{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,26]],"date-time":"2025-06-26T09:32:06Z","timestamp":1750930326554,"version":"3.37.3"},"reference-count":35,"publisher":"IEEE","license":[{"start":{"date-parts":[[2021,1,10]],"date-time":"2021-01-10T00:00:00Z","timestamp":1610236800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,1,10]],"date-time":"2021-01-10T00:00:00Z","timestamp":1610236800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,1,10]],"date-time":"2021-01-10T00:00:00Z","timestamp":1610236800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["52073169"],"award-info":[{"award-number":["52073169"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,1,10]]},"DOI":"10.1109\/icpr48806.2021.9412460","type":"proceedings-article","created":{"date-parts":[[2021,5,6]],"date-time":"2021-05-06T02:15:54Z","timestamp":1620267354000},"page":"1329-1335","source":"Crossref","is-referenced-by-count":1,"title":["GCNs-Based Context-Aware Short Text Similarity Model"],"prefix":"10.1109","author":[{"given":"Xiaoqi","family":"Sun","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shaochun","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yue","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"doi-asserted-by":"publisher","key":"ref33","DOI":"10.1609\/aaai.v34i05.6359"},{"doi-asserted-by":"publisher","key":"ref32","DOI":"10.3115\/v1\/P14-5010"},{"doi-asserted-by":"publisher","key":"ref31","DOI":"10.3115\/v1\/D14-1162"},{"doi-asserted-by":"publisher","key":"ref30","DOI":"10.3115\/1220355.1220406"},{"doi-asserted-by":"publisher","key":"ref35","DOI":"10.18653\/v1\/S16-1081"},{"doi-asserted-by":"publisher","key":"ref34","DOI":"10.18653\/v1\/D17-1159"},{"key":"ref10","article-title":"Semi-supervised classification with graph convolutional networks","author":"kipf","year":"2017","journal-title":"International Conference on Learning Representations"},{"doi-asserted-by":"publisher","key":"ref11","DOI":"10.18653\/v1\/D18-1244"},{"key":"ref12","doi-asserted-by":"crossref","first-page":"146:1","DOI":"10.1145\/3326362","article-title":"Dynamic graph cnn for learning on point clouds","volume":"38","author":"wang","year":"2019","journal-title":"ACM Transactions on Graphics"},{"key":"ref13","article-title":"Learning Localized Generative Models for 3D Point Clouds via Graph Convolution","author":"valsesia","year":"2019","journal-title":"International Conference on Learning Representations"},{"key":"ref14","first-page":"3538","article-title":"Deeper insights into graph convolutional networks for semi-supervised learning","author":"li","year":"2018","journal-title":"Thirty-Second AAAI Conference on Artificial Intelligence"},{"year":"2019","author":"wu","journal-title":"A comprehensive survey on graph neural networks","key":"ref15"},{"doi-asserted-by":"publisher","key":"ref16","DOI":"10.18653\/v1\/S15-2045"},{"doi-asserted-by":"publisher","key":"ref17","DOI":"10.18653\/v1\/D15-1181"},{"year":"2018","author":"cer","journal-title":"Universal sentence encoder","key":"ref18"},{"doi-asserted-by":"publisher","key":"ref19","DOI":"10.18653\/v1\/D17-1070"},{"key":"ref28","first-page":"385","article-title":"SemEval-2012 Task 6: A Pilot on Semantic Textual Similarity","author":"agirre","year":"2012","journal-title":"Proceedings of the First Joint Conference on Lexical and Computational Semantics-Volume 1 Proceedings of the Main Conference and the Shared Task and Volume 2 Proceedings of the Sixth International Workshop on Semantic Evaluation SemEval’ 12"},{"year":"2018","author":"battaglia","journal-title":"Relational inductive biases deep learning and graph networks","key":"ref4"},{"key":"ref27","first-page":"3844","article-title":"Convolutional neural networks on graphs with fast localized spectral filtering","author":"defferrard","year":"2016","journal-title":"Advances in neural information processing systems"},{"key":"ref3","doi-asserted-by":"crossref","first-page":"13","DOI":"10.5120\/11638-7118","article-title":"A Survey of Text Similarity Approaches","volume":"68","author":"wael","year":"2013","journal-title":"International Journal of Computer Applications"},{"doi-asserted-by":"publisher","key":"ref6","DOI":"10.1145\/2505515.2505688"},{"doi-asserted-by":"publisher","key":"ref29","DOI":"10.18653\/v1\/S17-2001"},{"key":"ref5","first-page":"1034","article-title":"Structured lexical similarity via convolution kernels on dependency trees","author":"croce","year":"2011","journal-title":"Conference on Empirical Methods in Natural Language Processing"},{"doi-asserted-by":"publisher","key":"ref8","DOI":"10.1109\/CVPR.2017.243"},{"key":"ref7","first-page":"32","article-title":"*SEM 2013 shared task: Semantic Textual Similarity","author":"agirre","year":"2013","journal-title":"Second Joint Conference on Lexical and Computational Semantics (*SEM) Volume 1 Proceedings of the Main Conference and the Shared Task Semantic Textual Similarity"},{"key":"ref2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/2807697","article-title":"On Selecting Recommenders for Trust Evaluation in Online Social Networks","volume":"15","author":"wenjun","year":"2015","journal-title":"ACM Transactions on Internet Technology"},{"key":"ref9","first-page":"2786","article-title":"Siamese recurrent architectures for learning sentence similarity","author":"mueller","year":"2015","journal-title":"Conference on Artificial Intelligence"},{"doi-asserted-by":"publisher","key":"ref1","DOI":"10.1016\/j.artint.2015.07.005"},{"doi-asserted-by":"publisher","key":"ref20","DOI":"10.3115\/v1\/S14-2010"},{"key":"ref22","first-page":"4171","article-title":"Bert: Pre-training of deep bidirectional transformers for language understanding","author":"devlin","year":"2019","journal-title":"Conference of the North American Chapter of the Association for Computational Linguistics"},{"doi-asserted-by":"publisher","key":"ref21","DOI":"10.3115\/v1\/P15-1150"},{"doi-asserted-by":"publisher","key":"ref24","DOI":"10.1609\/aaai.v33i01.33017370"},{"doi-asserted-by":"publisher","key":"ref23","DOI":"10.24963\/ijcai.2018\/575"},{"year":"2014","author":"kingma","journal-title":"A method for stochastic optimization","key":"ref26"},{"doi-asserted-by":"publisher","key":"ref25","DOI":"10.18653\/v1\/D19-1345"}],"event":{"name":"2020 25th International Conference on Pattern Recognition (ICPR)","start":{"date-parts":[[2021,1,10]]},"location":"Milan, Italy","end":{"date-parts":[[2021,1,15]]}},"container-title":["2020 25th International Conference on Pattern Recognition (ICPR)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9411940\/9411911\/09412460.pdf?arnumber=9412460","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T15:40:41Z","timestamp":1652197241000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9412460\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,1,10]]},"references-count":35,"URL":"https:\/\/doi.org\/10.1109\/icpr48806.2021.9412460","relation":{},"subject":[],"published":{"date-parts":[[2021,1,10]]}}}