{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,27]],"date-time":"2026-05-27T12:36:46Z","timestamp":1779885406846,"version":"3.53.1"},"reference-count":36,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2022,9,26]],"date-time":"2022-09-26T00:00:00Z","timestamp":1664150400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,9,26]],"date-time":"2022-09-26T00:00:00Z","timestamp":1664150400000},"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":["Knowl Inf Syst"],"published-print":{"date-parts":[[2023,1]]},"DOI":"10.1007\/s10115-022-01706-4","type":"journal-article","created":{"date-parts":[[2022,9,26]],"date-time":"2022-09-26T06:02:32Z","timestamp":1664172152000},"page":"111-132","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["MG2Vec+: A multi-headed graph attention network for multigraph embedding"],"prefix":"10.1007","volume":"65","author":[{"given":"Aman","family":"Roy","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shravika","family":"Mittal","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tanmoy","family":"Chakraborty","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,9,26]]},"reference":[{"key":"1706_CR1","unstructured":"Abu-El-Haija S, Perozzi B, Al-Rfou R, Alemi A (2017a) Watch your step: learning graph embeddings through attention. CoRR. arXiv:1710.09599"},{"key":"1706_CR2","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1016\/S0378-8733(03)00009-1","volume":"25","author":"LA Adamic","year":"2001","unstructured":"Adamic LA, Adar E (2001) Friends and neighbors on the web. Soc Netw 25:211\u2013230","journal-title":"Soc Netw"},{"key":"1706_CR3","doi-asserted-by":"crossref","unstructured":"Backstrom L, Leskovec J (2011) Supervised random walks: predicting and recommending links in social networks. In: WSDM, pp 635\u2013644","DOI":"10.1145\/1935826.1935914"},{"issue":"1","key":"1706_CR4","doi-asserted-by":"publisher","first-page":"159","DOI":"10.1007\/s10115-018-1156-3","volume":"57","author":"V Bhatia","year":"2018","unstructured":"Bhatia V, Rani R (2018) Dfuzzy: a deep learning-based fuzzy clustering model for large graphs. Knowl Inf Syst 57(1):159\u2013181. https:\/\/doi.org\/10.1007\/s10115-018-1156-3","journal-title":"Knowl Inf Syst"},{"key":"1706_CR5","unstructured":"Bruna J, Zaremba W, Szlam A, LeCun Y (2013) Spectral networks and locally connected networks on graphs. CoRR. arXiv:1312.6203"},{"key":"1706_CR6","doi-asserted-by":"crossref","unstructured":"Chakraborty T, Kumar S, Goyal P, Ganguly N, Mukherjee A (2014) Towards a stratified learning approach to predict future citation counts. In: JCDL, pp 351\u2013360","DOI":"10.1109\/JCDL.2014.6970190"},{"key":"1706_CR7","doi-asserted-by":"crossref","unstructured":"Chang S, Han W, Tang J, Qi GJ, Aggarwal CC, Huang TS (2015) Heterogeneous network embedding via deep architectures. In: ACM SIGKDD, pp 119\u2013128","DOI":"10.1145\/2783258.2783296"},{"key":"1706_CR8","unstructured":"Chen S, Niu S, Akoglu L, Kova\u010devi\u0107 J, Faloutsos C (2017) Fast, warped graph embedding: unifying framework and one-click algorithm. arXiv:1702.05764"},{"key":"1706_CR9","doi-asserted-by":"crossref","unstructured":"Chen H, Yin H, Wang W, Wang H, Nguyen QVH, Li X (2018) PME: projected metric embedding on heterogeneous networks for link prediction. In: ACM SIGKDD, ACM, pp 1177\u20131186","DOI":"10.1145\/3219819.3219986"},{"issue":"6","key":"1706_CR10","doi-asserted-by":"publisher","first-page":"2281","DOI":"10.1007\/s10115-019-01422-6","volume":"62","author":"Z Cui","year":"2020","unstructured":"Cui Z, Park N, Chakraborty T (2020) Incremental community discovery via latent network representation and probabilistic inference. Knowl Inf Syst 62(6):2281\u20132300. https:\/\/doi.org\/10.1007\/s10115-019-01422-6","journal-title":"Knowl