bingru Yang
City:
Beijing
Country:
China
Current Affiliation:
University of Science and Technology Beijing, China; Knowledge Engineering Institute.
Current Position:
Chief professor, Ph.D. supervisor of School of Information Engineering, dean of Institute of Knowledge Engineering
Career Highlights:
Prof. Bingru Yang has always been engaging in teaching and researching in the field of modern mathematics and computer science and technology. His main research interest includes Knowledge Discovery and Intelligent System, Flexible Model and Integration Technology. Prof. Yang is a famous expert, who earlier entered the field of KD in domestic. He spent more than ten years researching system of data mining based on structured data, complex types of data (such as Web and multi-media) entirely, steadily and systematically. He broke through two main issues in contemporary development of KD. His scholarship is introduced in the other paper
His lecture achievements are as follows: Professor Yang has taught 12 courses, while teaching without textbooks and drafts. He pursued scientific teaching style and artistic teaching style by repeatedly observing and imitating teaching. Teachers and students, who attended his lecture, all gave high comment on his teaching. He proposed his teaching opinion on the core function of knowledge logical structure and put forward teaching method combined with knowledge logic structure and thought inducement chart. He also published some papers about teaching reform and undertook some teaching reform projects. At the same time, he edited some textbooks alone or cooperating with others. He taught value project on CCTV and TianJin TV and won prize and good appraisement. Prof. Yang has tutored two young teachers, 2 post-doctor, 73 doctors, 77 Masters and 10 foreign students successively.
His lecture achievements are as follows: Professor Yang has taught 12 courses, while teaching without textbooks and drafts. He pursued scientific teaching style and artistic teaching style by repeatedly observing and imitating teaching. Teachers and students, who attended his lecture, all gave high comment on his teaching. He proposed his teaching opinion on the core function of knowledge logical structure and put forward teaching method combined with knowledge logic structure and thought inducement chart. He also published some papers about teaching reform and undertook some teaching reform projects. At the same time, he edited some textbooks alone or cooperating with others. He taught value project on CCTV and TianJin TV and won prize and good appraisement. Prof. Yang has tutored two young teachers, 2 post-doctor, 73 doctors, 77 Masters and 10 foreign students successively.
Field of Research:
INFORMATION AND COMPUTING SCIENCES - Artificial Intelligence and Image Processing - Pattern Recognition and Data Mining
Professional Memberships:
He is not only a specialist who obtained State Council Special Allowance for his outstanding contributions, but also a certified international science and technology specialist, member of expert team of Country Technology Basement Condition Platform Construction, senior syndic of National Education Degree Center, Ministry of Education Expert Committee, National 863 Project, National Natural Science Fund Project, Ministry of Education projects and reviewer of several domestic and international famous journals. He is assigned as honorary chairperson of Fuzzy Information and Engineering Academy China that belongs to International Common System Academy, director of Discrete Mathematics Association that is subject to Chinese Association for Artificial Intelligence. Professor Yang used to be senior supervisor of CIT, member of expert team of NIT, senior consultant in Patent Office Hong Kong.
Notable Grants/Projects:
30 scientific research achievements gained national and provincial certification and acceptance, many transverse research project have been completed, 5 subjects are being studied (subject director).Having obtained two international awards (with Appraisal letter), nominated twice champion of state technological invention awards by Ministry of Information Industry; having obtained 8 prizes for progress in science and technology at provincial and ministerial levels; having obtained 8 national invention patent certifications being the only inventor (another 2 patents are in process), one item of software copyright certification, one software certification.
