{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T21:11:04Z","timestamp":1770844264784,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":69,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,3,4]],"date-time":"2024-03-04T00:00:00Z","timestamp":1709510400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"US DARPA INCAS Program","award":["HR001121C0165"],"award-info":[{"award-number":["HR001121C0165"]}]},{"name":"Molecule Maker Lab Institute: An AI Research Institutes program supported by NSF","award":["2019897"],"award-info":[{"award-number":["2019897"]}]},{"name":"the Institute for Geospatial Understanding through an Integrative Discovery Environment (I-GUIDE) by NSF","award":["2118329"],"award-info":[{"award-number":["2118329"]}]},{"DOI":"10.13039\/501100006374","name":"National Science Foundation","doi-asserted-by":"publisher","award":["IIS-19-56151"],"award-info":[{"award-number":["IIS-19-56151"]}],"id":[{"id":"10.13039\/501100006374","id-type":"DOI","asserted-by":"publisher"}]},{"name":"US DARPA KAIROS Program","award":["FA8750-19-2-1004"],"award-info":[{"award-number":["FA8750-19-2-1004"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,3,4]]},"DOI":"10.1145\/3616855.3636450","type":"proceedings-article","created":{"date-parts":[[2024,3,4]],"date-time":"2024-03-04T18:18:12Z","timestamp":1709576292000},"page":"1122-1125","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Bridging Text Data and Graph Data: Towards Semantics and Structure-aware Knowledge Discovery"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1295-2829","authenticated-orcid":false,"given":"Bowen","family":"Jin","sequence":"first","affiliation":[{"name":"University of Illinois at Urbana-Champaign, Urbana, IL, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0540-6758","authenticated-orcid":false,"given":"Yu","family":"Zhang","sequence":"additional","affiliation":[{"name":"University of Illinois at Urbana-Champaign, Urbana, IL, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8848-0162","authenticated-orcid":false,"given":"Sha","family":"Li","sequence":"additional","affiliation":[{"name":"University of Illinois at Urbana-Champaign, Urbana, IL, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3629-2696","authenticated-orcid":false,"given":"Jiawei","family":"Han","sequence":"additional","affiliation":[{"name":"University of Illinois at Urbana-Champaign, Urbana, IL, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2024,3,4]]},"reference":[{"key":"e_1_3_2_1_1_1","unstructured":"Ashutosh Adhikari Xingdi Yuan Marc-Alexandre C\u00f4t\u00e9 Mikul\u00e1\u0161 Zelinka Marc-Antoine Rondeau Romain Laroche Pascal Poupart Jian Tang Adam Trischler and Will Hamilton. 2020. Learning dynamic belief graphs to generalize on text-based games. In NeurIPS'20."},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"crossref","unstructured":"Maciej Besta Nils Blach Ales Kubicek Robert Gerstenberger Lukas Gianinazzi Joanna Gajda Tomasz Lehmann Michal Podstawski Hubert Niewiadomski Piotr Nyczyk et al. 2023. Graph of thoughts: Solving elaborate problems with large language models. arXiv preprint arXiv:2308.09687 (2023).","DOI":"10.1609\/aaai.v38i16.29720"},{"key":"e_1_3_2_1_3_1","unstructured":"Tom B. Brown Benjamin Mann and Nick Ryder et al. 2020. Language Models are Few-Shot Learners. In NeurIPS'20."},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.findings-acl.453"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.acl-main.207"},{"key":"e_1_3_2_1_6_1","volume-title":"Explaining Answers with Entailment Trees. In EMNLP'21","author":"Dalvi Bhavana","year":"2021","unstructured":"Bhavana Dalvi, Peter Jansen, Oyvind Tafjord, Zhengnan Xie, Hannah Smith, Leighanna Pipatanangkura, and Peter Clark. 