{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T16:34:11Z","timestamp":1778258051341,"version":"3.51.4"},"publisher-location":"New York, NY, USA","reference-count":62,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,7,6]],"date-time":"2022-07-06T00:00:00Z","timestamp":1657065600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Innovation Research Team of Ministry of Education","award":["IRT_17R86"],"award-info":[{"award-number":["IRT_17R86"]}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2020AAA0108800"],"award-info":[{"award-number":["2020AAA0108800"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012456","name":"National Social Science Fund of China","doi-asserted-by":"publisher","award":["18XXW005"],"award-info":[{"award-number":["18XXW005"]}],"id":[{"id":"10.13039\/501100012456","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62137002"],"award-info":[{"award-number":["62137002"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["2020M683493"],"award-info":[{"award-number":["2020M683493"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["xzy022021048"],"award-info":[{"award-number":["xzy022021048"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Innovative Research Group of the National Natural Science Foundation of China","award":["61721002"],"award-info":[{"award-number":["61721002"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,7,6]]},"DOI":"10.1145\/3477495.3531996","type":"proceedings-article","created":{"date-parts":[[2022,7,7]],"date-time":"2022-07-07T15:12:13Z","timestamp":1657206733000},"page":"893-903","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":49,"title":["Incorporating Context Graph with Logical Reasoning for Inductive Relation Prediction"],"prefix":"10.1145","author":[{"given":"Qika","family":"Lin","sequence":"first","affiliation":[{"name":"Xi'an Jiaotong University, Xi'an, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jun","family":"Liu","sequence":"additional","affiliation":[{"name":"National Engineering Lab for Big Data Analytics, Xi'an, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fangzhi","family":"Xu","sequence":"additional","affiliation":[{"name":"Xi'an Jiaotong University, Xi'an, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yudai","family":"Pan","sequence":"additional","affiliation":[{"name":"Xi'an Jiaotong University, Xi'an, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yifan","family":"Zhu","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lingling","family":"Zhang","sequence":"additional","affiliation":[{"name":"Xi'an Jiaotong University, Xi'an, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tianzhe","family":"Zhao","sequence":"additional","affiliation":[{"name":"Xi'an Jiaotong University, Xi'an, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2022,7,7]]},"reference":[{"key":"e_1_3_2_2_1_1","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence (AAAI). 15985--15987","author":"Abdelaziz Ibrahim","unstructured":"Ibrahim Abdelaziz , Srinivas Ravishankar , Pavan Kapanipathi , Salim Roukos , and Alexander G. Gray . 2021. A Semantic Parsing and Reasoning-Based Approach to Knowledge Base Question Answering . In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI). 15985--15987 . Ibrahim Abdelaziz, Srinivas Ravishankar, Pavan Kapanipathi, Salim Roukos, and Alexander G. Gray. 2021. A Semantic Parsing and Reasoning-Based Approach to Knowledge Base Question Answering. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI). 15985--15987."