Typical Awards list:
1. “Outstanding Achievement Award” by World Academy of Sciences and award selection committee of congress in Las Vegas, in June 2006(Unique).[Award topic: Knowledge Discovery Theory based on Inner Mechanism]
2. “Achievement Award” by both “World Academy of Sciences” and the award selection committee of congress and the “Certified International Registered Technology Specialist” by International Technology Institute on world congress in computer science (World congress in large scale, including 13 subjects ) in Las Vegas, in June 2002 (Unique). [Award topic: Knowledge Discovery Theory and its Application based on Inner Cognitive Mechanism]
3. “The Second Prize for Natural Science” by Ministry of Education in 2008 (Unique).—have been recommended to the “National Award for Natural Science” [Award topic: The Construction of Knowledge Discovery Theory System and Its Methodology Based on Cognitive] [Competition topic: The construction, Expand and Value of Knowledge Discovery Theory System based on Inner Cognitive Mechanism].
4. “The Second Prize for Progress in Science and Technology, Tianjin” in 1993.[Award topic: The Research on the Decision-making and Integrating of Value Engineering](the first).
5. “The Second Prize for Electronic Information Science and Technology” in 2006(have been recommended to compete the National Award for Technological Invention by Ministry of Information Industry) in 2006.[Award topic: Data Mining Technology Innovation and its Application based on Cognitive Discovery]
6. “The Third Prize for Science and Technology, Beijing” in 2008; [Award topic: Data Mining Technology Innovation and its Application ]
7. “The Third Prize for Progress in Science and Technology, Tianjin” in 1991; [Award topic: Study on value engineering to improve the economic efficiency of the enterprises decision-making]
8. “The Second Prize for Research of Humanities and Social Sciences” by ministry of education in 1998; [Award topic: Inductive logic and Artificial Intelligence]
9. “The Second Prize for Electronic Information Science and Technology” in 2003; [Award topic: New intelligence system construction based on knowledge found and its application]
10. “The Third Prize for Electronic Information Science and Technology” in 2005;[Award topic: Complex system of data mining notation and its application]
11. Other awards as follows: “The Prize for Excellence Paper” on HQ-world congress of computer in 1999; “Silver Invention Prize” in the 46th international Eureka in 1997; “The Prize for Excellence Paper” on the congress of national computer application in 1995;and other academy prizes, etc.
Typical Awards list:
1. “Outstanding Achievement Award” by World Academy of Sciences and award selection committee of congress in Las Vegas, in June 2006(Unique).[Award topic: Knowledge Discovery Theory based on Inner Mechanism]
2. “Achievement Award” by both “World Academy of Sciences” and the award selection committee of congress and the “Certified International Registered Technology Specialist” by International Technology Institute on world congress in computer science (World congress in large scale, including 13 subjects ) in Las Vegas, in June 2002 (Unique). [Award topic: Knowledge Discovery Theory and its Application based on Inner Cognitive Mechanism]
3. “The Second Prize for Natural Science” by Ministry of Education in 2008 (Unique).—have been recommended to the “National Award for Natural Science” [Award topic: The Construction of Knowledge Discovery Theory System and Its Methodology Based on Cognitive] [Competition topic: The construction, Expand and Value of Knowledge Discovery Theory System based on Inner Cognitive Mechanism].
4. “The Second Prize for Progress in Science and Technology, Tianjin” in 1993.[Award topic: The Research on the Decision-making and Integrating of Value Engineering](the first).
5. “The Second Prize for Electronic Information Science and Technology” in 2006(have been recommended to compete the National Award for Technological Invention by Ministry of Information Industry) in 2006.[Award topic: Data Mining Technology Innovation and its Application based on Cognitive Discovery]
6. “The Third Prize for Science and Technology, Beijing” in 2008; [Award topic: Data Mining Technology Innovation and its Application ]
7. “The Third Prize for Progress in Science and Technology, Tianjin” in 1991; [Award topic: Study on value engineering to improve the economic efficiency of the enterprises decision-making]
8. “The Second Prize for Research of Humanities and Social Sciences” by ministry of education in 1998; [Award topic: Inductive logic and Artificial Intelligence]
9. “The Second Prize for Electronic Information Science and Technology” in 2003; [Award topic: New intelligence system construction based on knowledge found and its application]
10. “The Third Prize for Electronic Information Science and Technology” in 2005;[Award topic: Complex system of data mining notation and its application]
11. Other awards as follows: “The Prize for Excellence Paper” on HQ-world congress of computer in 1999; “Silver Invention Prize” in the 46th international Eureka in 1997; “The Prize for Excellence Paper” on the congress of national computer application in 1995;and other academy prizes, etc.
