{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T07:42:39Z","timestamp":1740123759359,"version":"3.37.3"},"reference-count":85,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2022,4,9]],"date-time":"2022-04-09T00:00:00Z","timestamp":1649462400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2022,4,9]],"date-time":"2022-04-09T00:00:00Z","timestamp":1649462400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/100014440","name":"Ministerio de Ciencia, Innovaci\u00f3n y Universidades","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100014440","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["User Model User-Adap Inter"],"published-print":{"date-parts":[[2023,4]]},"abstract":"Abstract<\/jats:title>Adapting to dynamic environments is essential for artificial agents, especially those aiming to communicate with people interactively. In this context, a social robot that adapts its behaviour to different users and proactively suggests their favourite activities may produce a more successful interaction. In this work, we describe how the autonomous decision-making system embedded in our social robot Mini can produce a personalised interactive communication experience by considering the preferences of the user the robot interacts with. We compared the performance of Top Label as Class and Ranking by Pairwise Comparison, two promising algorithms in the area, to find the one that best predicts the user preferences. Although both algorithms provide robust results in preference prediction, we decided to integrate Ranking by Pairwise Comparison since it provides better estimations. The method proposed in this contribution allows the autonomous decision-making system of the robot to work on different modes, balancing activity exploration with the selection of the favourite entertaining activities. The operation of the preference learning system is shown in three real case studies where the decision-making system works differently depending on the user the robot is facing. Then, we conducted a human\u2013robot interaction experiment to investigate whether the robot users perceive the personalised selection of activities more appropriate than selecting the activities at random. The results show how the study participants found the personalised activity selection more appropriate, improving their likeability towards the robot and how intelligent they perceive the system. query Please check the edit made in the article title.<\/jats:p>","DOI":"10.1007\/s11257-022-09321-2","type":"journal-article","created":{"date-parts":[[2022,4,9]],"date-time":"2022-04-09T20:02:40Z","timestamp":1649534560000},"page":"359-403","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["An adaptive decision-making system supported on user preference predictions for human\u2013robot interactive communication"],"prefix":"10.1007","volume":"33","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9576-1731","authenticated-orcid":false,"given":"Marcos","family":"Maroto-G\u00f3mez","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5189-0002","authenticated-orcid":false,"given":"\u00c1lvaro","family":"Castro-Gonz\u00e1lez","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0454-9466","authenticated-orcid":false,"given":"Jos\u00e9 Carlos","family":"Castillo","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2317-3329","authenticated-orcid":false,"given":"Mar\u00eda","family":"Malfaz","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0263-6606","authenticated-orcid":false,"given":"Miguel \u00c1ngel","family":"Salichs","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,4,9]]},"reference":[{"key":"9321_CR1","doi-asserted-by":"crossref","unstructured":"Adinolf, S., Wyeth, P., Brown, R., Harman, J.: My little robot: user preferences in game agent customization. In: Proceedings of the annual symposium on computer-human interaction in play, pp 461\u2013471 (2020)","DOI":"10.1145\/3410404.3414241"},{"issue":"12","key":"9321_CR2","doi-asserted-by":"publisher","first-page":"943","DOI":"10.1080\/10447318.2017.1300750","volume":"33","author":"MI Ahmad","year":"2017","unstructured":"Ahmad, M.I., Mubin, O., Orlando, J.: Adaptive social robot for sustaining social engagement during long-term children-robot interaction. Int. J. Human-Comput. Interact. 