{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:08:19Z","timestamp":1750219699192,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":22,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,7,15]],"date-time":"2023-07-15T00:00:00Z","timestamp":1689379200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,7,15]]},"DOI":"10.1145\/3631701.3631706","type":"proceedings-article","created":{"date-parts":[[2024,6,4]],"date-time":"2024-06-04T22:20:28Z","timestamp":1717539628000},"page":"23-27","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Bert-based Federated Learning to Rank Towards News Retrieval"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-0228-3477","authenticated-orcid":false,"given":"Chengtao","family":"Gan","sequence":"first","affiliation":[{"name":"School of Information Science and Technology, Guangdong University of Foreign Studies, China"}]}],"member":"320","published-online":{"date-parts":[[2024,6,4]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Jerry Chun-Wei Lin, and Gautam Srivastava","author":"Ahmed Usman","year":"2023","unstructured":"Usman Ahmed, Jerry Chun-Wei Lin, and Gautam Srivastava. 2023. Semisupervised Federated Learning for Temporal News Hyperpatism Detection. IEEE Transactions on Computational Social Systems (2023)."},{"key":"e_1_3_2_1_2_1","volume-title":"Rank-LIME: Local Model-Agnostic Feature Attribution for Learning to Rank. arXiv preprint arXiv:2212.12722","author":"Chowdhury Tanya","year":"2022","unstructured":"Tanya Chowdhury, Razieh Rahimi, and James Allan. 2022. Rank-LIME: Local Model-Agnostic Feature Attribution for Learning to Rank. arXiv preprint arXiv:2212.12722 (2022)."},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/3331184.3331303"},{"key":"e_1_3_2_1_4_1","volume-title":"Federated learning for ranking browser history suggestions. arXiv preprint arXiv:1911.11807","author":"Hartmann Florian","year":"2019","unstructured":"Florian Hartmann, Sunah Suh, Arkadiusz Komarzewski, Tim\u00a0D Smith, and Ilana Segall. 2019. Federated learning for ranking browser history suggestions. arXiv preprint arXiv:1911.11807 (2019)."},{"key":"e_1_3_2_1_5_1","volume-title":"Cross-lingual information retrieval with BERT. arXiv preprint arXiv:2004.13005","author":"Jiang Zhuolin","year":"2020","unstructured":"Zhuolin Jiang, Amro El-Jaroudi, William Hartmann, Damianos Karakos, and Lingjun Zhao. 2020. Cross-lingual information retrieval with BERT. arXiv preprint arXiv:2004.13005 (2020)."},{"key":"e_1_3_2_1_6_1","volume-title":"Advances and open problems in federated learning. Foundations and Trends\u00ae in Machine Learning 14, 1\u20132","author":"Kairouz Peter","year":"2021","unstructured":"Peter Kairouz, H\u00a0Brendan McMahan, Brendan Avent, Aur\u00e9lien Bellet, Mehdi Bennis, Arjun\u00a0Nitin Bhagoji, Kallista Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, 2021. Advances and open problems in federated learning. Foundations and Trends\u00ae in Machine Learning 14, 1\u20132 (2021), 1\u2013210."},{"key":"e_1_3_2_1_7_1","volume-title":"Privacy-adaptive bert for natural language understanding. arXiv preprint arXiv:2104.07504 190","author":"Qu Chen","year":"2021","unstructured":"Chen Qu, Weize Kong, Liu Yang, Mingyang Zhang, Michael Bendersky, and Marc Najork. 2021. Privacy-adaptive bert for natural language understanding. arXiv preprint arXiv:2104.07504 190 (2021)."},{"key":"e_1_3_2_1_8_1","volume-title":"Artificial Intelligence and Robotics: Proceedings of the 2nd International Conference on Deep Learning, Artificial Intelligence and Robotics,(ICDLAIR)","author":"Ruiz-Mill\u00e1n Jose\u00a0Antonio","year":"2022","unstructured":"Jose\u00a0Antonio Ruiz-Mill\u00e1n, Eugenio Mart\u00ednez-C\u00e1mara, M Victoria\u00a0Luz\u00f3n, and Francisco Herrera. 2022. Personalised Federated Learning with BERT Fine Tuning. Case Study on Twitter Sentiment Analysis. In Advances in Deep Learning, Artificial Intelligence and Robotics: Proceedings of the 2nd International Conference on Deep Learning, Artificial Intelligence and Robotics,(ICDLAIR) 2020. Springer, 193\u2013202."},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/3510033"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM41043.2020.9155494"},{"key":"e_1_3_2_1_11_1","volume-title":"Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval. 2801\u20132813","author":"Wang Shuyi","year":"2022","unstructured":"Shuyi Wang and Guido Zuccon. 