CN110119812A - A kind of knowledge base and its methods of exhibiting, querying method - Google Patents
A kind of knowledge base and its methods of exhibiting, querying method Download PDFInfo
- Publication number
- CN110119812A CN110119812A CN201810123453.1A CN201810123453A CN110119812A CN 110119812 A CN110119812 A CN 110119812A CN 201810123453 A CN201810123453 A CN 201810123453A CN 110119812 A CN110119812 A CN 110119812A
- Authority
- CN
- China
- Prior art keywords
- knowledge
- blocks
- level
- relationship
- coordinate
- 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.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computing arrangements using knowledge-based models
- G06N5/02—Knowledge representation; Symbolic representation
- G06N5/022—Knowledge engineering; Knowledge acquisition
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computing arrangements using knowledge-based models
- G06N5/02—Knowledge representation; Symbolic representation
- G06N5/027—Frames
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- General Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Data Mining & Analysis (AREA)
- Evolutionary Computation (AREA)
- Computational Linguistics (AREA)
- Computing Systems (AREA)
- General Physics & Mathematics (AREA)
- Mathematical Physics (AREA)
- Software Systems (AREA)
- Artificial Intelligence (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The invention discloses a kind of knowledge base and its methods of exhibiting, querying method.The method include the steps that 1) create simultaneously stored knowledge unit；Information unit is created, information unit and its incidence relation with blocks of knowledge are stored；2) the submission record that storage is selected and inputted between relationship blocks of knowledge；3) it is recorded according to the submission of step 2), relationship between calculation knowledge unit；4) according to specified blocks of knowledge set, using in step 3) the relationship for obtaining these blocks of knowledge and specified knowledge relation, the gridding coordinate of blocks of knowledge in set of computations；5) according to requirement is shown, the blocks of knowledge for needing to show is extracted, constitutes spacial flex；Wherein, the blocks of knowledge coordinate of spacial flex is generated using the linear transformation of gridding coordinate.The present invention can prompt blocks of knowledge necessary to the preposition study of learner, help learner to carry out the optimization of learning sequence, improve learning efficiency.
Description
Technical field
The present invention relates to a kind of knowledge base and its methods of exhibiting, querying method, belong to network technique field, more particularly to mutually
Networking field of Educational Technology.
Technical background
Traditional knowledge base is existed in the form of books.Then, the encyclopedia of disk distribution has been occurred.With
The appearance of internet, knowledge base are mainly the form of wiki.With traditional encyclopedia, professional dictionary is similar, it is with entry
Core provides the explanation information to the entry.
Existing knowledge base is not study optimization, does not solve the problems, such as the maximum that learner encounters:
Which (preposition) knowledge 1. learning this knowledge needs first to grasp?
2. if user does not understand the article reading of current knowledge, it should how to obtain other about current knowledge point
Article?
In the design in existing knowledge library, the data structure for the relationship that is ignorant can not set knowledge relation, also just can not be straight
It connects and solves preposition knowledge.For Second Problem, in existing knowledge library, link and the current knowledge of bibliography form are provided
The correlation degree of point is not very accurate.In the design in existing knowledge library, an entry can only have an article, cause not adapt to
The learner that a variety of study need.
Search engine is also the main means of the knowledge of people's search, and the skill and result searched for are selected, and are
The another difficulty that learner encounters.
Summary of the invention
For the technical problems in the prior art, the purpose of the present invention is to provide a kind of knowledge base and its displaying sides
Method, querying method.The application is to establish blocks of knowledge for core, and knowledge relation is connection, the multimedias letter of a variety of expression styles
The knowledge base of breath.Knowledge base is by input processing module, memory module, automatically process module, output processing module, human-computer interaction mould
Block composition.
This application involves content include:
The essential information of blocks of knowledge is set；Essential information includes title, description, affiliated ken；
The submission record of relationship between acquisition blocks of knowledge；
Blocks of knowledge relationship is generated based on submitting to record；
The three-dimensional coordinate that each blocks of knowledge is generated according to blocks of knowledge relationship, is visualized；
Information unit essential information；Title, abstract, author, medium type express style, and corresponding blocks of knowledge is fitted
With readers' range etc. and media information.
Author (informant) information；
The corresponding relationship of information unit and blocks of knowledge.