},{"key":"e_1_3_2_2_2_1","volume-title":"International Semantic Web Conference (ISWC) and Asian Semantic Web Conference (ASWC)","volume":"4825","author":"Auer S\u00f6ren","unstructured":"S\u00f6ren Auer , Christian Bizer , Georgi Kobilarov , Jens Lehmann , Richard Cyganiak , and Zachary G. Ives . 2007. DBpedia: A Nucleus for a Web of Open Data . In International Semantic Web Conference (ISWC) and Asian Semantic Web Conference (ASWC) , Vol. 4825 . 722--735. S\u00f6ren Auer, Christian Bizer, Georgi Kobilarov, Jens Lehmann, Richard Cyganiak, and Zachary G. Ives. 2007. DBpedia: A Nucleus for a Web of Open Data. In International Semantic Web Conference (ISWC) and Asian Semantic Web Conference (ASWC), Vol. 4825. 722--735."},{"key":"e_1_3_2_2_3_1","volume-title":"Dong Bok Lee, and Sung Ju Hwang","author":"Baek Jinheon","year":"2020","unstructured":"Jinheon Baek , Dong Bok Lee, and Sung Ju Hwang . 2020 . Learning to Extrapolate Knowledge : Transductive Few-shot Out-of-Graph Link Prediction. In Advances in Neural Information Processing Systems (NeurIPS) . Jinheon Baek, Dong Bok Lee, and Sung Ju Hwang. 2020. Learning to Extrapolate Knowledge: Transductive Few-shot Out-of-Graph Link Prediction. In Advances in Neural Information Processing Systems (NeurIPS)."},{"key":"e_1_3_2_2_4_1","volume-title":"Jacob C. Walker, Tim Scholtes, Jovana Mitrovic, and Charles Blundell.","author":"Banino Andrea","year":"2021","unstructured":"Andrea Banino , Adri\u00e0 Puigdom\u00e8 nech Badia , Jacob C. Walker, Tim Scholtes, Jovana Mitrovic, and Charles Blundell. 2021 . CoBERL: Contrastive BERT for Reinforcement Learning. CoRR , Vol. abs\/ 2107 .05431 (2021). Andrea Banino, Adri\u00e0 Puigdom\u00e8 nech Badia, Jacob C. Walker, Tim Scholtes, Jovana Mitrovic, and Charles Blundell. 2021. CoBERL: Contrastive BERT for Reinforcement Learning. CoRR, Vol. abs\/2107.05431 (2021)."},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/1376616.1376746"},{"key":"e_1_3_2_2_6_1","unstructured":"Antoine Bordes Nicolas Usunier Alberto Garc\u00eda-Dur\u00e1n Jason Weston and Oksana Yakhnenko. 2013. Translating Embeddings for Modeling Multi-relational Data. In Advances in Neural Information Processing Systems (NeurIPS). 2787--2795.  Antoine Bordes Nicolas Usunier Alberto Garc\u00eda-Dur\u00e1n Jason Weston and Oksana Yakhnenko. 2013. Translating Embeddings for Modeling Multi-relational Data. In Advances in Neural Information Processing Systems (NeurIPS). 2787--2795."},{"key":"e_1_3_2_2_7_1","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence (AAAI). 6271--6278","author":"Chen Jiajun","year":"2021","unstructured":"Jiajun Chen , Huarui He , Feng Wu , and Jie Wang . 2021 . Topology-Aware Correlations Between Relations for Inductive Link Prediction in Knowledge Graphs . In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI). 6271--6278 . Jiajun Chen, Huarui He, Feng Wu, and Jie Wang. 2021. Topology-Aware Correlations Between Relations for Inductive Link Prediction in Knowledge Graphs. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI). 6271--6278."},{"key":"e_1_3_2_2_8_1","volume-title":"Exploring Simple Siamese Representation Learning. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Computer Vision Foundation \/ IEEE, 15750--15758","author":"Chen Xinlei","year":"2021","unstructured":"Xinlei Chen and Kaiming He . 2021 . Exploring Simple Siamese Representation Learning. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Computer Vision Foundation \/ IEEE, 15750--15758 . Xinlei Chen and Kaiming He. 2021. Exploring Simple Siamese Representation Learning. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Computer Vision Foundation \/ IEEE, 15750--15758."},{"key":"e_1_3_2_2_9_1","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/D14-1179"},{"key":"e_1_3_2_2_10_1","volume-title":"Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling. CoRR","author":"Chung Junyoung","year":"2014","unstructured":"Junyoung Chung , \u00c7aglar G\u00fcl\u00e7ehre , KyungHyun Cho , and Yoshua Bengio . 2014. Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling. CoRR , Vol. abs\/ 1412 .3555 ( 2014 ). Junyoung Chung, \u00c7aglar G\u00fcl\u00e7ehre, KyungHyun Cho, and Yoshua Bengio. 2014. Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling. CoRR, Vol. abs\/1412.3555 (2014)."},{"key":"e_1_3_2_2_11_1","volume-title":"TensorLog: A Differentiable Deductive Database. CoRR","author":"Cohen William W.","year":"2016","unstructured":"William W. Cohen . 2016. TensorLog: A Differentiable Deductive Database. CoRR , Vol. abs\/ 1605 .06523 ( 2016 ). William W. Cohen. 2016. TensorLog: A Differentiable Deductive Database. CoRR, Vol. abs\/1605.06523 (2016)."},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"crossref","unstructured":"Tim Dettmers Pasquale Minervini Pontus Stenetorp and Sebastian Riedel. 2018. Convolutional 2D Knowledge Graph Embeddings. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI) the innovative Applications of Artificial Intelligence (IAAI) and the AAAI Symposium on Educational Advances in Artificial Intelligence (EAAI). 1811--1818.  Tim Dettmers Pasquale Minervini Pontus Stenetorp and Sebastian Riedel. 2018. Convolutional 2D Knowledge Graph Embeddings. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI) the innovative Applications of Artificial Intelligence (IAAI) and the AAAI Symposium on Educational Advances in Artificial Intelligence (EAAI). 1811--1818.","DOI":"10.1609\/aaai.v32i1.11573"},{"key":"e_1_3_2_2_13_1","volume-title":"A Mathematical Introduction to Logic","author":"Enderton Herbert B","unstructured":"Herbert B Enderton . 2001. A Mathematical Introduction to Logic . Elsevier . Herbert B Enderton. 2001. A Mathematical Introduction to Logic. Elsevier."},{"key":"e_1_3_2_2_14_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00778-015-0394-1"},{"key":"e_1_3_2_2_15_1","volume-title":"Suchanek","author":"Gal\u00e1rraga Luis Antonio","year":"2013","unstructured":"Luis Antonio Gal\u00e1rraga , Christina Teflioudi , Katja Hose , and Fabian M . Suchanek . 2013 . AMIE : Association Rule Mining under Incomplete Evidence in Ontological Knowledge Bases. In The World Wide Web Conference (WWW). 413--422. Luis Antonio Gal\u00e1rraga, Christina Teflioudi, Katja Hose, and Fabian M. Suchanek. 2013. AMIE: Association Rule Mining under Incomplete Evidence in Ontological Knowledge Bases. In The World Wide Web Conference (WWW). 413--422."},{"key":"e_1_3_2_2_16_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.acl-long.359"},{"key":"e_1_3_2_2_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.2992393"},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.findings-acl.223"},{"key":"e_1_3_2_2_19_1","volume-title":"Adam: A Method for Stochastic Optimization. In International Conference on Learning Representations (ICLR).","author":"Diederik","unstructured":"Diederik P. Kingma and Jimmy Ba. 2015 . Adam: A Method for Stochastic Optimization. In International Conference on Learning Representations (ICLR). Diederik P. Kingma and Jimmy Ba. 2015. Adam: A Method for Stochastic Optimization. In International Conference on Learning Representations (ICLR)."