{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T16:24:37Z","timestamp":1772814277794,"version":"3.50.1"},"reference-count":101,"publisher":"Association for Computing Machinery (ACM)","issue":"7","license":[{"start":{"date-parts":[[2025,2,10]],"date-time":"2025-02-10T00:00:00Z","timestamp":1739145600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Programs of NSFC","award":["U23A20317, 62172146"],"award-info":[{"award-number":["U23A20317, 62172146"]}]},{"name":"Provincial Key R&D Program of Hunan","award":["2024AQ2025, 2023GK2002"],"award-info":[{"award-number":["2024AQ2025, 2023GK2002"]}]},{"name":"Yuelu Mountain Industrial Innovation Center Project","award":["2023YCII0118"],"award-info":[{"award-number":["2023YCII0118"]}]},{"DOI":"10.13039\/501100004735","name":"Natural Science Foundation of Hunan Province","doi-asserted-by":"crossref","award":["2023JJ10016, 2023JJ30083"],"award-info":[{"award-number":["2023JJ10016, 2023JJ30083"]}],"id":[{"id":"10.13039\/501100004735","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Comput. Surv."],"published-print":{"date-parts":[[2025,7,31]]},"abstract":"<jats:p>Attributed graphs with both topological information and node information have prevalent applications in the real world, including recommendation systems, biological networks, community analysis, and so on. Recently, with rapid development of information gathering and extraction technology, the sources of data become more extensive and multi-view data attracts growing attention. Consequently, attributed graphs can be divided into two categories: single-view attributed graphs and multi-view attributed graphs. Compared with single-view attributed graphs, multi-view attributed graphs can provide more complementary information but also pose challenges to fusing information of multi-views. Moreover, attributed graph clustering aims to reveal the inherent community structure of the graph, which is widely applied in fraud detection, crime recognition, and recommendation systems. Recently, numerous methods based on various ideas and techniques have appeared to cluster attributed graphs, thus there is an urgent need to summarize related methods. To this end, we make a timely and comprehensive review of recent methods. Furthermore, we provide a novel standard according to fusion results to classify related methods into three categories: fusion on adjacency matrix methods, fusion on embedding methods, and model-based methods. Moreover, to conduct a comprehensive evaluation of existing methods, this article evaluates these advanced methods with sufficient experimental results and theoretical analysis. Finally, we analyze the challenges and open opportunities to promote the future development of this field.<\/jats:p>","DOI":"10.1145\/3714407","type":"journal-article","created":{"date-parts":[[2025,1,21]],"date-time":"2025-01-21T11:23:39Z","timestamp":1737458619000},"page":"1-36","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["Clustering on Attributed Graphs: From Single-view to Multi-view"],"prefix":"10.1145","volume":"57","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-6811-0863","authenticated-orcid":false,"given":"Mengyao","family":"Li","sequence":"first","affiliation":[{"name":"Hunan University, Changsha, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-1523-5253","authenticated-orcid":false,"given":"Zhibang","family":"Yang","sequence":"additional","affiliation":[{"name":"Changsha University, Changsha, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1400-8375","authenticated-orcid":false,"given":"Xu","family":"Zhou","sequence":"additional","affiliation":[{"name":"College of Computer Science and Electronic Engineering, Hunan University, Changsha, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5047-8593","authenticated-orcid":false,"given":"Yixiang","family":"Fang","sequence":"additional","affiliation":[{"name":"The Chinese University of Hong Kong, Shenzhen, Shenzhen, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2635-7716","authenticated-orcid":false,"given":"Kenli","family":"Li","sequence":"additional","affiliation":[{"name":"College