CN104462227A - Automatic construction method of graphic knowledge genealogy - Google Patents
Automatic construction method of graphic knowledge genealogy Download PDFInfo
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- CN104462227A CN104462227A CN201410639967.4A CN201410639967A CN104462227A CN 104462227 A CN104462227 A CN 104462227A CN 201410639967 A CN201410639967 A CN 201410639967A CN 104462227 A CN104462227 A CN 104462227A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/34—Browsing; Visualisation therefor
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/248—Presentation of query results
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/33—Querying
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computing arrangements using knowledge-based models
- G06N5/04—Inference or reasoning models
Abstract
The invention provides a rapid construction method of a graphic knowledge genealogy, and provides an automatic construction method and process of the knowledge genealogy which relates to complex problems of multiple fields. The knowledge genealogy is subjected to direct and bright graphic representation through a knowledge map. Related drill through, visual tracking, interactive presentation and extended reading of knowledge are realized, and improvement of the knowledge comprehensive management and information decision analysis capacity is facilitated.
Description
Technical field
The invention belongs to scientific knowledge visual with knowledge domain analysis field.
Background technology
Knowledge pedigree is from French philosopher good fortune Ke philosophy, and how truth system and the will to truth of its investigation generation knowledge are born in certain knowledge form and knowledge relation; Its investigate individuality is considered as work, speak, knowledge, biological theme be how in knowledge manufactured out; It investigates certain language is how generated in the main body of desire by knowledge relation and disseminate.Does is the effect of knowledge pedigree that the problem to being considered to solve is questioned closely: first, the root that this problem produces as problem? its aim makes things problem exactly, finds some contact produced between the things of this problem.
The Visualization mode of knowledge pedigree is knowledge mapping, also referred to as mapping knowledge domains, it is by by methods combining such as the theory and means of the subjects such as applied mathematics, graphics, Information Visualization Technology, information science and metrology citation analysis, Co-occurrence Analysis, and the core texture of subject, developing history, Disciplinary Frontiers and overall Knowledge framework reach the modern theory of Multidisciplinary Integration object to utilize visual collection of illustrative plates to show visually.Specifically, knowledge mapping is by by methods combining such as the theory and means of the subjects such as applied mathematics, graphics, Information Visualization Technology, information science and metrology citation analysis, Co-occurrence Analysis, and the core texture of subject, developing history, Disciplinary Frontiers and overall Knowledge framework reach the modern theory of Multidisciplinary Integration object to utilize visual collection of illustrative plates to show visually.It is shown the ken of complexity by data mining, information processing, knowledge measure and graphic plotting, disclose the active development rule of ken, for disciplinary study provides practical, valuable reference.Up to now, its actual developed country that is applied in progressively has expanded and has achieved good effect, but it still belongs to the starting stage of research in China.
Knowledge pedigree is built, foreign scholar thinks that the many check weighings of knowledge pedigree are in the visual analyzing of structure analysis and the structure of knowledge, and the visual analyzing wherein for the structure of knowledge has research optionally to add the concrete sample situation of visual static nature such as cluster and behavioral characteristics such as destination object to carry out structural description; Combine frequency spectrum cluster and feature selecting algorithm is analyzed simultaneously.From external research, more deep to the research of knowledge mapping, comprise the visual philosophical recognize of knowledge mapping, algorithm innovation and too development etc., its application covers numerous fields, especially if the aspects such as digital library, information management, technology foresight, technology policy and complex network are according to visual image technique.Domestic scholars lays particular emphasis on theoretical property and application more.As being applied to Library and digital library, scientific research management, business economic, higher education, computer software and computer utility, marcoeconomic management and sustainable development, physical culture, news and medium, education theory and educational management, management, economic theory and History of Economic Thought, industrial general technology and equipment, theory of natural science and method and philosophy.
Generally speaking to the research of knowledge pedigree, stress method for visualizing and the theory and application research at different subject.And the pedigree lacked relating to multi-field complicated knowledge problem builds research.
