{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T12:06:43Z","timestamp":1743077203686,"version":"3.40.3"},"publisher-location":"Cham","reference-count":26,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030608019"},{"type":"electronic","value":"9783030608026"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-3-030-60802-6_51","type":"book-chapter","created":{"date-parts":[[2020,10,13]],"date-time":"2020-10-13T18:04:35Z","timestamp":1602612275000},"page":"583-593","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["GTCN: Dynamic Network Embedding Based on Graph Temporal Convolution Neural Network"],"prefix":"10.1007","author":[{"given":"Zhichao","family":"Huang","sequence":"first","affiliation":[]},{"given":"Jingkuan","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Lijia","family":"Ma","sequence":"additional","affiliation":[]},{"given":"Fubing","family":"Mao","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,10,5]]},"reference":[{"issue":"52","key":"51_CR1","doi-asserted-by":"publisher","first-page":"20953","DOI":"10.1073\/pnas.1109521108","volume":"108","author":"G Facchetti","year":"2011","unstructured":"Facchetti, G., Iacono, G., Altafini, C.: Computing global structural balance in large-scale signed social networks. Proc. Natl. Acad. Sci. 108(52), 20953\u201320958 (2011)","journal-title":"Proc. Natl. Acad. Sci."},{"key":"51_CR2","doi-asserted-by":"crossref","unstructured":"Grover, A., Leskovec, J.: Node2vec: scalable feature learning for networks. In: ACMSIGKDD International Conference on Knowledge Discovery and Data Mining, San Francisco, USA, pp. 855\u2013864 (2016)","DOI":"10.1145\/2939672.2939754"},{"key":"51_CR3","unstructured":"Hamilton, W.L., Ying, R., Leskovec, J.: Representation learning on graphs: Methods and applications. CoRRabs\/1709.05584 (2017)"},{"key":"51_CR4","doi-asserted-by":"publisher","unstructured":"Zhang, D., Yin, J., Zhu, X., Zhang, C.: Network representation learning: a survey. IEEE Trans. Big Data (2018). https:\/\/doi.org\/10.1109\/tbdata.2018.2850013","DOI":"10.1109\/tbdata.2018.2850013"},{"key":"51_CR5","doi-asserted-by":"crossref","unstructured":"Perozzi, B., Al-Rfou, R., Skiena, S.: DeepWalk: online learning of social representations. In: ACMSIGKDD International Conference on Knowledge Discovery and Data Mining, NewYork, USA, pp. 701\u2013710 (2014)","DOI":"10.1145\/2623330.2623732"},{"key":"51_CR6","doi-asserted-by":"crossref","unstructured":"Tang, J., Qu, M., Wang, M., Zhang, M., Yan, J., Mei, Q.: Line: large-scale information network embedding. In: World Wide Web Conference. Florence, Italy, May 2015","DOI":"10.1145\/2736277.2741093"},{"key":"51_CR7","unstructured":"Kipf, T.N., Welling, M.: Semi-Supervised Classification with Graph Convolutional Networks. In: International Conference on Learning Representations. Palais des Congr\u00e8s Neptune, Toulon, France (2017)"},{"key":"51_CR8","doi-asserted-by":"crossref","unstructured":"Wang, X., Cui, P., Wang, J., Pei, J., Zhu, W., Yang, S.: Community preserving network embedding. In: AAAI Conference on Artificial Intelligence, San Francisco, California USA. AAAI (2017)","DOI":"10.1609\/aaai.v31i1.10488"},{"key":"51_CR9","unstructured":"Yang, L., Cao, X., He, D., Wang, C., Wang, X., Zhang, W.: Modularity based community detection with deep learning. In: International Joint Conference on Artificial Intelligence, New York, USA, pp. 2252\u20132258 (2016)"},{"key":"51_CR10","unstructured":"Skrlj, B., Kralj, J., Konc, J., Robnik-Sikonja, M., Lavrac, N.: Deep node ranking: an algorithm for structural network embedding and end-to-end classification. CoRRabs\/1902.03964 (2019)"},{"key":"51_CR11","unstructured":"K., E.G., Mirzasoleiman, B., Grosu, R., Leskovec, J.: Dynamic network model from partial observations. In: Advances in Neural Information Processing Systems. Montr\u00e9al, Canada (2018)"},{"key":"51_CR12","unstructured":"Rossetti, G., Cazabet, R.: Community discovery in dynamic networks: a survey. CoRRabs\/1707.03186 (2017)"},{"key":"51_CR13","doi-asserted-by":"crossref","unstructured":"Sekara, V., Stopczynski, A., Lehmann, S.: Fundamental structures of dynamic