| Open-World Knowledge Graph Completion B Shi, T Weninger AAAI 18, 2017 | 364 | 2017 |
| Proje: Embedding projection for knowledge graph completion B Shi, T Weninger Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 345 | 2017 |
| Discriminative predicate path mining for fact checking in knowledge graphs B Shi, T Weninger Knowledge-Based Systems 104, 123-133, 2016 | 229 | 2016 |
| Neural Tensor Factorization for Temporal Interaction Learning X Wu, B Shi, Y Dong, C Huang, N Chawla The 12th ACM International Conference on Web Search and Data Mining., 2018 | 130* | 2018 |
| Fact checking in heterogeneous information networks B Shi, T Weninger Proceedings of the 25th International Conference Companion on World Wide Web …, 2016 | 108 | 2016 |
| Restful: Resolution-aware forecasting of behavioral time series data X Wu, B Shi, Y Dong, C Huang, L Faust, NV Chawla Proceedings of the 27th ACM International Conference on Information and …, 2018 | 62 | 2018 |
| Performance-adaptive sampling strategy towards fast and accurate graph neural networks M Yoon, T Gervet, B Shi, S Niu, Q He, J Yang Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021 | 44 | 2021 |
| Deep job understanding at linkedin S Li, B Shi, J Yang, J Yan, S Wang, F Chen, Q He Proceedings of the 43rd international ACM SIGIR conference on research and …, 2020 | 43 | 2020 |
| Constructing knowledge graph for social networks in a deep and holistic way Q He, J Yang, B Shi Companion Proceedings of the Web Conference 2020, 307-308, 2020 | 34 | 2020 |
| Salience and Market-aware Skill Extraction for Job Targeting B Shi, J Yang, F Guo, Q He KDD 2020, 2020 | 31 | 2020 |
| Who will attend this event together? Event attendance prediction via deep LSTM networks X Wu, Y Dong, B Shi, A Swami, NV Chawla Proceedings of the 2018 SIAM international conference on data mining, 180-188, 2018 | 20 | 2018 |
| Learning to Ask Screening Questions for Job Postings B Shi, S Li, J Yang, ME Kazdagli, Q He Proceedings of the 43rd International ACM SIGIR Conference on Research and …, 2020 | 17 | 2020 |
| Mining Interesting Meta-Paths from Complex Heterogeneous Information Networks B Shi, T Weninger Data Mining Workshop (ICDMW), 488-495, 2014 | 17 | 2014 |
| Generating a machine-learned model for scoring skills based on feedback from job posters B Shi, F Guo, J Yang, Q He US Patent 11,663,536, 2023 | 11 | 2023 |
| Machine learned model framework for screening question generation B Shi, S Li, J Yang, ME Kazdagli, F Guo, F Chen, Q He US Patent 11,710,070, 2023 | 10 | 2023 |
| Representation Learning in Heterogeneous Professional Social Networks with Ambiguous Social Connections B Shi, J Yang, T Weninger, J How, Q He IEEE BigData, 2019 | 9 | 2019 |
| Forward backward similarity search in knowledge networks B Shi, L Yang, T Weninger Knowledge-Based Systems 119, 20-31, 2017 | 9 | 2017 |
| Similarity-aware network embedding with self-paced learning C Huang, B Shi, X Zhang, X Wu, NV Chawla Proceedings of the 28th ACM International Conference on Information and …, 2019 | 8 | 2019 |
| Machine learning techniques for analyzing textual content B Shi, A Zhu, F Guo, J Yang, F Chen, Q He US Patent 11,487,947, 2022 | 7 | 2022 |
| FairSample: Training fair and accurate graph convolutional neural networks efficiently Z Cong, B Shi, S Li, J Yang, Q He, J Pei IEEE Transactions on Knowledge and Data Engineering 36 (4), 1537-1551, 2023 | 6 | 2023 |
Tim WeningerFrank M. Freimann Collegiate Professor of Engineering at University of Notre DameVerified email at nd.edu
