{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T03:55:55Z","timestamp":1776138955237,"version":"3.50.1"},"reference-count":142,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2023,9,7]],"date-time":"2023-09-07T00:00:00Z","timestamp":1694044800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,9,7]],"date-time":"2023-09-07T00:00:00Z","timestamp":1694044800000},"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":["J Supercomput"],"published-print":{"date-parts":[[2024,2]]},"DOI":"10.1007\/s11227-023-05591-8","type":"journal-article","created":{"date-parts":[[2023,9,7]],"date-time":"2023-09-07T07:01:46Z","timestamp":1694070106000},"page":"3902-3942","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":73,"title":["A comprehensive survey of link prediction methods"],"prefix":"10.1007","volume":"80","author":[{"given":"Djihad","family":"Arrar","sequence":"first","affiliation":[]},{"given":"Nadjet","family":"Kamel","sequence":"additional","affiliation":[]},{"given":"Abdelaziz","family":"Lakhfif","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,9,7]]},"reference":[{"key":"5591_CR1","doi-asserted-by":"crossref","unstructured":"Su Z, Zheng X, Ai J, Shen Y, Zhang X (2020) Link prediction in recommender systems based on vector similarity. Physica A 560:125154","DOI":"10.1016\/j.physa.2020.125154"},{"key":"5591_CR2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s40537-020-00387-6","volume":"8","author":"M Vahidi Farashah","year":"2021","unstructured":"Vahidi Farashah M, Etebarian A, Azmi R, Ebrahimzadeh Dastjerdi R (2021) A hybrid recommender system based-on link prediction for movie baskets analysis. J Big Data 8:1\u201324","journal-title":"J Big Data"},{"issue":"8","key":"5591_CR3","volume":"29","author":"Z Su","year":"2019","unstructured":"Su Z, Zheng X, Ai J, Shang L, Shen Y (2019) Link prediction in recommender systems with confidence measures. Chaos Inter J Nonlinear Sci 29(8):083133","journal-title":"Chaos Inter J Nonlinear Sci"},{"key":"5591_CR4","doi-asserted-by":"crossref","DOI":"10.1016\/j.physa.2020.124650","volume":"554","author":"AM Abdolhosseini-Qomi","year":"2020","unstructured":"Abdolhosseini-Qomi AM, Yazdani N, Asadpour M (2020) Overlapping communities and the prediction of missing links in multiplex networks. Physica A 554:124650","journal-title":"Physica A"},{"key":"5591_CR5","volume":"166","author":"NN Daud","year":"2020","unstructured":"Daud NN, Ab Hamid SH, Saadoon M, Sahran F, Anuar NB (2020) Applications of link prediction in social networks: a review. J Netw Comput Appl 166:102716","journal-title":"J Netw Comput Appl"},{"issue":"4","key":"5591_CR6","doi-asserted-by":"crossref","first-page":"0154244","DOI":"10.1371\/journal.pone.0154244","volume":"11","author":"G Berlusconi","year":"2016","unstructured":"Berlusconi G, Calderoni F, Parolini N, Verani M, Piccardi C (2016) Link prediction in criminal networks: a tool for criminal intelligence analysis. PLoS ONE 11(4):0154244","journal-title":"PLoS ONE"},{"issue":"1","key":"5591_CR7","doi-asserted-by":"crossref","first-page":"8","DOI":"10.3390\/computers8010008","volume":"8","author":"M Lim","year":"2019","unstructured":"Lim M, Abdullah A, Jhanjhi N, Supramaniam M (2019) Hidden link prediction in criminal networks using the deep reinforcement learning technique. Computers 8(1):8","journal-title":"Computers"},{"issue":"6","key":"5591_CR8","doi-asserted-by":"crossref","first-page":"1467","DOI":"10.3390\/s19061467","volume":"19","author":"W Alnumay","year":"2019","unstructured":"Alnumay W, Ghosh U, Chatterjee P (2019) A trust-based predictive model for mobile ad hoc network in internet of things. Sensors 19(6):1467","journal-title":"Sensors"},{"issue":"4","key":"5591_CR9","doi-asserted-by":"crossref","DOI":"10.1103\/PhysRevE.95.042317","volume":"95","author":"C De Bacco","year":"2017","unstructured":"De Bacco C, Power EA, Larremore DB, Moore C (2017) Community detection, link prediction, and layer interdependence in multilayer networks. Phys Rev E 95(4):042317","journal-title":"Phys Rev E"},{"issue":"3","key":"5591_CR10","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1007\/s13278-010-0004-6","volume":"1","author":"I Esslimani","year":"2011","unstructured":"Esslimani I, Brun A, Boyer A (2011) Densifying a behavioral recommender system by social networks link prediction methods. Soc Netw Anal Min 1(3):159\u2013172","journal-title":"Soc Netw Anal Min"},{"key":"5591_CR11","doi-asserted-by":"crossref","unstructured":"Huang Z, Zeng DD (2006) A link prediction approach to anomalous email detection. In 2006 IEEE International Conference on Systems, Man and Cybernetics, vol 2, pp 1131\u20131136. IEEE","DOI":"10.1109\/ICSMC.2006.384552"},{"key":"5591_CR12","doi-asserted-by":"crossref","DOI":"10.1016\/j.compbiomed.2021.104772","volume":"137","author":"E Nasiri","year":"2021","unstructured":"Nasiri E, Berahmand K, Rostami M, Dabiri M (2021) A novel link prediction algorithm for protein-protein interaction networks by attributed graph embedding. Comput Biol Med 137:104772","journal-title":"Comput Biol Med"},{"issue":"1","key":"5591_CR13","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/srep01613","volume":"3","author":"CV Cannistraci","year":"2013","unstructured":"Cannistraci CV, Alanis-Lobato G, Ravasi T (2013) From link-prediction in brain connectomes and protein interactomes to the local-community-paradigm in complex networks. Sci Rep 3(1):1\u201314","journal-title":"Sci Rep"},{"issue":"1","key":"5591_CR14","first-page":"1","volume":"58","author":"P Wang","year":"2015","unstructured":"Wang P, Xu B, Wu Y, Zhou X (2015) Link prediction in social networks: the state-of-the-art. Sci China Inf Sci 58(1):1\u201338","journal-title":"Sci China Inf Sci"},{"issue":"4","key":"5591_CR15","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3012704","volume":"49","author":"V Mart\u00ednez","year":"2016","unstructured":"Mart\u00ednez