{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:16:40Z","timestamp":1750220200148,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":36,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,8,14]],"date-time":"2022-08-14T00:00:00Z","timestamp":1660435200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/100000001","name":"NSF (National Science Foundation)","doi-asserted-by":"publisher","award":["IIS-1633271, IIS-2124704, OAC-2106740"],"award-info":[{"award-number":["IIS-1633271, IIS-2124704, OAC-2106740"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,8,14]]},"DOI":"10.1145\/3534678.3539309","type":"proceedings-article","created":{"date-parts":[[2022,8,12]],"date-time":"2022-08-12T19:06:12Z","timestamp":1660331172000},"page":"1109-1119","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["RL2: A Call for Simultaneous Representation Learning and Rule Learning for Graph Streams"],"prefix":"10.1145","author":[{"given":"Qu","family":"Liu","sequence":"first","affiliation":[{"name":"University of Massachusetts, Lowell, Lowell, MA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tingjian","family":"Ge","sequence":"additional","affiliation":[{"name":"University of Massachusetts, Lowell, Lowell, MA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2022,8,14]]},"reference":[{"key":"e_1_3_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.pmcj.2011.09.004"},{"key":"e_1_3_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-36718-3_39"},{"volume-title":"Advances in Neural Information Processing Systems 26. Curran Associates","author":"Bordes Antoine","key":"e_1_3_2_2_3_1","unstructured":"Antoine Bordes, Nicolas Usunier, Alberto Garcia-Duran, Jason Weston, and Oksana Yakhnenko. 2013. Translating Embeddings for Modeling Multi-relational Data. In Advances in Neural Information Processing Systems 26. Curran Associates, Inc."},{"volume-title":"Advanced Lectures on Machine Learning: ML Summer Schools","author":"Bottou L\u00e9on","key":"e_1_3_2_2_4_1","unstructured":"L\u00e9on Bottou. 2004. Stochastic Learning. In Advanced Lectures on Machine Learning: ML Summer Schools. Springer Berlin Heidelberg, 146--168."},{"key":"e_1_3_2_2_5_1","volume-title":"A Comprehensive Survey of Graph Embedding: Problems, Techniques and Applications. CoRR abs\/1709.07604","author":"Cai HongYun","year":"2017","unstructured":"HongYun Cai, Vincent W. Zheng, and Kevin Chen-Chuan Chang. 2017. A Comprehensive Survey of Graph Embedding: Problems, Techniques and Applications. CoRR abs\/1709.07604 (2017). http:\/\/arxiv.org\/abs\/1709.07604"},{"key":"e_1_3_2_2_6_1","volume-title":"M. M. Hamirani, T. Kiran, N. Mehmood, J. Stirling, G. Dunn, and B. Deakin.","author":"Chaudhry I. B.","year":"2013","unstructured":"I. B. Chaudhry, N. Husain, M. O. Husain, J. Hallak, R. Drake, A. Kazmi, R. u. Rahman, M. M. Hamirani, T. Kiran, N. Mehmood, J. Stirling, G. Dunn, and B. Deakin. 2013. Ondansetron and simvastatin added to treatment as usual in patients with schizophrenia: study protocol for a randomized controlled trial. Trials 14 (2013)."},{"key":"e_1_3_2_2_7_1","volume-title":"Thomas","author":"Cover Thomas M.","year":"2006","unstructured":"Thomas M. Cover and Joy A. Thomas. 2006. Elements of Information Theory, 2nd Edition. Wiley.","edition":"2"},{"key":"e_1_3_2_2_8_1","unstructured":"Dataset. 2022. Available at http:\/\/realitycommons.media.mit.edu\/friendsdataset2.html."},{"key":"e_1_3_2_2_9_1","volume-title":"Chew","author":"Fagerstrom Josef","year":"2019","unstructured":"Josef Fagerstrom, Magnus Bang, Daniel Wilhelms, and Michelle S. Chew. 2019. LiSep LSTM: A Machine Learning Algorithm for Early Detection of Septic Shock. Scientific Reports, Nature Research 9, 15132 (2019)."},{"key":"e_1_3_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.12026"},{"key":"e_1_3_2_2_11_1","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"e_1_3_2_2_12_1","volume-title":"Abdullayeva","author":"Imamverdiyev Yadigar N.","year":"2020","unstructured":"Yadigar N. Imamverdiyev and Fargana J. Abdullayeva. 2020. Condition Monitoring of Equipment in Oil Wells using Deep Learning. Advances in Data Science and Adaptive Analysis 12, 1 (2020)."},{"key":"e_1_3_2_2_13_1","unstructured":"Woojeong Jin Meng Qu Xisen Jin and Xiang Ren. 2020. Recurrent Event Network: Autoregressive Structure Inference over Temporal Knowledge Graphs. In EMNLP."},{"key":"e_1_3_2_2_14_1","volume-title":"a freely accessible critical care database. Scientific Data","author":"Johnson AEW","year":"2016","unstructured":"AEW Johnson, TJ Pollard, L Shen, L Lehman, M Feng, M Ghassemi, B Moody, P Szolovits, LA Celi, and RG Mark. 2016. MIMIC-III, a freely accessible critical care database. Scientific Data (2016)."},{"key":"e_1_3_2_2_15_1","volume-title":"Proceedings of the 3rd International Conference on Learning Representations (ICLR","author":"Kingma D.","year":"2015","unstructured":"D. Kingma and J. Ba. 2015. Adam: A Method for Stochastic Optimization. In Proceedings of the 3rd International Conference on Learning Representations (ICLR 2015)."},{"key":"e_1_3_2_2_16_1","volume-title":"Two rival AI approaches combine to let machines learn about the world like a child. MIT Technology Review","author":"Knight Will","year":"2019","unstructured":"Will Knight. 