{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,8]],"date-time":"2025-10-08T03:40:50Z","timestamp":1759894850270,"version":"build-2065373602"},"publisher-location":"New York, NY, USA","reference-count":45,"publisher":"ACM","license":[{"start":{"date-parts":[[2025,5,8]],"date-time":"2025-05-08T00:00:00Z","timestamp":1746662400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,5,8]]},"DOI":"10.1145\/3701716.3715229","type":"proceedings-article","created":{"date-parts":[[2025,5,23]],"date-time":"2025-05-23T16:20:01Z","timestamp":1748017201000},"page":"611-620","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Global Feature Enhancing and Fusion Framework for Strain Gauge Status Recognition"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-5317-2422","authenticated-orcid":false,"given":"Xu","family":"Zhang","sequence":"first","affiliation":[{"name":"Shanghai Key Laboratory of Data Science, School of Computer Science and Technology, Fudan University, Shang Hai, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8136-9621","authenticated-orcid":false,"given":"Peng","family":"Wang","sequence":"additional","affiliation":[{"name":"Shanghai Key Laboratory of Data Science, School of Computer Science and Technology, Fudan University, Shanghai, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1698-8992","authenticated-orcid":false,"given":"Chen","family":"Wang","sequence":"additional","affiliation":[{"name":"National Engineering Research Center for Big Data Software, Tsinghua University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-3188-2258","authenticated-orcid":false,"given":"Zhe","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Software, Tsinghua University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-7277-9574","authenticated-orcid":false,"given":"Xiaohua","family":"Nie","sequence":"additional","affiliation":[{"name":"National Key Laboratory of Strength and Structural Integrity, Aircraft Strength Research Institute of China, Xi'an, Shaanxi, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0264-788X","authenticated-orcid":false,"given":"Wei","family":"Wang","sequence":"additional","affiliation":[{"name":"Shanghai Key Laboratory of Data Science, School of Computer Science and Technology, Fudan University, Shanghai, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2025,5,23]]},"reference":[{"key":"e_1_3_2_2_1_1","volume-title":"The anatomy of a large-scale hypertextual web search engine. Computer networks and ISDN systems","author":"Brin Sergey","year":"1998","unstructured":"Sergey Brin and Lawrence Page. 1998. The anatomy of a large-scale hypertextual web search engine. Computer networks and ISDN systems, Vol. 30, 1--7 (1998), 107--117."},{"key":"e_1_3_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/JAS.2019.1911459"},{"key":"e_1_3_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/2988450.2988454"},{"key":"e_1_3_2_2_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/3543507.3583205"},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1038\/s42256-023-00624-6"},{"key":"e_1_3_2_2_6_1","doi-asserted-by":"publisher","DOI":"10.3390\/S22093429nolinkurl10.3390\/S22093429"},{"key":"e_1_3_2_2_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/I2MTC60896.2024.10560727"},{"key":"e_1_3_2_2_8_1","volume-title":"3nd ECML\/PKDD Workshop on Advanced Analytics and Learning on Temporal Data","author":"Fawaz Hassan Ismail","year":"2018","unstructured":"Hassan Ismail Fawaz, Germain Forestier, Jonathan Weber, Lhassane Idoumghar, and Pierre-Alain Muller. 2018. Data augmentation using synthetic data for time series classification with deep residual networks. In 3nd ECML\/PKDD Workshop on Advanced Analytics and Learning on Temporal Data. Cornell University."},{"key":"e_1_3_2_2_9_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33013558"},{"key":"e_1_3_2_2_10_1","volume-title":"SkipcrossNets: Adaptive Skip-cross Fusion for Road Detection. arXiv preprint arXiv:2308.12863","author":"Gong Yan","year":"2023","unstructured":"Yan Gong, Xinyu Zhang, Hao Liu, Xinmin Jiang, Zhiwei Li, Xin Gao, Lei Lin, Dafeng Jin, Jun Li, and Huaping Liu. 2023. SkipcrossNets: Adaptive Skip-cross Fusion for Road Detection. arXiv preprint arXiv:2308.12863 (2023)."