V, Berzal F, Cubero J-C (2016) A survey of link prediction in complex networks. ACM Comput Surv 49(4):1\u201333","journal-title":"ACM Comput Surv"},{"key":"5591_CR16","volume":"553","author":"A Kumar","year":"2020","unstructured":"Kumar A, Singh SS, Singh K, Biswas B (2020) Link prediction techniques, applications, and performance: a survey. Physica A 553:124289","journal-title":"Physica A"},{"issue":"6","key":"5591_CR17","doi-asserted-by":"crossref","first-page":"1150","DOI":"10.1016\/j.physa.2010.11.027","volume":"390","author":"L L\u00fc","year":"2011","unstructured":"L\u00fc L, Zhou T (2011) Link prediction in complex networks: a survey. Physica A 390(6):1150\u20131170","journal-title":"Physica A"},{"issue":"1","key":"5591_CR18","doi-asserted-by":"crossref","first-page":"7147","DOI":"10.1038\/s41598-017-07315-4","volume":"7","author":"T Wang","year":"2017","unstructured":"Wang T, He X-S, Zhou M-Y, Fu Z-Q (2017) Link prediction in evolving networks based on popularity of nodes. Sci Rep 7(1):7147","journal-title":"Sci Rep"},{"key":"5591_CR19","doi-asserted-by":"crossref","first-page":"226","DOI":"10.1016\/j.knosys.2017.06.035","volume":"132","author":"Z Zhang","year":"2017","unstructured":"Zhang Z, Wen J, Sun L, Deng Q, Su S, Yao P (2017) Efficient incremental dynamic link prediction algorithms in social network. Knowl-Based Syst 132:226\u2013235","journal-title":"Knowl-Based Syst"},{"key":"5591_CR20","doi-asserted-by":"crossref","unstructured":"Lei K, Qin M, Bai B, Zhang G, Yang M (2019) Gcn-gan: a non-linear temporal link prediction model for weighted dynamic networks. In: IEEE INFOCOM 2019-IEEE Conference on Computer Communications, pp 388\u2013396. IEEE","DOI":"10.1109\/INFOCOM.2019.8737631"},{"key":"5591_CR21","doi-asserted-by":"crossref","first-page":"562","DOI":"10.1016\/j.neucom.2021.02.101","volume":"461","author":"AK Singh","year":"2021","unstructured":"Singh AK, Lakshmanan K (2021) Pilhnb: popularity, interests, location used hidden naive bayesian-based model for link prediction in dynamic social networks. Neurocomputing 461:562\u2013576","journal-title":"Neurocomputing"},{"key":"5591_CR22","doi-asserted-by":"crossref","first-page":"152","DOI":"10.1016\/j.ins.2018.06.051","volume":"463","author":"E B\u00fct\u00fcn","year":"2018","unstructured":"B\u00fct\u00fcn E, Kaya M, Alhajj R (2018) Extension of neighbor-based link prediction methods for directed, weighted and temporal social networks. Inf Sci 463:152\u2013165","journal-title":"Inf Sci"},{"key":"5591_CR23","doi-asserted-by":"crossref","DOI":"10.1016\/j.physa.2019.04.214","volume":"536","author":"S Najari","year":"2019","unstructured":"Najari S, Salehi M, Ranjbar V, Jalili M (2019) Link prediction in multiplex networks based on interlayer similarity. Physica A 536:120978","journal-title":"Physica A"},{"key":"5591_CR24","doi-asserted-by":"crossref","DOI":"10.1016\/j.chaos.2021.111230","volume":"151","author":"E Nasiri","year":"2021","unstructured":"Nasiri E, Berahmand K, Li Y (2021) A new link prediction in multiplex networks using topologically biased random walks. Chaos Solitons Fractals 151:111230","journal-title":"Chaos Solitons Fractals"},{"issue":"2","key":"5591_CR25","doi-asserted-by":"crossref","first-page":"494","DOI":"10.1109\/TNNLS.2021.3070843","volume":"33","author":"S Ji","year":"2021","unstructured":"Ji S, Pan S, Cambria E, Marttinen P, Philip SY (2021) A survey on knowledge graphs: representation, acquisition, and applications. IEEE Trans Neural Netw Learn Syst 33(2):494\u2013514","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"issue":"2","key":"5591_CR26","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3424672","volume":"15","author":"A Rossi","year":"2021","unstructured":"Rossi A, Barbosa D, Firmani D, Matinata A, Merialdo P (2021) Knowledge graph embedding for link prediction: a comparative analysis. ACM Trans Knowl Discov Data 15(2):1\u201349","journal-title":"ACM Trans Knowl Discov Data"},{"key":"5591_CR27","doi-asserted-by":"crossref","unstructured":"Tao Y, Li Y, Wu Z (2021) Temporal link prediction via reinforcement learning. In ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp 3470\u20133474. IEEE","DOI":"10.1109\/ICASSP39728.2021.9413413"},{"key":"5591_CR28","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.inffus.2018.04.004","volume":"46","author":"W Yuan","year":"2019","unstructured":"Yuan W, He K, Guan D, Zhou L, Li C (2019) Graph kernel based link prediction for signed social networks. Inform Fusion 46:1\u201310","journal-title":"Inform Fusion"},{"key":"5591_CR29","doi-asserted-by":"crossref","DOI":"10.1016\/j.physa.2022.128008","volume":"605","author":"S Mishra","year":"2022","unstructured":"Mishra S, Singh SS, Kumar A, Biswas B (2022) Elp: link prediction in social networks based on ego network perspective. Physica A 605:128008","journal-title":"Physica A"},{"key":"5591_CR30","volume":"159","author":"K Chi","year":"2022","unstructured":"Chi K, Qu H, Yin G (2022) Link prediction for existing links in dynamic networks based on the attraction force. Chaos Solitons Fractals 159:112120","journal-title":"Chaos Solitons Fractals"},{"key":"5591_CR31","first-page":"1","volume":"5","author":"R Giubilei","year":"2022","unstructured":"Giubilei R, Brutti P (2022) Supervised classification for link prediction in facebook ego networks with anonymized profile information. J Classif 5:1\u201324","journal-title":"J Classif"},{"key":"5591_CR32","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2020.106168","volume":"203","author":"N Shan","year":"2020","unstructured":"Shan N, Li L, Zhang Y, Bai S, Chen X (2020) Supervised link prediction in multiplex networks. Knowl-Based Syst 203:106168","journal-title":"Knowl-Based Syst"},{"issue":"4","key":"5591_CR33","doi-asserted-by":"crossref","DOI":"10.1016\/j.joi.2021.101178","volume":"15","author":"F