The technical solution of the present invention is as follows:
A kind of knowledge base methods of exhibiting, step include:
1) creation and stored knowledge unit；Information unit is created, information unit is stored and its is associated with blocks of knowledge
System；
2) the submission record that storage is selected and inputted between relationship blocks of knowledge；
3) it is recorded according to the submission of step 2), relationship between calculation knowledge unit；
4) relationship of these blocks of knowledge, the gridding coordinate of calculation knowledge unit are obtained using in step 3)；
5) according to requirement is shown, the blocks of knowledge for needing to show is extracted, constitutes spacial flex；Wherein, spacial flex is known
Know unit coordinate to generate using the linear transformation of gridding coordinate.
Further, use and for 1 same knowledge of the coefficient of efficiency array to same user to same a pair of of blocks of knowledge
Multiple submissions record of relationship carries out validity weighted calculation.
Further, it calculates the gridding and sits calibration method are as follows:
31) blocks of knowledge is chosen from blocks of knowledge set as original point, and provides initial coordinate values；Wherein,
The directive knowledge relation of a specified tool, as specified knowledge relation；Specified knowledge relation is neutralized to blocks of knowledge set
Recessive knowledge relation of equal value is replaced using specified knowledge relation；
If 32) blocks of knowledge in the blocks of knowledge set and the original point are relationship active direction, the knowledge
Unit is known as level-one blocks of knowledge, level coordinate value=original point+1 unit constant of level coordinate of level-one blocks of knowledge；
Then the blocks of knowledge in the blocks of knowledge set with level-one blocks of knowledge with relationship active direction, referred to as second level are successively searched
Blocks of knowledge calculates level coordinate value=level-one blocks of knowledge+1 unit constant of level coordinate of second level blocks of knowledge；According to
It is secondary to analogize, obtain with upper level blocks of knowledge there is the level of the blocks of knowledge at different levels of active direction to sit in the blocks of knowledge set
Scale value；
If 33) the blocks of knowledge a in the blocks of knowledge set is with several blocks of knowledge in the blocks of knowledge set
The passive direction of relationship, and these blocks of knowledge have corresponding level coordinate value in step 32), then choose level coordinate value most
Level coordinate value=blocks of knowledge b -1 unit constant of level coordinate of low blocks of knowledge b, blocks of knowledge a.
Further, for one or more blocks of knowledge with the not related path of the original point, then distinguish for it
One random level coordinate is set；It is closed if any the blocks of knowledge d in a blocks of knowledge c and the blocks of knowledge set with knowledge
System, then set the level coordinate of blocks of knowledge c to the level coordinate of blocks of knowledge d.
Further, it calculates in the gridding coordinate process, to two blocks of knowledge, if there is by other knowledge
The relationship for being directly connected to two blocks of knowledge is then deleted in unit, the identical knowledge relation path in relationship direction；If there is composition
The knowledge relation path of loop, then be marked as mistake.
Further, coordinate of the blocks of knowledge in level, method are determined are as follows: and have confirmed that the knowledge list of coordinate position
First A has knowledge relation and multiple blocks of knowledge in adjacent layer, sorts by the coefficient of relationship of itself and blocks of knowledge A, sequentially put to
To on by the optional position point of distance-taxis.
A kind of knowledge base, which is characterized in that including blocks of knowledge generation module, human-computer interaction module, input module, storage
Relationship computing module between module and blocks of knowledge；Wherein,
The blocks of knowledge generation module, for creating simultaneously stored knowledge unit；Information unit is created, information unit is stored
And its incidence relation with blocks of knowledge；
The human-computer interaction module, the submission for receiving user, which records, please send it to input module；Wherein, described
Submitting record includes the blocks of knowledge relation name of user information, two blocks of knowledge chosen；
The input module, the knowledge relation that the submission record for that will receive is saved in memory module are submitted in record；
Relationship computing module between the blocks of knowledge, for being calculated between each blocks of knowledge according to each submission record
Blocks of knowledge relationship is simultaneously saved in the memory module；And according to specified blocks of knowledge set, extract first complete in set
Then the knowledge relation of portion's blocks of knowledge is calculated according to the blocks of knowledge relationship between specified knowledge relation and each blocks of knowledge
The level coordinate of each blocks of knowledge and the memory module is saved in the blocks of knowledge set；Then according to each blocks of knowledge
Between blocks of knowledge relationship calculate the level coordinate of each blocks of knowledge in the blocks of knowledge set and be saved in the storage
Module；Wherein, the blocks of knowledge relationship has directionality, including relationship active direction and the passive direction of relationship.