},{"key":"e_1_3_2_2_20_1","volume-title":"DRGI: Deep Relational Graph Infomax for Knowledge Graph Completion","author":"Liang Shuang","year":"2021","unstructured":"Shuang Liang , Jie Shao , Dongyang Zhang , Jiasheng Zhang , and Bin Cui . 2021 . DRGI: Deep Relational Graph Infomax for Knowledge Graph Completion . IEEE Transactions on Knowledge and Data Engineering (TKDE) ( 2021). Shuang Liang, Jie Shao, Dongyang Zhang, Jiasheng Zhang, and Bin Cui. 2021. DRGI: Deep Relational Graph Infomax for Knowledge Graph Completion. IEEE Transactions on Knowledge and Data Engineering (TKDE) (2021)."},{"key":"e_1_3_2_2_21_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2021.06.040"},{"key":"e_1_3_2_2_22_1","volume-title":"2021 b. Contrastive Graph Representations for Logical Formulas Embedding","author":"Lin Qika","year":"2021","unstructured":"Qika Lin , Jun Liu , Lingling Zhang , Yudai Pan , Xin Hu , Fangzhi Xu , and Hongwei Zeng . 2021 b. Contrastive Graph Representations for Logical Formulas Embedding . IEEE Transactions on Knowledge and Data Engineering ( 2021 ). Qika Lin, Jun Liu, Lingling Zhang, Yudai Pan, Xin Hu, Fangzhi Xu, and Hongwei Zeng. 2021 b. Contrastive Graph Representations for Logical Formulas Embedding. IEEE Transactions on Knowledge and Data Engineering (2021)."},{"key":"e_1_3_2_2_23_1","volume-title":"Proceedings of the Annual Meeting of the Association for Computational Linguistics and the International Joint Conference on Natural Language Processing (ACL\/IJCNLP). 1016--1029","author":"Lovelace Justin","unstructured":"Justin Lovelace , Denis Newman-Griffis , Shikhar Vashishth , Jill Fain Lehman , and Carolyn P. Ros\u00e9 . 2021. Robust Knowledge Graph Completion with Stacked Convolutions and a Student Re-Ranking Network . In Proceedings of the Annual Meeting of the Association for Computational Linguistics and the International Joint Conference on Natural Language Processing (ACL\/IJCNLP). 1016--1029 . Justin Lovelace, Denis Newman-Griffis, Shikhar Vashishth, Jill Fain Lehman, and Carolyn P. Ros\u00e9. 2021. Robust Knowledge Graph Completion with Stacked Convolutions and a Student Re-Ranking Network. In Proceedings of the Annual Meeting of the Association for Computational Linguistics and the International Joint Conference on Natural Language Processing (ACL\/IJCNLP). 1016--1029."},{"key":"e_1_3_2_2_24_1","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence (AAAI). 4294--4302","author":"Mai Sijie","year":"2021","unstructured":"Sijie Mai , Shuangjia Zheng , Yuedong Yang , and Haifeng Hu . 2021 . Communicative Message Passing for Inductive Relation Reasoning . In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI). 4294--4302 . Sijie Mai, Shuangjia Zheng, Yuedong Yang, and Haifeng Hu. 2021. Communicative Message Passing for Inductive Relation Reasoning. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI). 4294--4302."},{"key":"e_1_3_2_2_25_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-00671-6_1"},{"key":"e_1_3_2_2_26_1","volume-title":"Hinton","author":"Neal Radford M.","year":"1998","unstructured":"Radford M. Neal and Geoffrey E . Hinton . 1998 . A View of the Em Algorithm that Justifies Incremental, Sparse, and other Variants. In Learning in Graphical Models. NATO ASI Series, Vol. 89 . Springer Netherlands , 355--368. Radford M. Neal and Geoffrey E. Hinton. 1998. A View of the Em Algorithm that Justifies Incremental, Sparse, and other Variants. In Learning in Graphical Models. NATO ASI Series, Vol. 89. Springer Netherlands, 355--368."