Inf Syst"},{"key":"1706_CR11","doi-asserted-by":"crossref","unstructured":"Dong Y, Chawla NV, Swami A (2017) Metapath2vec: scalable representation learning for heterogeneous networks. In: ACM SIGKDD, pp 135\u2013144","DOI":"10.1145\/3097983.3098036"},{"key":"1706_CR12","doi-asserted-by":"crossref","unstructured":"Grover A, Leskovec J (2016) Node2vec: scalable feature learning for networks. In: ACM SIGKDD, New York, NY, USA, pp 855\u2013864","DOI":"10.1145\/2939672.2939754"},{"key":"1706_CR13","doi-asserted-by":"crossref","unstructured":"Guo Q, Cozzo E, Zheng Z, Moreno Y (2016) L\u00e9vy random walks on multiplex networks. Sci Rep 6","DOI":"10.1038\/srep37641"},{"key":"1706_CR14","unstructured":"Hamilton WL, Ying R, Leskovec J (2017) Inductive representation learning on large graphs. CoRR. arXiv:1706.02216"},{"key":"1706_CR15","unstructured":"Kipf TN, Welling M (2016) Variational graph auto-encoders. NIPS 2016. arXiv:1611.07308"},{"key":"1706_CR16","unstructured":"Li Y, Tarlow D, Brockschmidt M, Zemel R (2015) Gated graph sequence neural networks. arXiv:1511.05493"},{"issue":"12","key":"1706_CR17","doi-asserted-by":"publisher","first-page":"2257","DOI":"10.1109\/TKDE.2018.2819980","volume":"30","author":"L Liao","year":"2018","unstructured":"Liao L, He X, Zhang H, Chua T (2018) Attributed social network embedding. IEEE Trans Knowl Data Eng 30(12):2257\u20132270","journal-title":"IEEE Trans Knowl Data Eng"},{"issue":"7","key":"1706_CR18","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. JASIST 58(7):1019\u20131031","journal-title":"JASIST"},{"key":"1706_CR19","doi-asserted-by":"crossref","unstructured":"Liu W, Chen PY, Yeung S, Suzumura T, Chen L (2017) Principled multilayer network embedding. In: ICDMW pp 134\u2013141","DOI":"10.1109\/ICDMW.2017.23"},{"issue":"7","key":"1706_CR20","doi-asserted-by":"publisher","first-page":"2685","DOI":"10.1007\/s10115-019-01433-3","volume":"62","author":"G Liu","year":"2020","unstructured":"Liu G, Guo J, Zuo Y, Wu J, Ry Guo (2020) Fraud detection via behavioral sequence embedding. Knowl Inf Syst 62(7):2685\u20132708. https:\/\/doi.org\/10.1007\/s10115-019-01433-3","journal-title":"Knowl Inf Syst"},{"key":"1706_CR21","doi-asserted-by":"crossref","unstructured":"Ma Y, Ren Z, Jiang Z, Tang J, Yin D (2018) Multi-dimensional network embedding with hierarchical structure. In: WSDM, pp 387\u2013395","DOI":"10.1145\/3159652.3159680"},{"key":"1706_CR22","unstructured":"Mikolov T, Chen K, Corrado G, Dean J (2013a) Efficient estimation of word representations in vector space. CoRR. arXiv:1301.3781"},{"key":"1706_CR23","unstructured":"Mikolov T, Sutskever I, Chen K, Corrado G, Dean J (2013b) Distributed representations of words and phrases and their compositionality. In: NIPS, pp 3111\u20133119"},{"key":"1706_CR24","doi-asserted-by":"publisher","first-page":"025102","DOI":"10.1103\/PhysRevE.64.025102","volume":"64","author":"MEJ Newman","year":"2001","unstructured":"Newman MEJ (2001) Clustering and preferential attachment in growing networks. Phys Rev E 64:025102","journal-title":"Phys Rev E"},{"key":"1706_CR25","doi-asserted-by":"crossref","unstructured":"Perozzi B, Al-Rfou R, Skiena S (2014) Deepwalk: online learning of social representations. In: ACM SIGKDD, New York, NY, USA, pp 701\u2013710","DOI":"10.1145\/2623330.2623732"},{"key":"1706_CR26","doi-asserted-by":"crossref","unstructured":"Roy A, Kumar V, Mukherjee D, Chakraborty T (2020) Learning multigraph node embeddings using guided l\u00e9vy flights. In: Pacific\u2013Asia conference on knowledge discovery and data mining. Springer, Berlin, pp 524\u2013537","DOI":"10.1007\/978-3-030-47426-3_41"},{"key":"1706_CR27","doi-asserted-by":"publisher","first-page":"593","DOI":"10.1007\/978-3-319-93417-4_38","volume-title":"The