Name: Liu Qiongxin
Discipline: Computer Application Technology
Title:
Tel: 13718727670,68913292
E-mail: summer@bit.edu.cn
Address: 1045 Central Teaching Building, No.5 Zhongguancun South Street, Haidian District, Beijing Personal Information
Liu Qiongxin, female, Doctor, associate professor, master tutor. He has been working at the School of Computer Science, Beijing Institute of Technology since July 1996. Research directions include: artificial intelligence, machine learning, knowledge graph, task planning related technologies, hosted and participated in a number of science and technology support projects of the Ministry of Science and Technology, 863 major scientific research projects, natural science foundation, Ministry of Science and Technology pre-research projects, and achieved a number of innovative achievements. He taught the compulsory courses of discrete Mathematics and Machine Learning for undergraduates.
Research Direction
1. Knowledge Graph
The key technologies of knowledge graph construction, such as knowledge reasoning and relationship extraction, are studied by using deep learning methods, and the application of knowledge graph in many fields, including search, recommendation, question and answer, etc.
2. Ai-based task planning and related technologies
Aiming at complex environment constraints, task constraints and goal constraints, swarm intelligence methods (genetic algorithm, ant colony algorithm, particle swarm optimization algorithm, etc.) are applied to study the key technologies of multi-objective optimization problems, such as cooperative task assignment, high-dimensional multi-objective programming, resource-constrained task scheduling, etc.
Personal Information
Liu Qiongxin, female, Doctor, associate professor, master tutor. He has been working at the School of Computer Science, Beijing Institute of Technology since July 1996. Research directions include: artificial intelligence, machine learning, knowledge graph, task planning related technologies, hosted and participated in a number of science and technology support projects of the Ministry of Science and Technology, 863 major scientific research projects, natural science foundation, Ministry of Science and Technology pre-research projects, and achieved a number of innovative achievements. He taught the compulsory courses of discrete Mathematics and Machine Learning for undergraduates.
Personal Information
Liu Qiongxin, female, Doctor, associate professor, master tutor. He has been working at the School of Computer Science, Beijing Institute of Technology since July 1996. Research directions include: artificial intelligence, machine learning, knowledge graph, task planning related technologies, hosted and participated in a number of science and technology support projects of the Ministry of Science and Technology, 863 major scientific research projects, natural science foundation, Ministry of Science and Technology pre-research projects, and achieved a number of innovative achievements. He taught the compulsory courses of discrete Mathematics and Machine Learning for undergraduates.
Representative Academic Achievements
2017 -- (One by myself or one by students)
[1] Curriculum learning for distant supervision relation extraction[J]. Journal of Web Semantics, 2020, (Feb, 61-62) : 100559. DOI: 10.1016 / j. ebsem. 2020.100559. < br >
[2] Distant Supervised Relation Extraction with Position Feature Attention and Selective Bag Attention. Neurocomputing (accepted)
[3] Generative knowledge question answering technique based on global coverage mechanism and representation learning [J/OL]. Journal of automation: 1-14 [2021-05-08]. HTTP: / / https://doi.org/10.16383/j.aas.c190785. < br >
[4] Panoramic video stitching of dual cameras based on spatio-temporal seam optimization[J]. Multimedia Tools and Applications, 2020, 79(5):3107-3124.
[5] A representation learning method incorporating entity association constraints [J]. Journal of Beijing Institute of Technology, 2019,40(01):90-97. (in Chinese)
[6] In-depth news recommendation network based on knowledge enhancement [J]. Journal of Beijing Institute of Technology,2021,41(03):286-294. (in Chinese)
[7] Path selection based representation learning in complex networks [J]. Journal of Beijing Institute of Technology,20,40(03):282-289. (in Chinese)
[8] An Advanced Load Balancing Strategy for Cloud Environment[C]// International Conference on Parallel & Distributed Computing. IEEE, 2017.
[9] A representation learning method based on entity association constraints [P]. Beijing: CN108647258B,2020-12-22.
[10] A collaborative matrix decomposition method based on knowledge representation learning [P]. Beijing: CN108804565B,2021-04-13.
Awards received
[1] Distributed data storage access and security technology. 2011 Ministry Science and Technology Progress award
[2] Decision aid technology. Third Prize of Science and Technology Progress of Ministry in 2001