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Zhao FengProfessor of Computer Science
Phone: Email: zhaof@hust.edu.cn Academic Areas: Knowledge engineering, knowledge graph, cognitive computing, data mining, natural language processing
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Personal Profile
Professor and doctoral supervisor of School of Computer Science of Huazhong University of Science and Technology, IEEE member, ACM member, CCF member, CCF information system committee. More than 60 papers have been published (accepted) in IEEE TSC, IEEE TBD, ICDM, CIKM, COLING, DASFAA, SRDS and other international famous journals and top-level conferences in the field. He served as a peer reviewer for more than 30 journals, including TC, TPDS, TBD, INS, INF, ISJ, IEEE Computer, and Science in China, and served as the chairman of the procedure committee/organizing committee and member of the procedure committee of several international academic conferences. More than 20 patents have been approved/applied, and more than 10 software copyrights have been approved. Presided over a number of national key research and development projects, National Natural Science Foundation of China, provincial science and technology research projects, and government/enterprise horizontal projects; As a major member, he has participated in the research of many topics such as the special project of the Ministry of Education, the national key basic research and development plan (973 project), the 863 project, and the key project of the Ministry of Education. He has won the Excellent Master's Thesis and Excellent Bachelor's Thesis Instructor of Hubei Province for many times, the first prize of Hubei Provincial Teaching Achievement Award and the second prize of Hubei Provincial Science and Technology Progress Award.
His research interests include knowledge discovery, semantic computing, data mining, information retrieval, system security, parallel distributed processing, etc. In recent years, he has mainly engaged in the research of knowledge engineering and information search, including (but not limited to):
1. Knowledge engineering:
(1) Knowledge discovery: knowledge management in the big data environment, starting from knowledge generation, storage, organization, autonomy, navigation, retrieval and other levels, studies the basic theory and key technologies of data driven knowledge discovery. For example, research the processing and transformation mechanism based on multi-source heterogeneous big data, build an efficient extraction functional framework of massive knowledge base, and realize the unified mapping and transformation technology of multiple knowledge bases.
(2) Knowledge map: Knowledge map is the combination of semantic network and big data. As the brain of intelligent system, it is an intelligent system
2. Information search:
(1) Deep Web search: More and more Web data are stored in accessible online databases. These Web data cannot be retrieved by traditional search engines (such as Google, Baidu, Yahoo, etc.). They can only be returned to users by querying dynamic pages generated in real time. They are "deep Web" data. We mainly study how to search and find the information required by users, mining the hidden knowledge behind Deep Web, such as query interface integration, data sampling, data acquisition, etc.
(2) Social network search: With the rapid development of computer technology and the rapid spread of the Internet, online social networks have achieved rapid development, and many social networking sites, such as Facebook, Twitter, Sina Weibo, Tencent, have risen rapidly. We mainly study how to implement fast and accurate access to these online data and obtain valuable information, such as real-time search, vertical search, personalized social recommendation, etc.
(3) Ubiquitous network information search: the recall and precision of information search in cloud computing environment, mobile network and Internet of Things are low. We mainly study the key technologies and core algorithms of parallel distributed retrieval of massive data in ubiquitous network environments such as mobile networks and the Internet of Things, such as IoT retrieval, mobile search, etc.
Academic Degrees
2003.9-2006.6
Huazhong University of Science and Technology
Doctoral Degree - Postgraduate (Doctoral)
2000.9-2003.6
Huazhong University of Science and Technology
Master's degree - Postgraduate (Master's Degree)
1994.9-1998.6
Wuhan University of Technology
Bachelor's Degree - Undergraduate (Bachelor's degree)
Professional Experience
Courses Taught
Awards and Honors
[1] 2019 Second prize of Hubei Provincial Science and Technology Progress Award
[2] 2017 First Prize of Hubei Province Teaching Achievement
[3] 2013 Hubei Excellent Instructor of Bachelor's Thesis
[4] 2016 Excellent Instructor of Master's Thesis in Hubei Province
Selected Projects Funded
Selected Publications
Professional Affiliations
Enrollment Information
We warmly welcome students to exempt and apply for doctoral and postgraduate examinations, and welcome undergraduate students to enter the research group and project group in advance to carry out early scientific research activities.
We warmly welcome doctoral graduates to engage in post doctoral research with preferential treatment.
Personal Homepage
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