It further, further include that a three dimensional network is formatted coordinate calculation module；The three-dimensional coordinate computing module is from knowledge list
A blocks of knowledge is chosen in member set as original point, and provides initial coordinate values；If one in the blocks of knowledge set
Blocks of knowledge and the original point are relationship active direction, then the blocks of knowledge is known as level-one blocks of knowledge, level-one blocks of knowledge
Level coordinate value=original point+1 unit constant of level coordinate；Then it successively searches and knows in the blocks of knowledge set with level-one
Know the blocks of knowledge that unit has relationship active direction, referred to as second level blocks of knowledge, calculates the level coordinate of second level blocks of knowledge
Value=level-one blocks of knowledge+1 unit constant of level coordinate；And so on, obtain in the blocks of knowledge set with upper level
Blocks of knowledge has the level coordinate value of the blocks of knowledge at different levels of active direction；If the knowledge list in the blocks of knowledge set
First a is the passive direction of relationship with several blocks of knowledge in the blocks of knowledge set, and these blocks of knowledge have corresponding level
Coordinate value then chooses the highest blocks of knowledge b of level coordinate value, level coordinate value=blocks of knowledge b layer of blocks of knowledge a
Grade -1 unit constant of coordinate.
It further, further include a display module, the display module extracts the knowledge for needing to show according to requirement is shown
Unit calls the three dimensional network to format coordinate calculation module, and computational gridding coordinate constitutes spacial flex；Wherein, spacial flex
Blocks of knowledge coordinate use the linear transformation of gridding coordinate generate.
A kind of querying method of knowledge base, step includes: the blocks of knowledge information inputted according to user, from the knowledge
All blocks of knowledge associated with it are searched in library；For each blocks of knowledge in query result, inquire the blocks of knowledge according to
Bad blocks of knowledge.
Advantages of the present invention is as follows:
This method can establish the knowledge index based on a blocks of knowledge；Multiple multimedias for explaining knowledge are believed
Breath, it is corresponding with blocks of knowledge, so that learner is carried out the fast search of information with blocks of knowledge；The relationship of blocks of knowledge, it is special
It is not dependence, system is allowed to prompt blocks of knowledge necessary to the preposition study of learner, learner is helped to learn
The optimization of sequence.
Detailed description of the invention
Fig. 1 is flow chart of the method for the present invention.
Specific embodiment
Method of the invention is described in further detail below with reference to specific example.
Method flow of the invention is as shown in Figure 1, its step includes:
One, relevant knowledge methods of exhibiting when learner learns
When user opens an information unit progress reading learning by human-computer interaction module selection, human-computer interaction module
It is completed with output module:
1.1 rely on knowledge prompt step:
Human-computer interaction module and output module provide " relying on blocks of knowledge prompt " for learner, are realized by following steps:
1. output module searches associated all blocks of knowledge according to actual information unit；2. inquiring these knowledge lists
The blocks of knowledge that member relies on (dependence is one of blocks of knowledge relationship)；3. passing to human-computer interaction module；4. man-machine
The information for relying on blocks of knowledge is shown to user by interactive module.Optimum treatment mode is opened up before user opens information unit
Show.
1.2 reference query steps:
Human-computer interaction module provides " checking reference " function button or other input modes for user, can be user
After input request:
1. human-computer interaction module sends the requests to output module, 2. output modules are deposited according to actual information unit, inquiry
Module is stored up, the associated all blocks of knowledge of actual information unit is searched: inquiring the associated all information units of these blocks of knowledge,
The relevant all information unit lists of actual information unit are generated, human-computer interaction module is passed to.If including multiple knowledge lists
Member then presses blocks of knowledge accumulated information unit.Information unit information includes title, author, medium type, style characteristic, adaptation
Readers' range/study requirement etc.；3. human-computer interaction module shows information unit information list.
1.3 association knowledges show step:
Association knowledge unit is shown: (the relevant knowledge unit list for generating actual information unit), human-computer interaction module mentions
Input item is inquired for relevant knowledge, after user's input:
1. user's request is transferred to output module by human-computer interaction module.
2. output module, which inquires memory module, inquires memory module according to the associated blocks of knowledge of actual information unit
Blocks of knowledge relationship obtains blocks of knowledge and relation information.By blocks of knowledge, with current knowledge unit relation name, relationship system
Number passes to human-computer interaction module.
