{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T15:48:22Z","timestamp":1785858502614,"version":"3.56.0"},"reference-count":55,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2022,2,5]],"date-time":"2022-02-05T00:00:00Z","timestamp":1644019200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,2,5]],"date-time":"2022-02-05T00:00:00Z","timestamp":1644019200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61902270"],"award-info":[{"award-number":["61902270"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Major Program of the Natural Science Foundation of Jiangsu Higher Education Institutions of China","award":["19KJA610002"],"award-info":[{"award-number":["19KJA610002"]}]},{"name":"Major Program of the Natural Science Foundation of Jiangsu Higher Education Institutions of China","award":["19KJB520050"],"award-info":[{"award-number":["19KJB520050"]}]},{"DOI":"10.13039\/501100000923","name":"Australian Research Council","doi-asserted-by":"crossref","award":["DP190101985"],"award-info":[{"award-number":["DP190101985"]}],"id":[{"id":"10.13039\/501100000923","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["The VLDB Journal"],"published-print":{"date-parts":[[2023,1]]},"DOI":"10.1007\/s00778-022-00730-8","type":"journal-article","created":{"date-parts":[[2022,2,5]],"date-time":"2022-02-05T07:03:17Z","timestamp":1644044597000},"page":"1-22","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["HFUL: a hybrid framework for user account linkage across location-aware social networks"],"prefix":"10.1007","volume":"32","author":[{"given":"Wei","family":"Chen","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weiqing","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongzhi","family":"Yin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lei","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaofang","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,2,5]]},"reference":[{"key":"730_CR1","doi-asserted-by":"crossref","unstructured":"Gao, H., Liu, H.: Data analysis on location-based social networks, in Mobile social networking, 2014, pp. 165\u2013194","DOI":"10.1007\/978-1-4614-8579-7_8"},{"key":"730_CR2","doi-asserted-by":"crossref","unstructured":"Pham, H., Shahabi, C., Liu, Y.: Ebm: an entropy-based model to infer social strength from spatiotemporal data, in SIGMOD, 2013, pp. 265\u2013276","DOI":"10.1145\/2463676.2465301"},{"key":"730_CR3","doi-asserted-by":"crossref","unstructured":"Lichman, M., Smyth, P.: Modeling human location data with mixtures of kernel densities, in KDD, 2014, pp. 35\u201344","DOI":"10.1145\/2623330.2623681"},{"key":"730_CR4","doi-asserted-by":"crossref","unstructured":"Riederer, C., Kim, Y., Chaintreau, A., Korula, N., Lattanzi, S.: Linking users across domains with location data: Theory and validation, in WWW, 2016, pp. 707\u2013719","DOI":"10.1145\/2872427.2883002"},{"key":"730_CR5","first-page":"70","volume":"11","author":"A Noulas","year":"2011","unstructured":"Noulas, A., Scellato, S., Mascolo, C., Pontil, M.: An empirical study of geographic user activity patterns in foursquare. ICWSM 11, 70\u2013573 (2011)","journal-title":"ICWSM"},{"key":"730_CR6","doi-asserted-by":"crossref","unstructured":"Wang, W., Yin, H., Sadiq, S., Chen, L., Xie, M., Zhou, X.: Spore: a sequential personalized spatial item recommender system, in ICDE, 2016, pp. 954\u2013965","DOI":"10.1109\/ICDE.2016.7498304"},{"key":"730_CR7","doi-asserted-by":"crossref","unstructured":"Zhang, J., Kong, X., Yu, P.