2022. Is Non-IID Data a Threat in Federated Online Learning to Rank?. In Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval. 2801\u20132813."},{"key":"e_1_3_2_1_12_1","volume-title":"2021 IEEE 37th International Conference on Data Engineering (ICDE). IEEE, 1128\u20131139","author":"Wang Yansheng","year":"2021","unstructured":"Yansheng Wang, Yongxin Tong, Dingyuan Shi, and Ke Xu. 2021. An efficient approach for cross-silo federated learning to rank. In 2021 IEEE 37th International Conference on Data Engineering (ICDE). IEEE, 1128\u20131139."},{"key":"e_1_3_2_1_13_1","volume-title":"Portfolio-Based Incentive Mechanism Design for Cross-Device Federated Learning. arXiv preprint arXiv:2305.04081","author":"Yang Jiaxi","year":"2023","unstructured":"Jiaxi Yang, Sheng Cao, Cuifang Zhao, Weina Niu, and Li-Chuan Tsai. 2023. Portfolio-Based Incentive Mechanism Design for Cross-Device Federated Learning. arXiv preprint arXiv:2305.04081 (2023)."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/3339474"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2020.2967772"},{"key":"e_1_3_2_1_16_1","first-page":"1035","article-title":"A survey of incentive mechanism design for federated learning","volume":"10","author":"Zhan Yufeng","year":"2021","unstructured":"Yufeng Zhan, Jie Zhang, Zicong Hong, Leijie Wu, Peng Li, and Song Guo. 2021. A survey of incentive mechanism design for federated learning. IEEE Transactions on Emerging Topics in Computing 10, 2 (2021), 1035\u20131044.","journal-title":"IEEE Transactions on Emerging Topics in Computing"},{"key":"e_1_3_2_1_17_1","volume-title":"Federated learning with non-iid data. arXiv preprint arXiv:1806.00582","author":"Zhao Yue","year":"2018","unstructured":"Yue Zhao, Meng Li, Liangzhen Lai, Naveen Suda, Damon Civin, and Vikas Chandra. 2018. Federated learning with non-iid data. arXiv preprint arXiv:1806.00582 (2018)."},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2021.07.098"},{"key":"e_1_3_2_1_19_1","first-page":"625","article-title":"Empirical studies of institutional federated learning for natural language processing","volume":"2020","author":"Zhu Xinghua","year":"2020","unstructured":"Xinghua Zhu, Jianzong Wang, Zhenhou Hong, and Jing Xiao. 2020. Empirical studies of institutional federated learning for natural language processing. In Findings of the Association for Computational Linguistics: EMNLP 2020. 625\u2013634.","journal-title":"Findings of the Association for Computational Linguistics: EMNLP"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/3477495.3531994"},{"key":"e_1_3_2_1_21_1","volume-title":"Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval. 1672\u20131676","author":"Zong Linlin","year":"2021","unstructured":"Linlin Zong, Qiujie Xie, Jiahui Zhou, Peiran Wu, Xianchao Zhang, and Bo Xu. 2021. FedCMR: Federated Cross-Modal Retrieval. In Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval. 1672\u20131676."},{"key":"e_1_3_2_1_22_1","volume-title":"Pretrained Language Models Rankers on Private Data: Is Online and Federated Learning the Solution?","author":"Zuccon Guido","year":"2022","unstructured":"Guido Zuccon. 2022. Pretrained Language Models Rankers on Private Data: Is Online and Federated Learning the Solution? (2022)."}],"event":{"name":"BDET 2023: 2023 5th International Conference on Big Data Engineering and Technology","acronym":"BDET 2023","location":"Singapore Singapore"},"container-title":["2023 5th International Conference on Big Data Engineering and Technology (BDET)"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3631701.3631706","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3631701.3631706","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T16:35:43Z","timestamp":1750178143000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3631701.3631706"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,7,15]]},"references-count":22,"alternative-id":["10.1145\/3631701.3631706","10.1145\/3631701"],"URL":"https:\/\/doi.org\/10.1145\/3631701.3631706","relation":{},"subject":[],"published":{"date-parts":[[2023,7,15]]},"assertion":[{"value":"2024-06-04","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}