Discovering Newsworthy Themes from Sequenced Data: A Step Towards Computational Journalism-Reference-Cited by-同舟云学术

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Discovering Newsworthy Themes from Sequenced Data: A Step Towards Computational Journalism

Published:2017-07-01 Issue:7 Volume:29 Page:1398-1411
ISSN:1041-4347
Container-title:IEEE Transactions on Knowledge and Data Engineering
language:
Short-container-title:IEEE Trans. Knowl. Data Eng.

Author:

Fan Qi,Li Yuchen,Zhang Dongxiang,Tan Kian-Lee

Funder

National Nature Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computational Theory and Mathematics,Computer Science Applications,Information Systems

Link

http://xplorestaging.ieee.org/ielx7/69/7938564/07883865.pdf?arnumber=7883865

Cited by 8 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. How to Avoid Jumping to Conclusions: Measuring the Robustness of Outstanding Facts in Knowledge Graphs;Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2024-08-24

2. Enabling Roll-Up and Drill-Down Operations in News Exploration with Knowledge Graphs for Due Diligence and Risk Management;2024 IEEE 40th International Conference on Data Engineering (ICDE);2024-05-13

3. Discovering Personalized Characteristic Communities in Attributed Graphs;2024 IEEE 40th International Conference on Data Engineering (ICDE);2024-05-13

4. Hybrid Regret Minimization: A Submodular Approach;IEEE Transactions on Knowledge and Data Engineering;2023

5. NewsLink: Empowering Intuitive News Search with Knowledge Graphs;2021 IEEE 37th International Conference on Data Engineering (ICDE);2021-04

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