3. human-computer interaction module shows association knowledge information, user can continue through the multistage pass of interface input selection
(level-one for being known as it with the blocks of knowledge A blocks of knowledge being directly linked is associated with connection parameter, and the level-one of blocks of knowledge A is associated
The direct correlation blocks of knowledge of blocks of knowledge, the second level association of referred to as blocks of knowledge A, and so on), it is passed by human-computer interaction module
Pass output module.
4. output module inquires memory module, multi-level knowledge units information and relationship are obtained, obtains blocks of knowledge and relationship
Information, by blocks of knowledge, with current knowledge unit relation name, coefficient of relationship passes to human-computer interaction module.
5. human-computer interaction module is by information and display control program.
6. the filter condition that human-computer interaction module can be selected according to user from interface will partially be unsatisfactory for the knowledge of condition
Unit information is hidden.
7. human-computer interaction module can close blocks of knowledge and knowledge according to blocks of knowledge in the three-dimensional coordinate of spacial flex
Three-dimensional space is tied up to show, blocks of knowledge is shown using basic model (such as cube or ball-type), and knowledge relation is indicated using line,
Different knowledge relations uses different colors.
Two, blocks of knowledge Automated generalization method
The relationship of 2.1 blocks of knowledge inputs
After blocks of knowledge relationship is submitted by user, system generates blocks of knowledge relationship as follows:
1. the coefficient of relationship of two blocks of knowledge that human-computer interaction module selects user, knowledge relation and input is transferred to
Input module；Relationship between blocks of knowledge: the relationship between them can be manually arranged in two blocks of knowledge A, B, if A is to B
Dependence.There are many relationships for blocks of knowledge, such as the relationship of logical categories :-special, be abstracted-specific, it is main-secondary, it is existing
As-essence, the relationship of object-oriented analysis: reason-is inherited, is realized, relying on, association, polymerization, combination as a result, concept-application
Relationship.The present invention especially increases the relationship towards study, and study relies on and learning sequence relationship.
Present invention employs two-stage knowledge relation, the first order is classification method (relationships of such as logical categories), and the second level is
Physical relationship (as-special).
2. input module believes user information, two blocks of knowledge, the two-stage relation name or ID of selection, coefficient of relationship etc.
Breath, the knowledge relation for being saved in memory module are submitted in record.
3. relationship computing module finds out all records in submitting record between blocks of knowledge, by two blocks of knowledge, knowledge
Relationship type polymerization, i.e. two blocks of knowledge ID, the identical record of knowledge relation ID.For one group of (two blocks of knowledge, knowledge
Relationship type is identical) record be weighted processing calculation knowledge unit between relationship:
1) for the single-relation of two blocks of knowledge, the user all submitted after duplicate removal, system root threshold process: are extracted
According to user gradation, user's concern value of this relationship, user's concern value=∑ (equivalent coefficient × these level number of users) are calculated；If
User's concern value of the relationship is more than the threshold value of setting, can just create relationship between the blocks of knowledge that system uses.
2) coefficient weighting is handled:
For the single-relation of two blocks of knowledge, when user has repeatedly submission, temporally by the submission record of user
Bit-reversed.Quantity coefficient of efficiency array identical with number is submitted is constructed, and is 1.In general, user's is more
Secondary submission, can only once effectively, then coefficient of efficiency array is (1,0 ... ...), and the coefficient of efficiency of last time is 1.
System gives grade weight coefficient according to user characteristics, such as user class, is weighted to the coefficient in relationship flat
?.Calculation method are as follows:
The mean coefficient of whole users under grade: ∑ (coefficient of efficiency × submission coefficient)/number of users；
∑ (grade mean coefficient X grade weight coefficient)/total number of grades.
3) by treated, blocks of knowledge relationship is saved in memory module.
2.2 information units are associated with blocks of knowledge
Information unit is generally all associated with a blocks of knowledge, can be by associated knowledge in input and preservation
Unit is stored in the storage of information unit.Information unit and with blocks of knowledge relationship pass through human-computer interaction module or front end system
The incidence relation of information unit and blocks of knowledge is stored in memory module by input, input module.Information unit includes author's letter
Breath, information unit feature (the adaptation reader of writer mark, writing style/feature etc.), corresponding blocks of knowledge is stored in storage
Module.