},{"key":"e_1_3_2_2_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2022.3186963"},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"publisher","DOI":"10.1007\/S10618-013-0322--1nolinkurl10.1007\/S10618-013-0322--1"},{"key":"e_1_3_2_2_13_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2021\/353"},{"key":"e_1_3_2_2_14_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10618-019-00619--1nolinkurl10.1007\/s10618-019-00619--1"},{"key":"e_1_3_2_2_15_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10618-020-00710-y"},{"key":"e_1_3_2_2_16_1","volume-title":"Categorical Reparameterization with Gumbel-Softmax. In International Conference on Learning Representations.","author":"Jang Eric","year":"2022","unstructured":"Eric Jang, Shixiang Gu, and Ben Poole. 2022. Categorical Reparameterization with Gumbel-Softmax. In International Conference on Learning Representations."},{"key":"e_1_3_2_2_17_1","doi-asserted-by":"crossref","unstructured":"Jianwen Jiang Yuxuan Wei Yifan Feng Jingxuan Cao and Yue Gao. 2019. Dynamic hypergraph neural networks.. In IJCAI. 2635--2641.","DOI":"10.24963\/ijcai.2019\/366"},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"publisher","DOI":"10.37398\/JSR.2020.640251"},{"key":"e_1_3_2_2_19_1","doi-asserted-by":"publisher","DOI":"10.3390\/S24113489nolinkurl10.3390\/S24113489"},{"key":"e_1_3_2_2_20_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10618-019-00647-x"},{"key":"e_1_3_2_2_21_1","volume-title":"Proceedings of the international conference on learning Representations.","author":"Maddison C","year":"2017","unstructured":"C Maddison, A Mnih, and Y Teh. 2017. The concrete distribution: A continuous relaxation of discrete random variables. In Proceedings of the international conference on learning Representations."},{"key":"e_1_3_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0016-0032(96)00063-4"},{"key":"e_1_3_2_2_23_1","volume-title":"Bake off redux: a review and experimental evaluation of recent time series classification algorithms. Data Mining and Knowledge Discovery","author":"Middlehurst Matthew","year":"2024","unstructured":"Matthew Middlehurst, Patrick Sch\u00e4fer, and Anthony Bagnall. 2024. Bake off redux: a review and experimental evaluation of recent time series classification algorithms. Data Mining and Knowledge Discovery (2024), 1--74."},{"key":"e_1_3_2_2_24_1","volume-title":"international conference on machine learning. PMLR, 7034--7044","author":"Moon Jooyoung","year":"2020","unstructured":"Jooyoung Moon, Jihyo Kim, Younghak Shin, and Sangheum Hwang. 2020. Confidence-aware learning for deep neural networks. In international conference on machine learning. PMLR, 7034--7044."},{"key":"e_1_3_2_2_25_1","doi-asserted-by":"publisher","DOI":"10.3390\/S23249794nolinkurl10.3390\/S23249794"},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/2623330.2623732"},{"key":"e_1_3_2_2_27_1","doi-asserted-by":"publisher","DOI":"10.1016\/J.KNOSYS.2004.10.007nolinkurl10.1016\/J.KNOSYS.2004.10.007"},{"key":"e_1_3_2_2_28_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.0706851105"},{"key":"e_1_3_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.74"},{"key":"e_1_3_2_2_30_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10618-022-00844-1"},{"key":"e_1_3_2_2_31_1","volume-title":"The Tenth International Conference on Learning Representations, ICLR 2022","author":"Tang Wensi","year":"2022","unstructured":"Wensi Tang, Guodong Long, Lu Liu, Tianyi Zhou, Michael Blumenstein, and Jing Jiang. 2022. Omni-Scale CNNs: a simple and effective kernel size configuration for time series classification. In The Tenth International Conference on Learning Representations, ICLR 2022, Virtual Event, April 25--29, 2022. OpenReview.net. https:\/\/openreview.net\/forum?id=PDYs7Z2XFGv"},{"key":"e_1_3_2_2_32_1","volume-title":"Rethinking 1d-cnn for time series classification: A stronger baseline. arXiv preprint arXiv:2002.10061","author":"Tang Wensi","year":"2020","unstructured":"Wensi Tang, Guodong Long, Lu Liu, Tianyi Zhou, Jing Jiang, and Michael Blumenstein. 