Summary of the invention
In view of this, the invention provides a kind of patterned knowledge pedigree fast construction method, the knowledge pedigree construction method and flow process that relate to multi-field challenge are provided, knowledge pedigree has been carried out the graphic representation of direct distinctness by Knowledge Map.Build form Knowledge Map by mass knowledge nodal hierarchy classification extractions, association analysis, combination, realize that knowledge connection drills through, visual tracking, present and reads with extension alternately, be conducive to lifting knowledge integration and manage and information decision analysis ability.
The present invention takes full advantage of and dynamically updates technology based on the open Knowledge Map component technology of XML file, the Knowledge Map airmanship of the relation that gears to the needs of the society and knowledge base, with reference to knowledge index system establishment standard criterion, construct challenge knowledge pedigree fast construction method.It is rapid that its main performing step comprises the following steps: (1) knowledge index system establishment and maintenance; (2) knowledge entry retrieval and acquisition; (3) knowledge node of knowledge based entry builds; (4) knowledge based node builds Knowledge Map; (5) knowledge pedigree dynamic drafting with drill through; (6) knowledge pedigree dynamically updates and files.
Beneficial effect:
The present invention is in Knowledge Map component technology, digital map navigation technology and with under the support of the seamless spliced technology of spatial data index, achieve following effect: (1) discloses the extraction of the relational implementation data between social field and knowledge and shared by Knowledge Map assembly, as hierarchical relationship, correlationship etc., the node that each knowledge node exists relation with other is connected, be connected to relevant personnel, data, be connected to relevant knowledge, constitute a knowledge network, along this network, all things relevant to node can be found.(2) Knowledge Map rapid navigation is provided to retrieve, the value that its data assets is excavated by facilitate tissue mechanism make various data resource in organizational structure be converted into Explicit Knowledge and and then internalization be the Knowledge Assets of tissue, play the leverage of the existing data resource of mechanism and Knowledge Assets, by the classification relation in the fields such as economy, environment, the energy, population in society, be connected the different members node in different geographical, mechanism and organization of unity, disclose the crossover network structural relation between different society field and social entity; (3) framework based on knowledge pedigree is utilized, based on data constellation, mutual, the visual digging technology of the page, quick position user is concerned about knowledget opic, extract and build seamless connection Knowledge Map, disclosing between knowledge node and knowledge node and data resource or particular event relation each other.
Accompanying drawing explanation
The knowledge pedigree of Fig. 1 subject-oriented builds flow process;
Fig. 2 utilizes graphical knowledge pedigree to carry out information management
Embodiment
The invention provides the fast construction method of graphical knowledge pedigree.Main implementation step is specific as follows:
Step one, knowledge index system establishment and maintenance.
Based on multi-field index classification system, index description standard, index definition category, index intension and extensions such as existing society, economy, environment, physical geographys, in conjunction with domain-specialist knowledge structure and relevant authority viewpoint, build multi-field knowledge index system.Index system establishment is a long-term process, and according to the development of the theory of different field, the change of Academic Methods, knowledge index system will dynamically update and maintenance.
1) wikipedia knowledge index system is downloaded, as knowledge index system basis;
2) leaving knowledge index entry in text database (such as business TRS database), laying the foundation for realizing text quick-searching below;
3) leave knowledge index entry in relevant database (such as business oracle database), it is a table that entry is deposited, and entry relationship leaves another table in, forms a reticulate texture;
4) expert is organized to carry out re-organized to this domain knowledge entry for application;
5) according to an expert view, text database and relevant database is upgraded.
The retrieval of step 2, knowledge entry and acquisition.
For relating to multi-field challenge, with this problem for traction, the Method and Technology of type of service, identifies knowledge by relation, term, rule etc. between the attribute of concept, concept, concept, obtains the professional knowledge pedigree content in this field.First, utilize text participle, database index method realizes extracting in core data bank the knowledge entry and historical summary that have accumulated.Secondly, according to associated specialist knowledge, theoretical method, domestic and international authoritative public opinion and the knowledge entry of comment, relevant acquisition of information particular topic of gathering information, the knowledge entry of up-to-date acquisition is entered database processes.