Karimi","year":"2021","unstructured":"Karimi F, Lotfi S, Izadkhah H (2021) Community-guided link prediction in multiplex networks. J Informet 15(4):101178","journal-title":"J Informet"},{"key":"5591_CR34","volume":"257","author":"Y Yang","year":"2022","unstructured":"Yang Y, Wang L, Liu D (2022) Anchor link prediction across social networks based on multiple consistency. Knowl-Based Syst 257:109939","journal-title":"Knowl-Based Syst"},{"key":"5591_CR35","doi-asserted-by":"crossref","DOI":"10.1016\/j.jocs.2022.101606","volume":"60","author":"S Mishra","year":"2022","unstructured":"Mishra S, Singh SS, Kumar A, Biswas B (2022) Mnerlp-mul: merged node and edge relevance based link prediction in multiplex networks. J Comput Sci 60:101606","journal-title":"J Comput Sci"},{"key":"5591_CR36","volume":"219","author":"H Luo","year":"2021","unstructured":"Luo H, Li L, Zhang Y, Fang S, Chen X (2021) Link prediction in multiplex networks using a novel multiple-attribute decision-making approach. Knowl-Based Syst 219:106904","journal-title":"Knowl-Based Syst"},{"issue":"08","key":"5591_CR37","doi-asserted-by":"crossref","first-page":"1750101","DOI":"10.1142\/S0129183117501017","volume":"28","author":"Y Yao","year":"2017","unstructured":"Yao Y, Zhang R, Yang F, Yuan Y, Sun Q, Qiu Y, Hu R (2017) Link prediction via layer relevance of multiplex networks. Int J Mod Phys C 28(08):1750101","journal-title":"Int J Mod Phys C"},{"key":"5591_CR38","volume":"69","author":"F Guo","year":"2023","unstructured":"Guo F, Zhou W, Wang Z, Ju C, Ji S, Lu Q (2023) A link prediction method based on topological nearest-neighbors similarity in directed networks. J Comput Sci 69:102002","journal-title":"J Comput Sci"},{"key":"5591_CR39","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2022.108977","volume":"133","author":"A Agibetov","year":"2023","unstructured":"Agibetov A (2023) Neural graph embeddings as explicit low-rank matrix factorization for link prediction. Pattern Recogn 133:108977","journal-title":"Pattern Recogn"},{"key":"5591_CR40","volume":"159","author":"L Lv","year":"2022","unstructured":"Lv L, Bardou D, Hu P, Liu Y, Yu G (2022) Graph regularized nonnegative matrix factorization for link prediction in directed temporal networks using pagerank centrality. Chaos Solitons Fractals 159:112107","journal-title":"Chaos Solitons Fractals"},{"key":"5591_CR41","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2020.113896","volume":"165","author":"H Ghorbanzadeh","year":"2021","unstructured":"Ghorbanzadeh H, Sheikhahmadi A, Jalili M, Sulaimany S (2021) A hybrid method of link prediction in directed graphs. Expert Syst Appl 165:113896","journal-title":"Expert Syst Appl"},{"issue":"3","key":"5591_CR42","doi-asserted-by":"crossref","first-page":"1080","DOI":"10.1109\/TKDE.2020.2997861","volume":"34","author":"X Du","year":"2020","unstructured":"Du X, Yan J, Zhang R, Zha H (2020) Cross-network skip-gram embedding for joint network alignment and link prediction. IEEE Trans Knowl Data Eng 34(3):1080\u20131095","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"5591_CR43","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2020.113290","volume":"148","author":"G Chen","year":"2020","unstructured":"Chen G, Xu C, Wang J, Feng J, Feng J (2020) Nonnegative matrix factorization for link prediction in directed complex networks using pagerank and asymmetric link clustering information. Expert Syst Appl 148:113290","journal-title":"Expert Syst Appl"},{"key":"5591_CR44","doi-asserted-by":"crossref","first-page":"316","DOI":"10.1016\/j.ins.2020.05.128","volume":"541","author":"S-Y Liu","year":"2020","unstructured":"Liu S-Y, Xiao J, Xu X-K (2020) Sign prediction by motif naive bayes model in social networks. Inf Sci 541:316\u2013331","journal-title":"Inf Sci"},{"key":"5591_CR45","volume":"31","author":"F Abbasi","year":"2022","unstructured":"Abbasi F, Muzammal M, Qureshi KN, Javed IT, Margaria T, Crespi N (2022) Exploiting optimised communities in directed weighted graphs for link prediction. Online Soc Netw Media 31:100222","journal-title":"Online Soc Netw Media"},{"issue":"6","key":"5591_CR46","doi-asserted-by":"crossref","first-page":"3699","DOI":"10.1109\/TSMC.2019.2932913","volume":"51","author":"J Chen","year":"2019","unstructured":"Chen J, Zhang J, Xu X, Fu C, Zhang D, Zhang Q, Xuan Q (2019) E-lstm-d: a deep learning framework for dynamic network link prediction. IEEE Trans Syst Man Cybern Syst 51(6):3699\u20133712","journal-title":"IEEE Trans Syst Man Cybern Syst"},{"key":"5591_CR47","unstructured":"Rossi E, Chamberlain B, Frasca F, Eynard D, Monti F, Bronstein M (xxxx) Temporal graph networks for deep learning on dynamic graphs"},{"key":"5591_CR48","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1016\/j.neucom.2022.07.030","volume":"505","author":"L Yang","year":"2022","unstructured":"Yang L, Jiang X, Ji Y, Wang H, Abraham A, Liu H (2022) Gated graph convolutional network based on spatio-temporal semi-variogram for link prediction in dynamic complex network. Neurocomputing 505:289\u2013303","journal-title":"Neurocomputing"},{"key":"5591_CR49","doi-asserted-by":"crossref","unstructured":"Sankar A, Wu Y, Gou L, Zhang W, Yang H (2020) Dysat: deep neural representation learning on dynamic graphs via self-attention networks. In: Proceedings of the 13th International Conference on Web Search and Data Mining, pp 519\u2013527","DOI":"10.1145\/3336191.3371845"},{"issue":"3","key":"5591_CR50","volume":"60","author":"D Huang","year":"2023","unstructured":"Huang D, Lei F (2023) Temporal group-aware graph diffusion networks for dynamic link prediction. Inform Process Manag 60(3):103292","journal-title":"Inform Process Manag"},{"key":"5591_CR51","volume":"170","author":"J Wu","year":"2023","unstructured":"Wu J, He L, Jia T, Tao L (2023) Temporal link prediction based on node dynamics. Chaos Solitons Fractals 170:113402","journal-title":"Chaos