33(12), 943\u2013962 (2017)","journal-title":"Int. J. Human-Comput. Interact."},{"key":"9321_CR3","unstructured":"Aiolli, F., Sperduti, A.: Learning preferences for multiclass problems. Adv. Neural Info. Process. Syst., pp 17\u201324 (2005)"},{"key":"9321_CR4","doi-asserted-by":"publisher","first-page":"38","DOI":"10.1016\/j.inffus.2016.09.002","volume":"35","author":"JA Aledo","year":"2017","unstructured":"Aledo, J.A., G\u00e1mez, J.A., Molina, D.: Tackling the supervised label ranking problem by bagging weak learners. Inf. Fus. 35, 38\u201350 (2017)","journal-title":"Inf. Fus."},{"key":"9321_CR5","doi-asserted-by":"crossref","unstructured":"Alkhabbas, F., Alawadi, S., Spalazzese, R., Davidsson, P.: Activity recognition and user preference learning for automated configuration of iot environments. In: Proceedings of the 10th international conference on the internet of things, pp 1\u20138 (2020)","DOI":"10.1145\/3410992.3411003"},{"key":"9321_CR6","doi-asserted-by":"crossref","unstructured":"Alonso-Mart\u00edn, F., Gonzalez-Pacheco, V., Castro-Gonz\u00e1lez, \u00c1., Ramey, A., Y\u00e9benes, M., Salichs, M.A. Using a social robot as a gaming platform. In: International Conference on Social Robotics, Springer, pp 30\u201339 (2010)","DOI":"10.1007\/978-3-642-17248-9_4"},{"key":"9321_CR7","doi-asserted-by":"crossref","unstructured":"Bartneck, C., Croft, E., Kulic, D.: Measuring the anthropomorphism, animacy, likeability, perceived intelligence and perceived safety of robots (2008)","DOI":"10.1007\/s12369-008-0001-3"},{"key":"9321_CR8","doi-asserted-by":"crossref","unstructured":"Bertel, L.B., Hannibal, G.: The nao robot as a persuasive educational and entertainment robot (peer)\u2013a case study on children\u2019s articulation, categorization and interaction with a social robot for learning. Tidsskriftet L\u00e6ring og Medier (LOM) 8(14) (2016)","DOI":"10.7146\/lom.v8i14.22057"},{"key":"9321_CR9","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1016\/j.knosys.2013.03.012","volume":"46","author":"J Bobadilla","year":"2013","unstructured":"Bobadilla, J., Ortega, F., Hernando, A., Guti\u00e9rrez, A.: Recommender systems survey. Know. -Based Syst. 46, 109\u2013132 (2013)","journal-title":"Know. -Based Syst."},{"issue":"1","key":"9321_CR10","doi-asserted-by":"publisher","first-page":"47","DOI":"10.3233\/SW-130099","volume":"5","author":"A Bouza","year":"2014","unstructured":"Bouza, A., Bernstein, A.: (partial) user preference similarity as classification-based model similarity. Semantic Web 5(1), 47\u201364 (2014)","journal-title":"Semantic Web"},{"issue":"1","key":"9321_CR11","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1023\/A:1010933404324","volume":"45","author":"L Breiman","year":"2001","unstructured":"Breiman, L.: Random forests. Mach. Learn. 45(1), 5\u201332 (2001)","journal-title":"Mach. Learn."},{"key":"9321_CR12","doi-asserted-by":"crossref","unstructured":"Brinker, K., H\u00fcllermeier, E.: Case-based label ranking. In: European Conference on Machine Learning, Springer, pp 566\u2013573 (2006)","DOI":"10.1007\/11871842_53"},{"key":"9321_CR13","unstructured":"Brinker, K., H\u00fcllermeier, E.: Case-based multilabel ranking. In: IJCAI, pp 702\u2013707 (2007)"},{"issue":"3","key":"9321_CR14","first-page":"13","volume":"32","author":"R Burke","year":"2011","unstructured":"Burke, R., Felfernig, A., G\u00f6ker, M.H.: Recommender systems: an overview. Ai Mag. 32(3), 13\u201318 (2011)","journal-title":"Ai Mag."