{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,21]],"date-time":"2026-02-21T08:14:09Z","timestamp":1771661649534,"version":"3.50.1"},"reference-count":26,"publisher":"Zhejiang University Press","issue":"12","license":[{"start":{"date-parts":[[2020,12,1]],"date-time":"2020-12-01T00:00:00Z","timestamp":1606780800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,12,1]],"date-time":"2020-12-01T00:00:00Z","timestamp":1606780800000},"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":["Front Inform Technol Electron Eng"],"published-print":{"date-parts":[[2020,12]]},"DOI":"10.1631\/fitee.1900663","type":"journal-article","created":{"date-parts":[[2020,12,23]],"date-time":"2020-12-23T08:03:30Z","timestamp":1608710610000},"page":"1795-1803","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["A local density optimization method based on a graph convolutional network"],"prefix":"10.1631","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9613-6169","authenticated-orcid":false,"given":"Hao","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Li-yan","family":"Dong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1496-9464","authenticated-orcid":false,"given":"Tie-hu","family":"Fan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ming-hui","family":"Sun","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"635","published-online":{"date-parts":[[2020,12,23]]},"reference":[{"key":"ref1","article-title":"A tutorial on network embeddings","author":"Chen","year":"2018"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/tkde.2007.46"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939754"},{"key":"ref4","article-title":"Graphite: iterative gen-erative modeling of graphs","author":"Grover","year":"2018"},{"key":"ref5","article-title":"Semi-supervised classification with graph convolutional networks","author":"Kipf","year":"2016"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1515\/9781400830329"},{"key":"ref7","first-page":"II-1188","article-title":"Distributed representations of sen-tences and documents","volume-title":"Proc 31 st Int Conf on Machine Learning","author":"Le","year":"2014"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1989.1.4.541"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1038\/nature14539"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/asonam.2010.19"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1080\/0022250x.1971.9989788"},{"key":"ref13","article-title":"Efficient estimation of word representations in vector space","author":"Mikolov","year":"2013"},{"key":"ref14","first-page":"2265","article-title":"Learning word embeddings efficiently with noise-contrastive estimation","volume-title":"Proc 26th Int Conf on Neural Information Processing Systems","author":"Mnih","year":"2013"},{"key":"ref15","article-title":"sub-graph2vec: learning distributed representations of rooted sub-graphs from large graphs","author":"Narayanan","year":"2016"},{"key":"ref16","first-page":"2014","article-title":"Learning convolutional neural networks for graphs","volume-title":"Proc 33rd Int Conf on Machine Learning","author":"Niepert","year":"2016"},{"key":"ref17","article-title":"The Pagerank Citation Ranking: Bringing Order to the Web","volume-title":"Technical Report SIDL- WP-1999\u20130120","author":"Page","year":"1998"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/2623330.2623732"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1177\/0268580907082260"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3098061"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/msp.2012.2235192"},{"issue":"3","key":"ref22","doi-asserted-by":"crossref","first-page":"447","DOI":"10.1007\/s10618-010-0210-x","article-title":"Leveraging social media networks for classification","volume":"23","author":"Tang","year":"2011","journal-title":"Data Min Knowl Discov"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1631\/fitee.1800146"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-35289-8_34"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1631\/fitee.1500025"},{"key":"ref26","first-page":"40","article-title":"Revisiting semi-supervised learning with graph embeddings","volume-title":"Proc 33rd Int Conf on Machine Learning","author":"Yang","year":"2016"}],"container-title":["Frontiers of Information Technology &amp; Electronic Engineering"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1631\/FITEE.1900663.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1631\/FITEE.1900663\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1631\/FITEE.1900663.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,21]],"date-time":"2026-02-21T07:29:22Z","timestamp":1771658962000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1631\/FITEE.1900663"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,12]]},"references-count":26,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2020,12]]}},"alternative-id":["1607"],"URL":"https:\/\/doi.org\/10.1631\/fitee.1900663","relation":{},"ISSN":["2095-9184","2095-9230"],"issn-type":[{"value":"2095-9184","type":"print"},{"value":"2095-9230","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,12]]},"assertion":[{"value":"30 November 2019","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 April 2020","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 December 2020","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}