2021. Explaining Answers with Entailment Trees. In EMNLP'21."},{"key":"e_1_3_2_1_7_1","volume-title":"BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. In NAACL-HLT'19.","author":"Devlin Jacob","year":"2019","unstructured":"Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. In NAACL-HLT'19."},{"key":"e_1_3_2_1_8_1","volume-title":"Be More with Less: Hypergraph Attention Networks for Inductive Text Classification. In EMNLP'20","author":"Ding Kaize","year":"2020","unstructured":"Kaize Ding, Jianling Wang, Jundong Li, Dingcheng Li, and Huan Liu. 2020. Be More with Less: Hypergraph Attention Networks for Inductive Text Classification. In EMNLP'20."},{"key":"e_1_3_2_1_9_1","volume-title":"Li, Sha","author":"Du Xinya","year":"2022","unstructured":"Xinya Du, Zixuan Zhang, and et al Li, Sha. 2022. RESIN-11: Schema-guided Event Prediction for 11 Newsworthy Scenarios. In NAACL'22, System Demonstrations."},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.acl-long.279"},{"key":"e_1_3_2_1_11_1","volume-title":"NIPS'17","author":"Hamilton Will","year":"2017","unstructured":"Will Hamilton, Zhitao Ying, and Jure Leskovec. 2017. Inductive representation learning on large graphs. In NIPS'17."},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/2872427.2883037"},{"key":"e_1_3_2_1_13_1","volume-title":"Classifying Twitter topic-networks using social network analysis. Social Media + Society","author":"Himelboim Itai","year":"2017","unstructured":"Itai Himelboim, Marc A Smith, Lee Rainie, Ben Shneiderman, and Camila Espina. 2017. Classifying Twitter topic-networks using social network analysis. Social Media + Society (2017)."},{"key":"e_1_3_2_1_14_1","volume-title":"Parameter-Efficient Transfer Learning for NLP. In ICML'19","author":"Houlsby Neil","year":"2019","unstructured":"Neil Houlsby, Andrei Giurgiu, Stanislaw Jastrzebski, Bruna Morrone, Quentin de Laroussilhe, Andrea Gesmundo, Mona Attariyan, and Sylvain Gelly. 2019. Parameter-Efficient Transfer Learning for NLP. In ICML'19."},{"key":"e_1_3_2_1_15_1","volume-title":"EMNLP'19","author":"Hu Linmei","year":"2019","unstructured":"Linmei Hu, Tianchi Yang, Chuan Shi, Houye Ji, and Xiaoli Li. 2019. Heterogeneous graph attention networks for semi-supervised short text classification. In EMNLP'19."},{"key":"e_1_3_2_1_16_1","volume-title":"Few-Shot Named Entity Recognition: An Empirical Baseline Study. In EMNLP'21","author":"Huang Jiaxin","year":"2021","unstructured":"Jiaxin Huang, Chunyuan Li, Krishan Subudhi, Damien Jose, Shobana Balakrishnan, Weizhu Chen, Baolin Peng, Jianfeng Gao, and Jiawei Han. 2021. Few-Shot Named Entity Recognition: An Empirical Baseline Study. In EMNLP'21."},{"key":"e_1_3_2_1_17_1","volume-title":"Few-Shot Fine-Grained Entity Typing with Automatic Label Interpretation and Instance Generation. In KDD'22","author":"Huang Jiaxin","year":"2022","unstructured":"Jiaxin Huang, Yu Meng, and Jiawei Han. 2022. Few-Shot Fine-Grained Entity Typing with Automatic Label Interpretation and Instance Generation. In KDD'22."},{"key":"e_1_3_2_1_18_1","volume-title":"Text-Augmented Open Knowledge Graph Completion via Pre-Trained Language Models. arXiv preprint arXiv:2305.15597","author":"Jiang Pengcheng","year":"2023","unstructured":"Pengcheng Jiang, Shivam Agarwal, Bowen Jin, Xuan Wang, Jimeng Sun, and Jiawei Han. 2023. Text-Augmented Open Knowledge Graph Completion via Pre-Trained Language Models. arXiv preprint arXiv:2305.15597 (2023)."