{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,28]],"date-time":"2026-08-28T22:14:51Z","timestamp":1787955291680,"version":"build-2784847793"},"publisher-location":"New York, NY, USA","reference-count":80,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,5,13]],"date-time":"2024-05-13T00:00:00Z","timestamp":1715558400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,5,13]]},"DOI":"10.1145\/3589334.3645649","type":"proceedings-article","created":{"date-parts":[[2024,5,8]],"date-time":"2024-05-08T07:08:13Z","timestamp":1715152093000},"page":"2259-2270","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":8,"title":["Multi-Label Zero-Shot Product Attribute-Value Extraction"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8945-6909","authenticated-orcid":false,"given":"Jiaying","family":"Gong","sequence":"first","affiliation":[{"name":"Virginia Tech, Blacksburg, VA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9712-6667","authenticated-orcid":false,"given":"Hoda","family":"Eldardiry","sequence":"additional","affiliation":[{"name":"Virginia Tech, Blacksburg, VA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2024,5,13]]},"reference":[{"key":"e_1_3_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.naacl-main.272"},{"key":"e_1_3_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2021\/597"},{"key":"e_1_3_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403182"},{"key":"e_1_3_2_2_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/3539597.3570484"},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.ecnlp-1.16"},{"key":"e_1_3_2_2_6_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.ecnlp-1.16"},{"key":"e_1_3_2_2_7_1","volume-title":"2023 a. Integrating Topology beyond Descriptions for Zero-shot Learning. Pattern Recognition","author":"Chen Ziyi","year":"2023","unstructured":"Ziyi Chen, Yutong Gao, Congyan Lang, Lili Wei, Yidong Li, Hongzhe Liu, and Fayao Liu. 2023 a. Integrating Topology beyond Descriptions for Zero-shot Learning. Pattern Recognition (2023), 109738."},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/3485447.3511954"},{"key":"e_1_3_2_2_9_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.findings-acl.5"},{"key":"e_1_3_2_2_10_1","doi-asserted-by":"crossref","unstructured":"Hejie Cui Rongmei Lin Nasser Zalmout Chenwei Zhang Jingbo Shang Carl Yang and Xian Li. 2023. PV2TEA: Patching Visual Modality to Textual-Established Information Extraction. arxiv: 2306.01016 [cs.CL]","DOI":"10.18653\/v1\/2023.findings-acl.127"},{"key":"e_1_3_2_2_11_1","volume-title":"AE-smnsMLC: Multi-Label Classification with Semantic Matching and Negative Label Sampling for Product Attribute Value Extraction. In 2022 IEEE International Conference on Big Data (Big Data). IEEE","author":"Deng Zhongfen","year":"2022","unstructured":"Zhongfen Deng, Wei-Te Chen, Lei Chen, and S Yu Philip. 2022. AE-smnsMLC: Multi-Label Classification with Semantic Matching and Negative Label Sampling for Product Attribute Value Extraction. In 2022 IEEE International Conference on Big Data (Big Data). IEEE, 1816--1821."},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/N19--1423"},{"key":"e_1_3_2_2_13_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.emnlp-main.399"},{"key":"e_1_3_2_2_14_1","first-page":"4125","article-title":"Heterogeneous hypergraph variational autoencoder for link prediction","volume":"44","author":"Fan Haoyi","year":"2021","unstructured":"Haoyi Fan, Fengbin Zhang, Yuxuan Wei, Zuoyong Li, Changqing Zou, Yue Gao, and Qionghai Dai. 2021. Heterogeneous hypergraph variational autoencoder for link prediction. IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 44, 8 (2021), 4125--4138.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"e_1_3_2_2_15_1","volume-title":"Zero-shot Item-based Recommendation via Multi-task Product Knowledge Graph Pre-Training. arXiv preprint arXiv:2305.07633","author":"Fan Ziwei","year":"2023","unstructured":"Ziwei Fan, Zhiwei Liu, Shelby Heinecke, Jianguo Zhang, Huan Wang, Caiming Xiong, and Philip S Yu. 2023. Zero-shot Item-based Recommendation via Multi-task Product Knowledge Graph Pre-Training. arXiv preprint arXiv:2305.07633 (2023)."