subsystem 303 includes that unit 3031 and map visualization unit 3032 are expressed in drawing.
Drawing is expressed unit 3031 and is passed through knowledge point and line, knowledge relation line and chapters and sections spatial data
Color, shape, symbol carry out drawing expresses, so that knowledge point and line, knowledge relation line and chapters and sections number
According to more attractive in appearance, coincidently graph expression specification.
Knot is expressed in knowledge point and line, knowledge relation line and chapters and sections drawing by map visualization unit 3032
Really Overlapping display is a secondary complete Knowledge Map, map can be zoomed in and out by map tool,
Roaming, and can show according to the change control figure layer of scale.
Fig. 4 shows that the one of the present invention generates Knowledge Map method based on subject logic knowledge relation
Embodiment flow chart.With reference to Fig. 4, the present invention is a kind of generates subject knowledge based on subject logic knowledge relation
Ground drawing method further includes steps of
Step 401, chapters and sections shape space.
By the chapters and sections figure geographic registration of picture format, after data binaryzation, utilize space automatic scanning technology
Be converted to the chapters and sections geometric space data of the vector form with geospatial coordinates.
Step S402, knowledge point and line automatically generate.
Generate logic knowledge point configuration file according to knowledge point form, then count according to chapters and sections shape, knowledge
Amount and hierarchical relationship generate knowledge point line and record knowledge point position coordinates, finally according to knowledge point space bit
Put Coordinate generation knowledge point spatial data and attribute data.
Step S403, knowledge relation line automatically generates.
Generate logic knowledge relation configuration file according to knowledge relation form, keep first of knowledge relation to know
Knowing point is starting point, and with shortest path as optimization principles, rearrangement knowledge point occurs in knowledge relation
Sequentially, Bezier generating algorithm is utilized to generate knowledge relation line.
Step S404, Knowledge Map visualizes
Knowledge point and line, knowledge relation line and chapters and sections spatial data are entered by color, shape, symbol
Row drawing is expressed, and by knowledge point and line, knowledge relation line and chapters and sections drawing expression of results Overlapping display
It is a secondary complete Knowledge Map, map can be zoomed in and out by map tool, roam, and energy
Change according to scale controls figure layer and shows.
Although the present invention is disclosed above with preferred embodiment, so it is not limited to the present invention, is not carrying on the back
In the case of present invention spirit and essence thereof, those of ordinary skill in the art are when making according to the present invention
Various corresponding changes and deformation, but these change accordingly and deformation all should belong to the right appended by the present invention
The protection domain required.
Claims (6)
1. the method generating Knowledge Map based on subject logic knowledge relation, including knowledge point and
Step that line automatically generates and the step that knowledge relation line automatically generates, it is characterised in that
The step that this knowledge point and line automatically generate farther includes:
One knowledge point configuration sub-step, for the chapters and sections graphic hotsopt chapters and sections space number according to picture format
According to and generate logic knowledge point configuration file according to knowledge point form；
One knowledge point line generates sub-step, for closing according to chapters and sections shape, knowledge point quantity and level
System generates knowledge point line and records knowledge point position coordinates；
One knowledge point spatial data generates sub-step, for knowing according to locus, knowledge point Coordinate generation
Know space of points data and attribute data.
The step that this knowledge relation line automatically generates farther includes:
One knowledge relation configuration sub-step, for generating the configuration of logic knowledge relation with knowledge relation form
File, and obtain knowledge point space coordinates；
One knowledge relation line generates sub-step, for according to shortest path principle, generates knowledge relation line
Shape data and attribute data.
The side generating Knowledge Map based on subject logic knowledge relation the most according to claim 1
Method, it is characterised in that described knowledge point configuration sub-step farther includes:
Step S101, according to the chapters and sections graphic hotsopt chapters and sections spatial data of picture format；
Step S102, generates logic knowledge point configuration file with knowledge point form.
The side generating Knowledge Map based on subject logic knowledge relation the most according to claim 1
Method, it is characterised in that described knowledge point line generates in sub-step, calculates abstract knowing according to chapters and sections shape
Know a some outsourcing figure, according to knowledge point from left to right, from top to bottom and the equidistant distribution rule in knowledge point at the same level,
In conjunction with knowledge point quantity and hierarchical relationship, geographic element space automatic imitation generation technique is used to generate knowledge point
Line also records knowledge point position coordinates.
The side generating Knowledge Map based on subject logic knowledge relation the most according to claim 1
Method, it is characterised in that described knowledge point spatial data generates in sub-step, empty according to the knowledge point calculated
Between Coordinate generation knowledge point, position spatial data, by the knowledge point coding in configuration file, knowledge point title,
Knowledge point classification, education resource mark data are converted into the attribute data of knowledge point, and with vector file format
Storage.
The side generating Knowledge Map based on subject logic knowledge relation the most according to claim 1
Method, it is characterised in that described knowledge relation configuration sub-step farther includes:
Step S201, generates logic knowledge relation configuration file with knowledge relation form；
Configuration file is expressed in xml format, and content includes knowledge relation coding, knowledge relation title, knows
Know point set, education resource mark.Knowledge relation coding is encoded to prefix with initial knowledge point, knows with identical
The ordinal number knowing the knowledge relation appearance that point is starting point is suffix, separates with underscore and constitutes knowledge relation coding.
Knowledge point set comprise this knowledge relation the coding of all knowledge points of process, each coding is split with underscore.
By structurized data representation, it is simple to system reads data genaration knowledge relation line.
The side generating Knowledge Map based on subject logic knowledge relation the most according to claim 1
Method, it is characterised in that described knowledge relation line generates sub-step and farther includes:
Step S202, according to the knowledge point set in knowledge relation configuration file, in conjunction with knowledge point spatial data,
Obtain knowledge point space coordinates；
Step S203, first knowledge point keeping knowledge relation is starting point, with shortest path for optimizing
Principle, the order that rearrangement knowledge point occurs in knowledge relation；
Step S204, according to the knowledge point of rearrangement, utilizes Bezier generating algorithm to generate knowledge
Relation line connects each knowledge point, according to the description content to knowledge relation comprised in knowledge relation configuration file,
Knowledge relation coding in configuration file, knowledge relation title, knowledge point set, education resource mark are converted
For the attribute data of knowledge relation, and with vector file format stored knowledge relation line data.
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