{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,9]],"date-time":"2025-04-09T11:33:43Z","timestamp":1744198423264,"version":"3.37.3"},"reference-count":44,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2021,1,29]],"date-time":"2021-01-29T00:00:00Z","timestamp":1611878400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,29]],"date-time":"2021-01-29T00:00:00Z","timestamp":1611878400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100000038","name":"Natural Sciences and Engineering Research Council of Canada","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100000038","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Soc. Netw. Anal. Min."],"published-print":{"date-parts":[[2021,12]]},"DOI":"10.1007\/s13278-020-00714-y","type":"journal-article","created":{"date-parts":[[2021,1,29]],"date-time":"2021-01-29T16:03:09Z","timestamp":1611936189000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["ShortWalk: an approach to network embedding on directed graphs"],"prefix":"10.1007","volume":"11","author":[{"given":"Fen","family":"Zhao","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yi","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1042-8847","authenticated-orcid":false,"given":"Jianguo","family":"Lu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,1,29]]},"reference":[{"key":"714_CR1","doi-asserted-by":"crossref","unstructured":"Abu-El-Haija S, Perozzi B, Al-Rfou R (2017) Learning edge representations via low-rank asymmetric projections. In: Proceedings of the 2017 ACM on conference on information and knowledge management, pp 1787\u20131796","DOI":"10.1145\/3132847.3132959"},{"key":"714_CR2","doi-asserted-by":"crossref","unstructured":"Belkin M, Niyogi P (2002) Laplacian eigenmaps and spectral techniques for embedding and clustering. In: Advances in neural information processing systems, pp 585\u2013591","DOI":"10.7551\/mitpress\/1120.003.0080"},{"issue":"2003","key":"714_CR3","first-page":"1137","volume":"3","author":"Y Bengio","year":"2003","unstructured":"Bengio Y, Ducharme R, Vincent P, Jauvin C (2003) A neural probabilistic language model. J Mach Learn Res 3(2003):1137\u20131155","journal-title":"J Mach Learn Res"},{"issue":"1\u20137","key":"714_CR4","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1016\/S0169-7552(98)00110-X","volume":"30","author":"S Brin","year":"1998","unstructured":"Brin S, Page L (1998) The anatomy of a large-scale hypertextual web search engine. Comput Netw ISDN Syst 30(1\u20137):107\u2013117. https:\/\/doi.org\/10.1016\/S0169-7552(98)00110-X","journal-title":"Comput Netw ISDN Syst"},{"issue":"9","key":"714_CR5","doi-asserted-by":"publisher","first-page":"1616","DOI":"10.1109\/TKDE.2018.2807452","volume":"30","author":"H Cai","year":"2018","unstructured":"Cai H, Zheng VW, Chang KC-C (2018) A comprehensive survey of graph embedding: problems, techniques, and applications. IEEE Trans Knowl Data Eng 30(9):1616\u20131637","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"714_CR6","doi-asserted-by":"crossref","unstructured":"Cao S, Lu W, Xu Q (2015) Grarep: learning graph representations with global structural information. In: Proceedings of the 24th ACM international on conference on information and knowledge management, pp 891\u2013900","DOI":"10.1145\/2806416.2806512"},{"key":"714_CR7","unstructured":"Chen M, Yang Q, Tang X et al (2007) Directed graph embedding. In: IJCAI, pp 2707\u20132712"},{"key":"714_CR8","doi-asserted-by":"crossref","unstructured":"Dong Y, Chawla NV, Swami A (2017) Metapath2vec: scalable representation learning for heterogeneous networks. In: Proceedings of the 23rd ACM SIGKDD international conference on knowledge discovery and data mining. ACM, pp 135\u2013144","DOI":"10.1145\/3097983.3098036"},{"key":"714_CR11","doi-asserted-by":"publisher","first-page":"78","DOI":"10.1016\/j.knosys.2018.03.022","volume":"151","author":"P Goyal","year":"2018","unstructured":"Goyal