},{"key":"e_1_3_2_2_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2022.3182052"},{"key":"e_1_3_2_2_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/3534678.3539453"},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.websem.2022.100757"},{"key":"e_1_3_2_2_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/1147234.1147241"},{"key":"e_1_3_2_2_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/WACV56688.2023.00363"},{"key":"e_1_3_2_2_21_1","volume-title":"Knowledge-Enhanced Multi-Label Few-Shot Product Attribute-Value Extraction. arXiv preprint arXiv:2308.08413","author":"Gong Jiaying","year":"2023","unstructured":"Jiaying Gong, Wei-Te Chen, and Hoda Eldardiry. 2023. Knowledge-Enhanced Multi-Label Few-Shot Product Attribute-Value Extraction. arXiv preprint arXiv:2308.08413 (2023)."},{"key":"e_1_3_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/3459637.3482403"},{"key":"e_1_3_2_2_23_1","unstructured":"Jiaying Gong and Hoda Eldardiry. 2023. Prompt-based Zero-shot Relation Extraction with Semantic Knowledge Augmentation. arxiv: 2112.04539 [cs.CL]"},{"key":"e_1_3_2_2_24_1","doi-asserted-by":"publisher","DOI":"10.3233\/SW-210435"},{"key":"e_1_3_2_2_25_1","doi-asserted-by":"publisher","DOI":"10.1109\/TCBB.2021.3110279"},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/3543507.3583402"},{"key":"e_1_3_2_2_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/3366423.3380027"},{"key":"e_1_3_2_2_28_1","volume-title":"Proceedings of the 29th International Conference on Computational Linguistics. 1163--1168","author":"Huang Yen-Hao","year":"2022","unstructured":"Yen-Hao Huang, Yi-Hsin Chen, and Yi-Shin Chen. 2022. ConTextING: Granting Document-Wise Contextual Embeddings to Graph Neural Networks for Inductive Text Classification. In Proceedings of the 29th International Conference on Computational Linguistics. 1163--1168."},{"key":"e_1_3_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.ecnlp-1.10"},{"key":"e_1_3_2_2_30_1","volume-title":"Heterogeneous Hypergraph Neural Network for Social Recommendation using Attention Network. ACM Transactions on Recommender Systems","author":"Khan Bilal","year":"2023","unstructured":"Bilal Khan, Jia Wu, Jian Yang, and Xiaoxiao Ma. 2023. Heterogeneous Hypergraph Neural Network for Social Recommendation using Attention Network. ACM Transactions on Recommender Systems (2023)."},{"key":"e_1_3_2_2_31_1","volume-title":"Auto-encoding variational bayes. arXiv preprint arXiv:1312.6114","author":"Kingma Diederik P","year":"2013","unstructured":"Diederik P Kingma and Max Welling. 2013. Auto-encoding variational bayes. arXiv preprint arXiv:1312.6114 (2013)."},{"key":"e_1_3_2_2_32_1","volume-title":"Bart: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension. arXiv preprint arXiv:1910.13461","author":"Lewis Mike","year":"2019","unstructured":"Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Ves Stoyanov, and Luke Zettlemoyer. 2019. Bart: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension. arXiv preprint arXiv:1910.13461 (2019)."},{"key":"e_1_3_2_2_33_1","volume-title":"Hypergraph transformer neural networks. ACM Transactions on Knowledge Discovery from Data","author":"Li Mengran","year":"2023","unstructured":"Mengran Li, Yong Zhang, Xiaoyong Li, Yuchen Zhang, and Baocai Yin. 2023. Hypergraph transformer neural networks. ACM Transactions on Knowledge Discovery from Data, Vol. 17, 5 (2023), 1--22."},{"key":"e_1_3_2_2_34_1","volume-title":"HMGCL: Heterogeneous multigraph contrastive learning for LBSN friend recommendation. World Wide Web","author":"Li Yongkang","year":"2022","unstructured":"Yongkang Li, Zipei Fan, Du Yin, Renhe Jiang, Jinliang Deng, and Xuan Song. 2022a. HMGCL: Heterogeneous multigraph contrastive learning for LBSN friend recommendation. World Wide Web (2022), 1--24."