\u00a0S.: Transferring heterogeneous links across location-based social networks, in WSDM, 2014, pp. 303\u2013312","DOI":"10.1145\/2556195.2559894"},{"key":"730_CR8","doi-asserted-by":"crossref","unstructured":"Li, Z., Ding, B., Han, J., Kays, R., Nye, P.: Mining periodic behaviors for moving objects, in KDD, 2010, pp. 1099\u20131108","DOI":"10.1145\/1835804.1835942"},{"key":"730_CR9","doi-asserted-by":"crossref","unstructured":"Yuan, Q., Cong, G., Ma, Z., Sun, A., Magnenat-Thalmann, N.: Who, where, when and what: discover spatio-temporal topics for twitter users, in KDD, 2013, pp. 605\u2013613","DOI":"10.1145\/2487575.2487576"},{"issue":"4","key":"730_CR10","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1080\/10618600.1994.10474656","volume":"3","author":"MP Wand","year":"1994","unstructured":"Wand, M.P.: Fast computation of multivariate kernel estimators. J. Comput. Graph. Stat. 3(4), 433\u2013445 (1994)","journal-title":"J. Comput. Graph. Stat."},{"issue":"3","key":"730_CR11","doi-asserted-by":"publisher","first-page":"331","DOI":"10.1177\/1094342015576813","volume":"29","author":"U Lopez-Novoa","year":"2015","unstructured":"Lopez-Novoa, U., S\u00e1enz, J., Mendiburu, A., Miguel-Alonso, J.: An efficient implementation of kernel density estimation for multi-core and many-core architectures. J. High Perform. Comput. Appl. 29(3), 331\u2013347 (2015)","journal-title":"J. High Perform. Comput. Appl."},{"issue":"2","key":"730_CR12","doi-asserted-by":"publisher","first-page":"545","DOI":"10.1007\/s11227-015-1577-7","volume":"72","author":"U Lopez-Novoa","year":"2016","unstructured":"Lopez-Novoa, U., Mendiburu, A., Miguel-Alonso, J.: Kernel density estimation in accelerators. J. Supercomput. 72(2), 545\u2013566 (2016)","journal-title":"J. Supercomput."},{"key":"730_CR13","doi-asserted-by":"crossref","unstructured":"Chen, W., Yin, H., Wang, W., Zhao, L., Hua, W., Zhou, X.: Exploiting spatio-temporal user behaviors for user linkage, in CIKM, 2017","DOI":"10.1145\/3132847.3132898"},{"key":"730_CR14","doi-asserted-by":"crossref","unstructured":"Chen, W., Yin, H., Wang, W., Zhao, L., Zhou, X.: Effective and efficient user account linkage across location based social networks, in ICDE, 2018, pp. 1085\u20131096","DOI":"10.1109\/ICDE.2018.00101"},{"issue":"2","key":"730_CR15","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1145\/3068777.3068781","volume":"18","author":"K Shu","year":"2017","unstructured":"Shu, K., Wang, S., Tang, J., Zafarani, R., Liu, H.: User identity linkage across online social networks: a review. SIGKDD Explor. 18(2), 5\u201317 (2017)","journal-title":"SIGKDD Explor."},{"key":"730_CR16","unstructured":"Huynh, T.\u00a0T., Tong, V.\u00a0V., Nguyen, T.\u00a0T., Yin, H., Weidlich, M., Hung, N.\u00a0Q.\u00a0V.: Adaptive network alignment with unsupervised and multi-order convolutional networks, in ICDE, 2020, pp. 85\u201396"},{"key":"730_CR17","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Yin, H., Huang, Z., Du, X., Yang, G., Lian, D.: Discrete deep learning for fast content-aware recommendation, in WSDM, 2018, pp. 717\u2013726","DOI":"10.1145\/3159652.3159688"},{"issue":"6","key":"730_CR18","doi-asserted-by":"publisher","first-page":"2611","DOI":"10.1007\/s11280-018-0572-3","volume":"22","author":"Y Wang","year":"2019","unstructured":"Wang, Y., Feng, C., Chen, L., Yin, H., Guo, C., Chu, Y.: User identity linkage across social networks via linked heterogeneous network embedding. World Wide Web 22(6), 2611\u20132632 (2019)","journal-title":"World Wide Web"},{"key":"730_CR19","doi-asserted-by":"crossref","unstructured":"Chen, H., Yin, H., Sun, X., Chen, T., Gabrys, B., Musial, K.: Multi-level graph convolutional networks for cross-platform anchor link prediction, in KDD, 2020, pp. 