{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,26]],"date-time":"2025-06-26T03:10:07Z","timestamp":1750907407903,"version":"3.41.0"},"reference-count":40,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2025,5,23]],"date-time":"2025-05-23T00:00:00Z","timestamp":1747958400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,5,23]],"date-time":"2025-05-23T00:00:00Z","timestamp":1747958400000},"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":["62120106008, 202206340057, 62120106008"],"award-info":[{"award-number":["62120106008, 202206340057, 62120106008"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Scientific Research Project of Anhui Provincial Health Commission","award":["AHWJ2022b058"],"award-info":[{"award-number":["AHWJ2022b058"]}]},{"name":"Joint Fund for Medical Artificial Intelligence of the First Affiliated Hospital of USTC","award":["MAI2022Q009"],"award-info":[{"award-number":["MAI2022Q009"]}]},{"name":"Program for Changjiang Scholars and Innovative Research Team in University (PCSIRT) of the Ministry of Education of China","award":["IRT17R32"],"award-info":[{"award-number":["IRT17R32"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Cogn Comput"],"published-print":{"date-parts":[[2025,6]]},"DOI":"10.1007\/s12559-025-10468-4","type":"journal-article","created":{"date-parts":[[2025,5,23]],"date-time":"2025-05-23T11:31:40Z","timestamp":1747999900000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Fuzzy Preference Completion with Ranked and Unranked Preferences"],"prefix":"10.1007","volume":"17","author":[{"given":"Lei","family":"Li","sequence":"first","affiliation":[]},{"given":"Pan","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Renjie","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Zhenchao","family":"Tao","sequence":"additional","affiliation":[]},{"given":"Xindong","family":"Wu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,5,23]]},"reference":[{"issue":"1","key":"10468_CR1","doi-asserted-by":"publisher","first-page":"112","DOI":"10.1162\/dint_a_00115","volume":"4","author":"L Li","year":"2022","unstructured":"Li L, Xue M, Zhang Z, Chen H, Wu X. Certainty-based preference completion. Data Intell. 2022;4(1):112\u201333.","journal-title":"Data Intell."},{"key":"10468_CR2","doi-asserted-by":"crossref","unstructured":"Liu A, Wu Q, Liu Z, Xia L. Near-neighbor methods in random preference completion. In: Proceedings of the AAAI Conference on Artificial Intelligence, 2019;33:4336\u20134343.","DOI":"10.1609\/aaai.v33i01.33014336"},{"key":"10468_CR3","doi-asserted-by":"crossref","unstructured":"Liu NN, Yang Q. Eigenrank: a ranking-oriented approach to collaborative filtering. In: Proceedings of the 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2008;83\u201390.","DOI":"10.1145\/1390334.1390351"},{"issue":"1","key":"10468_CR4","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/978-3-031-01582-3","volume":"13","author":"L Xia","year":"2019","unstructured":"Xia L. Learning and decision-making from rank data. Synthesis Lectures Artif Intell Mach Learn. 2019;13(1):1\u2013159.","journal-title":"Synthesis Lectures Artif Intell Mach Learn."},{"issue":"1","key":"10468_CR5","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1007\/BF02295838","volume":"69","author":"JP Doignon","year":"2004","unstructured":"Doignon JP, Peke\u010d A, Regenwetter M. The repeated insertion model for rankings: missing link between two subset choice models. Psychometrika. 2004;69(1):33\u201354.","journal-title":"Psychometrika."