{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,11]],"date-time":"2024-09-11T18:57:35Z","timestamp":1726081055298},"publisher-location":"Cham","reference-count":21,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030445836"},{"type":"electronic","value":"9783030445843"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-3-030-44584-3_41","type":"book-chapter","created":{"date-parts":[[2020,4,21]],"date-time":"2020-04-21T23:04:42Z","timestamp":1587510282000},"page":"522-534","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Comparing the Preservation of Network Properties by Graph Embeddings"],"prefix":"10.1007","author":[{"given":"R\u00e9mi","family":"Vaudaine","sequence":"first","affiliation":[]},{"given":"R\u00e9my","family":"Cazabet","sequence":"additional","affiliation":[]},{"given":"Christine","family":"Largeron","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,4,22]]},"reference":[{"key":"41_CR1","doi-asserted-by":"crossref","unstructured":"Belkin and Niyogi.Laplacian eigenmaps for dimensionality reduction and datarepresentation.Neural Comput., 2003.","DOI":"10.1162\/089976603321780317"},{"key":"41_CR2","doi-asserted-by":"crossref","unstructured":"Blondel, Guillaume, Lambiotte, and Lefebvre. Fast unfolding of communities in large networks. Journal of Statistical Mechanics: Theory and Experiment, 2008","DOI":"10.1088\/1742-5468\/2008\/10\/P10008"},{"key":"41_CR3","doi-asserted-by":"crossref","unstructured":"Bohlin, Edler, Lancichinetti, and Rosvall. Community Detection and Visualization of Networks with the Map Equation Framework. 2014","DOI":"10.1007\/978-3-319-10377-8_1"},{"key":"41_CR4","volume-title":"and Linton Freeman","author":"Stephen Borgatti","year":"2002","unstructured":"Borgatti, Stephen, Everett, Martin: and Linton Freeman. Software for social network analysis, Ucinet for windows (2002)"},{"key":"41_CR5","volume-title":"and Kevin Chen-Chuan Chang","author":"Zheng Cai","year":"2018","unstructured":"Cai, Zheng: and Kevin Chen-Chuan Chang. Problems, techniques, and applications. TKDE, A comprehensive survey of graph embedding (2018)"},{"key":"41_CR6","unstructured":"Cui, Wang, Pei, and Zhu. A survey on network embedding. CoRR, abs\/1711.08752, 2017"},{"key":"41_CR7","doi-asserted-by":"crossref","unstructured":"Fortunato and Hric. Community detection in networks: A user guide. CoRR, abs\/1608.00163, 2016","DOI":"10.1016\/j.physrep.2016.09.002"},{"key":"41_CR8","doi-asserted-by":"crossref","unstructured":"Palash Goyal and Emilio Ferrara.Graph embedding techniques, applications, and performance: A survey.Knowledge-Based Systems, 2018.","DOI":"10.1016\/j.knosys.2018.03.022"},{"key":"41_CR9","doi-asserted-by":"crossref","unstructured":"Grover and Leskovec. Node2vec: Scalable feature learning for networks. In Proceedings of the 22nd ACM SIGKDD Conference. ACM, 2016","DOI":"10.1145\/2939672.2939754"},{"key":"41_CR10","unstructured":"Hamilton, Ying, and Leskovec. Representation learning on graphs: Methods and applications. CoRR, abs\/1709.05584, 2017"},{"key":"41_CR11","doi-asserted-by":"crossref","unstructured":"Kamada and Kawai.An algorithm for drawing general undirected graphs.Information Processing Letters, 1989.","DOI":"10.1016\/0020-0190(89)90102-6"},{"key":"41_CR12","doi-asserted-by":"crossref","unstructured":"Kruskal. Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis. Psychometrika, 1964","DOI":"10.1007\/BF02289565"},{"key":"41_CR13","doi-asserted-by":"crossref","unstructured":"Lorrain and White.Structural equivalence of individuals in social networks.The Journal of Mathematical Sociology, 1971.","DOI":"10.1080\/0022250X.1971.9989788"},{"key":"41_CR14","doi-asserted-by":"crossref","unstructured":"Ou, Cui, Pei, Zhang, and Zhu. Asymmetric transitivity preserving graph embedding. In Proceedings of the 22Nd ACM SIGKDD Conference, 2016","DOI":"10.1145\/2939672.2939751"},{"key":"41_CR15","doi-asserted-by":"crossref","unstructured":"Ribeiro, Saverese, and Figueiredo. Struc2vec: Learning node representations from structural identity. New York, NY, USA, 2017. ACM SIGKDD","DOI":"10.1145\/3097983.3098061"},{"key":"41_CR16","doi-asserted-by":"crossref","unstructured":"Riesen, Emmenegger, and Bunke. A novel software toolkit for graph edit distance computation. In Graph-Based Representations in Pattern Recognition, 2013","DOI":"10.1007\/978-3-642-38221-5_15"},{"key":"41_CR17","doi-asserted-by":"crossref","unstructured":"Roweis and Saul.Nonlinear dimensionality reduction by locally linear embedding.Science, 2000.","DOI":"10.1126\/science.290.5500.2323"},{"key":"41_CR18","doi-asserted-by":"crossref","unstructured":"Tsitsulin, Mottin, Karras, and M\u00fcller. Verse: Versatile graph embeddings from similarity measures. WWW \u201918, 2018","DOI":"10.1145\/3178876.3186120"},{"key":"41_CR19","doi-asserted-by":"crossref","unstructured":"Wang, Cui, and Zhu. Structural deep network embedding. In SIGKDD, 2016","DOI":"10.1145\/2939672.2939753"},{"key":"41_CR20","unstructured":"Z. Wu, S. Pan, F. Chen, G. Long, C. Zhang, and P. S. Yu. A comprehensive survey on graph neural networks. CoRR, abs\/1901.00596, 2019"},{"key":"41_CR21","unstructured":"Zhang, Yin, Zhu, and Zhang. Network representation learning: A survey. CoRR, abs\/1801.05852, 2018"}],"container-title":["Lecture Notes in Computer Science","Advances in Intelligent Data Analysis XVIII"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-44584-3_41","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,4,21]],"date-time":"2020-04-21T23:12:37Z","timestamp":1587510757000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-44584-3_41"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030445836","9783030445843"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-44584-3_41","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":"22 April 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"IDA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Symposium on Intelligent Data Analysis","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Konstanz","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Germany","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":"27 April 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 April 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ida2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ida2020.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Easychair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"114","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"45","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"39% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3,5","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"6","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}