},{"key":"9321_CR15","doi-asserted-by":"crossref","unstructured":"Ca\u00f1amero, L.: Modeling motivations and emotions as a basis for intelligent behavior. In: Proceedings of the first international conference on Autonomous agents, pp 148\u2013155 (1997)","DOI":"10.1145\/267658.267688"},{"issue":"4","key":"9321_CR16","doi-asserted-by":"publisher","first-page":"445","DOI":"10.1016\/j.neunet.2005.03.003","volume":"18","author":"L Ca\u00f1amero","year":"2005","unstructured":"Ca\u00f1amero, L.: Emotion understanding from the perspective of autonomous robots research. Neural Netw. 18(4), 445\u2013455 (2005)","journal-title":"Neural Netw."},{"key":"9321_CR17","doi-asserted-by":"crossref","unstructured":"Castillo, J.C., Alvarez-Fernandez, D., Alonso-Martin, F., Marques-Villarroya, S., Salichs, M.A.: Social robotics in therapy of apraxia of speech. J. Healthcare Eng. 2018 (2018)","DOI":"10.1155\/2018\/7075290"},{"key":"9321_CR18","doi-asserted-by":"crossref","unstructured":"Cercignani, C.: The boltzmann equation. In: The Boltzmann Equation and its Applications, Springer, pp 40\u2013103 (1988)","DOI":"10.1007\/978-1-4612-1039-9_2"},{"key":"9321_CR19","doi-asserted-by":"publisher","first-page":"107164","DOI":"10.1016\/j.patcog.2019.107164","volume":"100","author":"H Cevikalp","year":"2020","unstructured":"Cevikalp, H., Benligiray, B., Gerek, O.N.: Semi-supervised robust deep neural networks for multi-label image classification. Pattern Recognit. 100, 107164 (2020)","journal-title":"Pattern Recognit."},{"key":"9321_CR20","unstructured":"Chen, Y., Zhang, J., Guo, M., Cao, J.: Learning user preference from heterogeneous information for store-type recommendation. IEEE Trans. Serv. Comput. (2017)"},{"issue":"4","key":"9321_CR21","doi-asserted-by":"publisher","first-page":"4070","DOI":"10.1109\/LRA.2019.2930364","volume":"4","author":"FJ Chu","year":"2019","unstructured":"Chu, F.J., Xu, R., Seguin, L., Vela, P.A.: Toward affordance detection and ranking on novel objects for real-world robotic manipulation. IEEE Robot. Autom. Lett. 4(4), 4070\u20134077 (2019)","journal-title":"IEEE Robot. Autom. Lett."},{"key":"9321_CR22","doi-asserted-by":"crossref","unstructured":"Churamani, N., Anton, P., Br\u00fcgger, M., Flie\u00dfwasser, E., Hummel, T., Mayer, J., Mustafa, W., Ng, H.G., Nguyen, T.L.C., Nguyen, Q., et\u00a0al.: The impact of personalisation on human-robot interaction in learning scenarios. In: Proceedings of the 5th international conference on human agent interaction, pp 171\u2013180 (2017)","DOI":"10.1145\/3125739.3125756"},{"key":"9321_CR23","unstructured":"Cohen, W.W., Schapire, R.E., Singer, Y.: Learning to order things. Adv. Neural Info. Process. Syst., pp 451\u2013457 (1998)"},{"key":"9321_CR24","unstructured":"Corder, G.W., Foreman, D.I.: Nonparametric statistics for non-statisticians (2011)"},{"key":"9321_CR25","unstructured":"Dery, L.: Multi-label ranking: Mining multi-label and label ranking data. arXiv preprint arXiv:210100583 (2021)"},{"key":"9321_CR26","doi-asserted-by":"publisher","first-page":"63","DOI":"10.1016\/j.ijinfomgt.2019.01.021","volume":"48","author":"Y Duan","year":"2019","unstructured":"Duan, Y., Edwards, J.S., Dwivedi, Y.K.: Artificial intelligence for decision making in the era of big data-evolution, challenges and research agenda. Int. J. Info. Manag. 48, 63\u201371 (2019)","journal-title":"Int. J. Info. Manag."},{"issue":"328","key":"9321_CR27","first-page":"1278","volume":"64","author":"B Efron","year":"1969","unstructured":"Efron, B.: Student\u2019s t-test under symmetry conditions. J. Am. Stat. Assoc. 64(328), 1278\u20131302 (1969)","journal-title":"J. Am. Stat. Assoc."