1) the Chief word of challenge is summed up, general 3 to 5 keywords;
2) according to key to the issue word, adopt text segmenting method retrieval text database, calculate text similarity simultaneously;
3) according to text similarity sequence, retrieval is obtained relevant entry title and numbering leaves in array;
4) if result for retrieval is too much, according to N bar record before similarity screening;
The knowledge node of step 3, knowledge based entry builds.
After obtaining knowledge pedigree relevant knowledge content, carry out organization knowledge by semantic relation (or theme), classification, classification are carried out to knowledge, determines all critical learning.Such as U.S. financial crisis; it is embodied in the aspects such as economy, diplomacy, safety to the impact of China and other concerned countries, and these are exactly the theme of Study on Problems, are the handgrips of knowledge organization; press systematic fashion organization knowledge on this basis, and determine all critical learning node.According to structuring, the non-structured data content such as associated description, intension, extension of knowledge entry, text participle, cluster, Similarity algorithm (range finding) is utilized to realize associating and mounting of knowledge entry and index system.By association knowledge entry and index system, in knowledge index system database, increase new knowledge entry content, form new knowledge node.
1) the knowledge entry array in organising step two, according to the hierarchical relationship between entry, dependence, is organized into the knowledge topological network of an object-oriented problem;
2) for each knowledge node in topological network, in data bank, retrieve corresponding node to be correlated with active file data;
3) for each knowledge node in topological network, web crawlers technology retrieval network relevent information and webpage is utilized;
4) according to knowledge node, in Text Knowledge-base, the knowledge node stored is retrieved;
5) above-mentioned result for retrieval is associated with corresponding node, complete each knowledge node content and build.
Step 4, knowledge based node draw Knowledge Map.
Mainly comprise knowledge connection, knowledge distribution, personalized realization etc.Knowledge Map is dynamic concept, sets up the connection between all kinds of knowledge, comprise the connection between expert and knowledge, between knowledge and knowledge by knowledge intelligent association (or setting up index); On the basis of knowledge connection, according to the membership of knowledge and degree of correlation, realize knowledge reasonable, effectively configure; For the individual demand of different user, embody the personalization that Knowledge Map builds in many ways.Such as in U.S. financial crisis; its impact is economically mainly reflected in 3 aspects; namely on the impact of Income Redistribution in global range, on the impact of financial liberalization process, the impact on international monetary system running; the membership of each aspect foundation problem and degree of correlation, can obtain more relevant knowledge again.
1) according to knowledge topological network in step 3, each knowledge node is drawn, using nodename as display keyword;
2) according to internodally interdepending, interactively, draw internodal relation arrows, and mark correlationship;
3) use ring topology mode to show each internodal mutual relationship of knowledge pedigree, complete Knowledge Map visual.
Step 5, knowledge pedigree dynamic drafting with drill through.
Knowledge based map, research relates to the form of expression and the treatment principle of the knowledge pedigree key element of multi-field challenge different themes, and rendering algorithm, model and technology, based on Flex cartoon technique research and development knowledge pedigree drawing tool, represent knowledge pedigree in modes such as traditional directory hierarchical manner, tree structure or reticulate textures.Meanwhile, based on nested retrieval, knowledge hierarchy structure realize knowledge node dynamic dispatching, navigate and drill through.
1) according to the Knowledge Map in step 4, to each knowledge node registered user alternative events;
2) register click event, when clicking knowledge node, eject node detailed knowledge content;
3) register double-click event, during double-click knowledge node, this node shows between two parties, and realizes next stage knowledge node drilling operation.
Step 6, knowledge pedigree dynamically update and file.
Due to multi-field challenge, the contents such as its PROBLEM DECOMPOSITION, description and management, knowledge base, case library are not unalterable, and having one upgrades and the process associated gradually, accordingly, knowledge pedigree neither be static constant, also has one and constantly dynamically update the process with auto-associating.The automatic renewal technology of the object such as reference database, text, realizes dynamically updating towards challenge knowledge pedigree.
1), when user browses knowledge pedigree, editor's change is carried out to knowledge node, completes dynamically updating and revising of knowledge node;
2) user finds that this knowledge pedigree is to after larger help of having dealt with problems, and can edit, arrange, comprehensively form new knowledge node and file knowledge base.