},{"key":"e_1_3_2_2_27_1","volume-title":"Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI). 2149--2155","author":"Omran Pouya Ghiasnezhad","year":"2018","unstructured":"Pouya Ghiasnezhad Omran , Kewen Wang , and Zhe Wang . 2018 . Scalable Rule Learning via Learning Representation . In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI). 2149--2155 . Pouya Ghiasnezhad Omran, Kewen Wang, and Zhe Wang. 2018. Scalable Rule Learning via Learning Representation. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI). 2149--2155."},{"key":"e_1_3_2_2_28_1","volume-title":"Learning First-Order Rules with Relational Path Contrast for Inductive Relation Reasoning. CoRR","author":"Pan Yudai","year":"2021","unstructured":"Yudai Pan , Jun Liu , Lingling Zhang , Xin Hu , Tianzhe Zhao , and Qika Lin . 2021. Learning First-Order Rules with Relational Path Contrast for Inductive Relation Reasoning. CoRR , Vol. abs\/ 2110 .08810 ( 2021 ). Yudai Pan, Jun Liu, Lingling Zhang, Xin Hu, Tianzhe Zhao, and Qika Lin. 2021. Learning First-Order Rules with Relational Path Contrast for Inductive Relation Reasoning. CoRR, Vol. abs\/2110.08810 (2021)."},{"key":"e_1_3_2_2_29_1","volume-title":"Estimating the Cost of Knowledge Graph Creation. In Proceedings of the International Semantic Web Conference (ISWC) (CEUR Workshop Proceedings","author":"Paulheim Heiko","year":"2018","unstructured":"Heiko Paulheim . 2018 . How much is a Triple ? Estimating the Cost of Knowledge Graph Creation. In Proceedings of the International Semantic Web Conference (ISWC) (CEUR Workshop Proceedings , Vol. 2180). Heiko Paulheim. 2018. How much is a Triple? Estimating the Cost of Knowledge Graph Creation. In Proceedings of the International Semantic Web Conference (ISWC) (CEUR Workshop Proceedings, Vol. 2180)."},{"key":"e_1_3_2_2_30_1","doi-asserted-by":"publisher","DOI":"10.1016\/0004-3702(93)90061-F"},{"key":"e_1_3_2_2_31_1","volume-title":"RNNLogic: Learning Logic Rules for Reasoning on Knowledge Graphs. In International Conference on Learning Representations (ICLR).","author":"Qu Meng","year":"2021","unstructured":"Meng Qu , Junkun Chen , Louis-Pascal A. C. Xhonneux , Yoshua Bengio , and Jian Tang . 2021 . RNNLogic: Learning Logic Rules for Reasoning on Knowledge Graphs. In International Conference on Learning Representations (ICLR). Meng Qu, Junkun Chen, Louis-Pascal A. C. Xhonneux, Yoshua Bengio, and Jian Tang. 2021. RNNLogic: Learning Logic Rules for Reasoning on Knowledge Graphs. In International Conference on Learning Representations (ICLR)."},{"key":"e_1_3_2_2_32_1","unstructured":"Meng Qu and Jian Tang. 2019. Probabilistic Logic Neural Networks for Reasoning. In Advances in Neural Information Processing Systems (NeurIPS). 7710--7720.  Meng Qu and Jian Tang. 2019. Probabilistic Logic Neural Networks for Reasoning. In Advances in Neural Information Processing Systems (NeurIPS). 7710--7720."},{"key":"e_1_3_2_2_33_1","doi-asserted-by":"publisher","DOI":"10.1162\/tacl_a_00332"},{"key":"e_1_3_2_2_34_1","volume-title":"Markov Logic Networks. Machine learning","author":"Richardson Matthew","year":"2006","unstructured":"Matthew Richardson and Pedro Domingos . 2006. Markov Logic Networks. Machine learning , Vol. 62 , 1--2 ( 2006 ), 107--136. Matthew Richardson and Pedro Domingos. 2006. Markov Logic Networks. Machine learning, Vol. 62, 1--2 (2006), 107--136."},{"key":"e_1_3_2_2_35_1","volume-title":"DRUM: End-To-End Differentiable Rule Mining On Knowledge Graphs. In Advances in Neural Information Processing Systems (NeurIPS). 