social networks. Proc. Nat. Acad. Sci. United States Am, p. 201602803 (2016)","DOI":"10.1073\/pnas.1602803113"},{"key":"51_CR14","unstructured":"Du, L., Wang, Y., Song, G., Lu, Z., Wang, J.: Dynamic network embedding by modeling triadic closure process. In: AAAI Conference on Artificial Intelligence, New Orleans, USA (2018)"},{"key":"51_CR15","doi-asserted-by":"crossref","unstructured":"Du, L., Wang, Y., Song, G., Lu, Z., Wang, J.: Dynamic network embedding: an extended approach for skip-gram based network embedding. In: International Joint Conference on Artificial Intelligence (2018)","DOI":"10.24963\/ijcai.2018\/288"},{"key":"51_CR16","unstructured":"Goyal, P., Kamra, N., He, X., Liu, Y.: Dyngem: deep embedding method for dynamic graphs. CoRRabs\/1805.11273 (2018)"},{"key":"51_CR17","doi-asserted-by":"publisher","first-page":"104816","DOI":"10.1016\/j.knosys.2019.06.024","volume":"187","author":"P Goyal","year":"2020","unstructured":"Goyal, P., Chhetri, S.R., Canedo, A.: Dyngraph2vec: capturing network dynamics using dynamic graph representation learning. Knowl. Based Syst. 187, 104816 (2020)","journal-title":"Knowl. Based Syst."},{"key":"51_CR18","unstructured":"Lipton, Z.C.: A critical review of recurrent neural networks for sequence learning. Computer Science (2015)"},{"key":"51_CR19","doi-asserted-by":"crossref","unstructured":"Sankar, A., Wu, Y., Gou, L., Zhang, W., Yang, H.: Dysat: deep neural representation learning on dynamic graphs via self-attention networks. In: International Conference on Web Search and Data Mining, Houson, USA, pp. 519\u2013527 (2020)","DOI":"10.1145\/3336191.3371845"},{"key":"51_CR20","unstructured":"Vaswani, A., et al.: Attention is all you need. In: Advances in Neural Information Processing Systems, Long Beach, USA, pp. 5998\u20136008 (2017)"},{"key":"51_CR21","unstructured":"Veli\u010dkovi\u0107, P., Cucurull, G., Casanova, A., Romero, A., Lio, P., Bengio, Y.: Graph attention networks. In: International Conference on Learning Representation, Vancouver, Canada (2018)"},{"key":"51_CR22","unstructured":"Bai, S., Kolter, J.Z., Koltun, V.: An empirical evaluation of generic convolutional and recurrent networks for sequence modeling. CoRR abs\/1803.01271 (2018)"},{"key":"51_CR23","doi-asserted-by":"crossref","unstructured":"Pan, S., Hu, R., Long, G., Jiang, J., Yao, L., Zhang, C.: Adversarially regularized graph autoencoder for graph embedding. In: International Joint Conference on Artificial Intelligence, Stockholm, Sweden, pp. 2609\u20132615 (2018)","DOI":"10.24963\/ijcai.2018\/362"},{"key":"51_CR24","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: IEEE Conference on Computer Vision and Pattern Recognition, Las Vegas, USA, pp. 770\u2013778 (2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"51_CR25","unstructured":"Kingma, D.P., Ba, J.: Adam: a method for stochastic optimization. Computer Science (2014)"},{"key":"51_CR26","doi-asserted-by":"crossref","unstructured":"Wang, D., Cui, P., Zhu, W.: Structural deep network embedding. In: ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Francisco, USA, pp. 1225\u20131234 (2016)","DOI":"10.1145\/2939672.2939753"}],"container-title":["Lecture Notes in Computer Science","Intelligent Computing Theories and Application"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-60802-6_51","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,23]],"date-time":"2022-11-23T04:15:03Z","timestamp":1669176903000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-60802-6_51"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030608019","9783030608026"],"references-count":26,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-60802-6_51","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"5 October 2020","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":"Bari","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2 October 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 October 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icic2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/ic-ic.tongji.edu.cn\/2020\/index.htm","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}