乐胖代购免代理版

{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T22:26:36Z","timestamp":1730327196610,"version":"3.28.0"},"publisher-location":"New York, NY, USA","reference-count":29,"publisher":"ACM","funder":[{"name":"Feedzai"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,11,27]]},"DOI":"10.1145\/3604237.3626842","type":"proceedings-article","created":{"date-parts":[[2023,11,25]],"date-time":"2023-11-25T23:09:47Z","timestamp":1700953787000},"page":"176-184","update-policy":"http:\/\/dx.doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["From random-walks to graph-sprints: a low-latency node embedding framework on continuous-time dynamic graphs"],"prefix":"10.1145","author":[{"ORCID":"http:\/\/orcid.org\/0000-0001-9552-3151","authenticated-orcid":false,"given":"Jacopo","family":"Bono","sequence":"first","affiliation":[{"name":"feedzai, PT"}]},{"ORCID":"http:\/\/orcid.org\/0000-0002-6854-4800","authenticated-orcid":false,"given":"Ahmad","family":"Naser Eddin","sequence":"additional","affiliation":[{"name":"Feedzai, PT and Departamento de Ci\u00eancia de Computadores, Faculdade de Ci\u00eancias, Universidade do Porto, Portugal"}]},{"ORCID":"http:\/\/orcid.org\/0000-0001-8250-041X","authenticated-orcid":false,"given":"David","family":"Apar\u00edcio","sequence":"additional","affiliation":[{"name":"Departamento de Ci\u00eancia de Computadores, Faculdade de Ci\u00eancias, Universidade do Porto, PT"}]},{"ORCID":"http:\/\/orcid.org\/0000-0001-8210-2112","authenticated-orcid":false,"given":"Hugo","family":"Ferreira","sequence":"additional","affiliation":[{"name":"Feedzai, PT"}]},{"ORCID":"http:\/\/orcid.org\/0000-0001-6658-2099","authenticated-orcid":false,"given":"Jo\u00e3o Tiago","family":"Ascens\u00e3o","sequence":"additional","affiliation":[{"name":"Feedzai, PT"}]},{"ORCID":"http:\/\/orcid.org\/0000-0002-5768-1383","authenticated-orcid":false,"given":"Pedro","family":"Ribeiro","sequence":"additional","affiliation":[{"name":"Departamento de Ci\u00eancia de Computadores, Faculdade de Ci\u00eancias, Universidade do Porto, Portugal"}]},{"ORCID":"http:\/\/orcid.org\/0000-0001-5281-1970","authenticated-orcid":false,"given":"Pedro","family":"Bizarro","sequence":"additional","affiliation":[{"name":"Feedzai, PT"}]}],"member":"320","published-online":{"date-parts":[[2023,11,25]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330701"},{"volume-title":"Deep coevolutionary network: Embedding user and item features for recommendation. arXiv preprint arXiv:1609.03675","year":"2016","author":"Dai Hanjun","key":"e_1_3_2_1_2_1","unstructured":"Hanjun Dai , Yichen Wang , Rakshit Trivedi , and Le Song . 2016. Deep coevolutionary network: Embedding user and item features for recommendation. arXiv preprint arXiv:1609.03675 ( 2016 ). Hanjun Dai, Yichen Wang, Rakshit Trivedi, and Le Song. 2016. Deep coevolutionary network: Embedding user and item features for recommendation. arXiv preprint arXiv:1609.03675 (2016)."},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"crossref","unstructured":"Wenqi Fan Yao Ma Qing Li Yuan He Eric Zhao Jiliang Tang and Dawei Yin. 2019. Graph neural networks for social recommendation. In The world wide web conference. 417\u2013426. Wenqi Fan Yao Ma Qing Li Yuan He Eric Zhao Jiliang Tang and Dawei Yin. 2019. Graph neural networks for social recommendation. In The world wide web conference. 417\u2013426.","DOI":"10.1145\/3308558.3313488"},{"volume-title":"Fast Graph Representation Learning with PyTorch Geometric. In ICLR Workshop on Representation Learning on Graphs and Manifolds.","year":"2019","author":"Fey Matthias","key":"e_1_3_2_1_4_1","unstructured":"Matthias Fey and Jan\u00a0 E. Lenssen . 2019 . Fast Graph Representation Learning with PyTorch Geometric. In ICLR Workshop on Representation Learning on Graphs and Manifolds. Matthias Fey and Jan\u00a0E. Lenssen. 2019. Fast Graph Representation Learning with PyTorch Geometric. In ICLR Workshop on Representation Learning on Graphs and Manifolds."},{"volume-title":"Dyngem: Deep embedding method for dynamic graphs. arXiv preprint arXiv:1805.11273","year":"2018","author":"Goyal Palash","key":"e_1_3_2_1_5_1","unstructured":"Palash Goyal , Nitin Kamra , Xinran He , and Yan Liu . 2018 . Dyngem: Deep embedding method for dynamic graphs. arXiv preprint arXiv:1805.11273 (2018). Palash Goyal, Nitin Kamra, Xinran He, and Yan Liu. 2018. Dyngem: Deep embedding method for dynamic graphs. arXiv preprint arXiv:1805.11273 (2018)."