Learning Concept Interestingness for Identifying Key Structures From Social Networks-Reference-Cited by-同舟云学术

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Learning Concept Interestingness for Identifying Key Structures From Social Networks

Published:2021-10-01 Issue:4 Volume:8 Page:3220-3232
ISSN:2327-4697
Container-title:IEEE Transactions on Network Science and Engineering
language:
Short-container-title:IEEE Trans. Netw. Sci. Eng.

Author:

Gao Jie^ORCID,Hao Fei^ORCID,Pei Zheng^ORCID,Min Geyong^ORCID

Funder

Fundamental Research Funds for the Central Universities China

National Natural Science Foundation of China

European Unions Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Computer Science Applications,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/6488902/9644929/09524490.pdf?arnumber=9524490

Cited by 12 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. An Efficient Approach for Concept Reduction on Dynamic Formal Context;2024 4th International Conference on Computer Communication and Artificial Intelligence (CCAI);2024-05-24

2. Non-redundant implicational base of formal context with constraints using SAT;PeerJ Computer Science;2024-01-31

3. Overlapping Community Detection Based on Weak Equiconcept;IEEE Access;2024

4. Identifying Important Concepts in the Concept Lattice Based on Concept Indices;Lecture Notes in Computer Science;2024

5. RD-FCA: A resilient distributed framework for formal concept analysis;Journal of Parallel and Distributed Computing;2023-09

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