2019. Two rival AI approaches combine to let machines learn about the world like a child. MIT Technology Review (2019)."},{"key":"e_1_3_2_2_17_1","unstructured":"Ninghao Liu Mengnan Du and Xia Hu. 2019. Representation Interpretation with Spatial Encoding and Multimodal Analytics. In WSDM."},{"key":"e_1_3_2_2_18_1","unstructured":"Ninghao Liu Xiao Huang Jundong Li and Xia Hu. 2018. On Interpretation of Network Embedding via Taxonomy Induction. In KDD."},{"key":"e_1_3_2_2_19_1","unstructured":"Jiayuan Mao Chuang Gan Pushmeet Kohli Joshua B. Tenenbaum and Jiajun Wu. 2019. The Neuro-Symbolic Concept Learner: Interpreting Scenes Words and Sentences From Natural Supervision. In ICLR."},{"key":"e_1_3_2_2_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/2627692.2627694"},{"key":"e_1_3_2_2_21_1","unstructured":"S.P. Meyn and R.L. Tweedie. 2012. Markov Chains and Stochastic Stability. Springer London. https:\/\/books.google.com\/books?id=LlTlBwAAQBAJ"},{"key":"e_1_3_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.5555\/117074.117075"},{"volume-title":"Probability and Computing: Randomized Algorithms and Probabilistic Analysis","author":"Mitzenmacher M.","key":"e_1_3_2_2_23_1","unstructured":"M. Mitzenmacher and E.Upfal. 2005. Probability and Computing: Randomized Algorithms and Probabilistic Analysis. Cambridge University Press."},{"key":"e_1_3_2_2_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/1102351.1102430"},{"key":"e_1_3_2_2_25_1","doi-asserted-by":"publisher","DOI":"10.2196\/16374"},{"key":"e_1_3_2_2_26_1","volume-title":"Evaluating the Calibration of Knowledge Graph Embeddings for Trustworthy Link Prediction. In The 2020 Conference on Empirical Methods in Natural Language Processing.","author":"Safavi Tara","year":"2020","unstructured":"Tara Safavi, Danai Koutra, and Edgar Meij. 2020. Evaluating the Calibration of Knowledge Graph Embeddings for Trustworthy Link Prediction. In The 2020 Conference on Empirical Methods in Natural Language Processing."},{"key":"e_1_3_2_2_27_1","unstructured":"Source code. 2022. Available at https:\/\/drive.google.com\/file\/d\/1l3aDHi620yDKgOGKxalZyEqP-MqXFcbC\/view?usp=sharing."},{"key":"e_1_3_2_2_28_1","volume-title":"Probability Calibration FOR KNOWLEDGE GRAPH EMBEDDING MODELS. In The International Conference on Learning Representations (ICLR).","author":"Tabacof Pedro","year":"2020","unstructured":"Pedro Tabacof and Luca Costabello. 2020. Probability Calibration FOR KNOWLEDGE GRAPH EMBEDDING MODELS. In The International Conference on Learning Representations (ICLR)."},{"key":"e_1_3_2_2_29_1","volume-title":"Introduction to Data Mining","author":"Tan Pang-Ning","unstructured":"Pang-Ning Tan, Michael Steinbach, Anuj Karpatne, and Vipin Kumar. 2018. Introduction to Data Mining (2nd ed.). Pearson.","edition":"2"},{"key":"e_1_3_2_2_30_1","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/25.3-4.285"},{"volume-title":"Lagrange multipliers","author":"Vapnyarskii I. B.","key":"e_1_3_2_2_31_1","unstructured":"I. B. Vapnyarskii. 2010. Lagrange multipliers. Springer."},{"key":"e_1_3_2_2_32_1","volume-title":"Graph Attention Networks. ICLR","author":"Velickovic Petar","year":"2018","unstructured":"Petar Velickovic, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Lio, and Yoshua Bengio. 2018. Graph Attention Networks. ICLR (2018)."},{"key":"e_1_3_2_2_33_1","doi-asserted-by":"crossref","unstructured":"XiangWang DingxianWang Canran Xu Xiangnan He Yixin Cao and Tat-Seng Chua. 2019. Explainable Reasoning over Knowledge Graphs for Recommendation. In AAAI.","DOI":"10.1609\/aaai.v33i01.33015329"},{"key":"e_1_3_2_2_34_1","volume-title":"On the Gittins index for multi-armed bandits. Annals of Applied Probability","author":"Weber R.","year":"1992","unstructured":"R. Weber. 1992. On the Gittins index for multi-armed bandits. Annals of Applied Probability (1992)."},{"key":"e_1_3_2_2_35_1","doi-asserted-by":"crossref","unstructured":"P. Wei Y. G. Zhang L. Ling Z. Q. Tao L. Y. Ji J. Bai B. Zong C. Y. Jiang Q. Zhang Q. Fu and X. J. Yang. 2016. Effects of the short-term application of pantoprazole combined with aspirin and clopidogrel in the treatment of acute STEMI. Experimental and therapeutic medicine 12 (2016) 2861--2864.","DOI":"10.3892\/etm.2016.3693"},{"key":"e_1_3_2_2_36_1","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2017.2755684"}],"event":{"name":"KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data"],"location":"Washington DC USA","acronym":"KDD '22"},"container-title":["Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3534678.3539309","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3534678.3539309","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3534678.3539309","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T19:02:47Z","timestamp":1750186967000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3534678.3539309"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,8,14]]},"references-count":36,"alternative-id":["10.1145\/3534678.3539309","10.1145\/3534678"],"URL":"https:\/\/doi.org\/10.1145\/3534678.3539309","relation":{},"subject":[],"published":{"date-parts":[[2022,8,14]]},"assertion":[{"value":"2022-08-14","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}