{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,14]],"date-time":"2025-10-14T06:42:50Z","timestamp":1760424170169,"version":"build-2065373602"},"publisher-location":"Singapore","reference-count":14,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819531844","type":"print"},{"value":"9789819531851","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T00:00:00Z","timestamp":1760313600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T00:00:00Z","timestamp":1760313600000},"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":[[2026]]},"DOI":"10.1007\/978-981-95-3185-1_5","type":"book-chapter","created":{"date-parts":[[2025,10,14]],"date-time":"2025-10-14T06:06:08Z","timestamp":1760421968000},"page":"69-77","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["An Efficient Explainability Framework for\u00a0Graph Neural Networks"],"prefix":"10.1007","author":[{"given":"Dehan","family":"Hu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chenyang","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoyu","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,10,13]]},"reference":[{"key":"5_CR1","unstructured":"Ali, A., Wolf, L., Cevikalp, H.: Degree-based stratification of nodes in graph neural networks. In: Asian Conference on Machine Learning, pp. 15\u201327. PMLR (2024)"},{"key":"5_CR2","unstructured":"Baldassarre, F., Azizpour, H.: Explainability techniques for graph convolutional networks. arXiv preprint arXiv:1905.13686 (2019)"},{"key":"5_CR3","doi-asserted-by":"crossref","unstructured":"Gao, H., Wang, Z., Ji, S.: Large-scale learnable graph convolutional networks. In: Proceedings of the 24th ACM SIGKDD international conference on knowledge discovery and data mining, pp. 1416\u20131424 (2018)","DOI":"10.1145\/3219819.3219947"},{"key":"5_CR4","unstructured":"Gilmer, J., Schoenholz, S.S., Riley, P.F., Vinyals, O., Dahl, G.E.: Neural message passing for quantum chemistry. In: International conference on machine learning, pp. 1263\u20131272. PMLR (2017)"},{"key":"5_CR5","unstructured":"Kipf, T.N., Welling, M.: Semi-supervised classification with graph convolutional networks. arXiv preprint arXiv:1609.02907 (2016)"},{"key":"5_CR6","unstructured":"Li, W., Wang, C.h., Cheng, G., Song, Q.: International conference on machine learning. Trans. Mach. Learn. Res. (2023)"},{"key":"5_CR7","first-page":"19620","volume":"33","author":"D Luo","year":"2020","unstructured":"Luo, D., et al.: Parameterized explainer for graph neural network. Adv. Neural. Inf. Process. Syst. 33, 19620\u201319631 (2020)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"5_CR8","doi-asserted-by":"crossref","unstructured":"Pope, P.E., Kolouri, S., Rostami, M., Martin, C.E., Hoffmann, H.: Explainability methods for graph convolutional neural networks. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 10772\u201310781 (2019)","DOI":"10.1109\/CVPR.2019.01103"},{"key":"5_CR9","unstructured":"Schlichtkrull, M.S., De\u00a0Cao, N., Titov, I.: Interpreting graph neural networks for NLP with differentiable edge masking. arXiv preprint arXiv:2010.00577 (2020)"},{"key":"5_CR10","doi-asserted-by":"crossref","unstructured":"Wang, X., et al.: Heterogeneous graph attention network. In: The world Wide Web Conference, pp. 2022\u20132032 (2019)","DOI":"10.1145\/3308558.3313562"},{"issue":"9","key":"5_CR11","doi-asserted-by":"publisher","first-page":"2579","DOI":"10.1093\/bioinformatics\/btac112","volume":"38","author":"Z Wang","year":"2022","unstructured":"Wang, Z., et al.: Advanced graph and sequence neural networks for molecular property prediction and drug discovery. Bioinformatics 38(9), 2579\u20132586 (2022)","journal-title":"Bioinformatics"},{"key":"5_CR12","unstructured":"Ying, Z., Bourgeois, D., You, J., Zitnik, M., Leskovec, J.: Gnnexplainer: generating explanations for graph neural networks. Adv. Neural Inf. Process. Syst. 32 (2019)"},{"key":"5_CR13","unstructured":"Yuan, H., Ji, S.: Structpool: structured graph pooling via conditional random fields. In: Proceedings of the 8th International Conference on Learning Representations (2020)"},{"key":"5_CR14","doi-asserted-by":"crossref","unstructured":"Zhang, M., Cui, Z., Neumann, M., Chen, Y.: An end-to-end deep learning architecture for graph classification. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol.\u00a032 (2018)","DOI":"10.1609\/aaai.v32i1.11782"}],"container-title":["Lecture Notes in Computer Science","Data Security and Privacy Protection"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-95-3185-1_5","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,14]],"date-time":"2025-10-14T06:06:14Z","timestamp":1760421974000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-95-3185-1_5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,13]]},"ISBN":["9789819531844","9789819531851"],"references-count":14,"URL":"https:\/\/doi.org\/10.1007\/978-981-95-3185-1_5","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,13]]},"assertion":[{"value":"13 October 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"DSPP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Data Security and Privacy Protection","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Xi'an","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":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16 October 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18 October 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"dspp2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/dspp2025.xidian.edu.cn\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}