{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,28]],"date-time":"2025-10-28T15:14:25Z","timestamp":1761664465749,"version":"3.28.0"},"reference-count":38,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,7,18]],"date-time":"2022-07-18T00:00:00Z","timestamp":1658102400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,7,18]],"date-time":"2022-07-18T00:00:00Z","timestamp":1658102400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,7,18]]},"DOI":"10.1109\/ijcnn55064.2022.9892730","type":"proceedings-article","created":{"date-parts":[[2022,9,30]],"date-time":"2022-09-30T19:56:04Z","timestamp":1664567764000},"page":"1-8","source":"Crossref","is-referenced-by-count":5,"title":["Graph Intention Neural Network for Knowledge Graph Reasoning"],"prefix":"10.1109","author":[{"given":"Weihao","family":"Jiang","sequence":"first","affiliation":[{"name":"Hikvision Research Institute Hikvision,Hangzhou,China"}]},{"given":"Yao","family":"Fu","sequence":"additional","affiliation":[{"name":"Hikvision Research Institute Hikvision,Hangzhou,China"}]},{"given":"Hong","family":"Zhao","sequence":"additional","affiliation":[{"name":"Hikvision Research Institute Hikvision,Hangzhou,China"}]},{"given":"Junhong","family":"Wan","sequence":"additional","affiliation":[{"name":"Hikvision Research Institute Hikvision,Hangzhou,China"}]},{"given":"Shiliang","family":"Pu","sequence":"additional","affiliation":[{"name":"Hikvision Research Institute Hikvision,Hangzhou,China"}]}],"member":"263","reference":[{"key":"ref38","first-page":"593","article-title":"Modeling relational data with graph convolutional networks","author":"schlichtkrull","year":"0","journal-title":"European Semantic Web Conference"},{"key":"ref33","first-page":"448","article-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift","author":"ioffe","year":"0","journal-title":"International Conference on Machine Learning"},{"key":"ref32","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2014","journal-title":"ArXiv Preprint"},{"key":"ref31","first-page":"5998","article-title":"Attention is all you need","author":"vaswani","year":"2017","journal-title":"Advances in neural information processing systems"},{"key":"ref30","first-page":"1097","article-title":"Imagenet classification with deep convolutional neural networks","volume":"25","author":"krizhevsky","year":"2012","journal-title":"Advances in neural information processing systems"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.29007\/zrzd"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/W15-4007"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.308"},{"key":"ref34","first-page":"1929","article-title":"Dropout: A simple way to prevent neural networks from overfitting","volume":"15","author":"srivastava","year":"2014","journal-title":"The Journal of Machine Learning Research"},{"key":"ref10","article-title":"Embedding entities and relations for learning and inference in knowledge bases","author":"yang","year":"2014","journal-title":"ArXiv Preprint"},{"key":"ref11","first-page":"2071","article-title":"Complex embeddings for simple link prediction","author":"trouillon","year":"0","journal-title":"International Conference on Machine Learning"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11573"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v28i1.8870"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v29i1.9491"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/P15-1067"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33013060"},{"key":"ref17","article-title":"Knowledge graph embedding using graph convolutional networks with relation-aware attention","author":"sheikh","year":"2021","journal-title":"ArXiv Preprint"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.acl-main.526"},{"key":"ref19","article-title":"A three-way model for collective learning on multi-relational data","author":"nickel","year":"0","journal-title":"ICML"},{"key":"ref28","article-title":"Semi-supervised classification with graph convolutional networks","author":"kipf","year":"2016","journal-title":"ArXiv Preprint"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i05.6478"},{"key":"ref27","article-title":"Spectral networks and locally connected networks on graphs","author":"bruna","year":"2013","journal-title":"ArXiv Preprint"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/3308558.3313705"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5815"},{"key":"ref29","article-title":"Graph attention networks","author":"veli?kovi?","year":"2017","journal-title":"ArXiv Preprint"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2017.2754499"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i03.5701"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2019.112948"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5945"},{"key":"ref9","article-title":"Translating embeddings for modeling multi-relational data","volume":"26","author":"bordes","year":"2013","journal-title":"Advances in neural information processing systems"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2020\/242"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.29007\/21r5"},{"key":"ref22","article-title":"A novel embedding model for knowledge base completion based on convolutional neural network","author":"nguyen","year":"2017","journal-title":"ArXiv Preprint"},{"key":"ref21","article-title":"A survey on knowledge graphs: Representation, acquisition, and applications","author":"ji","year":"2021","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330961"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1145\/3308558.3313488"},{"key":"ref26","article-title":"Representation learning on graphs: Methods and applications","author":"hamilton","year":"2017","journal-title":"ArXiv Preprint"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.2978386"}],"event":{"name":"2022 International Joint Conference on Neural Networks (IJCNN)","start":{"date-parts":[[2022,7,18]]},"location":"Padua, Italy","end":{"date-parts":[[2022,7,23]]}},"container-title":["2022 International Joint Conference on Neural Networks (IJCNN)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9891857\/9889787\/09892730.pdf?arnumber=9892730","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,4]],"date-time":"2022-11-04T01:26:54Z","timestamp":1667525214000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9892730\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7,18]]},"references-count":38,"URL":"https:\/\/doi.org\/10.1109\/ijcnn55064.2022.9892730","relation":{},"subject":[],"published":{"date-parts":[[2022,7,18]]}}}