},{"key":"e_1_3_2_2_35_1","doi-asserted-by":"publisher","DOI":"10.1145\/3511808.3557609"},{"key":"e_1_3_2_2_36_1","doi-asserted-by":"publisher","DOI":"10.1145\/3447548.3467164"},{"key":"e_1_3_2_2_37_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.acl-long.397"},{"key":"e_1_3_2_2_38_1","doi-asserted-by":"publisher","DOI":"10.1145\/3539618.3591900"},{"key":"e_1_3_2_2_39_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-15937-4_33"},{"key":"e_1_3_2_2_40_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2022.08.028"},{"key":"e_1_3_2_2_41_1","unstructured":"Mengyin Liu Chao Zhu Hongyu Gao Weibo Gu Hongfa Wang Wei Liu and Xu cheng Yin. 2023 d. Boosting Multi-Modal E-commerce Attribute Value Extraction via Unified Learning Scheme and Dynamic Range Minimization. arxiv: 2207.07278 [cs.CV]"},{"key":"e_1_3_2_2_42_1","doi-asserted-by":"publisher","DOI":"10.1145\/3539597.3570423"},{"key":"e_1_3_2_2_43_1","first-page":"804","article-title":"Transductive Relation-Propagation Network for Few-shot Learning","volume":"20","author":"Ma Yuqing","year":"2020","unstructured":"Yuqing Ma, Shihao Bai, Shan An, Wei Liu, Aishan Liu, Xiantong Zhen, and Xianglong Liu. 2020. Transductive Relation-Propagation Network for Few-shot Learning.. In IJCAI, Vol. 20. 804--810.","journal-title":"IJCAI"},{"key":"e_1_3_2_2_44_1","doi-asserted-by":"publisher","DOI":"10.3390\/biotech11030024"},{"key":"e_1_3_2_2_45_1","volume-title":"Conditional generative adversarial nets. arXiv preprint arXiv:1411.1784","author":"Mirza Mehdi","year":"2014","unstructured":"Mehdi Mirza and Simon Osindero. 2014. Conditional generative adversarial nets. arXiv preprint arXiv:1411.1784 (2014)."},{"key":"e_1_3_2_2_46_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D19-1018"},{"key":"e_1_3_2_2_47_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2022.3191696"},{"key":"e_1_3_2_2_48_1","doi-asserted-by":"publisher","DOI":"10.5555\/2145432.2145598"},{"key":"e_1_3_2_2_49_1","unstructured":"Alec Radford Jeffrey Wu Rewon Child David Luan Dario Amodei Ilya Sutskever et al. 2019. Language models are unsupervised multitask learners. OpenAI blog Vol. 1 8 (2019) 9."},{"key":"e_1_3_2_2_50_1","doi-asserted-by":"publisher","DOI":"10.5555\/3455716.3455856"},{"key":"e_1_3_2_2_51_1","doi-asserted-by":"publisher","DOI":"10.1145\/3437963.3441746"},{"key":"e_1_3_2_2_52_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2019.00202"},{"key":"e_1_3_2_2_53_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.ecnlp-1.2"},{"key":"e_1_3_2_2_54_1","volume-title":"Exploring Generative Models for Joint Attribute Value Extraction from Product Titles. arXiv preprint arXiv:2208.07130","author":"Roy Kalyani","year":"2022","unstructured":"Kalyani Roy, Tapas Nayak, and Pawan Goyal. 2022. Exploring Generative Models for Joint Attribute Value Extraction from Product Titles. arXiv preprint arXiv:2208.07130 (2022)."},{"key":"e_1_3_2_2_55_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.emnlp-main.92"},{"key":"e_1_3_2_2_56_1","volume-title":"Markus Hagenbuchner, and Gabriele Monfardini.","author":"Scarselli Franco","year":"2008","unstructured":"Franco Scarselli, Marco Gori, Ah Chung Tsoi, Markus Hagenbuchner, and Gabriele Monfardini. 2008. The graph neural network model. IEEE transactions on neural networks , Vol. 20, 1 (2008), 61--80."},{"key":"e_1_3_2_2_57_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.acl-short.25"},{"key":"e_1_3_2_2_58_1","volume-title":"A Unified Generative Approach to Product Attribute-Value Identification. arXiv preprint arXiv:2306.05605","author":"Shinzato Keiji","year":"2023","unstructured":"Keiji Shinzato, Naoki Yoshinaga, Yandi Xia, and Wei-Te Chen. 2023. A Unified Generative Approach to Product Attribute-Value Identification. arXiv preprint arXiv:2306.05605 (2023)."},{"key":"e_1_3_2_2_59_1","doi-asserted-by":"publisher","DOI":"10.1145\/3437963.3441835"},{"key":"e_1_3_2_2_60_1","volume-title":"MPKGAC: Multimodal Product Attribute Completion in E-commerce. In Companion Proceedings of the ACM Web Conference","author":"Wang Kai","year":"2023","unstructured":"Kai Wang, Jianzhi Shao, Tao Zhang, Qijin Chen, and Chengfu Huo. 2023. MPKGAC: Multimodal Product Attribute Completion in E-commerce. In Companion Proceedings of the ACM Web Conference 2023. 336--340."