of Computer Science and Electronic Engineering, Hunan University, Changsha, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5224-4048","authenticated-orcid":false,"given":"Keqin","family":"Li","sequence":"additional","affiliation":[{"name":"Hunan University, Changsha, China and State University of New York, New York USA"}]}],"member":"320","published-online":{"date-parts":[[2025,2,10]]},"reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-019-04064-5"},{"issue":"5","key":"e_1_3_3_3_2","article-title":"A new attributed graph clustering by using label propagation in complex networks","volume":"34","author":"Berahmand Kamal","year":"2022","unstructured":"Kamal Berahmand, Sogol Haghani, Mehrdad Rostami, and Yuefeng Li. 2022. A new attributed graph clustering by using label propagation in complex networks. J. King Saud Univ. Comput. Inf. Sci. 34, 5 (2022), 1869\u20131883.","journal-title":"J. King Saud Univ. Comput. Inf. Sci."},{"key":"e_1_3_3_4_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2021.104933"},{"issue":"7","key":"e_1_3_3_5_2","first-page":"667","article-title":"BSO-MV: An optimized multiview clustering approach for items recommendation in social networks","volume":"27","author":"Berkani Lamia","year":"2021","unstructured":"Lamia Berkani, Lylia Betit, and Louiza Belarif. 2021. BSO-MV: An optimized multiview clustering approach for items recommendation in social networks. J. Univ. Comput. Sci. 27, 7 (2021), 667\u2013692.","journal-title":"J. Univ. Comput. Sci."},{"key":"e_1_3_3_6_2","doi-asserted-by":"publisher","DOI":"10.1145\/3366423.3380214"},{"key":"e_1_3_3_7_2","doi-asserted-by":"publisher","DOI":"10.1017\/nws.2015.9"},{"key":"e_1_3_3_8_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2017.2772880"},{"key":"e_1_3_3_9_2","doi-asserted-by":"publisher","DOI":"10.14778\/3636218.3636223"},{"key":"e_1_3_3_10_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-59419-0_4"},{"key":"e_1_3_3_11_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2020.05.044"},{"key":"e_1_3_3_12_2","doi-asserted-by":"publisher","DOI":"10.2478\/popets-2020-0066"},{"key":"e_1_3_3_13_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cosrev.2020.100286"},{"key":"e_1_3_3_14_2","doi-asserted-by":"publisher","DOI":"10.1109\/ASONAM.2012.215"},{"key":"e_1_3_3_15_2","first-page":"127904","article-title":"Extending bootstrap AMG for clustering of attributed graphs","volume":"447","author":"D\u2019Ambra Pasqua","year":"2023","unstructured":"Pasqua D\u2019Ambra, Panayot S. Vassilevski, and Luisa Cutillo. 2023. Extending bootstrap AMG for clustering of attributed graphs. Appl. Math. Comput. 447 (2023), 127904.","journal-title":"Appl. Math. Comput."},{"key":"e_1_3_3_16_2","doi-asserted-by":"publisher","DOI":"10.1142\/S0219720018500075"},{"key":"e_1_3_3_17_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2018.09.053"},{"key":"e_1_3_3_18_2","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2022.3168775"},{"key":"e_1_3_3_19_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10898-021-01024-z"},{"key":"e_1_3_3_20_2","doi-asserted-by":"publisher","DOI":"10.1145\/3366423.3380079"},{"key":"e_1_3_3_21_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i6.25918"},{"key":"e_1_3_3_22_2","doi-asserted-by":"publisher","DOI":"10.1145\/3539597.3570367"},{"key":"e_1_3_3_23_2","article-title":"Visualizing social networks","volume":"1","author":"Freeman Linton C.","year":"2000","unstructured":"Linton C. Freeman. 2000. Visualizing social networks. J. Soc. Struct. 1 (2000), 4.","journal-title":"J. Soc. Struct."