},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939754"},{"volume-title":"Continuous Temporal Graph Networks for Event-Based Graph Data. arXiv preprint arXiv:2205.15924","year":"2022","author":"Guo Jin","key":"e_1_3_2_1_7_1","unstructured":"Jin Guo , Zhen Han , Zhou Su , Jiliang Li , Volker Tresp , and Yuyi Wang . 2022. Continuous Temporal Graph Networks for Event-Based Graph Data. arXiv preprint arXiv:2205.15924 ( 2022 ). Jin Guo, Zhen Han, Zhou Su, Jiliang Li, Volker Tresp, and Yuyi Wang. 2022. Continuous Temporal Graph Networks for Event-Based Graph Data. arXiv preprint arXiv:2205.15924 (2022)."},{"volume-title":"Joint European Conference on Machine Learning and Knowledge Discovery in Databases. Springer, 483\u2013506","year":"2019","author":"Jin Di","key":"e_1_3_2_1_8_1","unstructured":"Di Jin , Mark Heimann , Ryan\u00a0 A Rossi , and Danai Koutra . 2019 . Node2bits: Compact time-and attribute-aware node representations for user stitching . In Joint European Conference on Machine Learning and Knowledge Discovery in Databases. Springer, 483\u2013506 . Di Jin, Mark Heimann, Ryan\u00a0A Rossi, and Danai Koutra. 2019. Node2bits: Compact time-and attribute-aware node representations for user stitching. In Joint European Conference on Machine Learning and Knowledge Discovery in Databases. Springer, 483\u2013506."},{"volume-title":"From static to dynamic node embeddings. arXiv preprint arXiv:2009.10017","year":"2020","author":"Jin Di","key":"e_1_3_2_1_9_1","unstructured":"Di Jin , Sungchul Kim , Ryan\u00a0 A Rossi , and Danai Koutra . 2020. From static to dynamic node embeddings. arXiv preprint arXiv:2009.10017 ( 2020 ). Di Jin, Sungchul Kim, Ryan\u00a0A Rossi, and Danai Koutra. 2020. From static to dynamic node embeddings. arXiv preprint arXiv:2009.10017 (2020)."},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/3488560.3498428"},{"key":"e_1_3_2_1_11_1","unstructured":"Ming Jin Yuan-Fang Li and Shirui Pan. 2022. Neural Temporal Walks: Motif-Aware Representation Learning on Continuous-Time Dynamic Graphs. In Advances in Neural Information Processing Systems. Ming Jin Yuan-Fang Li and Shirui Pan. 2022. Neural Temporal Walks: Motif-Aware Representation Learning on Continuous-Time Dynamic Graphs. In Advances in Neural Information Processing Systems."},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330895"},{"key":"e_1_3_2_1_13_1","first-page":"931","article-title":"Dynamic node embeddings from edge streams","volume":"5","author":"Lee John\u00a0Boaz","year":"2020","unstructured":"John\u00a0Boaz Lee , Giang Nguyen , Ryan\u00a0 A Rossi , Nesreen\u00a0 K Ahmed , Eunyee Koh , and Sungchul Kim . 2020 . Dynamic node embeddings from edge streams . IEEE Transactions on Emerging Topics in Computational Intelligence 5 , 6 (2020), 931 \u2013 946 . John\u00a0Boaz Lee, Giang Nguyen, Ryan\u00a0A Rossi, Nesreen\u00a0K Ahmed, Eunyee Koh, and Sungchul Kim. 2020. Dynamic node embeddings from edge streams. IEEE Transactions on Emerging Topics in Computational Intelligence 5, 6 (2020), 931\u2013946.","journal-title":"IEEE Transactions on Emerging Topics in Computational Intelligence"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/3184558.3191526"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/2623330.2623732"},{"volume-title":"Temporal Graph Networks for Deep Learning on Dynamic Graphs. In ICML 2020 Workshop on Graph Representation Learning.","year":"2020","author":"Rossi Emanuele","key":"e_1_3_2_1_16_1","unstructured":"Emanuele Rossi , Ben Chamberlain , Fabrizio Frasca , Davide Eynard , Federico Monti , and Michael Bronstein . 2020 . Temporal Graph Networks for Deep Learning on Dynamic Graphs. In ICML 2020 Workshop on Graph Representation Learning. Emanuele Rossi, Ben Chamberlain, Fabrizio Frasca, Davide Eynard, Federico Monti, and Michael Bronstein. 2020. Temporal Graph Networks for Deep Learning on Dynamic Graphs. In ICML 2020 Workshop on Graph Representation Learning."},{"volume-title":"Efficient representation learning using random walks for dynamic graphs. arXiv preprint arXiv:1901.01346","year":"2019","author":"Sajjad Hooman\u00a0Peiro","key":"e_1_3_2_1_17_1","unstructured":"Hooman\u00a0Peiro Sajjad , Andrew Docherty , and Yuriy Tyshetskiy . 2019. Efficient representation learning using random walks for dynamic graphs. arXiv preprint arXiv:1901.01346 ( 2019 ). Hooman\u00a0Peiro Sajjad, Andrew Docherty, and Yuriy Tyshetskiy. 2019. Efficient representation learning using random walks for dynamic graphs. arXiv preprint arXiv:1901.01346 (2019)."},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/3336191.3371845"},{"key":"e_1_3_2_1_19_1","first-page":"32257","article-title":"Provably expressive temporal graph networks","volume":"35","author":"Souza Amauri","year":"2022","unstructured":"Amauri Souza , Diego Mesquita , Samuel Kaski , and Vikas Garg . 