| Efficient joinable table discovery in data lakes: A high-dimensional similarity-based approach Y Dong, K Takeoka, C Xiao, M Oyamada International Conference on Data Engineering (ICDE), 456-467, 2021 | 95 | 2021 |
| Meimei: An efficient probabilistic approach for semantically annotating tables K Takeoka, M Oyamada, S Nakadai, T Okadome AAAI Conference on Artificial Intelligence (AAAI) 33 (01), 281-288, 2019 | 59 | 2019 |
| Jellyfish: Instruction-Tuning Local Large Language Models for Data Preprocessing H Zhang, Y Dong, C Xiao, M Oyamada Empirical Methods in Natural Language Processing (EMNLP), 8754-8782, 2024 | 49* | 2024 |
| Deepjoin: Joinable table discovery with pre-trained language models Y Dong, C Xiao, T Nozawa, M Enomoto, M Oyamada VLDB, 2022 | 34 | 2022 |
| Low-resource taxonomy enrichment with pretrained language models K Takeoka, K Akimoto, M Oyamada Empirical Methods in Natural Language Processing (EMNLP), 2747-2758, 2021 | 32 | 2021 |
| Relational Mixture of Experts: Explainable Demographics Prediction with Behavioral Data M Oyamada, S Nakadai IEEE International Conference on Data Mining (ICDM), 357-366, 2017 | 24* | 2017 |
| Data Stream Processing with Concurrency Control M Oyamada, H Kawashima, H Kitagawa ACM SIGAPP Applied Computing Review 13 (2), 54-65, 2013 | 17* | 2013 |
| Continuous top-k spatial–keyword search on dynamic objects Y Dong, C Xiao, H Chen, JX Yu, K Takeoka, M Oyamada, H Kitagawa The VLDB Journal 30 (2), 141-161, 2021 | 16 | 2021 |
| Extracting feature engineering knowledge from data science notebooks M Oyamada IEEE International Conference on Big Data (Big Data), 6172-6173, 2019 | 14 | 2019 |
| Table enrichment system for machine learning Y Dong, M Oyamada Conference on Research and Development in Information Retrieval (SIGIR …, 2022 | 13 | 2022 |
| Learning with unsure responses K Takeoka, Y Dong, M Oyamada AAAI Conference on Artificial Intelligence (AAAI) 34 (01), 230-237, 2020 | 11 | 2020 |
| Data processing device, data processing method, and recording medium M Oyamada US Patent 10,621,173, 2020 | 9* | 2020 |
| Table-meaning estimation system, method, and program H Sato, M Oyamada, S Nakadai US Patent 11,062,213, 2021 | 7 | 2021 |
| Context Quality Matters in Training Fusion-in-Decoder for Extractive Open-Domain Question Answering K Akimoto, K Takeoka, M Oyamada Findings of Empirical Methods in Natural Language Processing (EMNLP Findings), 2023 | 5 | 2023 |
| User Identity Linkage for Different Behavioral Patterns across Domains G Kusano, M Oyamada AAAI Conference on Web and Social Media (ICWSM) 15, 351-360, 2021 | 4 | 2021 |
| Compressed Vector Set: A Fast and Space-Efficient Data Mining Framework M Oyamada, J Liu, S Ito, K Narita, T Araki, H Kitagawa Journal of information processing 26, 416-426, 2018 | 4* | 2018 |
| QA-Matcher: Unsupervised Entity Matching Using a Question Answering Model S Hayashi, Y Dong, M Oyamada Pacific-Asia Conference on Knowledge Discovery and Data Mining, 174-185, 2023 | 2 | 2023 |
| Clustering system, method, and program, and recommendation system K Tomobe, M Oyamada, S Nakadai US Patent 10,614,505, 2020 | 2 | 2020 |
| Information processing apparatus, classification method, and storage medium M Oyamada US Patent App. 18/274,449, 2024 | 1 | 2024 |
| Information processing apparatus, analysis method, and storage medium T Nozawa, M Oyamada, Y Dong, G Kusano US Patent App. 18/266,745, 2024 | 1 | 2024 |
Yuyang DongNEC Corporation, Research Labs, JapanVerified email at nec.com