},{"key":"e_1_3_2_1_19_1","volume-title":"Open-Vocabulary Argument Role Prediction for Event Extraction. In EMNLP'22","author":"Jiao Yizhu","year":"2022","unstructured":"Yizhu Jiao, Sha Li, Yiqing Xie, Ming Zhong, Heng Ji, and Jiawei Han. 2022. Open-Vocabulary Argument Role Prediction for Event Extraction. In EMNLP'22."},{"key":"e_1_3_2_1_20_1","volume-title":"Large Language Models on Graphs: A Comprehensive Survey. arXiv preprint arXiv:2312.02783","author":"Jin Bowen","year":"2023","unstructured":"Bowen Jin, Gang Liu, Chi Han, Meng Jiang, Heng Ji, and Jiawei Han. 2023. Large Language Models on Graphs: A Comprehensive Survey. arXiv preprint arXiv:2312.02783 (2023)."},{"key":"e_1_3_2_1_21_1","volume-title":"Patton: Language Model Pretraining on Text-Rich Networks. In ACL'23","author":"Jin Bowen","year":"2023","unstructured":"Bowen Jin, Wentao Zhang, Yu Zhang, Yu Meng, Xinyang Zhang, Qi Zhu, and Jiawei Han. 2023. Patton: Language Model Pretraining on Text-Rich Networks. In ACL'23."},{"key":"e_1_3_2_1_22_1","volume-title":"Learning Multiplex Embeddings on Text-rich Networks with One Text Encoder. arXiv preprint arXiv:2310.06684","author":"Jin Bowen","year":"2023","unstructured":"Bowen Jin, Wentao Zhang, Yu Zhang, Yu Meng, Han Zhao, and Jiawei Han. 2023. Learning Multiplex Embeddings on Text-rich Networks with One Text Encoder. arXiv preprint arXiv:2310.06684 (2023)."},{"key":"e_1_3_2_1_23_1","volume-title":"Edgeformers: Graph-Empowered Transformers for Representation Learning on Textual-Edge Networks. In ICLR'23","author":"Jin Bowen","year":"2023","unstructured":"Bowen Jin, Yu Zhang, Yu Meng, and Jiawei Han. 2023. Edgeformers: Graph-Empowered Transformers for Representation Learning on Textual-Edge Networks. In ICLR'23."},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/3580305.3599376"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/3437963.3441774"},{"key":"e_1_3_2_1_26_1","volume-title":"SpanBERT: Improving Pre-training by Representing and Predicting Spans. TACL","author":"Joshi Mandar","year":"2020","unstructured":"Mandar Joshi, Danqi Chen, Yinhan Liu, Daniel S. Weld, Luke Zettlemoyer, and Omer Levy. 2020. SpanBERT: Improving Pre-training by Representing and Predicting Spans. TACL (2020)."},{"key":"e_1_3_2_1_27_1","volume-title":"Semi-Supervised Classification with Graph Convolutional Networks. In ICLR'16","author":"Kipf Thomas N","year":"2016","unstructured":"Thomas N Kipf and Max Welling. 2016. Semi-Supervised Classification with Graph Convolutional Networks. In ICLR'16."},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.acl-short.3"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.acl-main.703"},{"key":"e_1_3_2_1_30_1","volume-title":"Ultra-fine Entity Typing with Indirect Supervision from Natural Language Inference. TACL","author":"Li Bangzheng","year":"2022","unstructured":"Bangzheng Li, Wenpeng Yin, and Muhao Chen. 2022. Ultra-fine Entity Typing with Indirect Supervision from Natural Language Inference. TACL (2022)."},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.emnlp-main.422"},{"key":"e_1_3_2_1_32_1","volume-title":"Prefix-Tuning: Optimizing Continuous Prompts for Generation. In ACL'21","author":"Li Xiang Lisa","year":"2021","unstructured":"Xiang Lisa Li and Percy Liang. 2021. Prefix-Tuning: Optimizing Continuous Prompts for Generation. In ACL'21."},{"key":"e_1_3_2_1_33_1","volume-title":"BOND: BERT-Assisted Open-Domain Named Entity Recognition with Distant Supervision. In KDD'20","author":"Liang Chen","year":"2020","unstructured":"Chen Liang, Yue Yu, Haoming Jiang, Siawpeng Er, Ruijia Wang, Tuo Zhao, and Chao Zhang. 