},{"key":"10468_CR6","doi-asserted-by":"crossref","unstructured":"Lu Y, Zhang Y, Richter F, Seidl T. k-nearest neighbor based clustering with shape alternation adaptivity. In: Proceedings of the 2020 International Joint Conference on Neural Networks (IJCNN), 2020;1\u20138.","DOI":"10.1109\/IJCNN48605.2020.9207321"},{"key":"10468_CR7","doi-asserted-by":"crossref","unstructured":"Sanz-Cruzado J, Castells P, L\u00f3pez E. A simple multi-armed nearest-neighbor bandit for interactive recommendation. In: Proceedings of the 13th ACM Conference on Recommender Systems, 2019;358\u2013362.","DOI":"10.1145\/3298689.3347040"},{"key":"10468_CR8","doi-asserted-by":"crossref","unstructured":"Yang C, Liu T, Liu L, Chen X. A nearest neighbor based personal rank algorithm for collaborator recommendation. In: Proceedings of the 2018 15th International Conference on Service Systems and Service Management (ICSSSM), 2018;1\u20135.","DOI":"10.1109\/ICSSSM.2018.8465112"},{"key":"10468_CR9","doi-asserted-by":"crossref","unstructured":"Zhang Y, Gong Z, Hao Z, Xu J. A cognitive uncertainty calculation method based on probabilistic linguistic term set and applications in geopolitical risk assessment. Cogn Comput. 2023;1\u201316.","DOI":"10.1007\/s12559-023-10166-z"},{"issue":"3","key":"10468_CR10","doi-asserted-by":"publisher","first-page":"494","DOI":"10.1007\/s12559-015-9377-1","volume":"8","author":"F Cai","year":"2016","unstructured":"Cai F, Chen H. A probabilistic model for information retrieval by mining user behaviors. Cogn Comput. 2016;8(3):494\u2013504.","journal-title":"Cogn Comput."},{"key":"10468_CR11","unstructured":"Cheng W, H\u00fcllermeier E. A simple instance-based approach to multilabel classification using the mallows model. In: Working Notes of the First International Workshop on Learning from Multi-Label Data, 2009;28\u201338."},{"issue":"1\/2","key":"10468_CR12","doi-asserted-by":"publisher","first-page":"114","DOI":"10.2307\/2333244","volume":"44","author":"CL Mallows","year":"1957","unstructured":"Mallows CL. Non-null ranking models. Biometrika. 1957;44(1\/2):114\u201330.","journal-title":"Biometrika."},{"issue":"4","key":"10468_CR13","doi-asserted-by":"publisher","first-page":"273","DOI":"10.1037\/h0070288","volume":"34","author":"LL Thurstone","year":"1927","unstructured":"Thurstone LL. A law of comparative judgment. Psychol Rev. 1927;34(4):273.","journal-title":"Psychol Rev."},{"issue":"1","key":"10468_CR14","first-page":"186","volume":"50","author":"G Debreu","year":"1960","unstructured":"Debreu G. Individual choice behavior: a theoretical analysis. Am Econ Rev. 1960;50(1):186\u20138.","journal-title":"Am Econ Rev."},{"issue":"2","key":"10468_CR15","first-page":"193","volume":"24","author":"RL Plackett","year":"1975","unstructured":"Plackett RL. The analysis of permutations. J Royal Stat Soc Series C: Appl Stat. 1975;24(2):193\u2013202.","journal-title":"J Royal Stat Soc Series C: Appl Stat."},{"issue":"71","key":"10468_CR16","first-page":"1","volume":"2016","author":"E Irurozki","year":"2016","unstructured":"Irurozki E, Calvo B, Lozano JA. Permallows: an r package for mallows and generalized mallows models. J Stat Softw. 2016;2016(71):1\u201330.","journal-title":"J Stat Softw."},{"issue":"9","key":"10468_CR17","first-page":"2401","volume":"2008","author":"G Lebanon","year":"2008","unstructured":"Lebanon G, Mao Y. Non-parametric modeling of partially ranked data. J Mach Learn Res. 2008;2008(9):2401\u201329.","journal-title":"J Mach Learn Res."},{"key":"10468_CR18","unstructured":"Katz-Samuels J, Scott C. Nonparametric preference completion. In: Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics. 2018;84:632\u2013641."},{"issue":"5","key":"10468_CR19","doi-asserted-by":"publisher","first-page":"615","DOI":"10.1016\/j.aam.2012.01.001","volume":"48","author":"A Gnedin","year":"2012","unstructured":"Gnedin A, Olshanski G. The two-sided infinite extension of the mallows model for random permutations. Adv Appl Math. 2012;48(5):615\u201339.","journal-title":"Adv Appl Math."},{"key":"10468_CR20","unstructured":"Meila M, Bao L. Estimation and clustering with infinite rankings. 2012. arXiv:1206.3270"},{"issue":"3","key":"10468_CR21","doi-asserted-by":"publisher","first-page":"917","DOI":"10.1016\/j.csda.2004.06.012","volume":"49","author":"A D\u2019Elia","year":"2005","unstructured":"D\u2019Elia A, Piccolo D. A mixture model for preferences data analysis. Comput Stat Data Anal. 2005;49(3):917\u201334.","journal-title":"Comput Stat Data Anal."},{"key":"10468_CR22","unstructured":"Meila M, Chen H. Dirichlet process mixtures of generalized mallows models. 