15321--15331.","author":"Sadeghian Ali","year":"2019","unstructured":"Ali Sadeghian , Mohammadreza Armandpour , Patrick Ding , and Daisy Zhe Wang . 2019 . DRUM: End-To-End Differentiable Rule Mining On Knowledge Graphs. In Advances in Neural Information Processing Systems (NeurIPS). 15321--15331. Ali Sadeghian, Mohammadreza Armandpour, Patrick Ding, and Daisy Zhe Wang. 2019. DRUM: End-To-End Differentiable Rule Mining On Knowledge Graphs. In Advances in Neural Information Processing Systems (NeurIPS). 15321--15331."},{"key":"e_1_3_2_2_36_1","volume-title":"Modeling Relational Data with Graph Convolutional Networks. In European Semantic Web Conference (ESWC). 593--607","author":"Schlichtkrull Michael Sejr","unstructured":"Michael Sejr Schlichtkrull , Thomas N. Kipf , Peter Bloem , Rianne van den Berg, Ivan Titov, and Max Welling. 2018 . Modeling Relational Data with Graph Convolutional Networks. In European Semantic Web Conference (ESWC). 593--607 . Michael Sejr Schlichtkrull, Thomas N. Kipf, Peter Bloem, Rianne van den Berg, Ivan Titov, and Max Welling. 2018. Modeling Relational Data with Graph Convolutional Networks. In European Semantic Web Conference (ESWC). 593--607."},{"key":"e_1_3_2_2_37_1","volume-title":"The Evidential Foundations of Probabilistic Reasoning","author":"Schum David A","unstructured":"David A Schum . 2001. The Evidential Foundations of Probabilistic Reasoning . Northwestern University Press . David A Schum. 2001. The Evidential Foundations of Probabilistic Reasoning. Northwestern University Press."},{"key":"e_1_3_2_2_38_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33013060"},{"key":"e_1_3_2_2_39_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11535"},{"key":"e_1_3_2_2_40_1","doi-asserted-by":"publisher","DOI":"10.1016\/0004-3702(73)90006-4"},{"key":"e_1_3_2_2_41_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2020\/392"},{"key":"e_1_3_2_2_42_1","doi-asserted-by":"publisher","DOI":"10.1145\/1242572.1242667"},{"key":"e_1_3_2_2_43_1","volume-title":"International Conference on Machine Learning (ICML). 9448--9457","author":"Teru Komal K.","year":"2020","unstructured":"Komal K. Teru , Etienne Denis , and Will Hamilton . 2020 . Inductive Relation Prediction by Subgraph Reasoning . In International Conference on Machine Learning (ICML). 9448--9457 . Komal K. Teru, Etienne Denis, and Will Hamilton. 2020. Inductive Relation Prediction by Subgraph Reasoning. In International Conference on Machine Learning (ICML). 9448--9457."},{"key":"e_1_3_2_2_44_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D15-1174"},{"key":"e_1_3_2_2_45_1","volume-title":"Complex Embeddings for Simple Link Prediction. In International Conference on Machine Learning (ICML)","volume":"48","author":"Trouillon Th\u00e9o","year":"2016","unstructured":"Th\u00e9o Trouillon , Johannes Welbl , Sebastian Riedel , \u00c9ric Gaussier , and Guillaume Bouchard . 2016 . Complex Embeddings for Simple Link Prediction. In International Conference on Machine Learning (ICML) , Vol. 48 . 2071--2080. Th\u00e9o Trouillon, Johannes Welbl, Sebastian Riedel, \u00c9ric Gaussier, and Guillaume Bouchard. 2016. Complex Embeddings for Simple Link Prediction. In International Conference on Machine Learning (ICML), Vol. 48. 2071--2080."},{"key":"e_1_3_2_2_46_1","article-title":"Visualizing Data Using t-SNE","volume":"9","author":"der Maaten Laurens Van","year":"2008","unstructured":"Laurens Van der Maaten and Geoffrey Hinton . 