Research Interests:
I．Knowledge Discovery and Knowledge Engineer
Knowledge Discovery (KD) is a newfound, crossed, interdisciplinary subject proposed in 1989, and has less than 20 years history. In the status in which experts in the field study mainstream develop algorithm and application, in 1997, he broke a new path in which he studied KD ontology (process or system) from the cognitive science, found the inner rule of KD mechanism; internationally be the first to construct KDTICM(Knowledge Discovery Theory based on Inner Cognitive Mechanism) in 2002, and then expand step by step; KDTICM study the practical significance and application instead of the virtual construction, in the recent years, a series of research results which reflect KDTICM science and application value has been proved this point.
1.Find Four rules About Cognitive Mechanism in KD System independently
1.1 Double bases cooperating mechanism（Reveal the inner relation between knowledge base and database）
We found the relationship between database and knowledge base, and then designed Heuristic Coordinator and Maintenance Coordinator that can resolve many problems such as directional search, directional mining and real-time maintenance, etc.
1.2 Double basis fusion mechanism（Reveal the inner relation between the two knowledge discovery process）
Our team discovered the relationship between process KDD and KDK, and united them in one KD system by double basis fusion mechanism, then designed R type, S type and T type coordinators.
1.3 Information spreading mechanism（Reveal the regularity of dynamic mining process）
1.4 Immune evolutionary mechanism（Reveal the regularity of dynamic mining system）
We propose concept of dynamic mining process based on data increment to resolve some problems of dynamic data mining. As the comparability between dynamic mining and biology immune evolutionary process, we then propose the meaning of immune evolutionary mechanism in KD.
2.The first to construct theory system
2.1 Four forerunner system frameworks:
The direct result of finding four mechanisms is induce new process models, derive some new technique methods, produce four “system framework”—and then construct theory system KDTICM.
Framework 1: On the basis of cognitive psychology, finding double bases cooperating mechanism (structure corresponding theory), and inducing new process model KDD* and M algorithm which is used in associate rule mining.
Framework 2: On the basis of cooperating theory, finding double basis fusion mechanism (process model logic equivalence theory), and inducing new process model KDK* and relevant new KDK algorithms.
Framework 3: On the basis of cognitive physics, finding information spreading mechanism (dynamic process parameter evolvement theory), and inducing new complex type data mining process model DFSSM, then obtaining new type text classifier and clustering algorithm and SID3 mining algorithm which is based on new information entropy formula.
Framework 4: On the basis of cognitive biology, fining immune evolutionary mechanism (cooperating theory), and inducing new knowledge discovery structure model based on immune evolutionary mechanism, obtaining time sequence mining algorithm, rough set classifying algorithm and clustering mining based on immune evolutionary mechanism.
2.2 Construction of KDTICM theory system based on system frameworks
Over more than ten years’ research, integrating and inosculating four system frameworks to form new process models and algorithms, such as process model KD (D&K)=KDD*+KDK*, multi-relationship frequent pattern mining, linking mining methods based on graph, multi-relationship classifying research, MRFPDA algorithm, MLMFPD algorithm and etc. Finally constructing KDTICM (knowledge discovery theory based on inner cognitive mechanism) based on theory foundation, four mechanisms, eight new process model and seventeen new technological methods. We designed the ICCKDSS software based on KDTICM, It has been passed by China software testing center and gained software copyright.