},{"key":"e_1_3_2_2_61_1","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403047"},{"key":"e_1_3_2_2_62_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.findings-emnlp.20"},{"key":"e_1_3_2_2_63_1","doi-asserted-by":"crossref","unstructured":"Xiao Wang Houye Ji Chuan Shi Bai Wang Yanfang Ye Peng Cui and Philip S Yu. 2019. Heterogeneous graph attention network. In The world wide web conference. 2022--2032.","DOI":"10.1145\/3308558.3313562"},{"key":"e_1_3_2_2_64_1","volume-title":"Dual subgraph-based graph neural network for friendship prediction in location-based social networks. ACM Transactions on Knowledge Discovery from Data","author":"Wei Xuemei","year":"2023","unstructured":"Xuemei Wei, Yezheng Liu, Jianshan Sun, Yuanchun Jiang, Qifeng Tang, and Kun Yuan. 2023. Dual subgraph-based graph neural network for friendship prediction in location-based social networks. ACM Transactions on Knowledge Discovery from Data, Vol. 17, 3 (2023), 1--28."},{"key":"e_1_3_2_2_65_1","doi-asserted-by":"publisher","DOI":"10.1109\/PAAP56126.2022.10010428"},{"key":"e_1_3_2_2_66_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDMW.2009.81"},{"key":"e_1_3_2_2_67_1","first-page":"3245","article-title":"Hypergraph collaborative network on vertices and hyperedges","volume":"45","author":"Wu Hanrui","year":"2022","unstructured":"Hanrui Wu, Yuguang Yan, and Michael Kwok-Po Ng. 2022. Hypergraph collaborative network on vertices and hyperedges. IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 45, 3 (2022), 3245--3258.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"e_1_3_2_2_68_1","volume-title":"Inductive representation learning on temporal graphs. arXiv preprint arXiv:2002.07962","author":"Xu Da","year":"2020","unstructured":"Da Xu, Chuanwei Ruan, Evren Korpeoglu, Sushant Kumar, and Kannan Achan. 2020. Inductive representation learning on temporal graphs. arXiv preprint arXiv:2002.07962 (2020)."},{"key":"e_1_3_2_2_69_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P19-1514"},{"key":"e_1_3_2_2_70_1","volume-title":"2023 b. Towards Open-World Product Attribute Mining: A Lightly-Supervised Approach. arXiv preprint arXiv:2305.18350","author":"Xu Liyan","year":"2023","unstructured":"Liyan Xu, Chenwei Zhang, Xian Li, Jingbo Shang, and Jinho D Choi. 2023 b. Towards Open-World Product Attribute Mining: A Lightly-Supervised Approach. arXiv preprint arXiv:2305.18350 (2023)."},{"key":"e_1_3_2_2_71_1","doi-asserted-by":"publisher","DOI":"10.1145\/3543507.3583331"},{"key":"e_1_3_2_2_72_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_73_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.acl-long.362"},{"key":"e_1_3_2_2_74_1","doi-asserted-by":"publisher","DOI":"10.1145\/3488560.3498377"},{"key":"e_1_3_2_2_75_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP43922.2022.9747687"},{"key":"e_1_3_2_2_76_1","doi-asserted-by":"publisher","DOI":"10.3390\/math10111921"},{"key":"e_1_3_2_2_77_1","doi-asserted-by":"publisher","DOI":"10.1145\/3485447.3512035"},{"key":"e_1_3_2_2_78_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.findings-acl.831"},{"key":"e_1_3_2_2_79_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219839"},{"key":"e_1_3_2_2_80_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.emnlp-main.166"}],"event":{"name":"WWW '24: The ACM Web Conference 2024","location":"Singapore Singapore","acronym":"WWW '24","sponsor":["SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web"]},"container-title":["Proceedings of the ACM Web Conference 2024"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3589334.3645649","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3589334.3645649","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T00:24:04Z","timestamp":1755822244000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3589334.3645649"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,5,13]]},"references-count":80,"alternative-id":["10.1145\/3589334.3645649","10.1145\/3589334"],"URL":"https:\/\/doi.org\/10.1145\/3589334.3645649","relation":{},"subject":[],"published":{"date-parts":[[2024,5,13]]},"assertion":[{"value":"2024-05-13","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}