Embodiment
Certain Information Resources Integration utilizes in platform, by Knowledge Map system, knowledge pedigree has been carried out graphic representation.In fields such as society, economy, environment, culture, Knowledge Map is formed based on mass knowledge nodal hierarchy classification extraction, association analysis, combination cluster, realize that knowledge connection drills through, visual tracking, present and read with extension alternately, realize quick combing and the integration of integrated information resource, significantly improve the informix decision analysis ability of managerial personnel.
Claims (3)
1. the knowledge pedigree construction method of a subject-oriented: (1) knowledge index system establishment and maintenance; (2) knowledge entry retrieval and acquisition; (3) knowledge node of knowledge based entry builds; (4) knowledge based node builds Knowledge Map; (5) knowledge pedigree dynamic drafting with drill through; (6) knowledge pedigree dynamically updates and files.
2. the knowledge pedigree construction method of subject-oriented according to claim 1, is characterized in that, what it adopted is Knowledge Map interactive application mode: eject node detailed content when (1) clicks knowledge node; (2) during double-click knowledge node, this node shows between two parties, and realizes next stage knowledge node drilling operation; (3) ring topology mode is used to show each internodal mutual relationship of knowledge pedigree.
3. the graphical knowledge pedigree method for auto constructing according to claim 1 and 2, it is characterized in that, technology is dynamically updated towards challenge knowledge base, multi-source information or knowledge are through extracting screening, association analysis, theme classification, form the Knowledge Map of subject-oriented, file after visual analysis in knowledge base, realize dynamically updating of challenge knowledge base.
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Cited By (19)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105426460A (en) * | 2015-11-12 | 2016-03-23 | 上海电机学院 | Scientific research information management method |
| CN105930461A (en) * | 2016-04-21 | 2016-09-07 | 成都数联铭品科技有限公司 | Data processing method for realizing associated information node visualization tracking |
| CN106295187A (en) * | 2016-08-11 | 2017-01-04 | 中国科学院计算技术研究所 | Construction of knowledge base method and system towards intelligent clinical auxiliary decision-making support system |
| CN106776861A (en) * | 2016-11-28 | 2017-05-31 | 北京亚信数据有限公司 | A kind of indicator consilience analysis method and analysis system |
| CN107194466A (en) * | 2017-05-23 | 2017-09-22 | 广东工业大学 | Knowledge Visualization method and system between one conception of species |
| CN107239832A (en) * | 2017-06-12 | 2017-10-10 | 西南交通大学 | A kind of online dynamic knowledge atlas preparation method |
| CN107506359A (en) * | 2016-06-14 | 2017-12-22 | 科大讯飞股份有限公司 | Examination question high-order attribute excavation method and system |
| CN107660296A (en) * | 2015-03-30 | 2018-02-02 | 克拉斯库博有限公司 | For providing the method for learning information, system and the computer-readable recording medium of non-transitory |
| CN107679194A (en) * | 2017-10-09 | 2018-02-09 | 东软集团股份有限公司 | A kind of text based entity relationship construction method, device and equipment |
| CN108463818A (en) * | 2016-10-31 | 2018-08-28 | 微软技术许可有限责任公司 | Establish and update connection segment collection of illustrative plates |
| CN108536872A (en) * | 2018-04-27 | 2018-09-14 | 武汉文都信息技术有限公司 | Optimize the method and apparatus of knowledge base structure |
| CN109804364A (en) * | 2016-10-18 | 2019-05-24 | 浙江核新同花顺网络信息股份有限公司 | Knowledge mapping constructs system and method |
| CN109903617A (en) * | 2017-12-11 | 2019-06-18 | 北京三好互动教育科技有限公司 | Individualized exercise method and system |