},{"key":"e_1_3_3_24_2","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/467"},{"key":"e_1_3_3_25_2","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/467"},{"key":"e_1_3_3_26_2","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2020.2968901"},{"key":"e_1_3_3_27_2","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2022\/418"},{"key":"e_1_3_3_28_2","doi-asserted-by":"publisher","DOI":"10.1136\/bmj.b2680"},{"key":"e_1_3_3_29_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-022-03381-y"},{"key":"e_1_3_3_30_2","doi-asserted-by":"publisher","DOI":"10.1007\/s12652-018-1054-2"},{"issue":"2","key":"e_1_3_3_31_2","first-page":"523","article-title":"An algorithm of inductively identifying clusters from attributed graphs","volume":"8","author":"Hu Lun","year":"2022","unstructured":"Lun Hu, Shicheng Yang, Xin Luo, and MengChu Zhou. 2022. An algorithm of inductively identifying clusters from attributed graphs. IEEE Trans. Big Data 8, 2 (2022), 523\u2013534.","journal-title":"IEEE Trans. Big Data"},{"key":"e_1_3_3_32_2","doi-asserted-by":"publisher","DOI":"10.3390\/s19020260"},{"key":"e_1_3_3_33_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-57454-7_29"},{"key":"e_1_3_3_34_2","doi-asserted-by":"publisher","DOI":"10.1007\/BF01908075"},{"key":"e_1_3_3_35_2","doi-asserted-by":"publisher","DOI":"10.1587\/transinf.2018DAP0022"},{"key":"e_1_3_3_36_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2021.3088880"},{"key":"e_1_3_3_37_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2021.07.012"},{"issue":"3","key":"e_1_3_3_38_2","first-page":"31:1\u201331:31","article-title":"GRACE: A general graph convolution framework for attributed graph clustering","volume":"17","author":"Kamhoua Barakeel Fanseu","year":"2023","unstructured":"Barakeel Fanseu Kamhoua, Lin Zhang, Kaili Ma, James Cheng, Bo Li, and Bo Han. 2023. GRACE: A general graph convolution framework for attributed graph clustering. ACM Trans. Knowl. Discov. Data 17, 3 (2023), 31:1\u201331:31.","journal-title":"ACM Trans. Knowl. Discov. Data"},{"key":"e_1_3_3_39_2","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611977172.42"},{"key":"e_1_3_3_40_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jocs.2022.101837"},{"key":"e_1_3_3_41_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ipm.2019.102054"},{"key":"e_1_3_3_42_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2022.08.124"},{"key":"e_1_3_3_43_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-020-02030-6"},{"key":"e_1_3_3_44_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2014.119"},{"key":"e_1_3_3_45_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2014.119"},{"key":"e_1_3_3_46_2","doi-asserted-by":"publisher","DOI":"10.1145\/2806416.2806501"},{"key":"e_1_3_3_47_2","doi-asserted-by":"publisher","DOI":"10.1587\/transfun.E100.A.2507"},{"key":"e_1_3_3_48_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2022.108665"},{"key":"e_1_3_3_49_2","article-title":"Dual information enhanced multi-view attributed graph clustering","volume":"2211","author":"Lin Jia-Qi","year":"2022","unstructured":"Jia-Qi Lin, Mansheng Chen, Xi-Ran Zhu, Chang-Dong Wang, and Haizhang Zhang. 2022. Dual information enhanced multi-view attributed graph clustering. CoRR abs\/2211.14987 (2022).","journal-title":"CoRR"},{"key":"e_1_3_3_50_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3034623"},{"key":"e_1_3_3_51_2","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2021\/375"},{"issue":"2","key":"e_1_3_3_52_2","first-page":"1872","article-title":"Multi-view attributed graph clustering","volume":"35","author":"Lin Zhiping","year":"2023","unstructured":"Zhiping Lin, Zhao Kang, Lizong Zhang, and Ling Tian. 2023. Multi-view attributed graph clustering. IEEE Trans. Knowl. Data Eng. 35, 2 (2023), 1872\u20131880.","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"e_1_3_3_53_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2022.09.042"},{"key":"e_1_3_3_54_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10115-021-01646-5"},{"key":"e_1_3_3_55_2","doi-asserted-by":"publisher","DOI":"10.3233\/JIFS-222627"},{"key":"e_1_3_3_56_2","article-title":"New attributed graph clustering by bridging attribute and topology spaces","volume":"28","author":"Maekawa Seiji","year":"2020","unstructured":"Seiji Maekawa, Koh Takeuchi, and Makoto Onizuka. 2020. New attributed graph clustering by bridging attribute and topology spaces. J. Inf. Process. 28 (2020), 427\u2013435.","journal-title":"J. Inf. Process."