2012. arXiv:1203.3496"},{"issue":"3\u20134","key":"10468_CR23","doi-asserted-by":"publisher","first-page":"645","DOI":"10.1016\/S0167-9473(02)00165-2","volume":"41","author":"TB Murphy","year":"2003","unstructured":"Murphy TB, Martin D. Mixtures of distance-based models for ranking data. Comput Stat Data Anal. 2003;41(3\u20134):645\u201355.","journal-title":"Comput Stat Data Anal."},{"issue":"5","key":"10468_CR24","doi-asserted-by":"publisher","first-page":"98","DOI":"10.1007\/s11222-023-10266-8","volume":"33","author":"M Crispino","year":"2023","unstructured":"Crispino M, Mollica C, Astuti V, Tardella L. Efficient and accurate inference for mixtures of Mallows models with Spearman distance. Stat Comput. 2023;33(5):98.","journal-title":"Stat Comput."},{"key":"10468_CR25","doi-asserted-by":"crossref","unstructured":"Vojnovic M, Yun S. Parameter estimation for generalized Thurstone choice models. In: Proceedings of the 2016 International Conference on Machine Learning, 2016;498\u2013506.","DOI":"10.2172\/1353026"},{"issue":"14","key":"10468_CR26","doi-asserted-by":"publisher","first-page":"5315","DOI":"10.1080\/00207543.2023.2291519","volume":"62","author":"M Capponi","year":"2024","unstructured":"Capponi M, Gervasi R, Mastrogiacomo L, Franceschini F. Assessing perceived assembly complexity in human-robot collaboration processes: a proposal based on Thurstone\u2019s law of comparative judgement. Int J Prod Res. 2024;62(14):5315\u201335.","journal-title":"Int J Prod Res."},{"key":"10468_CR27","unstructured":"Hajek B, Oh S, Xu J. Minimax-optimal inference from partial rankings. In: Proceedings of the 2014 Annual Conference on Neural Information Processing Systems 2014;1475\u20131483."},{"key":"10468_CR28","doi-asserted-by":"crossref","unstructured":"Nguyen D, Zhang AY. Efficient and accurate learning of mixtures of Plackett-Luce models. In: Proceedings of Thirty-Seventh AAAI Conference on Artificial Intelligence, AAAI 2023. 2023;9294\u20139301.","DOI":"10.1609\/aaai.v37i8.26114"},{"issue":"12","key":"10468_CR29","doi-asserted-by":"publisher","first-page":"7889","DOI":"10.1109\/TSMC.2020.2992272","volume":"51","author":"N Wu","year":"2020","unstructured":"Wu N, Xu Y, Kilgour DM, Fang L. Composite decision makers in the graph model for conflict resolution: hesitant fuzzy preference modeling. IEEE Trans Syst, Man, Cybernet: Syst. 2020;51(12):7889\u2013902.","journal-title":"IEEE Trans Syst, Man, Cybernet: Syst."},{"issue":"2","key":"10468_CR30","doi-asserted-by":"publisher","first-page":"329","DOI":"10.1016\/j.cie.2003.12.012","volume":"46","author":"ZP Fan","year":"2004","unstructured":"Fan ZP, Xiao SH, Hu GF. An optimization method for integrating two kinds of preference information in group decision-making. Comput Indust Eng. 2004;46(2):329\u201335.","journal-title":"Comput Indust Eng."},{"key":"10468_CR31","doi-asserted-by":"crossref","unstructured":"Li J, Ye J, Niu Ll, Chen Q, Wang Zx. Decision-making models based on satisfaction degree with incomplete hesitant fuzzy preference relation. Soft Comput. 2022;26(7):3129\u20133145.","DOI":"10.1007\/s00500-021-06635-y"},{"issue":"2","key":"10468_CR32","doi-asserted-by":"publisher","first-page":"2009","DOI":"10.1109\/TETCI.2024.3359096","volume":"8","author":"L Li","year":"2024","unstructured":"Li L, Liu P, Bu C, Zhang Z, Wu X. Fuzzy ranking-based preference completion via graph pattern matching and rematching. IEEE Trans Emerg Top Comput Intell. 2024;8(2):2009\u201321.","journal-title":"IEEE Trans Emerg Top Comput Intell."},{"key":"10468_CR33","doi-asserted-by":"crossref","unstructured":"Valdivia A, Luz\u00ed\u00f3n MV, Herrera F. Neutrality in the sentiment analysis problem based on fuzzy majority. In: Proceedings of the 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2017;1\u20136.","DOI":"10.1109\/FUZZ-IEEE.2017.8015751"},{"issue":"5","key":"10468_CR34","doi-asserted-by":"publisher","first-page":"1231","DOI":"10.1109\/TFUZZ.2016.2604006","volume":"25","author":"BS Ahn","year":"2016","unstructured":"Ahn BS. A new approach to solve the constrained OWA aggregation problem. IEEE Trans Fuzzy Syst. 2016;25(5):1231\u20138.","journal-title":"IEEE Trans Fuzzy Syst."