1503\u20131511","DOI":"10.1145\/3394486.3403201"},{"key":"730_CR20","doi-asserted-by":"publisher","first-page":"354","DOI":"10.1609\/icwsm.v3i1.13993","volume":"9","author":"R Zafarani","year":"2009","unstructured":"Zafarani, R., Liu, H.: Connecting corresponding identities across communities. ICWSM 9, 354\u2013357 (2009)","journal-title":"ICWSM"},{"issue":"1","key":"730_CR21","first-page":"23","volume":"2","author":"J Vosecky","year":"2010","unstructured":"Vosecky, J., Hong, D., Shen, V.Y.: User identification across social networks using the web profile and friend network. J. Web Appl. 2(1), 23\u201334 (2010)","journal-title":"J. Web Appl."},{"key":"730_CR22","unstructured":"Iofciu, T., Fankhauser, P., Abel, F., Bischoff, K.: Identifying users across social tagging systems. in ICWSM, 2011"},{"key":"730_CR23","doi-asserted-by":"crossref","unstructured":"Liu, J., Zhang, F., Song, X., Song, Y.-I., Lin, C.-Y., Hon, H.-W.: What\u2019s in a name?: an unsupervised approach to link users across communities, in WSDM, 2013, pp. 495\u2013504","DOI":"10.1145\/2433396.2433457"},{"key":"730_CR24","doi-asserted-by":"crossref","unstructured":"R.\u00a0Zafarani and H.\u00a0Liu, Connecting users across social media sites: a behavioral-modeling approach, in KDD, 2013, pp. 41\u201349","DOI":"10.1145\/2487575.2487648"},{"key":"730_CR25","doi-asserted-by":"crossref","unstructured":"Peled, O., Fire, M., Rokach, L., Elovici, Y.: Entity matching in online social networks, in Social Computing, 2013, pp. 339\u2013344","DOI":"10.1109\/SocialCom.2013.53"},{"key":"730_CR26","doi-asserted-by":"crossref","unstructured":"Liu, S., Wang, S., Zhu, F., Zhang, J., Krishnan, R.: Hydra: Large-scale social identity linkage via heterogeneous behavior modeling, in KDD, 2014, pp. 51\u201362","DOI":"10.1145\/2588555.2588559"},{"key":"730_CR27","doi-asserted-by":"crossref","unstructured":"Shen, Y., Jin, H.: Controllable information sharing for user accounts linkage across multiple online social networks, in CIKM, 2014, pp. 381\u2013390","DOI":"10.1145\/2661829.2661985"},{"key":"730_CR28","doi-asserted-by":"crossref","unstructured":"Mu, X., Zhu, F., Lim, E.-P., Xiao, J., Wang, J., Zhou, Z.-H.: User identity linkage by latent user space modelling, in KDD, 2016, pp. 1775\u20131784","DOI":"10.1145\/2939672.2939849"},{"key":"730_CR29","doi-asserted-by":"crossref","unstructured":"Zhou, F., Liu, L., Zhang, K., Trajcevski, G., Wu, J., Zhong, T.: Deeplink: a deep learning approach for user identity linkage, in INFOCOM, 2018, pp. 1313\u20131321","DOI":"10.1109\/INFOCOM.2018.8486231"},{"key":"730_CR30","doi-asserted-by":"crossref","unstructured":"Xie, W., Mu, X., Lee, R.\u00a0K.-W., Zhu, F., Lim, E.-P.: Unsupervised user identity linkage via factoid embedding, in ICDM, 2018, pp. 1338\u20131343","DOI":"10.1109\/ICDM.2018.00182"},{"key":"730_CR31","first-page":"595","volume":"7","author":"L Liu","year":"2019","unstructured":"Liu, L., Zhang, Y., Fu, S., Zhong, F., Hu, J., Zhang, P.: Abne: an attention-based network embedding for user alignment across social networks. IEEE Access 7, 595\u2013605 (2019)","journal-title":"IEEE Access"},{"key":"730_CR32","doi-asserted-by":"crossref","unstructured":"Zhou, J., Fan, J.: Translink: user identity linkage across heterogeneous social networks via translating embeddings, in INFOCOM, 2019, pp. 2116\u20132124","DOI":"10.1109\/INFOCOM.2019.8737542"},{"key":"730_CR33","doi-asserted-by":"publisher","first-page":"105301105301","DOI":"10.1016\/j.knosys.2019.105301","volume":"193","author":"S Fu","year":"2020","unstructured":"Fu, S., Wang, G., Xia, S., Liu, L.: Deep multi-granularity graph embedding for user identity linkage across social networks. Knowl. Based Syst. 193, 105301105301 (2020)","journal-title":"Knowl. Based Syst."