The calculation method of blocks of knowledge coordinate in 4 three-dimensional visualization spaces
In order to show blocks of knowledge and its between relationship, can be used three-dimensional space displaying.It is calculated to simplify, it can be with
Using selecting partial knowledge unit, based on a kind of Key Relationships (especially dependence), blocks of knowledge is organized, it can be with
Construct knowledge three-dimensional display space under this relationship.Spacial flex is firstly the need of calculation knowledge unit three-dimensional coordinate, for convenience
Gridding methods building can be used in processing, handles rule agreement are as follows:
1) relationship direction.Blocks of knowledge relationship is directional (if the blocks of knowledge of blocks of knowledge A and blocks of knowledge B closes
System is dependence, and dependence is that blocks of knowledge A relies on blocks of knowledge B, then blocks of knowledge A is active, blocks of knowledge B is
Passively.Conversely, then blocks of knowledge B is active, blocks of knowledge A is passive), the blocks of knowledge of the active direction of relationship can be arranged
In high-level, level direction is using any one in XYZ coordinate axis.Select a reference axis as level coordinate；2)
Only one blocks of knowledge in one three-dimensional grid；3) D coordinates value of blocks of knowledge is all integer.Unit constant, knowledge list
The minimum value of first distance, non-zero integer, is traditionally arranged to be 1.
It is hereinafter empty using the Knowledge Show of particular kind of relationship 1 to establish a specified blocks of knowledge relationship (such as dependence)
Between, processing step are as follows:
1. first by displaying requirement or range searching blocks of knowledge, and search result concentrates the knowledge between all blocks of knowledge to close
System.
2. in the blocks of knowledge relationship of result set in the previous step, particular kind of relationship 1 and all particular kind of relationship 1 are searched for
Recessive relationship, (the application relationship of such as two blocks of knowledge is recessive dependence), is uniformly replaced by particular kind of relationship 1.
3. recessive relationship will lead to the relationships of two blocks of knowledge there are multiple, remove in result set simple repeats passes
System.
4. the direct relation that removal has other relation paths.If A relies on B, B relies on C, and A relies on C.Between A and C, there are A-
Two paths B-C and A-C, then remove A-C relationship.
5. searching wrong knowledge relation path.Most probable can export carry out artificial treatment problem appear to is that circulating path,
Or it is automatically deleted the relationship for causing mistake.
6. pair blocks of knowledge sorts by relationship, the level coordinate of blocks of knowledge is established.
61) it initializes: specifying a blocks of knowledge as original point, and provide initial coordinate values.Most base can generally be selected
The blocks of knowledge of plinth selects " natural number " as original point as original point, in full association.
62) relationship active direction is handled: and original point has blocks of knowledge (the referred to as level-one knowledge list of direct active relationship
Member) level coordinate value=original point+1 unit constant of level coordinate.There is direct active relationship knowledge with level-one blocks of knowledge
Unit is second level blocks of knowledge, level coordinate=level-one blocks of knowledge level+1 unit constant of coordinate.Other blocks of knowledge
Successively handle.
63) relationship passive direction processing: some blocks of knowledge without and other blocks of knowledge have an active relationship, but and its
There is the blocks of knowledge of passive relationship to have level coordinate in above-mentioned calculating.Then from the top knowledge list in back result
Member searches the blocks of knowledge being directly linked by the passive direction of relationship, and the level coordinate of the blocks of knowledge in passive relationship direction is than its pass
The low unit constant of the blocks of knowledge of connection, other each levels are successively handled；
64) independent knowledge unit: and one of the not related path of original point and multiple blocks of knowledge are independent knowledge list
Member.Individually random level coordinate can be set for it；One group of knowledge list for having specified knowledge relation (containing a recessive relationship)
Member is randomly provided level coordinate value first for one of blocks of knowledge, and then this group of blocks of knowledge presses relationship active/passive side
To processing rule, its level coordinate is set.
65) other knowledge relations are handled: other blocks of knowledge relationships, i.e., non-designated relationship and recessive relationship.Simply, may be used
To set same level coordinate for other two blocks of knowledge with knowledge relation.
66) the level adjustment of independent knowledge unit.Independent knowledge unit passes through other knowledge relations.
7. same layer blocks of knowledge position is handled:
71) treatment principle, which is different blocks of knowledge, cannot occupy same position, and same layer processing is processing blocks of knowledge
X, y-coordinate, the coordinate for finally obtaining each blocks of knowledge is (x, y, level coordinate).