},{"issue":"4","key":"10468_CR35","doi-asserted-by":"publisher","first-page":"2099","DOI":"10.1109\/TFUZZ.2017.2762637","volume":"26","author":"M Amarante","year":"2017","unstructured":"Amarante M. MM-OWA: a generalization of OWA operators. IEEE Trans Fuzzy Syst. 2017;26(4):2099\u2013106.","journal-title":"IEEE Trans Fuzzy Syst."},{"key":"10468_CR36","doi-asserted-by":"publisher","first-page":"162903","DOI":"10.1109\/ACCESS.2020.3018957","volume":"8","author":"X Geng","year":"2020","unstructured":"Geng X, Ma Y. n-intuitionistic polygonal fuzzy aggregation operators and their application to multi-attribute decision making. IEEE Access. 2020;8:162903\u201316.","journal-title":"IEEE Access"},{"key":"10468_CR37","doi-asserted-by":"crossref","unstructured":"Jin L. Some consistency properties and individual preference monotonicity for weighted aggregation operators. IEEE Trans Fuzzy Syst. 2021;30(6):2113\u20137.","DOI":"10.1109\/TFUZZ.2021.3065536"},{"issue":"3","key":"10468_CR38","doi-asserted-by":"publisher","first-page":"638","DOI":"10.1109\/TFUZZ.2020.3042611","volume":"30","author":"H Bustince","year":"2022","unstructured":"Bustince H, Bedregal B, Campi\u00f3n MJ, da Silva I, Fernandez J, Indur\u00e1in E, Ravent\u00f3s-Pujol A, Santiago RH. Aggregation of individual rankings through fusion functions: criticism and optimality analysis. IEEE Trans Fuzzy Syst. 2022;30(3):638\u201348.","journal-title":"IEEE Trans Fuzzy Syst"},{"issue":"3\/4","key":"10468_CR39","doi-asserted-by":"publisher","first-page":"470","DOI":"10.2307\/2332878","volume":"44","author":"EC Fieller","year":"1957","unstructured":"Fieller EC, Hartley HO, Pearson ES. Tests for rank correlation coefficients. Biometrika. 1957;44(3\/4):470\u201381.","journal-title":"Biometrika."},{"issue":"3","key":"10468_CR40","doi-asserted-by":"publisher","first-page":"225","DOI":"10.1561\/1500000016","volume":"3","author":"TY Liu","year":"2009","unstructured":"Liu TY. Learning to rank for information retrieval. Found Trends Inf Retriev. 2009;3(3):225\u2013331.","journal-title":"Found Trends Inf Retriev."}],"container-title":["Cognitive Computation"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12559-025-10468-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12559-025-10468-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12559-025-10468-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,26]],"date-time":"2025-06-26T02:41:46Z","timestamp":1750905706000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12559-025-10468-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,5,23]]},"references-count":40,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2025,6]]}},"alternative-id":["10468"],"URL":"https:\/\/doi.org\/10.1007\/s12559-025-10468-4","relation":{},"ISSN":["1866-9956","1866-9964"],"issn-type":[{"type":"print","value":"1866-9956"},{"type":"electronic","value":"1866-9964"}],"subject":[],"published":{"date-parts":[[2025,5,23]]},"assertion":[{"value":"20 September 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 May 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 May 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Xindong Wu has received research support from Zhejiang Lab, China. Lei Li is an unpaid Senior Member of IEEE. Zhenchao Tao has been a visiting scholar for Nanyang Technology University from 2022 to 2023. Xindong Wu is an unpaid Fellow of AAAI and IEEE.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing Interests"}},{"value":"Xindong Wu has received research support from Zhejiang Lab, China.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Financial Interests"}},{"value":"Lei Li is an unpaid Senior Member of IEEE. Zhenchao Tao has been a visiting scholar for Nanyang Technology University from 2022 to 2023. Xindong Wu is an unpaid Fellow of AAAI and IEEE.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Non-financial Interests"}}],"article-number":"108"}}