},{"key":"730_CR34","doi-asserted-by":"crossref","unstructured":"Han, X., Wang, L., Xu, L., Zhang, S.: Social media account linkage using user-generated geo-location data, in ISI, 2016, pp. 157\u2013162","DOI":"10.1109\/ISI.2016.7745460"},{"key":"730_CR35","doi-asserted-by":"crossref","unstructured":"Gao, X., Ji, W., Li, Y., Deng, Y., Dong, W.: User identification with spatio-temporal awareness across social networks, in CIKM, 2018, pp. 1831\u20131834","DOI":"10.1145\/3269206.3269248"},{"key":"730_CR36","doi-asserted-by":"crossref","unstructured":"Jin, F., Hua, W., Xu, J., Zhou, X.: Moving object linking based on historical trace, in ICDE, 2019, pp. 1058\u20131069","DOI":"10.1109\/ICDE.2019.00098"},{"key":"730_CR37","doi-asserted-by":"crossref","unstructured":"Zhang, W., Lai, X., Wang, J.: Social link inference via multiview matching network from spatiotemporal trajectories, IEEE Transactions on Neural Networks and Learning Systems, pp. 1\u201312, 2020","DOI":"10.1109\/TNNLS.2020.2986472"},{"issue":"6","key":"730_CR38","doi-asserted-by":"publisher","first-page":"1353","DOI":"10.1080\/03610928508828980","volume":"14","author":"DW Scott","year":"1985","unstructured":"Scott, D.W., Sheather, S.J.: Kernel density estimation with binned data. Commun. Stat.-Theory Methods 14(6), 1353\u20131359 (1985)","journal-title":"Commun. Stat.-Theory Methods"},{"key":"730_CR39","unstructured":"Silverman, B.\u00a0W.: Density estimation for statistics and data analysis, 1986, vol.\u00a026"},{"key":"730_CR40","doi-asserted-by":"crossref","unstructured":"Zhang, J.-D., Chow, C.-Y.: igslr: personalized geo-social location recommendation: a kernel density estimation approach, in GIS, 2013, pp. 334\u2013343","DOI":"10.1145\/2525314.2525339"},{"key":"730_CR41","doi-asserted-by":"crossref","unstructured":"Hulden, M., Silfverberg, M., Francom, J.: Kernel density estimation for text-based geolocation. in AAAI, 2015, pp. 145\u2013150","DOI":"10.1609\/aaai.v29i1.9149"},{"key":"730_CR42","unstructured":"Backurs, A., Indyk, P., Wagner, T.: Space and time efficient kernel density estimation in high dimensions, in NeurIPS, 2019, pp. 15\u00a0773\u201315\u00a0782"},{"key":"730_CR43","doi-asserted-by":"crossref","unstructured":"Hohl, A., Chen, P.: Spatiotemporal simulation: local ripley\u2019s K function parameterizes adaptive kernel density estimation, in SIGSPATIAL, 2019, pp. 16\u201323","DOI":"10.1145\/3356470.3365528"},{"key":"730_CR44","doi-asserted-by":"crossref","unstructured":"Hasan, S., Zhan, X., Ukkusuri, S.\u00a0V.: Understanding urban human activity and mobility patterns using large-scale location-based data from online social media, In Proceedings of the 2nd ACM SIGKDD international workshop on urban computing, 2013","DOI":"10.1145\/2505821.2505823"},{"key":"730_CR45","doi-asserted-by":"crossref","unstructured":"Zhang, P., Deng, M., Van\u00a0de Weghe, N.: Clustering spatio-temporal trajectories based on kernel density estimation, in ICCSA, 2014, pp. 298\u2013311","DOI":"10.1007\/978-3-319-09144-0_21"},{"key":"730_CR46","doi-asserted-by":"crossref","unstructured":"Romano, B., Jiang, Z.: Visualizing traffic accident hotspots based on spatial-temporal network kernel density estimation, in SIGSPATIAL, 2017, pp. 1\u20134","DOI":"10.1145\/3139958.3139981"},{"issue":"12","key":"730_CR47","doi-asserted-by":"publisher","first-page":"544","DOI":"10.3390\/ijgi8120544","volume":"8","author":"Z Wang","year":"2019","unstructured":"Wang, Z., Liu, L., Zhou, H., Lan, M.: How is the confidentiality of crime locations affected by parameters in kernel density estimation? Int. J. Geo-Inf. 8(12), 544 (2019)","journal-title":"Int. J. Geo-Inf."