2008 . Visualizing Data Using t-SNE . Journal of Machine Learning Research (JMLR) , Vol. 9 , 11 (2008). Laurens Van der Maaten and Geoffrey Hinton. 2008. Visualizing Data Using t-SNE. Journal of Machine Learning Research (JMLR), Vol. 9, 11 (2008).","journal-title":"Journal of Machine Learning Research (JMLR)"},{"key":"e_1_3_2_2_47_1","volume-title":"Probabilistic Logic Graph Attention Networks for Reasoning. In The World Wide Web Conference (WWW). 669--673","author":"Vardhan L. Vivek Harsha","year":"2020","unstructured":"L. Vivek Harsha Vardhan , Guo Jia , and Stanley Kok . 2020 . Probabilistic Logic Graph Attention Networks for Reasoning. In The World Wide Web Conference (WWW). 669--673 . L. Vivek Harsha Vardhan, Guo Jia, and Stanley Kok. 2020. Probabilistic Logic Graph Attention Networks for Reasoning. In The World Wide Web Conference (WWW). 669--673."},{"key":"e_1_3_2_2_48_1","volume-title":"Composition-based Multi-Relational Graph Convolutional Networks. In International Conference on Learning Representations (ICLR).","author":"Vashishth Shikhar","unstructured":"Shikhar Vashishth , Soumya Sanyal , Vikram Nitin , and Partha P. Talukdar . 2020 . Composition-based Multi-Relational Graph Convolutional Networks. In International Conference on Learning Representations (ICLR). Shikhar Vashishth, Soumya Sanyal, Vikram Nitin, and Partha P. Talukdar. 2020. Composition-based Multi-Relational Graph Convolutional Networks. In International Conference on Learning Representations (ICLR)."},{"key":"e_1_3_2_2_49_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.findings-acl.171"},{"key":"e_1_3_2_2_50_1","volume-title":"Proceedings of the 21st World Wide Web Conference (WWW). 1063--1064","author":"Vrandecic Denny","year":"2012","unstructured":"Denny Vrandecic . 2012 . Wikidata: A New Platform for Collaborative Data Collection . In Proceedings of the 21st World Wide Web Conference (WWW). 1063--1064 . Denny Vrandecic. 2012. Wikidata: A New Platform for Collaborative Data Collection. In Proceedings of the 21st World Wide Web Conference (WWW). 1063--1064."},{"key":"e_1_3_2_2_51_1","volume-title":"Knowledge Graph Convolutional Networks for Recommender Systems. In The World Wide Web Conference (WWW). ACM, 3307--3313","author":"Wang Hongwei","year":"2019","unstructured":"Hongwei Wang , Miao Zhao , Xing Xie , Wenjie Li , and Minyi Guo . 2019 b . Knowledge Graph Convolutional Networks for Recommender Systems. In The World Wide Web Conference (WWW). ACM, 3307--3313 . Hongwei Wang, Miao Zhao, Xing Xie, Wenjie Li, and Minyi Guo. 2019 b. Knowledge Graph Convolutional Networks for Recommender Systems. In The World Wide Web Conference (WWW). ACM, 3307--3313."},{"key":"e_1_3_2_2_52_1","volume-title":"2019 a","author":"Wang Minjie","year":"2019","unstructured":"Minjie Wang , Lingfan Yu , Da Zheng , Quan Gan , Yu Gai , Zihao Ye , Mufei Li , Jinjing Zhou , Qi Huang , Chao Ma , Ziyue Huang , Qipeng Guo , Hao Zhang , Haibin Lin , Junbo Zhao , Jinyang Li , Alexander J. Smola , and Zheng Zhang . 2019 a . Deep Graph Library : Towards Efficient and Scalable Deep Learning on Graphs. CoRR, Vol. abs\/ 1909 .01315 ( 2019 ). Minjie Wang, Lingfan Yu, Da Zheng, Quan Gan, Yu Gai, Zihao Ye, Mufei Li, Jinjing Zhou, Qi Huang, Chao Ma, Ziyue Huang, Qipeng Guo, Hao Zhang, Haibin Lin, Junbo Zhao, Jinyang Li, Alexander J. Smola, and Zheng Zhang. 2019 a. Deep Graph Library: Towards Efficient and Scalable Deep Learning on Graphs. CoRR, Vol. abs\/1909.01315 (2019)."