2020. BOND: BERT-Assisted Open-Domain Named Entity Recognition with Distant Supervision. In KDD'20."},{"key":"e_1_3_2_1_34_1","volume-title":"RoBERTa: A robustly optimized bert pretraining approach. arXiv preprint arXiv:1907.11692","author":"Liu Yinhan","year":"2019","unstructured":"Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019. RoBERTa: A robustly optimized bert pretraining approach. arXiv preprint arXiv:1907.11692 (2019)."},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.findings-acl.210"},{"key":"e_1_3_2_1_36_1","volume-title":"META: Metadata-Empowered Weak Supervision for Text Classification. In EMNLP'20","author":"Mekala Dheeraj","year":"2020","unstructured":"Dheeraj Mekala, Xinyang Zhang, and Jingbo Shang. 2020. META: Metadata-Empowered Weak Supervision for Text Classification. In EMNLP'20."},{"key":"e_1_3_2_1_37_1","unstructured":"Yu Meng Chenyan Xiong Payal Bajaj Saurabh Tiwary Paul Bennett Jiawei Han and Xia Song. 2021. COCO-LM: Correcting and Contrasting Text Sequences for Language Model Pretraining. In NeurIPS'21."},{"key":"e_1_3_2_1_38_1","volume-title":"Neighborhood Contrastive Learning for Scientific Document Representations with Citation Embeddings. In EMNLP'22","author":"Ostendorff Malte","year":"2022","unstructured":"Malte Ostendorff, Nils Rethmeier, Isabelle Augenstein, Bela Gipp, and Georg Rehm. 2022. Neighborhood Contrastive Learning for Scientific Document Representations with Citation Embeddings. In EMNLP'22."},{"key":"e_1_3_2_1_39_1","unstructured":"Alec Radford Jeffrey Wu Rewon Child David Luan Dario Amodei and Ilya Sutskever. 2019. Language models are unsupervised multitask learners. In OpenAI blog."},{"key":"e_1_3_2_1_40_1","volume":"202","author":"Raffel Colin","unstructured":"Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J Liu. 2020. Exploring the limits of transfer learning with a unified text-to-text transformer. JMLR (2020).","journal-title":"Peter J Liu."},{"key":"e_1_3_2_1_41_1","volume-title":"FactGraph: Evaluating Factuality in Summarization with Semantic Graph Representations. In NAACL'22","author":"Ribeiro Leonardo F. R.","year":"2022","unstructured":"Leonardo F. R. Ribeiro, Mengwen Liu, Iryna Gurevych, Markus Dreyer, and Mohit Bansal. 2022. FactGraph: Evaluating Factuality in Summarization with Semantic Graph Representations. In NAACL'22."},{"key":"e_1_3_2_1_42_1","volume-title":"Expla-Graphs: An Explanation Graph Generation Task for Structured Commonsense Reasoning. In EMNLP'21","author":"Saha Swarnadeep","year":"2021","unstructured":"Swarnadeep Saha, Prateek Yadav, Lisa Bauer, and Mohit Bansal. 2021. Expla-Graphs: An Explanation Graph Generation Task for Structured Commonsense Reasoning. In EMNLP'21."},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.acl-long.780"},{"key":"e_1_3_2_1_44_1","volume-title":"SciRepEval: A Multi-Format Benchmark for Scientific Document Representations. arXiv preprint arXiv:2211.13308","author":"Singh Amanpreet","year":"2022","unstructured":"Amanpreet Singh, Mike D'Arcy, Arman Cohan, Doug Downey, and Sergey Feldman. 2022. SciRepEval: A Multi-Format Benchmark for Scientific Document Representations. arXiv preprint arXiv:2211.13308 (2022)."},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.findings-acl.343"},{"key":"e_1_3_2_1_46_1","volume-title":"Graph Attention Networks. In ICLR'19","author":"Veli\u010dkovi\u0107 Petar","year":"2018","unstructured":"Petar Veli\u010dkovi\u0107, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Li\u00f2, and Yoshua Bengio. 