P, Ferrara E (2018) Graph embedding techniques, applications, and performance: a survey. Knowl-Based Syst 151:78\u201394. https:\/\/doi.org\/10.1016\/j.knosys.2018.03.022","journal-title":"Knowl-Based Syst"},{"issue":"6\u20138","key":"714_CR12","doi-asserted-by":"publisher","first-page":"633","DOI":"10.1016\/j.ipl.2015.02.015","volume":"115","author":"V Grolmusz","year":"2015","unstructured":"Grolmusz V (2015) A note on the pagerank of undirected graphs. Inf Process Lett 115(6\u20138):633\u2013634. https:\/\/doi.org\/10.1016\/j.ipl.2015.02.015","journal-title":"Inf Process Lett"},{"key":"714_CR13","doi-asserted-by":"crossref","unstructured":"Grover A, Leskovec J (2016a) Node2vec: scalable feature learning for networks. In: Proceedings of the 22nd ACM SIGKDD international conference on knowledge discovery and data mining. ACM, pp 855\u2013864","DOI":"10.1145\/2939672.2939754"},{"key":"714_CR14","doi-asserted-by":"crossref","unstructured":"Grover A, Leskovec J (2016b) node2vec: scalable feature learning for networks. In: SIGKDD. ACM, pp 855\u2013864","DOI":"10.1145\/2939672.2939754"},{"key":"714_CR15","unstructured":"Gutmann M, Hyv\u00e4rinen A (2010) Noise-contrastive estimation: a new estimation principle for unnormalized statistical models. In: Proceedings of the thirteenth international conference on artificial intelligence and statistics, pp 297\u2013304"},{"issue":"1","key":"714_CR16","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1148\/radiology.143.1.7063747","volume":"143","author":"JA Hanley","year":"1982","unstructured":"Hanley JA, McNeil BJ (1982) The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology 143(1):29\u201336. https:\/\/doi.org\/10.1148\/radiology.143.1.7063747","journal-title":"Radiology"},{"issue":"6","key":"714_CR17","doi-asserted-by":"publisher","first-page":"e98679","DOI":"10.1371\/journal.pone.0098679","volume":"9","author":"M Jacomy","year":"2014","unstructured":"Jacomy M, Venturini T, Heymann S, Bastian M (2014) ForceAtlas2, a continuous graph layout algorithm for handy network visualization designed for the Gephi software. PLoS ONE 9(6):e98679. https:\/\/doi.org\/10.1371\/journal.pone.0098679","journal-title":"PLoS ONE"},{"key":"714_CR18","doi-asserted-by":"crossref","unstructured":"Khosla M, Leonhardt J, Nejdl W, Anand A (2019) Node representation learning for directed graphs. In: Joint European conference on machine learning and knowledge discovery in databases. Springer, pp 395\u2013411","DOI":"10.1007\/978-3-030-46150-8_24"},{"key":"714_CR19","doi-asserted-by":"crossref","unstructured":"Kim J, Park H, Lee J-E, Kang U (2018) Side: representation learning in signed directed networks. In: Proceedings of the 2018 World Wide Web Conference, pp 509\u2013518","DOI":"10.1145\/3178876.3186117"},{"key":"714_CR20","doi-asserted-by":"publisher","unstructured":"Kunegis J (2013) KONECT: the Koblenz Network Collection. In: Proceedings of the 22nd international conference on World Wide Web (WWW \u201913 Companion). ACM, Rio de Janeiro, Brazil, pp 1343\u20131350. https:\/\/doi.org\/10.1145\/2487788.2488173","DOI":"10.1145\/2487788.2488173"},{"key":"714_CR21","unstructured":"Leskovec J, Krevl A (2014) SNAP datasets: Stanford large network dataset collection, June 2014"},{"issue":"7","key":"714_CR22","doi-asserted-by":"publisher","first-page":"1019","DOI":"10.1002\/asi.20591","volume":"58","author":"D Liben-Nowell","year":"2007","unstructured":"Liben-Nowell D, Kleinberg J (2007) The link-prediction problem for social networks. J Am Soc Inf Sci Technol 58(7):1019\u20131031. https:\/\/doi.org\/10.1002\/asi.20591","journal-title":"J Am Soc Inf Sci Technol"},{"key":"714_CR23","unstructured":"Liu L, Cheung WK, Li X, Liao L (2016) Aligning users across social networks using network embedding. In: IJCAI, pp 1774\u20131780"},{"issue":"2","key":"714_CR24","doi-asserted-by":"publisher","first-page":"203","DOI":"10.3758\/BF03204766","volume":"28","author":"K