},{"issue":"12","key":"9321_CR28","doi-asserted-by":"publisher","first-page":"3440","DOI":"10.3390\/s20123440","volume":"20","author":"E Fern\u00e1ndez-Rodicio","year":"2020","unstructured":"Fern\u00e1ndez-Rodicio, E., Castro-Gonz\u00e1lez, \u00c1., Alonso-Mart\u00edn, F., Maroto-G\u00f3mez, M., Salichs, M.\u00c1.: Modelling multimodal dialogues for social robots using communicative acts. Sensors 20(12), 3440 (2020)","journal-title":"Sensors"},{"key":"9321_CR29","doi-asserted-by":"crossref","unstructured":"F\u00fcrnkranz, J., H\u00fcllermeier, E.: Pairwise preference learning and ranking. In: European Conference on Machine Learning, Springer, pp 145\u2013156 (2003)","DOI":"10.1007\/978-3-540-39857-8_15"},{"key":"9321_CR30","doi-asserted-by":"crossref","unstructured":"F\u00fcrnkranz, J., H\u00fcllermeier, E.: Preference learning and ranking by pairwise comparison. In: Preference Learning, Springer, pp 65\u201382 (2010)","DOI":"10.1007\/978-3-642-14125-6_4"},{"key":"9321_CR31","doi-asserted-by":"crossref","unstructured":"F\u00fcrnkranz, J., H\u00fcllermeier, E., Vanderlooy, S.: Binary decomposition methods for multipartite ranking. In: Joint European Conference on Machine Learning and Knowledge Discovery in Databases, Springer, pp 359\u2013374 (2009)","DOI":"10.1007\/978-3-642-04180-8_41"},{"key":"9321_CR32","doi-asserted-by":"crossref","unstructured":"F\u00fcrnkranz, J. HE: Preference learning: an introduction. In: Preference Learning, Springer, pp 1\u201317 (2010)","DOI":"10.1007\/978-3-642-14125-6_1"},{"key":"9321_CR33","doi-asserted-by":"crossref","unstructured":"Gao, N., Bagdouri, M., Oard, D.W.: Pearson rank: a head-weighted gap-sensitive score-based correlation coefficient. In: Proceedings of the 39th International ACM SIGIR conference on research and development in information retrieval, pp 941\u2013944 (2016)","DOI":"10.1145\/2911451.2914728"},{"key":"9321_CR34","doi-asserted-by":"publisher","first-page":"125","DOI":"10.1016\/j.asoc.2019.03.041","volume":"79","author":"F Gargiulo","year":"2019","unstructured":"Gargiulo, F., Silvestri, S., Ciampi, M., De Pietro, G.: Deep neural network for hierarchical extreme multi-label text classification. Appl. Soft Comput. 79, 125\u2013138 (2019)","journal-title":"Appl. Soft Comput."},{"key":"9321_CR35","doi-asserted-by":"crossref","unstructured":"Gharroudi, O., Elghazel, H., Aussem, A.: A comparison of multi-label feature selection methods using the random forest paradigm. In: Canadian Conference on Artificial Intelligence, Springer, pp 95\u2013106 (2014)","DOI":"10.1007\/978-3-319-06483-3_9"},{"key":"9321_CR36","doi-asserted-by":"crossref","unstructured":"Giakoumis D, Peleka, G., Vasileiadis, M., Kostavelis, I., Tzovaras, D.: Service robot behaviour adaptation based on user mood, towards better personalized support of mci patients at home. In: Smart Assisted Living, Springer, pp 209\u2013226 (2020)","DOI":"10.1007\/978-3-030-25590-9_10"},{"issue":"2","key":"9321_CR37","first-page":"69","volume":"4","author":"K Goztepe","year":"2015","unstructured":"Goztepe, K.: New directions in military and security studies: artificial intelligence and military decision making process. Int. J. Info. Security Sci. 4(2), 69\u201380 (2015)","journal-title":"Int. J. Info. Security Sci."},{"issue":"3","key":"9321_CR38","doi-asserted-by":"publisher","first-page":"462","DOI":"10.1075\/is.17.3.08deg","volume":"17","author":"MM de Graaf","year":"2016","unstructured":"de Graaf, M.M., Allouch, S.B., van Dijk, J.A.: Long-term evaluation of a social robot in real homes. Interact. Stud. 17(3), 462\u2013491 (2016)","journal-title":"Interact. Stud."