Solitons Fractals"},{"key":"5591_CR52","volume":"62","author":"M Kumar","year":"2022","unstructured":"Kumar M, Mishra S, Pandey RD, Biswas B (2022) Cflp: a new cost based feature for link prediction in dynamic networks. J Comput Sci 62:101726","journal-title":"J Comput Sci"},{"key":"5591_CR53","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.socnet.2020.11.001","volume":"65","author":"L Zou","year":"2021","unstructured":"Zou L, Wang C, Zeng A, Fan Y, Di Z (2021) Link prediction in growing networks with aging. Soc Netw 65:1\u20137","journal-title":"Soc Netw"},{"key":"5591_CR54","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1016\/j.knosys.2018.05.027","volume":"156","author":"CP Muniz","year":"2018","unstructured":"Muniz CP, Goldschmidt R, Choren R (2018) Combining contextual, temporal and topological information for unsupervised link prediction in social networks. Knowl-Based Syst 156:129\u2013137","journal-title":"Knowl-Based Syst"},{"key":"5591_CR55","doi-asserted-by":"crossref","first-page":"184797","DOI":"10.1109\/ACCESS.2019.2958873","volume":"7","author":"M Lim","year":"2019","unstructured":"Lim M, Abdullah A, Jhanjhi N, Khan MK, Supramaniam M (2019) Link prediction in time-evolving criminal network with deep reinforcement learning technique. IEEE Access 7:184797\u2013184807","journal-title":"IEEE Access"},{"key":"5591_CR56","doi-asserted-by":"crossref","first-page":"90","DOI":"10.1016\/j.patrec.2023.02.004","volume":"167","author":"HA Mohamed","year":"2023","unstructured":"Mohamed HA, Pilutti D, James S, Del Bue A, Pelillo M, Vascon S (2023) Locality-aware subgraphs for inductive link prediction in knowledge graphs. Pattern Recogn Lett 167:90\u201397","journal-title":"Pattern Recogn Lett"},{"key":"5591_CR57","volume":"200","author":"A Zeb","year":"2022","unstructured":"Zeb A, Saif S, Chen J, Haq AU, Gong Z, Zhang D (2022) Complex graph convolutional network for link prediction in knowledge graphs. Expert Syst Appl 200:116796","journal-title":"Expert Syst Appl"},{"issue":"13","key":"5591_CR58","doi-asserted-by":"crossref","first-page":"5839","DOI":"10.1002\/cpe.5839","volume":"34","author":"A Kumari","year":"2022","unstructured":"Kumari A, Behera RK, Sahoo KS, Nayyar A, Kumar Luhach A, Prakash Sahoo S (2022) Supervised link prediction using structured-based feature extraction in social network. Concurr Comput Practice Exp 34(13):5839","journal-title":"Concurr Comput Practice Exp"},{"key":"5591_CR59","doi-asserted-by":"crossref","DOI":"10.1016\/j.physa.2019.122950","volume":"539","author":"S Rafiee","year":"2020","unstructured":"Rafiee S, Salavati C, Abdollahpouri A (2020) Cndp: link prediction based on common neighbors degree penalization. Physica A 539:122950","journal-title":"Physica A"},{"key":"5591_CR60","doi-asserted-by":"crossref","DOI":"10.1016\/j.chaos.2022.112421","volume":"162","author":"M Tang","year":"2022","unstructured":"Tang M, Wang W (2022) Cold-start link prediction integrating community information via multi-nonnegative matrix factorization. Chaos Solitons Fractals 162:112421","journal-title":"Chaos Solitons Fractals"},{"key":"5591_CR61","volume":"620","author":"M Zhou","year":"2023","unstructured":"Zhou M, Han Q, Li M, Li K, Qian Z (2023) Nearest neighbor walk network embedding for link prediction in complex networks. Physica A 620:128757","journal-title":"Physica A"},{"key":"5591_CR62","doi-asserted-by":"crossref","unstructured":"Mavromatis C, Karypis G (2021) Graph infoclust: maximizing coarse-grain mutual information in graphs. In Pacific-Asia Conference on Knowledge Discovery and Data Mining, pp 541\u2013553. Springer","DOI":"10.1007\/978-3-030-75762-5_43"},{"key":"5591_CR63","doi-asserted-by":"crossref","first-page":"62633","DOI":"10.1109\/ACCESS.2019.2907202","volume":"7","author":"J Wang","year":"2019","unstructured":"Wang J, Ma Y, Liu M, Shen W (2019) Link prediction based on community information and its parallelization. IEEE Access 7:62633\u201362645","journal-title":"IEEE Access"},{"key":"5591_CR64","doi-asserted-by":"crossref","DOI":"10.1016\/j.physa.2023.128546","volume":"616","author":"H Yuliansyah","year":"2023","unstructured":"Yuliansyah H, Othman ZA, Bakar AA (2023) A new link prediction method to alleviate the cold-start problem based on extending common neighbor and degree centrality. Physica A 616:128546","journal-title":"Physica A"},{"issue":"1","key":"5591_CR65","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41598-019-56847-4","volume":"10","author":"I Ahmad","year":"2020","unstructured":"Ahmad I, Akhtar MU, Noor S, Shahnaz A (2020) Missing link prediction using common neighbor and centrality based parameterized algorithm. Sci Rep 10(1):1\u20139","journal-title":"Sci Rep"},{"key":"5591_CR66","doi-asserted-by":"crossref","DOI":"10.1016\/j.physa.2020.124980","volume":"557","author":"F Aziz","year":"2020","unstructured":"Aziz F, Gul H, Muhammad I, Uddin I (2020) Link prediction using node information on local paths. Physica A 557:124980","journal-title":"Physica A"},{"issue":"1","key":"5591_CR67","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s13278-019-0618-2","volume":"10","author":"J Ayoub","year":"2020","unstructured":"Ayoub J, Lotfi D, El Marraki M, Hammouch A (2020) Accurate link prediction method based on path length between a pair of unlinked nodes and their degree. Soc Netw Anal Min 10(1):1\u201313","journal-title":"Soc Netw Anal Min"},{"key":"5591_CR68","doi-asserted-by":"crossref","unstructured":"Jibouni A, Lotfi D, El\u00a0Marraki M, Hammouch A (2018) A novel parameter free approach for link prediction. In 2018 6th International Conference on Wireless Networks and Mobile Communications (WINCOM), pp 1\u20136. IEEE","DOI":"10.1109\/WINCOM.2018.8629586"},{"key":"5591_CR69","doi-asserted-by":"crossref","DOI":"10.1016\/j.jocs.2021.101358","volume":"53","author":"G Wang","year":"2021","unstructured":"Wang G, Wang