},{"key":"730_CR48","first-page":"379","volume":"7","author":"Z Zhou","year":"2019","unstructured":"Zhou, Z., Lan, R., Rui, Y., Zhou, J., Dong, L., Cheng, R., Cai, X.: A new acoustic emission source location method using tri-variate kernel density estimator. IEEE Access 7, 379\u2013388 (2019)","journal-title":"IEEE Access"},{"key":"730_CR49","doi-asserted-by":"crossref","unstructured":"Coleman, B., Shrivastava, A.: Sub-linear races sketches for approximate kernel density estimation on streaming data, in WWW, 2020, pp. 1739\u20131749","DOI":"10.1145\/3366423.3380244"},{"issue":"6191","key":"730_CR50","doi-asserted-by":"publisher","first-page":"1492","DOI":"10.1126\/science.1242072","volume":"344","author":"A Rodriguez","year":"2014","unstructured":"Rodriguez, A., Laio, A.: Clustering by fast search and find of density peaks. Science 344(6191), 1492\u20131496 (2014)","journal-title":"Science"},{"issue":"1","key":"730_CR51","first-page":"194","volume":"26","author":"A Albanese","year":"2014","unstructured":"Albanese, A., Pal, S.K., Petrosino, A.: Rough sets, kernel set, and spatiotemporal outlier detection. TKDE 26(1), 194\u2013207 (2014)","journal-title":"TKDE"},{"key":"730_CR52","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.datak.2017.12.001","volume":"122","author":"MB Duggimpudi","year":"2019","unstructured":"Duggimpudi, M.B., Abbady, S., Chen, J., Raghavan, V.V.: Spatio-temporal outlier detection algorithms based on computing behavioral outlierness factor. Data Knowl. Eng. 122, 1\u201324 (2019)","journal-title":"Data Knowl. Eng."},{"key":"730_CR53","doi-asserted-by":"crossref","unstructured":"Begum, N., Ulanova, L., Wang, J., Keogh, E.\u00a0J.: Accelerating dynamic time warping clustering with a novel admissible pruning strategy, in KDD, 2015, pp. 49\u201358","DOI":"10.1145\/2783258.2783286"},{"key":"730_CR54","doi-asserted-by":"crossref","unstructured":"Cao, W., Wu, Z., Wang, D., Li, J., Wu, H.: Automatic user identification method across heterogeneous mobility data sources, in ICDE, 2016, pp. 978\u2013989","DOI":"10.1109\/ICDE.2016.7498306"},{"key":"730_CR55","doi-asserted-by":"crossref","unstructured":"Y.\u00a0Theodoridis, J.\u00a0R.\u00a0O. Silva, and M.\u00a0A. Nascimento, On the generation of spatiotemporal datasets, in SSD, vol. 1651, 1999, pp. 147\u2013164","DOI":"10.1007\/3-540-48482-5_11"}],"container-title":["The VLDB Journal"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00778-022-00730-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00778-022-00730-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00778-022-00730-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,17]],"date-time":"2024-09-17T22:46:22Z","timestamp":1726613182000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00778-022-00730-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,2,5]]},"references-count":55,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2023,1]]}},"alternative-id":["730"],"URL":"https:\/\/doi.org\/10.1007\/s00778-022-00730-8","relation":{},"ISSN":["1066-8888","0949-877X"],"issn-type":[{"value":"1066-8888","type":"print"},{"value":"0949-877X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,2,5]]},"assertion":[{"value":"3 June 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 December 2021","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 December 2021","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 February 2022","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}