{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T03:23:32Z","timestamp":1742959412290,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":23,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819756629"},{"type":"electronic","value":"9789819756636"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-981-97-5663-6_37","type":"book-chapter","created":{"date-parts":[[2024,8,1]],"date-time":"2024-08-01T01:10:40Z","timestamp":1722474640000},"page":"439-450","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["HFGCN: Hybrid Filter Graph Convolutional Network for Heterophilic Graphs"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8730-9497","authenticated-orcid":false,"given":"Zitong","family":"Bo","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chaoyi","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-0487-228X","authenticated-orcid":false,"given":"Yilin","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kaiyue","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0002-2328","authenticated-orcid":false,"given":"Ying","family":"Qiao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chang","family":"Leng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongan","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,8,1]]},"reference":[{"key":"37_CR1","unstructured":"Abu-El-Haija, S., Perozzi, B., Kapoor, A., et al.: Mixhop: higher-order graph convolutional architectures via sparsified neighborhood mixing. In: International Conference on Machine Learning, pp. 21\u201329. PMLR (2019)"},{"key":"37_CR2","doi-asserted-by":"crossref","unstructured":"Bo, D., Wang, X., Shi, C., Shen, H.: Beyond low-frequency information in graph convolutional networks. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 35, pp. 3950\u20133957 (2021)","DOI":"10.1609\/aaai.v35i5.16514"},{"key":"37_CR3","unstructured":"Bruna, J., Zaremba, W., Szlam, A., et al.: Spectral networks and locally connected networks on graphs. arXiv preprint arXiv:1312.6203 (2013)"},{"key":"37_CR4","unstructured":"Castleman, K.R.: Digital Image Processing. Prentice Hall Press (1996)"},{"key":"37_CR5","unstructured":"Chien, E., Peng, J., Li, P., et al.: Adaptive universal generalized pagerank graph neural network. arXiv preprint arXiv:2006.07988 (2020)"},{"key":"37_CR6","unstructured":"Defferrard, M., Bresson, X., Vandergheynst, P.: Convolutional neural networks on graphs with fast localized spectral filtering. In: Advances in Neural Information Processing Systems, vol. 29 (2016)"},{"key":"37_CR7","doi-asserted-by":"crossref","unstructured":"Gao, Y., Wang, X., He, X., Liu, Z., Feng, H., Zhang, Y.: Addressing heterophily in graph anomaly detection: a perspective of graph spectrum. In: Proceedings of the ACM Web Conference 2023, pp. 1528\u20131538 (2023)","DOI":"10.1145\/3543507.3583268"},{"key":"37_CR8","unstructured":"Hamilton, W., Ying, Z., Leskovec, J.: Inductive representation learning on large graphs. In: Advances in Neural Information Processing Systems, vol. 30 (2017)"},{"key":"37_CR9","unstructured":"Kingma, D.P., Ba, J.: Adam: a method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014)"},{"key":"37_CR10","unstructured":"Kipf, T.N., Welling, M.: Semi-supervised classification with graph convolutional networks. arXiv preprint arXiv:1609.02907 (2016)"},{"key":"37_CR11","doi-asserted-by":"crossref","unstructured":"Lee, J.S.: Digital image enhancement and noise filtering by use of local statistics. IEEE Trans. Pattern Anal. Mach. Intell. PAMI-2, 165\u2013168 (1980)","DOI":"10.1109\/TPAMI.1980.4766994"},{"key":"37_CR12","doi-asserted-by":"crossref","unstructured":"Liu, K., Xue, F., Guo, D., et al.: Multimodal graph contrastive learning for multimedia-based recommendation. IEEE Trans. Multimedia (2023)","DOI":"10.1109\/TMM.2023.3251108"},{"key":"37_CR13","unstructured":"Van der Maaten, L., Hinton, G.: Visualizing data using t-sne. J. Mach. Learn. Res. 9(11) (2008)"},{"key":"37_CR14","unstructured":"Pei, H., Wei, B., Chang, K.C.C., et al.: Geom-GCN: geometric graph convolutional networks. arXiv preprint arXiv:2002.05287 (2020)"},{"key":"37_CR15","unstructured":"Vaswani, A., Shazeer, N.M., Parmar, N., et al.: Attention is all you need. In: Neural Information Processing Systems (2017)"},{"key":"37_CR16","unstructured":"Veli\u010dkovi\u0107, P., Cucurull, G., Casanova, et al.: Graph attention networks. arXiv preprint arXiv:1710.10903 (2017)"},{"key":"37_CR17","doi-asserted-by":"crossref","unstructured":"Wang, T., Jin, D., Wang, R., et al.: Powerful graph convolutional networks with adaptive propagation mechanism for homophily and heterophily. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 36, pp. 4210\u2013 4218 (2022)","DOI":"10.1609\/aaai.v36i4.20340"},{"key":"37_CR18","doi-asserted-by":"crossref","unstructured":"Xu, B., Xu, C., Su, B.: Cross-modal graph attention network for entity alignment. In: Proceedings of the 31st ACM International Conference on Multimedia, pp. 3715\u20133723 (2023)","DOI":"10.1145\/3581783.3612151"},{"key":"37_CR19","doi-asserted-by":"crossref","unstructured":"Xu, B., Shen, H., Cao, Q., et al.: Graph convolutional networks using heat kernel for semi-supervised learning. arXiv preprint arXiv:2007.16002 (2020)","DOI":"10.24963\/ijcai.2019\/267"},{"key":"37_CR20","unstructured":"Xu, B., Shen, H., Cao, Q., et al.: Graph wavelet neural network. arXiv preprint arXiv:1904.07785 (2019)"},{"key":"37_CR21","unstructured":"Xu, K., Li, C., Tian, Y., Sonobe, T., Kawarabayashi, K.i., Jegelka, S.: Representation learning on graphs with jumping knowledge networks. In: International Conference on Machine Learning, pp. 5453\u20135462. PMLR (2018)"},{"key":"37_CR22","doi-asserted-by":"crossref","unstructured":"Yu, P., Tan, Z., Lu, G., Bao, B.K.: Multi-view graph convolutional network for multimedia recommendation. In: Proceedings of the 31st ACM International Conference on Multimedia. MM\u201923, Association for Computing Machinery, NY, USA, pp. 6576\u20136585 (2023)","DOI":"10.1145\/3581783.3613915"},{"key":"37_CR23","unstructured":"Zhu, J., Yan, Y., Zhao, L., et al.: Beyond homophily in graph neural networks: Current limitations and effective designs. In: Advances in Neural Information Processing Systems, vol. 33, pp. 7793\u20137804 (2020)"}],"container-title":["Lecture Notes in Computer Science","Advanced Intelligent Computing Technology and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-97-5663-6_37","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,1]],"date-time":"2024-08-01T01:37:45Z","timestamp":1722476265000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-97-5663-6_37"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9789819756629","9789819756636"],"references-count":23,"URL":"https:\/\/doi.org\/10.1007\/978-981-97-5663-6_37","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"1 August 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICIC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Tianjin","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 August 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 August 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icic2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ic-icc.cn\/2024\/index.htm","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}