},{"issue":"2","key":"e_1_3_3_57_2","first-page":"100030","article-title":"A modified label propagation algorithm for community detection in attributed networks","volume":"1","author":"Malhotra Deepanshu","year":"2021","unstructured":"Deepanshu Malhotra and Anuradha Chug. 2021. A modified label propagation algorithm for community detection in attributed networks. Int. J. Inf. Manag. Data Insights 1, 2 (2021), 100030.","journal-title":"Int. J. Inf. Manag. Data Insights"},{"key":"e_1_3_3_58_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-019-07745-4"},{"key":"e_1_3_3_59_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2021.104772"},{"key":"e_1_3_3_60_2","volume-title":"Proceedings of the 18th International Joint Conference on Artificial Intelligence: Text Mining and Link Analysis Workshop","author":"Neville Jennifer","year":"2003","unstructured":"Jennifer Neville, Micah Adler, and David Jensen. 2003. Clustering relational data using attribute and link information. In Proceedings of the 18th International Joint Conference on Artificial Intelligence: Text Mining and Link Analysis Workshop."},{"key":"e_1_3_3_61_2","first-page":"849","volume-title":"Proceedings of the Conference on Neural Information Processing Systems: Natural and Synthetic (NIPS\u201901)","author":"Ng Andrew Y.","year":"2001","unstructured":"Andrew Y. Ng, Michael I. Jordan, and Yair Weiss. 2001. On spectral clustering: Analysis and an algorithm. In Proceedings of the Conference on Neural Information Processing Systems: Natural and Synthetic (NIPS\u201901). MIT Press, 849\u2013856."},{"key":"e_1_3_3_62_2","doi-asserted-by":"publisher","DOI":"10.1109\/MILCOM.2015.7357637"},{"key":"e_1_3_3_63_2","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2017.2679100"},{"key":"e_1_3_3_64_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2020.09.010"},{"key":"e_1_3_3_65_2","volume-title":"Proceedings of the Annual Conference on Neural Information Processing Systems (NeurIPS\u201921)","author":"Pan Erlin","year":"2021","unstructured":"Erlin Pan and Zhao Kang. 2021. Multi-view contrastive graph clustering. In Proceedings of the Annual Conference on Neural Information Processing Systems (NeurIPS\u201921)."},{"key":"e_1_3_3_66_2","doi-asserted-by":"publisher","DOI":"10.5555\/2832415.2832538"},{"key":"e_1_3_3_67_2","doi-asserted-by":"publisher","DOI":"10.1145\/3474085.3475276"},{"key":"e_1_3_3_68_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2018.2889413"},{"key":"e_1_3_3_69_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2018.07.037"},{"key":"e_1_3_3_70_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2022.3175317"},{"key":"e_1_3_3_71_2","doi-asserted-by":"publisher","DOI":"10.1109\/TrustCom\/BigDataSE.2018.00070"},{"key":"e_1_3_3_72_2","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2022.3143806"},{"key":"e_1_3_3_73_2","article-title":"Pitfalls of graph neural network evaluation","volume":"1811","author":"Shchur Oleksandr","year":"2018","unstructured":"Oleksandr Shchur, Maximilian Mumme, Aleksandar Bojchevski, and Stephan G\u00fcnnemann. 2018. Pitfalls of graph neural network evaluation. CoRR abs\/1811.05868 (2018).","journal-title":"CoRR"},{"key":"e_1_3_3_74_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-387-77672-9_19"},{"key":"e_1_3_3_75_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2009.11.001"},{"key":"e_1_3_3_76_2","first-page":"583","article-title":"Cluster ensembles\u2014A knowledge reuse framework for combining multiple partitions","volume":"3","author":"Strehl Alexander","year":"2002","unstructured":"Alexander Strehl and Joydeep Ghosh. 2002. Cluster ensembles\u2014A knowledge reuse framework for combining multiple partitions. J. Mach. Learn. Res. 3 (2002), 583\u2013617.","journal-title":"J. Mach. Learn. Res."},{"key":"e_1_3_3_77_2","unstructured":"Xing Su Shan Xue Fanzhen Liu Jia Wu Jian Yang Chuan Zhou Wenbin Hu C\u00e9cile Paris Surya Nepal Di Jin Quan Z. Sheng and Philip S. Yu. 2021. A comprehensive survey on community detection with deep learning. CoRR abs\/2105.12584 (2021)."