Y, Li J, Liu K (2021) A multidimensional network link prediction algorithm and its application for predicting social relationships. J Comput Sci 53:101358","journal-title":"J Comput Sci"},{"issue":"8","key":"5591_CR70","first-page":"5375","volume":"34","author":"K Berahmand","year":"2022","unstructured":"Berahmand K, Nasiri E, Forouzandeh S, Li Y (2022) A preference random walk algorithm for link prediction through mutual influence nodes in complex networks. J King Saud Univ Comput Inf Sci 34(8):5375\u20135387","journal-title":"J King Saud Univ Comput Inf Sci"},{"key":"5591_CR71","doi-asserted-by":"crossref","first-page":"43233","DOI":"10.1109\/ACCESS.2019.2908208","volume":"7","author":"L Li","year":"2019","unstructured":"Li L, Fang S, Bai S, Xu S, Cheng J, Chen X (2019) Effective link prediction based on community relationship strength. IEEE Access 7:43233\u201343248","journal-title":"IEEE Access"},{"key":"5591_CR72","doi-asserted-by":"crossref","first-page":"402","DOI":"10.1016\/j.ins.2019.11.026","volume":"514","author":"SS Singh","year":"2020","unstructured":"Singh SS, Mishra S, Kumar A, Biswas B (2020) Clp-id: community-based link prediction using information diffusion. Inf Sci 514:402\u2013433","journal-title":"Inf Sci"},{"key":"5591_CR73","first-page":"25","volume":"31","author":"M Zhang","year":"2018","unstructured":"Zhang M, Chen Y (2018) Link prediction based on graph neural networks. Adv Neural Inf Process Syst 31:25","journal-title":"Adv Neural Inf Process Syst"},{"key":"5591_CR74","doi-asserted-by":"crossref","unstructured":"Zhang M, Chen Y (2017) Weisfeiler-lehman neural machine for link prediction. In Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp 575\u2013583","DOI":"10.1145\/3097983.3097996"},{"key":"5591_CR75","unstructured":"Daud NN, Hamid SHA, Seri C, Saadoon M, Anuar NB (2022) Scalable link prediction in twitter using self-configured framework. arXiv preprint arXiv:2208.09798"},{"issue":"5","key":"5591_CR76","doi-asserted-by":"crossref","first-page":"642","DOI":"10.1177\/0165551519891345","volume":"47","author":"MM Keikha","year":"2021","unstructured":"Keikha MM, Rahgozar M, Asadpour M (2021) Deeplink: a novel link prediction framework based on deep learning. J Inf Sci 47(5):642\u2013657","journal-title":"J Inf Sci"},{"key":"5591_CR77","doi-asserted-by":"crossref","unstructured":"Cai L, Ji S (2020) A multi-scale approach for graph link prediction. In Proceedings of the AAAI Conference on Artificial Intelligence, vol 34, pp 3308\u20133315","DOI":"10.1609\/aaai.v34i04.5731"},{"key":"5591_CR78","doi-asserted-by":"crossref","first-page":"2227","DOI":"10.1007\/s00607-021-00982-2","volume":"103","author":"K Berahmand","year":"2021","unstructured":"Berahmand K, Nasiri E, Rostami M, Forouzandeh S (2021) A modified deepwalk method for link prediction in attributed social network. Computing 103:2227\u20132249","journal-title":"Computing"},{"key":"5591_CR79","doi-asserted-by":"crossref","unstructured":"Fu X, Zhang J, Meng Z, King I (2020) Magnn: Metapath aggregated graph neural network for heterogeneous graph embedding. In Proceedings of The Web Conference 2020, pp 2331\u20132341","DOI":"10.1145\/3366423.3380297"},{"key":"5591_CR80","doi-asserted-by":"crossref","unstructured":"Chen H, Yin H, Sun X, Chen T, Gabrys B, Musial K (2020) Multi-level graph convolutional networks for cross-platform anchor link prediction. In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, pp 1503\u20131511","DOI":"10.1145\/3394486.3403201"},{"key":"5591_CR81","doi-asserted-by":"crossref","first-page":"665","DOI":"10.1016\/j.ins.2023.03.022","volume":"634","author":"P Zhang","year":"2023","unstructured":"Zhang P, Chen J, Che C, Zhang L, Jin B, Zhu Y (2023) Iea-gnn: anchor-aware graph neural network fused with information entropy for node classification and link prediction. Inf Sci 634:665\u2013676","journal-title":"Inf Sci"},{"key":"5591_CR82","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2021.115991","volume":"188","author":"G Chen","year":"2022","unstructured":"Chen G, Wang H, Fang Y, Jiang L (2022) Link prediction by deep non-negative matrix factorization. Expert Syst Appl 188:115991","journal-title":"Expert Syst Appl"},{"key":"5591_CR83","doi-asserted-by":"crossref","unstructured":"Cotta L, Bevilacqua B, Ahmed N, Ribeiro B (2023) Causal lifting and link prediction. arXiv preprint arXiv:2302.01198","DOI":"10.1098\/rspa.2023.0121"},{"key":"5591_CR84","doi-asserted-by":"crossref","DOI":"10.1016\/j.asoc.2022.108657","volume":"120","author":"U Zulaika","year":"2022","unstructured":"Zulaika U, Sanchez-Corcuera R, Almeida A, Lopez-de-Ipina D (2022) Lwp-wl: link weight prediction based on cnns and the weisfeiler-lehman algorithm. Appl Soft Comput 120:108657","journal-title":"Appl Soft Comput"},{"key":"5591_CR85","doi-asserted-by":"crossref","first-page":"120325","DOI":"10.1016\/j.eswa.2023.120325","volume":"2","author":"Y Zhao","year":"2023","unstructured":"Zhao Y, Sun Y, Huang Y, Li L, Dong H (2023) Link prediction in heterogeneous networks based on metapath projection and aggregation. Expert Syst Appl 2:120325","journal-title":"Expert Syst Appl"},{"key":"5591_CR86","doi-asserted-by":"crossref","first-page":"1591","DOI":"10.1016\/j.ins.2022.07.030","volume":"608","author":"Y Liu","year":"2022","unstructured":"Liu Y, Liu S, Yu F, Yang X (2022) Link prediction algorithm based on the initial information contribution of nodes. Inf Sci 608:1591\u20131616","journal-title":"Inf Sci"},{"issue":"4","key":"5591_CR87","doi-asserted-by":"crossref","first-page":"452","DOI":"10.1086\/jar.33.4.3629752","volume":"33","author":"WW Zachary","year":"1977","unstructured":"Zachary WW (1977) An information flow model for conflict and fission in small groups. J Anthropol Res 33(4):452\u2013473","journal-title":"J Anthropol Res"},{"key":"5591_CR88","doi-asserted-by":"crossref","first-page":"396","DOI":"10.1007\/s00265-003-0651-y","volume":"54","author":"D