},{"key":"e_1_3_2_2_53_1","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3450133"},{"key":"e_1_3_2_2_54_1","doi-asserted-by":"publisher","DOI":"10.5555\/2893873.2894046"},{"key":"e_1_3_2_2_55_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D17-1060"},{"key":"e_1_3_2_2_56_1","volume-title":"Embedding Entities and Relations for Learning and Inference in Knowledge Bases. In International Conference on Learning Representations (ICLR).","author":"Yang Bishan","year":"2015","unstructured":"Bishan Yang , Wen-tau Yih, Xiaodong He , Jianfeng Gao , and Li Deng . 2015 . Embedding Entities and Relations for Learning and Inference in Knowledge Bases. In International Conference on Learning Representations (ICLR). Bishan Yang, Wen-tau Yih, Xiaodong He, Jianfeng Gao, and Li Deng. 2015. Embedding Entities and Relations for Learning and Inference in Knowledge Bases. In International Conference on Learning Representations (ICLR)."},{"key":"e_1_3_2_2_57_1","volume-title":"Cohen","author":"Yang Fan","year":"2017","unstructured":"Fan Yang , Zhilin Yang , and William W . Cohen . 2017 . Differentiable Learning of Logical Rules for Knowledge Base Reasoning. In Advances in Neural Information Processing Systems (NeurIPS) . 2319--2328. Fan Yang, Zhilin Yang, and William W. Cohen. 2017. Differentiable Learning of Logical Rules for Knowledge Base Reasoning. In Advances in Neural Information Processing Systems (NeurIPS). 2319--2328."},{"key":"e_1_3_2_2_58_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/574"},{"key":"e_1_3_2_2_59_1","unstructured":"Muhan Zhang and Yixin Chen. 2018. Link Prediction Based on Graph Neural Networks. In Advances in Neural Information Processing Systems (NeurIPS). 5171--5181.  Muhan Zhang and Yixin Chen. 2018. Link Prediction Based on Graph Neural Networks. In Advances in Neural Information Processing Systems (NeurIPS). 5171--5181."},{"key":"e_1_3_2_2_60_1","volume-title":"Efficient Probabilistic Logic Reasoning with Graph Neural Networks. In International Conference on Learning Representations (ICLR).","author":"Zhang Yuyu","year":"2020","unstructured":"Yuyu Zhang , Xinshi Chen , Yuan Yang , Arun Ramamurthy , Bo Li , Yuan Qi , and Le Song . 2020 . Efficient Probabilistic Logic Reasoning with Graph Neural Networks. In International Conference on Learning Representations (ICLR). Yuyu Zhang, Xinshi Chen, Yuan Yang, Arun Ramamurthy, Bo Li, Yuan Qi, and Le Song. 2020. Efficient Probabilistic Logic Reasoning with Graph Neural Networks. In International Conference on Learning Representations (ICLR)."},{"key":"e_1_3_2_2_61_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.12057"},{"key":"e_1_3_2_2_62_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2021.3125424"}],"event":{"name":"SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval","location":"Madrid Spain","acronym":"SIGIR '22","sponsor":["SIGIR ACM Special Interest Group on Information Retrieval"]},"container-title":["Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3477495.3531996","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3477495.3531996","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T18:10:20Z","timestamp":1750183820000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3477495.3531996"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7,6]]},"references-count":62,"alternative-id":["10.1145\/3477495.3531996","10.1145\/3477495"],"URL":"https:\/\/doi.org\/10.1145\/3477495.3531996","relation":{},"subject":[],"published":{"date-parts":[[2022,7,6]]},"assertion":[{"value":"2022-07-07","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}