| CN109922075A (en) * | 2019-03-22 | 2019-06-21 | 中国南方电网有限责任公司 | Network security knowledge map construction method and apparatus, computer equipment |
| CN110209814A (en) * | 2019-05-23 | 2019-09-06 | 西安交通大学 | A method of knowledget opic is extracted from encyclopaedic knowledge website using field modeling |
| CN111324753A (en) * | 2020-01-22 | 2020-06-23 | 天窗智库文化传播(苏州)有限公司 | Media information publishing management method and system |
| CN111383145A (en) * | 2019-11-12 | 2020-07-07 | 上海软科教育信息咨询有限公司 | Subject layout and subject layout comparison method, system, terminal and medium |
| CN111444181A (en) * | 2020-03-20 | 2020-07-24 | 腾讯科技（深圳）有限公司 | Knowledge graph updating method and device and electronic equipment |
| CN111695022A (en) * | 2019-01-18 | 2020-09-22 | 创新奇智(重庆)科技有限公司 | Interest searching method based on knowledge graph visualization |
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| CN107660296A (en) * | 2015-03-30 | 2018-02-02 | 克拉斯库博有限公司 | For providing the method for learning information, system and the computer-readable recording medium of non-transitory |
| CN105426460A (en) * | 2015-11-12 | 2016-03-23 | 上海电机学院 | Scientific research information management method |
| CN105930461A (en) * | 2016-04-21 | 2016-09-07 | 成都数联铭品科技有限公司 | Data processing method for realizing associated information node visualization tracking |
| CN107506359B (en) * | 2016-06-14 | 2020-02-07 | 科大讯飞股份有限公司 | Test question high-order attribute mining method and system |
| CN107506359A (en) * | 2016-06-14 | 2017-12-22 | 科大讯飞股份有限公司 | Examination question high-order attribute excavation method and system |
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| CN107679194A (en) * | 2017-10-09 | 2018-02-09 | 东软集团股份有限公司 | A kind of text based entity relationship construction method, device and equipment |
| CN107679194B (en) * | 2017-10-09 | 2020-04-10 | 东软集团股份有限公司 | Text-based entity relationship construction method, device and equipment |
| CN109903617A (en) * | 2017-12-11 | 2019-06-18 | 北京三好互动教育科技有限公司 | Individualized exercise method and system |
| CN109903617B (en) * | 2017-12-11 | 2021-02-02 | 北京三好互动教育科技有限公司 | Personalized exercise method and system |
| CN108536872A (en) * | 2018-04-27 | 2018-09-14 | 武汉文都信息技术有限公司 | Optimize the method and apparatus of knowledge base structure |
| CN108536872B (en) * | 2018-04-27 | 2020-12-25 | 湖北时代万新国际教育发展有限公司 | Method and device for optimizing knowledge base structure |
| CN111695022A (en) * | 2019-01-18 | 2020-09-22 | 创新奇智(重庆)科技有限公司 | Interest searching method based on knowledge graph visualization |
| CN109922075A (en) * | 2019-03-22 | 2019-06-21 | 中国南方电网有限责任公司 | Network security knowledge map construction method and apparatus, computer equipment |
| CN109922075B (en) * | 2019-03-22 | 2020-06-02 | 中国南方电网有限责任公司 | Network security knowledge graph construction method and device and computer equipment |
| CN110209814A (en) * | 2019-05-23 | 2019-09-06 | 西安交通大学 | A method of knowledget opic is extracted from encyclopaedic knowledge website using field modeling |
| CN111383145A (en) * | 2019-11-12 | 2020-07-07 | 上海软科教育信息咨询有限公司 | Subject layout and subject layout comparison method, system, terminal and medium |
| CN111324753A (en) * | 2020-01-22 | 2020-06-23 | 天窗智库文化传播(苏州)有限公司 | Media information publishing management method and system |
| CN111324753B (en) * | 2020-01-22 | 2021-09-03 | 天窗智库文化传播(苏州)有限公司 | Media information publishing management method and system |
| CN111444181A (en) * | 2020-03-20 | 2020-07-24 | 腾讯科技（深圳）有限公司 | Knowledge graph updating method and device and electronic equipment |
| CN111444181B (en) * | 2020-03-20 | 2021-05-11 | 腾讯科技（深圳）有限公司 | Knowledge graph updating method and device and electronic equipment |
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