72) optimized treatment method: adjacent layer is used, the blocks of knowledge of fixed coordinates, as a reference point；And reference point
Relevant knowledge unit sorts by the coefficient of relationship of they and reference point；Position will can be distributed by the distance-taxis with reference point；It will
Coordinate to be allocated after sequence, which is arranged by blocks of knowledge sequence to ordering, distributes position.Such as: reference point blocks of knowledge
Coordinate is (0,0,10), and alternative position of distance reference point is in order are as follows: nearest vertical line tie point (0,0,11), it is secondary
(1,0,11), (0,1,11), (- 1,0,11), (0, -1,11), original point blocks of knowledge has 5 active relationship direction knowledge
Unit, these blocks of knowledge sort by coefficient of relationship, set gradually position coordinates.
8. storing the result into the blocks of knowledge three-dimensional coordinate of the spacial flex of memory module.
9. the three-dimensional coordinate actually shown generates displaing coordinate after doing linear transformation according to the above results.
There are many definition, the present invention to be defined using generalized knowledge unit for blocks of knowledge, i.e. the intension of concept is to refer to knowledge
The relatively independent location contents of any one.
Information unit is the form for carrying knowledge, can be independent text, picture, video etc. is also possible to mixed composition
Multimedia article.
It is above to implement to be merely illustrative of the technical solution of the present invention rather than be limited, the ordinary skill people of this field
Member can be with modification or equivalent replacement of the technical solution of the present invention are made, without departing from the spirit and scope of the present invention, this hair
Bright protection scope should be subject to described in claims.
Claims (10)
1. a kind of knowledge base methods of exhibiting, step include:
1) creation and stored knowledge unit；Information unit is created, information unit and its incidence relation with blocks of knowledge are stored；
2) the submission record that storage is selected and inputted between relationship blocks of knowledge；
3) it is recorded according to the submission of step 2), relationship between calculation knowledge unit；
4) relationship of these blocks of knowledge, the gridding coordinate of calculation knowledge unit are obtained using in step 3)；
5) according to requirement is shown, the blocks of knowledge for needing to show is extracted, constitutes spacial flex；Wherein, the knowledge list of spacial flex
First coordinate is generated using the linear transformation of gridding coordinate.
2. the method as described in claim 1, which is characterized in that use and for 1 coefficient of efficiency array to same user to same
The carry out validity weighted calculation of multiple submissions record of the same knowledge relation of a pair of of blocks of knowledge.
3. the method as described in claim 1, which is characterized in that calculate the gridding and sit calibration method are as follows:
31) blocks of knowledge is chosen from blocks of knowledge set as original point, and provides initial coordinate values；Wherein, it specifies
One directive knowledge relation of tool, as specified knowledge relation；It is recessive that specified knowledge relation is neutralized to blocks of knowledge set
Knowledge relation of equal value is replaced using specified knowledge relation；
If 32) blocks of knowledge in the blocks of knowledge set and the original point are relationship active direction, the blocks of knowledge
Referred to as level-one blocks of knowledge, level coordinate value=original point+1 unit constant of level coordinate of level-one blocks of knowledge；Then
Successively search the blocks of knowledge in the blocks of knowledge set with level-one blocks of knowledge with relationship active direction, referred to as second level knowledge
Unit calculates level coordinate value=level-one blocks of knowledge+1 unit constant of level coordinate of second level blocks of knowledge；Successively class
It pushes away, obtains the level coordinate in the blocks of knowledge set with upper level blocks of knowledge with the blocks of knowledge at different levels of active direction
Value；
If 33) the blocks of knowledge a in the blocks of knowledge set and several blocks of knowledge in the blocks of knowledge set are relationship
Passive direction, and these blocks of knowledge have corresponding level coordinate value in step 32), then it is minimum to choose level coordinate value
Level coordinate value=blocks of knowledge b -1 unit constant of level coordinate of blocks of knowledge b, blocks of knowledge a.
4. method as claimed in claim 3, which is characterized in that for one or more with the not related path of the original point
Then a random level coordinate is respectively set for it in a blocks of knowledge；If any in a blocks of knowledge c and the blocks of knowledge set
Blocks of knowledge d has knowledge relation, then sets the level coordinate of blocks of knowledge c to the level coordinate of blocks of knowledge d.
5. method as claimed in claim 3, which is characterized in that calculate in the gridding coordinate process, to two knowledge lists
Member, if there is other blocks of knowledge are passed through, the identical knowledge relation path in relationship direction then deletes and is directly connected to two knowledge
The relationship of unit；If there is the knowledge relation path for constituting loop, then mistake is marked as.