Lund","year":"1996","unstructured":"Lund K, Burgess C (1996) Producing high-dimensional semantic spaces from lexical co-occurrence. Behav Res Methods Instrum Comput 28(2):203\u2013208. https:\/\/doi.org\/10.3758\/BF03204766","journal-title":"Behav Res Methods Instrum Comput"},{"key":"714_CR25","first-page":"1823","volume":"16","author":"T Man","year":"2016","unstructured":"Man T, Shen H, Liu S, Jin X, Cheng X (2016) Predict anchor links across social networks via an embedding approach. IJCAI 16:1823\u20131829","journal-title":"IJCAI"},{"key":"714_CR26","unstructured":"Mikolov T, Sutskever I, Chen K, Corrado GS, Dean J (2013) Distributed representations of words and phrases and their compositionality. In: Advances in neural information processing systems, pp 3111\u20133119"},{"key":"714_CR28","doi-asserted-by":"publisher","unstructured":"Ou M, Cui P, Pei J, Zhang Z, Zhu W (2016) Asymmetric transitivity preserving graph embedding. In: Proceedings of the 22nd ACM SIGKDD international conference on Knowledge Discovery and Data Mining\u2014KDD \u201916. ACM Press, San Francisco, California, USA, pp 1105\u20131114. https:\/\/doi.org\/10.1145\/2939672.2939751","DOI":"10.1145\/2939672.2939751"},{"issue":"6","key":"714_CR29","doi-asserted-by":"publisher","first-page":"186","DOI":"10.1088\/1367-2630\/9\/6\/186","volume":"9","author":"G Palla","year":"2007","unstructured":"Palla G, Farkas IJ, Pollner P, Der\u00e9nyi I, Vicsek T (2007) Directed network modules. New J Phys 9(6):186\u2013186. https:\/\/doi.org\/10.1088\/1367-2630\/9\/6\/186","journal-title":"New J Phys"},{"key":"714_CR30","doi-asserted-by":"crossref","unstructured":"Pennington J, Socher R, Manning C (2014) Glove: global vectors for word representation. In: Proceedings of the 2014 conference on Empirical Methods in Natural Language Processing (EMNLP), pp 1532\u20131543","DOI":"10.3115\/v1\/D14-1162"},{"key":"714_CR31","doi-asserted-by":"crossref","unstructured":"Perozzi B, Al-Rfou R, Skiena S (2014) Deepwalk: online learning of social representations. In: Proceedings of the 20th ACM SIGKDD international conference on knowledge discovery and data mining. ACM, pp 701\u2013710","DOI":"10.1145\/2623330.2623732"},{"key":"714_CR32","unstructured":"Perozzi B, Kulkarni V, Skiena S (2016) Walklets: multiscale graph embeddings for interpretable network classification. arXiv preprint arXiv:1605.02115"},{"key":"714_CR33","unstructured":"\u0158ehu\u0159ek R, Sojka P (2010) Software framework for topic modelling with large corpora. In: Proceedings of the LREC 2010 workshop on new challenges for NLP frameworks. ELRA, Valletta, Malta, pp 45\u201350"},{"key":"714_CR34","doi-asserted-by":"publisher","unstructured":"Sen T, Chaudhary DK (2017) Contrastive study of simple PageRank, HITS and weighted PageRank algorithms: review. In: 2017 7th international conference on cloud computing, data science engineering\u2014Confluence, pp 721\u2013727. https:\/\/doi.org\/10.1109\/CONFLUENCE.2017.7943245","DOI":"10.1109\/CONFLUENCE.2017.7943245"},{"key":"714_CR35","doi-asserted-by":"crossref","unstructured":"Sun J, Bandyopadhyay B, Bashizade A, Liang J, Sadayappan P, Parthasarathy S (2018) ATP: directed graph embedding with asymmetric transitivity preservation. CoRR arXiv:1811.00839","DOI":"10.1609\/aaai.v33i01.3301265"},{"key":"714_CR36","doi-asserted-by":"crossref","unstructured":"Tang J, Meng Q, Wang M, Zhang M, Yan J, Mei Qaozhu (2015a) LINE: large-scale information network embedding. In: WWW. ACM, pp 1067\u20131077","DOI":"10.1145\/2736277.2741093"},{"key":"714_CR37","doi-asserted-by":"crossref","unstructured":"Tang J, Qu M, Wang M, Zhang M, Yan J, Mei Q (2015b) Line: large-scale information network embedding. In: Proceedings of the 24th international conference on World Wide Web. ACM, pp 1067\u20131077","DOI":"10.1145\/2736277.2741093"},{"issue":"5500","key":"714_CR38","doi-asserted-by":"publisher","first-page":"2319","DOI":"10.1126\/science.290.5500.2319","volume":"290","author":"JB