2018. Graph Attention Networks. In ICLR'19."},{"key":"e_1_3_2_1_47_1","volume-title":"Microsoft academic graph: When experts are not enough. Quantitative Science Studies","author":"Wang Kuansan","year":"2020","unstructured":"Kuansan Wang, Zhihong Shen, Chiyuan Huang, Chieh-Han Wu, Yuxiao Dong, and Anshul Kanakia. 2020. Microsoft academic graph: When experts are not enough. Quantitative Science Studies (2020)."},{"key":"e_1_3_2_1_48_1","volume-title":"Legal networks: The promises and challenges of legal network analysis. Michigan State Law Review","author":"Whalen Ryan","year":"2016","unstructured":"Ryan Whalen. 2016. Legal networks: The promises and challenges of legal network analysis. Michigan State Law Review (2016)."},{"key":"e_1_3_2_1_49_1","volume-title":"EIDER: Evidence-enhanced Document-level Relation Extraction. In ACL'22","author":"Xie Yiqing","year":"2022","unstructured":"Yiqing Xie, Jiaming Shen, Sha Li, Yuning Mao, and Jiawei Han. 2022. EIDER: Evidence-enhanced Document-level Relation Extraction. In ACL'22."},{"key":"e_1_3_2_1_50_1","unstructured":"Junhan Yang Zheng Liu Shitao Xiao Chaozhuo Li Defu Lian Sanjay Agrawal Amit Singh Guangzhong Sun and Xing Xie. 2021. GraphFormers: GNN-nested transformers for representation learning on textual graph. In NeurIPS'21."},{"key":"e_1_3_2_1_51_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33017370"},{"key":"e_1_3_2_1_52_1","volume-title":"Tree of thoughts: Deliberate problem solving with large language models. arXiv preprint arXiv:2305.10601","author":"Yao Shunyu","year":"2023","unstructured":"Shunyu Yao, Dian Yu, Jeffrey Zhao, Izhak Shafran, Thomas L Griffiths, Yuan Cao, and Karthik Narasimhan. 2023. Tree of thoughts: Deliberate problem solving with large language models. arXiv preprint arXiv:2305.10601 (2023)."},{"key":"e_1_3_2_1_53_1","unstructured":"Michihiro Yasunaga Antoine Bosselut Hongyu Ren Xikun Zhang Christopher D Manning Percy Liang and Jure Leskovec. 2022. Deep Bidirectional Language-Knowledge Graph Pretraining. In NeurIPS'22."},{"key":"e_1_3_2_1_54_1","volume-title":"LinkBERT: Pretraining Language Models with Document Links. In ACL'22","author":"Yasunaga Michihiro","year":"2022","unstructured":"Michihiro Yasunaga, Jure Leskovec, and Percy Liang. 2022. LinkBERT: Pretraining Language Models with Document Links. In ACL'22."},{"key":"e_1_3_2_1_55_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM51629.2021.00095"},{"key":"e_1_3_2_1_56_1","volume-title":"Aspect-based Sentiment Classification with Aspect-specific Graph Convolutional Networks. In EMNLP'19","author":"Zhang Chen","year":"2019","unstructured":"Chen Zhang, Qiuchi Li, and Dawei Song. 2019. Aspect-based Sentiment Classification with Aspect-specific Graph Convolutional Networks. In EMNLP'19."},{"key":"e_1_3_2_1_57_1","volume-title":"Weakly-supervised Text Classification Based on Keyword Graph. In EMNLP'21","author":"Zhang Lu","year":"2021","unstructured":"Lu Zhang, Jiandong Ding, Yi Xu, Yingyao Liu, and Shuigeng Zhou. 2021. Weakly-supervised Text Classification Based on Keyword Graph. In EMNLP'21."},{"key":"e_1_3_2_1_58_1","volume":"202","author":"Zhang X","unstructured":"X Zhang, A Bosselut, M Yasunaga, H Ren, P Liang, C Manning, and J Leskovec. 2022. GreaseLM: Graph REASoning Enhanced Language Models for Question Answering. In ICLR'22.","journal-title":"J Leskovec."},{"key":"e_1_3_2_1_59_1","doi-asserted-by":"publisher","DOI":"10.1145\/3580305.3599921"},{"key":"e_1_3_2_1_60_1","volume-title":"Jingbo Shang, and Jiawei Han.","author":"Zhang Xinyang","year":"2021","unstructured":"Xinyang Zhang, Chenwei Zhang, Xin Luna Dong, Jingbo Shang, and Jiawei Han. 2021. Minimally-Supervised Structure-Rich Text Categorization via Learning on Text-Rich Networks. In WWW'21."