6. method as claimed in claim 3, which is characterized in that determine coordinate of the blocks of knowledge in level, method are as follows: and
Have confirmed that the blocks of knowledge A of coordinate position has knowledge relation and multiple blocks of knowledge in adjacent layer, by it with blocks of knowledge A's
Coefficient of relationship sequence is sequentially put to on the optional position point by distance-taxis.
7. a kind of knowledge base, which is characterized in that including blocks of knowledge generation module, human-computer interaction module, input module, storage mould
Relationship computing module between block and blocks of knowledge；Wherein,
The blocks of knowledge generation module, for creating simultaneously stored knowledge unit；Create information unit, store information unit and its
With the incidence relation of blocks of knowledge；
The human-computer interaction module, the submission for receiving user, which records, please send it to input module；Wherein, the submission
Record includes the blocks of knowledge relation name of user information, two blocks of knowledge chosen；
The input module, the knowledge relation that the submission record for that will receive is saved in memory module are submitted in record；
Relationship computing module between the blocks of knowledge, for according to each knowledge submitted between each blocks of knowledge of record calculating
Unit relationship is simultaneously saved in the memory module；And according to specified blocks of knowledge set, extracts in set all know first
Know the knowledge relation of unit, this is then calculated according to the blocks of knowledge relationship between specified knowledge relation and each blocks of knowledge and is known
Know the level coordinate of each blocks of knowledge in unit set and is saved in the memory module；Then according between each blocks of knowledge
Blocks of knowledge relationship calculate the level coordinate of each blocks of knowledge in the blocks of knowledge set and be saved in the memory module；
Wherein, the blocks of knowledge relationship has directionality, including relationship active direction and the passive direction of relationship.
8. knowledge base as claimed in claim 7, which is characterized in that further include a gridding three-dimensional coordinate computing module；It is described
Three-dimensional coordinate computing module chooses a blocks of knowledge as original point from blocks of knowledge set, and provides initial coordinate values；
If the blocks of knowledge and the original point in the blocks of knowledge set are relationship active direction, which is known as level-one
Blocks of knowledge, level coordinate value=original point+1 unit constant of level coordinate of level-one blocks of knowledge；Then it successively searches
There is in the blocks of knowledge set with level-one blocks of knowledge the blocks of knowledge of relationship active direction, referred to as second level blocks of knowledge, meter
Calculate level coordinate value=level-one blocks of knowledge+1 unit constant of level coordinate of second level blocks of knowledge；And so on, it obtains
There is in the blocks of knowledge set with upper level blocks of knowledge the level coordinate value of the blocks of knowledge at different levels of active direction；If should
Several blocks of knowledge are the passive direction of relationship in a blocks of knowledge a and the blocks of knowledge set in blocks of knowledge set, and this
A little blocks of knowledge have corresponding level coordinate value, then choose the highest blocks of knowledge b of level coordinate value, blocks of knowledge a's
Level coordinate value=blocks of knowledge b -1 unit constant of level coordinate.
9. knowledge base as claimed in claim 7, which is characterized in that further include a display module, the display module is according to exhibition
Show requirement, extract the blocks of knowledge for needing to show, the three dimensional network is called to format coordinate calculation module, computational gridding coordinate,
Constitute spacial flex；Wherein, the blocks of knowledge coordinate of spacial flex is generated using the linear transformation of gridding coordinate.