3. Expand on Theory system in depth
3.1 Internationally Pioneering New Research Direction—KDK included by KDTICM
It’s a non-pioneering issue internationally. We firstly proposed KDK which is based on knowledge base in 2003 (we found some scholars proposed that ”learning some knowledge firstly, and then mining the knowledge. ” when they are dealing with text mining). Using conclusion learning method to generate hypothesis in according to the rules in knowledge base, then using Cohen’s inductive logic to verify and evaluate; adopting high factorial logic to induce hypothesis and verify. We have done research on this issue with supports of many national foundations. (Appraised excerpt: "Knowledge Discovery in Knowledge base(KDK) is put forward by applicants independently internationally"; "It is a new study field to be pioneered at home and abroad. The main purpose of the subject is to discovery more profound knowledge on the background of higher-order logic, and it may solve the bottleneck which is “lack of knowledge” in existing intelligent systems, have theoretical and practical value, and have innovativeness. ").We have published many influencing papers internationally, which have attracted many researchers to start studying it.
3.2 Put forward four new kinds of intelligent systems derived from KDTICM independently
ESKD (expert system based on knowledge discovery), IDSSKD (intelligent decision support system based on knowledge discovery), IFSSKD (intelligent forecasting support system based on knowledge discovery) and CAIISKD (computer assistant innovation intelligent system based on knowledge discovery), which resolve bottle problems such as knowledge obtaining and knowledge sparseness, and improve the structure, function and intelligence of classic intelligent system.
ESKD have the new general framework, new component knowledge obtained automatically, new dynamic knowledge base system, new inference engine, that the features are multi-knowledge source, multi-knowledge integration, and multi-abstract level. "Technology Times" has reported the paper and its important impact which published on "Science in China".
ESKD successfully applied and runs in agriculture (agricultural demonstration district in Hefei) and electrolytic Aluminum production (Qingtongxia Aluminum Group Co.Ltd); IDSSKD applied in the business of foreign trade processing of International Electronic Commerce Center (Beijing).
3.3 Internationally proposed five key issues in the fields of knowledge discovery
4. Scientific value of theory system
4.1 Out of the field: International issues in biology information field—breakthrough in protein secondary structure prediction research.
We use KDTICM as the core technology and methodology, and then achieved results as followed: 93.88% Q3 accuracy on ILP dataset(maximal 81% we have known in the world); 84.1% Q3 accuracy on RS126 dataset(maximal 81.65% we have known in the world); 80.49% Q3 accuracy on CB513 dataset(maximal 78.44% we have known in the world). Our research result is the highest in the world. We can improve the prediction accuracy in optimization layer until this achievement.
4.2 Inside of the field:
1) The promote effect of KDTICM for the main stream of knowledge discovery.
2）The expand research on KDTICM in depth has been appraised to exploit the new branches and research directions (subject) in the field of knowledge discovery and knowledge engineering
(1) The KDK before-mentioned has been appraised as "knowledge discovery based knowledge-base is a new development at home and abroad, research has yet to be leading.", And has attracted scholars to carry out the study-related.
(2) The successful construct idea and methodology of ESKD and IDSSKD have strong subject (knowledge engineering) driving promotion: provide typical examples for the constructions of other smart systems based on KDTICM(such as intelligent predictive knowledge systems, natural language understanding system, intelligent robot systems, intelligent control system , intelligent fault diagnosis system, etc.) and trigger new topics exploit deeply in the field of intelligent systems.
(3) Among five key issues we proposed: the mass data mining based on non-equilibrium state conversion is begin with the system state research and system state evolution process, and from the perspective of nonlinear dynamics to study the mass data mining process, and is expected to form the theoretical system parallel developed with KDTICM; the solve process of "two conjectures", "challenging issues", "technical standard" will continue to lead new research topics; the successful exploration of protein secondary structure Prediction -- international problems of Molecular Biology (Bioinformatics) field has a great promotion for the micro-economics, medical informatics and other related disciplines in the field of the major issues resolved.
Fully above all reflects the scientific value of theoretical system of knowledge discovery, and may be to open up new branches and research directions (thematic) for knowledge discovery and knowledge engineering.