},{"key":"e_1_3_2_1_61_1","volume-title":"Pre-training Multi-task Contrastive Learning Models for Scientific Literature Understanding. arXiv preprint arXiv:2305.14232","author":"Zhang Yu","year":"2023","unstructured":"Yu Zhang, Hao Cheng, Zhihong Shen, Xiaodong Liu, Ye-Yi Wang, and Jianfeng Gao. 2023. Pre-training Multi-task Contrastive Learning Models for Scientific Literature Understanding. arXiv preprint arXiv:2305.14232 (2023)."},{"key":"e_1_3_2_1_62_1","doi-asserted-by":"publisher","DOI":"10.1145\/3488560.3498384"},{"key":"e_1_3_2_1_63_1","volume-title":"Weakly Supervised Multi-Label Classification of Full-Text Scientific Papers. In KDD'23","author":"Zhang Yu","year":"2023","unstructured":"Yu Zhang, Bowen Jin, Xiusi Chen, Yanzhen Shen, Yunyi Zhang, Yu Meng, and Jiawei Han. 2023. Weakly Supervised Multi-Label Classification of Full-Text Scientific Papers. In KDD'23."},{"key":"e_1_3_2_1_64_1","volume-title":"The Effect of Metadata on Scientific Literature Tagging: A Cross-Field Cross-Model Study. In WWW'23","author":"Zhang Yu","year":"2023","unstructured":"Yu Zhang, Bowen Jin, Qi Zhu, Yu Meng, and Jiawei Han. 2023. The Effect of Metadata on Scientific Literature Tagging: A Cross-Field Cross-Model Study. In WWW'23."},{"key":"e_1_3_2_1_65_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401168"},{"key":"e_1_3_2_1_66_1","volume-title":"MATCH: Metadata-Aware Text Classification in A Large Hierarchy. In WWW'21","author":"Zhang Yu","year":"2021","unstructured":"Yu Zhang, Zhihong Shen, Yuxiao Dong, Kuansan Wang, and Jiawei Han. 2021. MATCH: Metadata-Aware Text Classification in A Large Hierarchy. In WWW'21."},{"key":"e_1_3_2_1_67_1","volume-title":"Metadata-Induced Contrastive Learning for Zero-Shot Multi-Label Text Classification. In WWW'22","author":"Zhang Yu","year":"2022","unstructured":"Yu Zhang, Zhihong Shen, Chieh-Han Wu, Boya Xie, Junheng Hao, Ye-Yi Wang, Kuansan Wang, and Jiawei Han. 2022. Metadata-Induced Contrastive Learning for Zero-Shot Multi-Label Text Classification. In WWW'22."},{"key":"e_1_3_2_1_68_1","doi-asserted-by":"crossref","unstructured":"Sizhe Zhou Suyu Ge Jiaming Shen and Jiawei Han. 2023. Corpus-Based Relation Extraction by Identifying and Refining Relation Patterns. In ECML\/PKDD'23.","DOI":"10.1007\/978-3-031-43421-1_2"},{"key":"e_1_3_2_1_69_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.acl-long.303"}],"event":{"name":"WSDM '24: The 17th ACM International Conference on Web Search and Data Mining","location":"Merida Mexico","acronym":"WSDM '24","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data","SIGIR ACM Special Interest Group on Information Retrieval"]},"container-title":["Proceedings of the 17th ACM International Conference on Web Search and Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3616855.3636450","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3616855.3636450","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T00:47:55Z","timestamp":1755823675000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3616855.3636450"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,3,4]]},"references-count":69,"alternative-id":["10.1145\/3616855.3636450","10.1145\/3616855"],"URL":"https:\/\/doi.org\/10.1145\/3616855.3636450","relation":{},"subject":[],"published":{"date-parts":[[2024,3,4]]},"assertion":[{"value":"2024-03-04","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}