semantic web","author":"M Schlichtkrull","year":"2018","unstructured":"Schlichtkrull M, Kipf TN, Bloem P, van den Berg R, Titov I, Welling M (2018) Modeling relational data with graph convolutional networks. In: Gangemi A, Navigli R, Vidal ME, Hitzler P, Troncy R, Hollink L, Tordai A, Alam M (eds) The semantic web. Springer, Cham, pp 593\u2013607"},{"issue":"2","key":"1706_CR28","first-page":"357","volume":"31","author":"C Shi","year":"2019","unstructured":"Shi C, Hu B, Zhao WX, Philip SY (2019) Heterogeneous information network embedding for recommendation. IEEE TKDE 31(2):357\u2013370","journal-title":"IEEE TKDE"},{"issue":"1","key":"1706_CR29","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1111\/j.1467-9531.2006.00176.x","volume":"36","author":"TA Snijders","year":"2006","unstructured":"Snijders TA, Pattison PE, Robins GL, Handcock MS (2006) New specifications for exponential random graph models. Sociol Methodol 36(1):99\u2013153","journal-title":"Sociol Methodol"},{"key":"1706_CR30","doi-asserted-by":"publisher","first-page":"447","DOI":"10.1007\/s10618-010-0210-x","volume":"23","author":"L Tang","year":"2010","unstructured":"Tang L, Liu H (2010) Leveraging social media networks for classification. Data Min Knowl Discov 23:447\u2013478","journal-title":"Data Min Knowl Discov"},{"key":"1706_CR31","doi-asserted-by":"crossref","unstructured":"Tang J, Qu M, Wang M, Zhang M, Yan J, Mei Q (2015) Line: large-scale information network embedding. In: WWW, pp 1067\u20131077","DOI":"10.1145\/2736277.2741093"},{"key":"1706_CR32","unstructured":"Veli\u010dkovi\u0107 P, Cucurull G, Casanova A, Romero A, Li\u00f2 P, Bengio Y (2018) Graph attention networks. CoRR. arXiv:1710.10903"},{"issue":"4","key":"1706_CR33","doi-asserted-by":"publisher","first-page":"1286","DOI":"10.2307\/2577271","volume":"57","author":"LM Verbrugge","year":"1979","unstructured":"Verbrugge LM (1979) Multiplexity in adult friendships. Soc Forces 57(4):1286\u20131309","journal-title":"Soc Forces"},{"key":"1706_CR34","doi-asserted-by":"crossref","unstructured":"Verma J, Gupta S, Mukherjee D, Chakraborty T (2019) Heterogeneous edge embeddings for friend recommendation. arXiv:1902.03124","DOI":"10.1007\/978-3-030-15719-7_22"},{"key":"1706_CR35","unstructured":"You J, Ying R, Ren X, Hamilton WL, Leskovec J (2018) Graphrnn: a deep generative model for graphs. CoRR. arXiv:1802.08773"},{"key":"1706_CR36","doi-asserted-by":"crossref","unstructured":"Zhang H, Qiu L, Yi L, Song Y (2018) Scalable multiplex network embedding. In: IJCAI, pp 3082\u20133088","DOI":"10.24963\/ijcai.2018\/428"}],"container-title":["Knowledge and Information Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10115-022-01706-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10115-022-01706-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10115-022-01706-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,17]],"date-time":"2023-01-17T02:04:21Z","timestamp":1673921061000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10115-022-01706-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9,26]]},"references-count":36,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2023,1]]}},"alternative-id":["1706"],"URL":"https:\/\/doi.org\/10.1007\/s10115-022-01706-4","relation":{},"ISSN":["0219-1377","0219-3116"],"issn-type":[{"value":"0219-1377","type":"print"},{"value":"0219-3116","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,9,26]]},"assertion":[{"value":"28 October 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 April 2022","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 April 2022","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 September 2022","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}