Lusseau","year":"2003","unstructured":"Lusseau D, Schneider K, Boisseau OJ, Haase P, Slooten E, Dawson SM (2003) The bottlenose dolphin community of doubtful sound features a large proportion of long-lasting associations: can geographic isolation explain this unique trait? Behav Ecol Sociobiol 54:396\u2013405","journal-title":"Behav Ecol Sociobiol"},{"issue":"14","key":"5591_CR89","doi-asserted-by":"crossref","first-page":"5925","DOI":"10.1073\/pnas.0608361104","volume":"104","author":"H Kreft","year":"2007","unstructured":"Kreft H, Jetz W (2007) Global patterns and determinants of vascular plant diversity. Proc Natl Acad Sci 104(14):5925\u20135930","journal-title":"Proc Natl Acad Sci"},{"issue":"04","key":"5591_CR90","doi-asserted-by":"crossref","first-page":"565","DOI":"10.1142\/S0219525903001067","volume":"6","author":"PM Gleiser","year":"2003","unstructured":"Gleiser PM, Danon L (2003) Community structure in jazz. Adv Complex Syst 6(04):565\u2013573","journal-title":"Adv Complex Syst"},{"key":"5591_CR91","unstructured":"Batagelj V, Mrvar A (2006) Pajek datasets http:\/\/vlado.fmf.uni-lj.si\/pub\/networks\/data\/mix.USAir97.net"},{"key":"5591_CR92","doi-asserted-by":"crossref","unstructured":"Anelli VW, Deli\u0107 A, Sottocornola G, Smith J, Andrade N, Belli L, Bronstein M, Gupta A, Ira\u00a0Ktena S, Lung-Yut-Fong A et al. (2020) Recsys 2020 challenge workshop: engagement prediction on twitter\u2019s home timeline. In Proceedings of the 14th ACM Conference on Recommender Systems, pp 623\u2013627","DOI":"10.1145\/3383313.3411532"},{"key":"5591_CR93","first-page":"58","volume":"25","author":"J Leskovec","year":"2012","unstructured":"Leskovec J, Mcauley J (2012) Learning to discover social circles in ego networks. Adv Neural Inf Process Syst 25:58","journal-title":"Adv Neural Inf Process Syst"},{"key":"5591_CR94","unstructured":"Anonymous: Facebook wall posts network dataset. http:\/\/konect.cc\/networks\/facebook-wosn-wall\/ (2017)"},{"key":"5591_CR95","doi-asserted-by":"crossref","unstructured":"Yin H, Benson AR, Leskovec J, Gleich DF (2017) Local higher-order graph clustering. In Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp 555\u2013564","DOI":"10.1145\/3097983.3098069"},{"issue":"6887","key":"5591_CR96","doi-asserted-by":"crossref","first-page":"399","DOI":"10.1038\/nature750","volume":"417","author":"C Von Mering","year":"2002","unstructured":"Von Mering C, Krause R, Snel B, Cornell M, Oliver SG, Fields S, Bork P (2002) Comparative assessment of large-scale data sets of protein-protein interactions. Nature 417(6887):399\u2013403","journal-title":"Nature"},{"issue":"6684","key":"5591_CR97","doi-asserted-by":"crossref","first-page":"440","DOI":"10.1038\/30918","volume":"393","author":"DJ Watts","year":"1998","unstructured":"Watts DJ, Strogatz SH (1998) Collective dynamics of \u2018small-world\u2019 networks. Nature 393(6684):440\u2013442","journal-title":"Nature"},{"issue":"5","key":"5591_CR98","doi-asserted-by":"crossref","first-page":"911","DOI":"10.1002\/asi.21015","volume":"60","author":"P Panzarasa","year":"2009","unstructured":"Panzarasa P, Opsahl T, Carley KM (2009) Patterns and dynamics of users\u2019 behavior and interaction: network analysis of an online community. J Am Soc Inform Sci Technol 60(5):911\u2013932","journal-title":"J Am Soc Inform Sci Technol"},{"key":"5591_CR99","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1140\/epjds\/s13688-016-0087-z","volume":"5","author":"D Hristova","year":"2016","unstructured":"Hristova D, Noulas A, Brown C, Musolesi M, Mascolo C (2016) A multilayer approach to multiplexity and link prediction in online geo-social networks. EPJ Data Sci 5:1\u201317","journal-title":"EPJ Data Sci"},{"key":"5591_CR100","volume-title":"Representing classroom social structure","author":"M Vickers","year":"1981","unstructured":"Vickers M, Chan S (1981) Representing classroom social structure. Victoria Institute of Secondary Education, Melbourne"},{"key":"5591_CR101","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2023.119680","volume":"219","author":"L Chai","year":"2023","unstructured":"Chai L, Tu L, Yu X, Wang X, Chen J (2023) Link prediction and its optimization based on low-rank representation of network structures. Expert Syst Appl 219:119680","journal-title":"Expert Syst Appl"},{"key":"5591_CR102","doi-asserted-by":"crossref","first-page":"702","DOI":"10.1016\/j.ins.2022.05.079","volume":"606","author":"EP Barracchia","year":"2022","unstructured":"Barracchia EP, Pio G, Bifet A, Gomes HM, Pfahringer B, Ceci M (2022) Lp-robin: link prediction in dynamic networks exploiting incremental node embedding. Inf Sci 606:702\u2013721","journal-title":"Inf Sci"},{"key":"5591_CR103","first-page":"56","volume":"2","author":"L Cai","year":"2021","unstructured":"Cai L, Li J, Wang J, Ji S (2021) Line graph neural networks for link prediction. IEEE Trans Pattern Anal Mach Intell 2:56","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"5591_CR104","volume":"140","author":"Z Zhang","year":"2023","unstructured":"Zhang Z, Sun S, Ma G, Zhong C (2023) Line graph contrastive learning for link prediction. Pattern Recogn 140:109537","journal-title":"Pattern Recogn"},{"issue":"1","key":"5591_CR105","doi-asserted-by":"crossref","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","journal-title":"Radiology"},{"issue":"7","key":"5591_CR106","doi-asserted-by":"crossref","first-page":"6289","DOI":"10.1002\/cpe.6289","volume":"34","author":"D Mumin","year":"2022","unstructured":"Mumin D, Shi L-L, Liu L (2022) An efficient algorithm for link prediction based on local information: considering the effect of node degree. Concurr Comput Pract Exp 34(7):6289","journal-title":"Concurr Comput Pract Exp"},{"issue":"2","key":"5591_CR107","volume":"64","author":"ME Newman","year":"2001","unstructured":"Newman ME (2001) Clustering