5. Appliance value of theory system
5.1 We have successfully applied the theory of KDTICM and its’ intelligent system in many fields such as Agriculture, Modern Distance Education Network, Weather, International Business, Electrolytic Aluminum production, Digital Resources Process and Tax Finance etc. and verify the theoretical system KDTICM effectively; and solve a number of typical problems in the field.
5.2 Business foreground of this research:
1) Based on the relationship between protein structure and biology function, according to the requirements, we can determine protein structure and improve its’ sequence and structure by gene technology, which can be used in many fields such as industry, agriculture, medicine etc.
2) Protein solid structure is precondition of producing biological medicine.
3) Applying many models, which can bring production benefit: such as constructing protein solid structure repository; constructing special repository of single nucleotide polymorphism, which sequence is playing great importance in selecting little molecule medicine.
5.3 It’s a fact in foreign country that data mining technology can be successfully applied in business decision support but not in the industry field. What we have done has breakthrough these bottle problems, and obtain By choosing the larger enterprises and companies of national and crafts typical (Qingtongxia Aluminum Co., Ltd., Beijing Huashen Science and Technology Development Co., Ltd. ), and then in the industry promotion, the annual direct economic benefits of up to 20.5 million yuan (300 million to promote post-Tatsu 3 million); through the cooperation of the two companies in Beijing, respectively, to obtain the annual 10 million, 50 million yuan of direct economic benefits. (Both corresponding financial certificate) Our production has been successfully applied in six companies, and we have signed sale and develop agreements with thirteen companies, which include America Zaptron Company and Hamburg University of Berlin Germany.
II．Flexible Model and Integration Technology
1. Proposed new models, technology and methods.
Pro. Yang proposed new model ,new technology and new methods used in intelligence control and management. Such as fuzzy algebra structure of type B-D and multi hiberarchy structure logic, cause relationship-reasoning model and generalized cell automatically machine model, expert knowledge inducing mechanism, fuzzy integrating technology based on rough language space and fuzzy language optimization model. All of the above can solve four important problems: 1) logical basic analysis in experiments; 2) multi-parameters cooperating control model based on qualitative induction; 3) hiberarchy structure analysis on huge system function and integrating technology on fuzzy language optimization; 4) Integrating technology based on fuzzy language space’s production equipment danger grade assess.
2. Applied innovative models and methods on intelligent control, value engineering and security system engineering fields.
Pro. Yang took part in national important modern optimization management project—Value Engineering from 1991 to 1993, took lectures in value engineering in CCTV and Tianjin TV channel and gained awards, popularised and applied those models and technical methods in over ten big companies, which have gained significant economic benefit and social benefit.
Publication History:
Pro. Yang has published approximate to 450 pieces of paper in internal famous journals such as International Journal on Artificial Intelligence Tools, Fuzzy Sets and Systems, Journal of Computational Information Systems, Fuzzy Optimization and Decision Making, International Journal of Plant Engineering & Management, Chinese Science, Chinese engineering science, natural science development, computer science, atomization journal, electronics journal, computer research and development etc. According to the novel retrieval, his papers have been included by SCI,EI,ISTP for 155 pieces, WOS cite: 21pieces of paper have been cited for 51times(note: this research field has a history of less than 20 years ), some papers have been cited by important international journal such as “REPRODUCTION IN DOMESTIC ANIMALS”、“JOURNAL OF FOOD SAFETY; He also published fifteen literatures (eight of them are written by himself-one of them is published in English; the rest seven literatures are written with others); the first literature internal about Knowledge Discovery, , has been cited for 231times.
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Documents
| Date Uploaded | Name | Description | File | Ratings | Options |
| 2009-08-12 14:05PM | Biography of Professor Bingru Yang | Biography of Professor Bingru Yang | biography_of_professor_bingru_yang.doc |
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| 2009-08-12 13:51PM | Academic achievements of Professor Bingru Yang | Academic achievements of Professor Bingru Yang | academic_achievements_of_professor_bingru_yang.doc |
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| 2009-07-24 00:00AM | 知识工程研究所简介 | 知识工程研究所简介 | 知识工程研究所(0613).ppt |
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