10. a kind of querying method based on knowledge base described in claim 7, step includes: the knowledge list inputted according to user
Metamessage searches all blocks of knowledge associated with it from the knowledge base；For each blocks of knowledge in query result,
Inquire the blocks of knowledge of blocks of knowledge dependence.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810123453.1A CN110119812A (en) | 2018-02-07 | 2018-02-07 | A kind of knowledge base and its methods of exhibiting, querying method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810123453.1A CN110119812A (en) | 2018-02-07 | 2018-02-07 | A kind of knowledge base and its methods of exhibiting, querying method |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN110119812A true CN110119812A (en) | 2019-08-13 |
Family
ID=67520140
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810123453.1A Pending CN110119812A (en) | 2018-02-07 | 2018-02-07 | A kind of knowledge base and its methods of exhibiting, querying method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110119812A (en) |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106021836A (en) * | 2015-10-12 | 2016-10-12 | 苏州中科知图信息科技有限公司 | Method and system for generating disciplinary knowledge map based on disciplinary logic knowledge relation |
| CN106372087A (en) * | 2015-07-23 | 2017-02-01 | 北京大学 | Information retrieval-oriented information map generation method and dynamic updating method |
| CN106909680A (en) * | 2017-03-03 | 2017-06-30 | 中国科学技术信息研究所 | A kind of sci tech experts information aggregation method of knowledge based tissue semantic relation |
| CN106933983A (en) * | 2017-02-20 | 2017-07-07 | 广东省中医院 | A kind of construction method of knowledge of TCM collection of illustrative plates |
| CN106997399A (en) * | 2017-05-24 | 2017-08-01 | 海南大学 | A kind of classification question answering system design method that framework is associated based on data collection of illustrative plates, Information Atlas, knowledge mapping and wisdom collection of illustrative plates |
| CN107016079A (en) * | 2017-03-28 | 2017-08-04 | 青岛伟东云教育集团有限公司 | The methods of exhibiting and device of a kind of knowledge point |
| CN107451183A (en) * | 2017-06-19 | 2017-12-08 | 中国信息通信研究院 | Knowledge Map construction method based on text cluster thought |
-
2018
- 2018-02-07 CN CN201810123453.1A patent/CN110119812A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106372087A (en) * | 2015-07-23 | 2017-02-01 | 北京大学 | Information retrieval-oriented information map generation method and dynamic updating method |
| CN106021836A (en) * | 2015-10-12 | 2016-10-12 | 苏州中科知图信息科技有限公司 | Method and system for generating disciplinary knowledge map based on disciplinary logic knowledge relation |
| CN106933983A (en) * | 2017-02-20 | 2017-07-07 | 广东省中医院 | A kind of construction method of knowledge of TCM collection of illustrative plates |
| CN106909680A (en) * | 2017-03-03 | 2017-06-30 | 中国科学技术信息研究所 | A kind of sci tech experts information aggregation method of knowledge based tissue semantic relation |
| CN107016079A (en) * | 2017-03-28 | 2017-08-04 | 青岛伟东云教育集团有限公司 | The methods of exhibiting and device of a kind of knowledge point |
| CN106997399A (en) * | 2017-05-24 | 2017-08-01 | 海南大学 | A kind of classification question answering system design method that framework is associated based on data collection of illustrative plates, Information Atlas, knowledge mapping and wisdom collection of illustrative plates |
| CN107451183A (en) * | 2017-06-19 | 2017-12-08 | 中国信息通信研究院 | Knowledge Map construction method based on text cluster thought |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Resnick | Adventures in stochastic processes | |
| Norton et al. | Introductory concepts in information science | |
| CN109918532A (en) | Image search method, device, equipment and computer readable storage medium | |
| Vega-Redondo | Evolution, games, and economic behaviour | |
| Scheiner et al. | Design and analysis of ecological experiments | |
| JP3648051B2 (en) | Related information retrieval apparatus and program recording medium | |
| CN111949787A (en) | Automatic question-answering method, device, equipment and storage medium based on knowledge graph | |
| CN103927615B (en) | Entity is associated with classification | |
| CN106570708A (en) | Management method and management system of intelligent customer service knowledge base | |
| CN104573130B (en) | The entity resolution method and device calculated based on colony | |
| CN107016001A (en) | A kind of data query method and device | |
| JP6819355B2 (en) | Recommendation generation | |
| CN103942571B (en) | Graphic image sorting method based on genetic programming algorithm | |
| CN113706251B (en) | Model-based commodity recommendation method, device, computer equipment and storage medium | |
| CN110019736A (en) | Question and answer matching process, system, equipment and storage medium based on language model | |
| CN109213859A (en) | A kind of Method for text detection, apparatus and system | |
| CN110795613B (en) | Commodity searching method, device and system and electronic equipment | |
| TW201820172A (en) | System, method and non-transitory computer readable storage medium for conversation analysis | |
| Recker et al. | Development of an estimation procedure for an activity‐based travel demand model | |
| CN110321492A (en) | A kind of item recommendation method and system based on community information | |
| Balakrishnan et al. | Triangulation in decision support systems: algorithms for product design | |
| CN108829670A (en) | Based on single semantic unregistered word processing method, intelligent answer method and device | |
| CN110502701A (en) | Introduce friend recommendation method, system and the storage medium of attention mechanism | |
| CN108764279A (en) | A kind of picture grouping acquisition system based on crowdsourcing | |
| CN110119812A (en) | A kind of knowledge base and its methods of exhibiting, querying method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20190813 |
|
| RJ01 | Rejection of invention patent application after publication |