2020. Rethinking 1d-cnn for time series classification: A stronger baseline. arXiv preprint arXiv:2002.10061 (2020), 1--7."},{"key":"e_1_3_2_2_33_1","volume-title":"International conference on machine learning. PMLR, 9690--9700","author":"Amersfoort Joost Van","year":"2020","unstructured":"Joost Van Amersfoort, Lewis Smith, Yee Whye Teh, and Yarin Gal. 2020. Uncertainty estimation using a single deep deterministic neural network. In International conference on machine learning. PMLR, 9690--9700."},{"key":"e_1_3_2_2_34_1","volume-title":"Attention is all you need. Advances in neural information processing systems","author":"Vaswani Ashish","year":"2017","unstructured":"Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, \u0141ukasz Kaiser, and Illia Polosukhin. 2017. Attention is all you need. Advances in neural information processing systems, Vol. 30 (2017)."},{"key":"e_1_3_2_2_35_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01152"},{"key":"e_1_3_2_2_36_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2023.109319"},{"key":"e_1_3_2_2_37_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2022.108459"},{"key":"e_1_3_2_2_38_1","doi-asserted-by":"publisher","DOI":"10.1145\/3394171.3413621"},{"volume-title":"Time series classification from scratch with deep neural networks: A strong baseline. In 2017 International joint conference on neural networks (IJCNN)","author":"Wang Zhiguang","key":"e_1_3_2_2_39_1","unstructured":"Zhiguang Wang, Weizhong Yan, and Tim Oates. 2017. Time series classification from scratch with deep neural networks: A strong baseline. In 2017 International joint conference on neural networks (IJCNN). IEEE, 1578--1585."},{"key":"e_1_3_2_2_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/3583780.3614765"},{"key":"e_1_3_2_2_41_1","doi-asserted-by":"publisher","DOI":"10.3390\/s22228847"},{"key":"e_1_3_2_2_42_1","doi-asserted-by":"publisher","DOI":"10.1109\/TETCI.2019.2952908"},{"key":"e_1_3_2_2_43_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2019.8794371"},{"key":"e_1_3_2_2_44_1","volume-title":"Hypergcn: A new method for training graph convolutional networks on hypergraphs. Advances in neural information processing systems","author":"Yadati Naganand","year":"2019","unstructured":"Naganand Yadati, Madhav Nimishakavi, Prateek Yadav, Vikram Nitin, Anand Louis, and Partha Talukdar. 2019. Hypergcn: A new method for training graph convolutional networks on hypergraphs. Advances in neural information processing systems, Vol. 32 (2019)."},{"key":"e_1_3_2_2_45_1","volume-title":"Time series shapelets: a novel technique that allows accurate, interpretable and fast classification. Data mining and knowledge discovery","author":"Ye Lexiang","year":"2011","unstructured":"Lexiang Ye and Eamonn Keogh. 2011. Time series shapelets: a novel technique that allows accurate, interpretable and fast classification. Data mining and knowledge discovery, Vol. 22 (2011), 149--182."}],"event":{"name":"WWW '25: The ACM Web Conference 2025","sponsor":["SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web"],"location":"Sydney NSW Australia","acronym":"WWW '25"},"container-title":["Companion Proceedings of the ACM on Web Conference 2025"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3701716.3715229","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3701716.3715229","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,8]],"date-time":"2025-10-08T03:06:19Z","timestamp":1759892779000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3701716.3715229"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,5,8]]},"references-count":45,"alternative-id":["10.1145\/3701716.3715229","10.1145\/3701716"],"URL":"https:\/\/doi.org\/10.1145\/3701716.3715229","relation":{},"subject":[],"published":{"date-parts":[[2025,5,8]]},"assertion":[{"value":"2025-05-23","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}