Tenenbaum","year":"2000","unstructured":"Tenenbaum JB, De Silva V, Langford JC (2000) A global geometric framework for nonlinear dimensionality reduction. Science 290(5500):2319\u20132323","journal-title":"Science"},{"key":"714_CR39","doi-asserted-by":"crossref","unstructured":"Tsitsulin A, Mottin D, Karras P, M\u00fcller E (2018) Verse: versatile graph embeddings from similarity measures. In: Proceedings of the 2018 World Wide Web Conference, pp 539\u2013548","DOI":"10.1145\/3178876.3186120"},{"issue":"1","key":"714_CR40","first-page":"3221","volume":"15","author":"L Van Der Maaten","year":"2014","unstructured":"Van Der Maaten L (2014) Accelerating T-SNE using tree-based algorithms. J Mach Learn Res 15(1):3221\u20133245","journal-title":"J Mach Learn Res"},{"issue":"1","key":"714_CR41","doi-asserted-by":"publisher","first-page":"35","DOI":"10.26599\/BDMA.2018.9020029","volume":"2","author":"Y Wang","year":"2020","unstructured":"Wang Y, Yao Y, Tong H, Feng X, Jian L (2020) A brief review of network embedding. Big Data Min Anal 2(1):35\u201347","journal-title":"Big Data Min Anal"},{"key":"714_CR42","unstructured":"Yang Z, Tang J, Cohen W (2015) Multi-modal Bayesian embeddings for learning social knowledge graphs. arXiv preprint arXiv:1508.00715"},{"key":"714_CR43","unstructured":"Zhang D, Yin J, Zhu X, Zhang C (2017) Network representation learning: a survey. arXiv:1801.05852 [cs, stat]"},{"key":"714_CR44","doi-asserted-by":"crossref","unstructured":"Zhang Y, Lu J, Shai O (2018) Improve network embeddings with regularization. In: Proceedings of the 27th ACM international conference on information and knowledge management, pp 1643\u20131646","DOI":"10.1145\/3269206.3269320"},{"issue":"3","key":"714_CR45","doi-asserted-by":"publisher","first-page":"1119","DOI":"10.1007\/s11192-019-03010-5","volume":"118","author":"F Zhao","year":"2019","unstructured":"Zhao F, Zhang Y, Jianguo L, Shai O (2019) Measuring academic influence using heterogeneous author-citation networks. Scientometrics 118(3):1119\u20131140. https:\/\/doi.org\/10.1007\/s11192-019-03010-5","journal-title":"Scientometrics"},{"key":"714_CR46","doi-asserted-by":"crossref","unstructured":"Zhou C, Liu Y, Liu X, Liu Z, Gao J (2017a) Scalable graph embedding for asymmetric proximity. In: Proceedings of the thirty-first AAAI conference on artificial intelligence, pp 2942\u20132948","DOI":"10.1609\/aaai.v31i1.10878"},{"key":"714_CR47","doi-asserted-by":"crossref","unstructured":"Zhou C, Liu Y, Liu X, Liu Z, Gao J (2017b) Scalable graph embedding for asymmetric proximity. In: Thirty-first AAAI conference on artificial intelligence","DOI":"10.1609\/aaai.v31i1.10878"}],"container-title":["Social Network Analysis and Mining"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13278-020-00714-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s13278-020-00714-y\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13278-020-00714-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,23]],"date-time":"2024-08-23T06:06:40Z","timestamp":1724393200000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s13278-020-00714-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,1,29]]},"references-count":44,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2021,12]]}},"alternative-id":["714"],"URL":"https:\/\/doi.org\/10.1007\/s13278-020-00714-y","relation":{},"ISSN":["1869-5450","1869-5469"],"issn-type":[{"type":"print","value":"1869-5450"},{"type":"electronic","value":"1869-5469"}],"subject":[],"published":{"date-parts":[[2021,1,29]]},"assertion":[{"value":"1 August 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 October 2020","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 December 2020","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 January 2021","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}],"article-number":"15"}}