},{"key":"e_1_3_3_78_2","doi-asserted-by":"publisher","DOI":"10.4018\/IJISP.2020070102"},{"key":"e_1_3_3_79_2","article-title":"Community detection based on structural and attribute similarities","author":"Dang A.","year":"2012","unstructured":"A. Dang and E. Viennet. 2012. Community detection based on structural and attribute similarities. In Proceedings of the 6th International Conference on Digital Society (ICDS\u201912).","journal-title":"Proceedings of the 6th International Conference on Digital Society (ICDS\u201912)"},{"key":"e_1_3_3_80_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00180-019-00909-8"},{"key":"e_1_3_3_81_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i11.17198"},{"key":"e_1_3_3_82_2","volume-title":"Proceedings of the 6th International Conference on Learning Representations (ICLR\u201918)","author":"Velickovic Petar","year":"2018","unstructured":"Petar Velickovic, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Li\u00f2, and Yoshua Bengio. 2018. Graph attention networks. In Proceedings of the 6th International Conference on Learning Representations (ICLR\u201918). OpenReview.net."},{"key":"e_1_3_3_83_2","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/509"},{"key":"e_1_3_3_84_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2021.108230"},{"key":"e_1_3_3_85_2","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2022.3148272"},{"key":"e_1_3_3_86_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2021.06.058"},{"key":"e_1_3_3_87_2","unstructured":"Tong Wang Guanyu Yang Qijia He Zhenquan Zhang and Junhua Wu. 2022. NCAGC: A neighborhood contrast framework for attributed graph clustering. arxiv:2206.07897"},{"key":"e_1_3_3_88_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v30i1.9977"},{"key":"e_1_3_3_89_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2010.48"},{"key":"e_1_3_3_90_2","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN55064.2022.9892848"},{"key":"e_1_3_3_91_2","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN55064.2022.9892820"},{"key":"e_1_3_3_92_2","article-title":"Self-supervised contrastive attributed graph clustering","volume":"2110","author":"Xia Wei","year":"2021","unstructured":"Wei Xia, Quanxue Gao, Ming Yang, and Xinbo Gao. 2021. Self-supervised contrastive attributed graph clustering. CoRR abs\/2110.08264 (2021).","journal-title":"CoRR"},{"key":"e_1_3_3_93_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2020.08.021"},{"key":"e_1_3_3_94_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2023.120479"},{"key":"e_1_3_3_95_2","doi-asserted-by":"publisher","DOI":"10.1186\/s12859-020-03646-8"},{"key":"e_1_3_3_96_2","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3449875"},{"key":"e_1_3_3_97_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2022.09.100"},{"key":"e_1_3_3_98_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00778-019-00572-x"},{"key":"e_1_3_3_99_2","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/601"},{"key":"e_1_3_3_100_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2021.05.026"},{"key":"e_1_3_3_101_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2022.04.018"},{"key":"e_1_3_3_102_2","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2021\/473"}],"container-title":["ACM Computing Surveys"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3714407","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3714407","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T01:17:56Z","timestamp":1750295876000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3714407"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,2,10]]},"references-count":101,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2025,7,31]]}},"alternative-id":["10.1145\/3714407"],"URL":"https:\/\/doi.org\/10.1145\/3714407","relation":{},"ISSN":["0360-0300","1557-7341"],"issn-type":[{"value":"0360-0300","type":"print"},{"value":"1557-7341","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,2,10]]},"assertion":[{"value":"2023-09-20","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-01-06","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-02-10","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}