and preferential attachment in growing networks. Phys Rev E 64(2):025102","journal-title":"Phys Rev E"},{"key":"5591_CR108","first-page":"58","volume":"2","author":"G Salton","year":"1973","unstructured":"Salton G, Yang C-S (1973) On the specification of term values in automatic indexing. J Doc 2:58","journal-title":"J Doc"},{"key":"5591_CR109","first-page":"547","volume":"37","author":"P Jaccard","year":"1901","unstructured":"Jaccard P (1901) \u00c9tude comparative de la distribution florale dans une portion des alpes et des jura. Bull Soc Vaudoise Sci Nat 37:547\u2013579","journal-title":"Bull Soc Vaudoise Sci Nat"},{"key":"5591_CR110","first-page":"1","volume":"5","author":"TA Sorensen","year":"1948","unstructured":"Sorensen TA (1948) A method of establishing groups of equal amplitude in plant sociology based on similarity of species content and its application to analyses of the vegetation on danish commons. Biol Skar 5:1\u201334","journal-title":"Biol Skar"},{"key":"5591_CR111","doi-asserted-by":"crossref","unstructured":"Liben-Nowell D, Kleinberg J (2003) The link prediction problem for social networks. In Proceedings of the Twelfth International Conference on Information and Knowledge Management, pp 556\u2013559","DOI":"10.1145\/956863.956972"},{"issue":"5439","key":"5591_CR112","doi-asserted-by":"crossref","first-page":"509","DOI":"10.1126\/science.286.5439.509","volume":"286","author":"A-L Barab\u00e1si","year":"1999","unstructured":"Barab\u00e1si A-L, Albert R (1999) Emergence of scaling in random networks. Science 286(5439):509\u2013512","journal-title":"Science"},{"issue":"3","key":"5591_CR113","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1016\/S0378-8733(03)00009-1","volume":"25","author":"LA Adamic","year":"2003","unstructured":"Adamic LA, Adar E (2003) Friends and neighbors on the web. Soc Netw 25(3):211\u2013230","journal-title":"Soc Netw"},{"issue":"10","key":"5591_CR114","doi-asserted-by":"crossref","first-page":"4511","DOI":"10.1073\/pnas.1000488107","volume":"107","author":"T Zhou","year":"2010","unstructured":"Zhou T, Kuscsik Z, Liu J-G, Medo M, Wakeling JR, Zhang Y-C (2010) Solving the apparent diversity-accuracy dilemma of recommender systems. Proc Natl Acad Sci 107(10):4511\u20134515","journal-title":"Proc Natl Acad Sci"},{"issue":"1","key":"5591_CR115","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1007\/BF02289026","volume":"18","author":"L Katz","year":"1953","unstructured":"Katz L (1953) A new status index derived from sociometric analysis. Psychometrika 18(1):39\u201343","journal-title":"Psychometrika"},{"key":"5591_CR116","doi-asserted-by":"crossref","unstructured":"Tong H, Faloutsos C, Pan J-Y (2006) Fast random walk with restart and its applications. In Sixth International Conference on Data Mining (ICDM\u201906), pp 613\u2013622. IEEE","DOI":"10.1109\/ICDM.2006.70"},{"key":"5591_CR117","doi-asserted-by":"crossref","unstructured":"Jeh G, Widom J (2002) Simrank: a measure of structural-context similarity. In Proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp 538\u2013543","DOI":"10.1145\/775047.775126"},{"issue":"2","key":"5591_CR118","doi-asserted-by":"crossref","DOI":"10.1103\/PhysRevE.73.026120","volume":"73","author":"EA Leicht","year":"2006","unstructured":"Leicht EA, Holme P, Newman ME (2006) Vertex similarity in networks. Phys Rev E 73(2):026120","journal-title":"Phys Rev E"},{"issue":"9","key":"5591_CR119","first-page":"1505","volume":"58","author":"P CHEBOTAREV","year":"1997","unstructured":"CHEBOTAREV P (1997) The matrix-forest theorem and measuring relations in small social groups. Autom Remote Control 58(9):1505\u20131514","journal-title":"Autom Remote Control"},{"issue":"5","key":"5591_CR120","doi-asserted-by":"crossref","first-page":"58007","DOI":"10.1209\/0295-5075\/89\/58007","volume":"89","author":"W Liu","year":"2010","unstructured":"Liu W, L\u00fc L (2010) Link prediction based on local random walk. Europhys Lett 89(5):58007","journal-title":"Europhys Lett"},{"key":"5591_CR121","doi-asserted-by":"crossref","first-page":"623","DOI":"10.1140\/epjb\/e2009-00335-8","volume":"71","author":"T Zhou","year":"2009","unstructured":"Zhou T, L\u00fc L, Zhang Y-C (2009) Predicting missing links via local information. Eur Phys J B 71:623\u2013630","journal-title":"Eur Phys J B"},{"key":"5591_CR122","volume-title":"Introduction to modern information retrieval","author":"G Salton","year":"1983","unstructured":"Salton G (1983) Introduction to modern information retrieval. McGraw-Hill, London"},{"key":"5591_CR123","doi-asserted-by":"crossref","unstructured":"Pons P, Latapy M (2005) Computing communities in large networks using random walks. In Computer and Information Sciences-ISCIS 2005: 20th International Symposium, Istanbul, Turkey, October 26\u201328, 2005. Proceedings 20, pp 284\u2013293. Springer","DOI":"10.1007\/11569596_31"},{"issue":"4","key":"5591_CR124","doi-asserted-by":"crossref","first-page":"150","DOI":"10.3390\/info10040150","volume":"10","author":"K Kowsari","year":"2019","unstructured":"Kowsari K, Jafari Meimandi K, Heidarysafa M, Mendu S, Barnes L, Brown D (2019) Text classification algorithms: a survey. Information 10(4):150","journal-title":"Information"},{"key":"5591_CR125","doi-asserted-by":"crossref","unstructured":"Sen PC, Hajra M, Ghosh M (2020) Supervised classification algorithms in machine learning: A survey and review. In Emerging Technology in Modelling and Graphics: Proceedings of IEM Graph 2018, pp 99\u2013111. Springer","DOI":"10.1007\/978-981-13-7403-6_11"},{"key":"5591_CR126","doi-asserted-by":"crossref","unstructured":"Wu L, Cui P, Pei J, Zhao L, Guo X (2022) Graph neural networks: foundation, frontiers and applications. In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, pp 4840\u20134841","DOI":"10.1145\/3534678.3542609"},{"key":"5591_CR127","unstructured":"Kipf TN, Welling M (xxxx) Semi-supervised classification with graph convolutional networks"},{"key":"5591_CR128","first-page":"58","volume":"30","author":"M Zaheer","year":"2017","unstructured":"Zaheer M, Kottur S, Ravanbakhsh S, Poczos B, Salakhutdinov RR, Smola AJ (2017) Deep sets. Adv Neural Inf Process Syst 30:58","journal-title":"Adv Neural Inf Process Syst"},{"key":"5591_CR129","unstructured":"Li Y, Zemel R, Brockschmidt M, Tarlow D (2016) Gated graph sequence neural networks. In Proceedings of ICLR\u201916"},{"key":"5591_CR130","doi-asserted-by":"crossref","first-page":"110589","DOI":"10.1016\/j.knosys.2023.110589","volume":"5","author":"C He","year":"2023","unstructured":"He C, Cheng J, Fei X, Weng Y, Zheng Y, Tang Y (2023) Community preserving adaptive graph convolutional networks for link prediction in attributed networks. Knowl-Based Syst 5:110589","journal-title":"Knowl-Based Syst"},{"key":"5591_CR131","volume":"136","author":"Q Mi","year":"2023","unstructured":"Mi Q, Wang X, Lin Y (2023) A double attention graph network for link prediction on temporal graph. Appl Soft Comput 136:110059","journal-title":"Appl Soft Comput"},{"issue":"7540","key":"5591_CR132","doi-asserted-by":"crossref","first-page":"529","DOI":"10.1038\/nature14236","volume":"518","author":"V Mnih","year":"2015","unstructured":"Mnih V, Kavukcuoglu K, Silver D, Rusu AA, Veness J, Bellemare MG, Graves A, Riedmiller M, Fidjeland AK, Ostrovski G et al (2015) Human-level control through deep reinforcement learning. Nature 518(7540):529\u2013533","journal-title":"Nature"},{"issue":"6","key":"5591_CR133","first-page":"245","volume":"11","author":"M Lim","year":"2020","unstructured":"Lim M, Abdullah A, Jhanjhi N (2020) Data fusion-link prediction for evolutionary network with deep reinforcement learning. Int J Adv Comput Sci Appl 11(6):245","journal-title":"Int J Adv Comput Sci Appl"},{"issue":"4","key":"5591_CR134","doi-asserted-by":"crossref","first-page":"4715","DOI":"10.1007\/s10489-021-02672-0","volume":"52","author":"L Chen","year":"2022","unstructured":"Chen L, Cui J, Tang X, Qian Y, Li Y, Zhang Y (2022) Rlpath: a knowledge graph link prediction method using reinforcement learning based attentive relation path searching and representation learning. Appl Intell 52(4):4715\u20134726","journal-title":"Appl Intell"},{"key":"5591_CR135","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.ins.2020.09.039","volume":"548","author":"Y Xiao","year":"2021","unstructured":"Xiao Y, Li R, Lu X, Liu Y (2021) Link prediction based on feature representation and fusion. Inf Sci 548:1\u201317","journal-title":"Inf Sci"},{"key":"5591_CR136","volume":"266","author":"T Le","year":"2023","unstructured":"Le T, Tran H, Le B (2023) Knowledge graph embedding with the special orthogonal group in quaternion space for link prediction. Knowl-Based Syst 266:110400","journal-title":"Knowl-Based Syst"},{"key":"5591_CR137","volume":"539","author":"G Chen","year":"2020","unstructured":"Chen G, Xu C, Wang J, Feng J, Feng J (2020) Robust non-negative matrix factorization for link prediction in complex networks using manifold regularization and sparse learning. Physica A 539:122882","journal-title":"Physica A"},{"issue":"3","key":"5591_CR138","doi-asserted-by":"crossref","DOI":"10.1103\/PhysRevA.107.032605","volume":"107","author":"JP Moutinho","year":"2023","unstructured":"Moutinho JP, Melo A, Coutinho B, Kov\u00e1cs IA, Omar Y (2023) Quantum link prediction in complex networks. Phys Rev A 107(3):032605","journal-title":"Phys Rev A"},{"key":"5591_CR139","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1016\/j.comcom.2022.10.006","volume":"196","author":"M Kumar","year":"2022","unstructured":"Kumar M, Mishra S, Biswas B (2022) Pqklp: projected quantum kernel based link prediction in dynamic networks. Comput Commun 196:249\u2013267","journal-title":"Comput Commun"},{"key":"5591_CR140","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2022.108821","volume":"248","author":"SS Singh","year":"2022","unstructured":"Singh SS, Srivastva D, Kumar A, Srivastava V (2022) Flp-id: Fuzzy-based link prediction in multiplex social networks using information diffusion perspective. Knowl-Based Syst 248:108821","journal-title":"Knowl-Based Syst"},{"key":"5591_CR141","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1016\/j.ins.2022.03.010","volume":"597","author":"J Zheng","year":"2022","unstructured":"Zheng J, Qin Z, Wang S, Li D (2022) Attention-based explainable friend link prediction with heterogeneous context information. Inf Sci 597:211\u2013229","journal-title":"Inf Sci"},{"key":"5591_CR142","doi-asserted-by":"crossref","first-page":"342","DOI":"10.1016\/j.ins.2021.10.061","volume":"584","author":"R-Q Xu","year":"2022","unstructured":"Xu R-Q, Zhou M-Y, Liao H (2022) Pnr: How to optimally combine different link prediction approaches? Inf Sci 584:342\u2013359","journal-title":"Inf Sci"}],"container-title":["The Journal of Supercomputing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-023-05591-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11227-023-05591-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-023-05591-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,22]],"date-time":"2024-01-22T11:12:23Z","timestamp":1705921943000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11227-023-05591-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,9,7]]},"references-count":142,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2024,2]]}},"alternative-id":["5591"],"URL":"https:\/\/doi.org\/10.1007\/s11227-023-05591-8","relation":{},"ISSN":["0920-8542","1573-0484"],"issn-type":[{"value":"0920-8542","type":"print"},{"value":"1573-0484","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,9,7]]},"assertion":[{"value":"17 August 2023","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 September 2023","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}