2022 . Provably expressive temporal graph networks . Advances in Neural Information Processing Systems 35 (2022), 32257 \u2013 32269 . Amauri Souza, Diego Mesquita, Samuel Kaski, and Vikas Garg. 2022. Provably expressive temporal graph networks. Advances in Neural Information Processing Systems 35 (2022), 32257\u201332269.","journal-title":"Advances in Neural Information Processing Systems"},{"volume-title":"A review on graph neural network methods in financial applications. arXiv preprint arXiv:2111.15367","year":"2021","author":"Wang Jianian","key":"e_1_3_2_1_20_1","unstructured":"Jianian Wang , Sheng Zhang , Yanghua Xiao , and Rui Song . 2021. A review on graph neural network methods in financial applications. arXiv preprint arXiv:2111.15367 ( 2021 ). Jianian Wang, Sheng Zhang, Yanghua Xiao, and Rui Song. 2021. A review on graph neural network methods in financial applications. arXiv preprint arXiv:2111.15367 (2021)."},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10618-021-00774-4"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/3448016.3457564"},{"volume-title":"Inductive representation learning in temporal networks via causal anonymous walks. arXiv preprint arXiv:2101.05974","year":"2021","author":"Wang Yanbang","key":"e_1_3_2_1_23_1","unstructured":"Yanbang Wang , Yen-Yu Chang , Yunyu Liu , Jure Leskovec , and Pan Li. 2021. Inductive representation learning in temporal networks via causal anonymous walks. arXiv preprint arXiv:2101.05974 ( 2021 ). Yanbang Wang, Yen-Yu Chang, Yunyu Liu, Jure Leskovec, and Pan Li. 2021. Inductive representation learning in temporal networks via causal anonymous walks. arXiv preprint arXiv:2101.05974 (2021)."},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3449884"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.2978386"},{"volume-title":"Inductive representation learning on temporal graphs. arXiv preprint arXiv:2002.07962","year":"2020","author":"Xu Da","key":"e_1_3_2_1_26_1","unstructured":"Da Xu , Chuanwei Ruan , Evren Korpeoglu , Sushant Kumar , and Kannan Achan . 2020. Inductive representation learning on temporal graphs. arXiv preprint arXiv:2002.07962 ( 2020 ). Da Xu, Chuanwei Ruan, Evren Korpeoglu, Sushant Kumar, and Kannan Achan. 2020. Inductive representation learning on temporal graphs. arXiv preprint arXiv:2002.07962 (2020)."},{"key":"e_1_3_2_1_27_1","first-page":"5296","article-title":"Streaming graph embeddings via incremental neighborhood sketching","volume":"35","author":"Yang Dingqi","year":"2022","unstructured":"Dingqi Yang , Bingqing Qu , Jie Yang , Liang Wang , and Philippe Cudre-Mauroux . 2022 . Streaming graph embeddings via incremental neighborhood sketching . IEEE Transactions on Knowledge and Data Engineering 35 , 5 (2022), 5296 \u2013 5310 . Dingqi Yang, Bingqing Qu, Jie Yang, Liang Wang, and Philippe Cudre-Mauroux. 2022. Streaming graph embeddings via incremental neighborhood sketching. IEEE Transactions on Knowledge and Data Engineering 35, 5 (2022), 5296\u20135310.","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/3534678.3539300"},{"volume-title":"Graph neural networks and their current applications in bioinformatics. Frontiers in genetics 12","year":"2021","author":"Zhang Xiao-Meng","key":"e_1_3_2_1_29_1","unstructured":"Xiao-Meng Zhang , Li Liang , Lin Liu , and Ming-Jing Tang . 2021. Graph neural networks and their current applications in bioinformatics. Frontiers in genetics 12 ( 2021 ), 690049. Xiao-Meng Zhang, Li Liang, Lin Liu, and Ming-Jing Tang. 2021. Graph neural networks and their current applications in bioinformatics. Frontiers in genetics 12 (2021), 690049."}],"event":{"name":"ICAIF '23: 4th ACM International Conference on AI in Finance","acronym":"ICAIF '23","location":"Brooklyn NY USA"},"container-title":["4th ACM International Conference on AI in Finance"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3604237.3626842","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,27]],"date-time":"2023-11-27T11:21:50Z","timestamp":1701084110000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3604237.3626842"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,11,25]]},"references-count":29,"alternative-id":["10.1145\/3604237.3626842","10.1145\/3604237"],"URL":"https:\/\/doi.org\/10.1145\/3604237.3626842","relation":{},"subject":[],"published":{"date-parts":[[2023,11,25]]},"assertion":[{"value":"2023-11-25","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}