| Aspect-level sentiment analysis based on gradual machine learning Y Wang, Q Chen, J Shen, B Hou, M Ahmed, Z Li Knowledge-Based Systems 212, 106509, 2021 | 48 | 2021 |
| Parallelizing maximal clique and k-plex enumeration over graph data Z Wang, Q Chen, B Hou, B Suo, Z Li, W Pan, ZG Ives Journal of Parallel and Distributed Computing 106, 79-91, 2017 | 48 | 2017 |
| Gradual Machine Learning for Entity Resolution B Hou, Q Chen, Y Wang, Y Nafa, Z Li IEEE Transactions on Knowledge and Data Engineering 34 (4), 1803-1814, 2020 | 34 | 2020 |
| Efficient maximal clique enumeration over graph data B Hou, Z Wang, Q Chen, B Suo, C Fang, Z Li, ZG Ives Data Science and Engineering 1, 219-230, 2016 | 29 | 2016 |
| Towards interpretable and learnable risk analysis for entity resolution Z Chen, Q Chen, B Hou, Z Li, G Li Proceedings of the 2020 ACM SIGMOD international conference on Management of …, 2020 | 23 | 2020 |
| r-HUMO: A Risk-Aware Human-Machine Cooperation Framework for Entity Resolution with Quality Guarantees B Hou, Q Chen, Z Chen, Y Nafa, Z Li IEEE Transactions on Knowledge and Data Engineering 32 (2), 347-359, 2018 | 13 | 2018 |
| Improving machine-based entity resolution with limited human effort: A risk perspective Z Chen, Q Chen, B Hou, M Ahmed, Z Li Proceedings of the International Workshop on Real-Time Business Intelligence …, 2018 | 8 | 2018 |
| Attention-enhanced gradual machine learning for entity resolution P Zhong, Z Li, Q Chen, B Hou IEEE Intelligent Systems 36 (6), 71-79, 2021 | 4 | 2021 |
| Gradual machine learning for aspect-level sentiment analysis Y Wang, Q Chen, J Shen, B Hou, M Ahmed, Z Li arXiv preprint arXiv:1906.02502, 2019 | 3 | 2019 |
| Numerical Markov logic network: A scalable probabilistic framework for hybrid knowledge inference P Zhong, Z Li, Q Chen, B Hou, M Ahmed Information 12 (3), 124, 2021 | 2 | 2021 |
| Adaptive deep learning for entity disambiguation via knowledge-based risk analysis Y Nafa, Q Chen, B Hou, Z Li Expert Systems with Applications 238, 122342, 2024 | 1 | 2024 |
| r-HUMO: A Risk-aware human-machine cooperation framework for entity resolution with quality guarantees (technical report) B Hou, Q Chen, Z Chen, Y Nafa, LZ Li tech. rep., 2018. http://www. wowbigdata. com. cn/r-HUMO/r-HUMO-technical …, 2018 | 1 | 2018 |
| Enabling temporal reasoning for fact statements: a web-based approad (Technical report) B Hou, Y Nafa Technical report, 2018 | 1 | 2018 |
| Improving the Results of Machine-based Entity Resolution with Limited Human Effort: A Risk Perspective Z Chen, Q Chen, B Hou, MHM Ahmed, Z Li CoRR, 2018 | 1 | 2018 |
| 人工智能风险分析技术研究进展 陈群， 陈肇强， 侯博议， 王丽娟， 罗雨晨， 李战怀 大数据 6 (1), 47-59, 2020 | | 2020 |
| Gradual machine learning for aspect-level sentiment analysis. under review Y Wang, Q Chen, J Shen, B Hou, M Ahmed, Z Li | | 2019 |
| Enabling Temporal Reasoning for Fact Statements: A Web-Based Approach B Hou, Y Nafa Database Systems for Advanced Applications: DASFAA 2018 International …, 2018 | | 2018 |
| i-HUMO: An Interactive Human and Machine Cooperation Framework for Entity Resolution with Quality Guarantees B Hou, Q Chen, Z Chen, Y Nafa, Z Li CoRR, 2018 | | 2018 |