},{"key":"9321_CR39","doi-asserted-by":"crossref","unstructured":"Han, M., G\u00fcnay, S.Y., Yildiz, I., Bonato, P., Onal, C.D., Padir, T., Schirner, G., Erdo\u011fmu\u015f, D.: From hand-perspective visual information to grasp type probabilities: deep learning via ranking labels. In: Proceedings of the 12th ACM international conference on pervasive technologies related to assistive environments, pp 256\u2013263 (2019)","DOI":"10.1145\/3316782.3316794"},{"issue":"16\u201317","key":"9321_CR40","doi-asserted-by":"publisher","first-page":"1897","DOI":"10.1016\/j.artint.2008.08.002","volume":"172","author":"E H\u00fcllermeier","year":"2008","unstructured":"H\u00fcllermeier, E., F\u00fcrnkranz, J., Cheng, W., Brinker, K.: Label ranking by learning pairwise preferences. Artif. Intell. 172(16\u201317), 1897\u20131916 (2008)","journal-title":"Artif. Intell."},{"issue":"8","key":"9321_CR41","doi-asserted-by":"publisher","first-page":"34","DOI":"10.1109\/MC.2007.289","volume":"40","author":"T Joachims","year":"2007","unstructured":"Joachims, T., Radlinski, F.: Search engines that learn from implicit feedback. Computer 40(8), 34\u201340 (2007)","journal-title":"Computer"},{"key":"9321_CR42","doi-asserted-by":"crossref","unstructured":"Kendall, M.G.: The treatment of ties in ranking problems. Biometrika pp 239\u2013251 (1945)","DOI":"10.1093\/biomet\/33.3.239"},{"key":"9321_CR43","doi-asserted-by":"crossref","unstructured":"Khalili, A.H., Wu, C., Aghajan, H.: Hierarchical preference learning for light control from user feedback. In: 2010 IEEE computer society conference on computer vision and pattern recognition-workshops, IEEE, pp 56\u201362 (2010)","DOI":"10.1109\/CVPRW.2010.5543265"},{"issue":"4","key":"9321_CR44","doi-asserted-by":"publisher","first-page":"881","DOI":"10.1109\/TCDS.2018.2843122","volume":"10","author":"M Khamassi","year":"2018","unstructured":"Khamassi, M., Velentzas, G., Tsitsimis, T., Tzafestas, C.: Robot fast adaptation to changes in human engagement during simulated dynamic social interaction with active exploration in parameterized reinforcement learning. IEEE Trans. Cognitive Dev. Syst. 10(4), 881\u2013893 (2018)","journal-title":"IEEE Trans. Cognitive Dev. Syst."},{"key":"9321_CR45","doi-asserted-by":"crossref","unstructured":"Kubota, A., Riek, L.D.: Methods for robot behavior adaptation for cognitive neurorehabilitation. Annual review of control, robotics, and autonomous systems 5 (2021)","DOI":"10.1146\/annurev-control-042920-093225"},{"key":"9321_CR46","doi-asserted-by":"crossref","unstructured":"Lei, Z., Zeng, Y., Liu, P., Su, X.: Active deep learning for hyperspectral image classification with uncertainty learning. IEEE Geosci. Remote Sens. Lett. (2021)","DOI":"10.1109\/LGRS.2020.3045437"},{"issue":"2","key":"9321_CR47","doi-asserted-by":"publisher","first-page":"291","DOI":"10.1007\/s12369-013-0178-y","volume":"5","author":"I Leite","year":"2013","unstructured":"Leite, I., Martinho, C., Paiva, A.: Social robots for long-term interaction: a survey. Int. J. Soc. Robot. 5(2), 291\u2013308 (2013)","journal-title":"Int. J. Soc. Robot."},{"key":"9321_CR48","doi-asserted-by":"crossref","unstructured":"Liu, J., Chang, W.C., Wu, Y., Yang, Y.: Deep learning for extreme multi-label text classification. In: Proceedings of the 40th international ACM SIGIR conference on research and development in information retrieval, pp 115\u2013124 (2017)","DOI":"10.1145\/3077136.3080834"},{"key":"9321_CR49","doi-asserted-by":"crossref","unstructured":"Long, Y., Lu, Q., Xiao, Y., Li, M., Huang, C.R.: Domain-specific user preference prediction based on multiple user activities. In: 2016 IEEE international conference on big data (big data), IEEE, pp 3913\u20133921 (2016)","DOI":"10.1109\/BigData.2016.7841066"},{"issue":"8","key":"9321_CR50","doi-asserted-by":"publisher","first-page":"2691","DOI":"10.3390\/s18082691","volume":"18","author":"M Maroto-G\u00f3mez","year":"2018","unstructured":"Maroto-G\u00f3mez, M., Castro-Gonz\u00e1lez, \u00c1., Castillo, J.C., Malfaz, M., Salichs, M.A.: A bio-inspired motivational decision making system for social robots based on the perception of the user. Sensors 18(8), 2691 (2018)","journal-title":"Sensors"},{"issue":"17","key":"9321_CR51","doi-asserted-by":"publisher","first-page":"4792","DOI":"10.3390\/s20174792","volume":"20","author":"A Mart\u00edn","year":"2020","unstructured":"Mart\u00edn, A., Pulido, J.C., Gonz\u00e1lez, J.C., Garc\u00eda-Olaya, \u00c1., Su\u00e1rez, C.: A framework for user adaptation and profiling for social robotics in rehabilitation. Sensors 20(17), 4792 (2020)","journal-title":"Sensors"},{"issue":"1","key":"9321_CR52","doi-asserted-by":"publisher","first-page":"185","DOI":"10.1007\/s12369-018-0485-4","volume":"11","author":"GS Martins","year":"2019","unstructured":"Martins, G.S., Santos, L., Dias, J.: User-adaptive interaction in social robots: a survey focusing on non-physical interaction. Int. J. Soc. Robot. 11(1), 185\u2013205 (2019)","journal-title":"Int. J. Soc. Robot."},{"issue":"3","key":"9321_CR53","first-page":"43","volume":"9","author":"I Olaronke","year":"2017","unstructured":"Olaronke, I., Oluwaseun, O., Rhoda, I.: State of the art: a study of human-robot interaction in healthcare. Int. J. Info. Eng. Elect. Bus. 9(3), 43 (2017)","journal-title":"Int. J. Info. Eng. Elect. Bus."},{"key":"9321_CR54","doi-asserted-by":"crossref","unstructured":"Olsson, T., Salo, M.: Online user survey on current mobile augmented reality applications. In: 2011 10th IEEE International symposium on mixed and augmented reality, IEEE, pp 75\u201384 (2011)","DOI":"10.1109\/ISMAR.2011.6092372"},{"key":"9321_CR55","doi-asserted-by":"crossref","unstructured":"Pang, L., Lan, Y., Guo, J., Xu, J., Xu, J., Cheng, X.: Deeprank: A new deep architecture for relevance ranking in information retrieval. In: Proceedings of the 2017 ACM on conference on information and knowledge management, pp 257\u2013266 (2017)","DOI":"10.1145\/3132847.3132914"},{"issue":"6245","key":"9321_CR56","doi-asserted-by":"publisher","first-page":"267","DOI":"10.1126\/science.aaa8403","volume":"349","author":"DC Parkes","year":"2015","unstructured":"Parkes, D.C., Wellman, M.P.: Economic reasoning and artificial intelligence. Science 349(6245), 267\u2013272 (2015)","journal-title":"Science"},{"key":"9321_CR57","unstructured":"Prelipcean, G., Boscoianu, M., Moisescu, F.: New ideas on the artificial intelligence support in military applications. In: Proceedings of the 9th WSEAS international conference on Artificial intelligence, knowledge engineering and data bases, World Scientific and Engineering Academy and Society (WSEAS), pp 34\u201339 (2010)"},{"key":"9321_CR58","doi-asserted-by":"crossref","unstructured":"Rosenthal-von\u00a0der P\u00fctten, A., Abrams, A.M.: Social dynamics in human-robot groups\u2013possible consequences of unequal adaptation to group members through machine learning in human-robot groups. In: International Conference on Human-Computer Interaction, Springer, pp 396\u2013411 (2020)","DOI":"10.1007\/978-3-030-50334-5_27"},{"key":"9321_CR59","doi-asserted-by":"publisher","first-page":"77","DOI":"10.1613\/jair.279","volume":"4","author":"JR Quinlan","year":"1996","unstructured":"Quinlan, J.R.: Improved use of continuous attributes in c4. 5. J. Artif. Intell. Res. 4, 77\u201390 (1996)","journal-title":"J. Artif. Intell. Res."},{"key":"9321_CR60","doi-asserted-by":"crossref","unstructured":"Ritschel, H., Andr\u00e9, E.: Real-time robot personality adaptation based on reinforcement learning and social signals. In: Proceedings of the companion of the 2017 acm\/iEEE international conference on human-robot interaction, pp 265\u2013266 (2017)","DOI":"10.1145\/3029798.3038381"},{"key":"9321_CR61","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1016\/j.patrec.2017.06.002","volume":"99","author":"S Rossi","year":"2017","unstructured":"Rossi, S., Ferland, F., Tapus, A.: User profiling and behavioral adaptation for hri: a survey. Pattern Recog. Lett. 99, 3\u201312 (2017)","journal-title":"Pattern Recog. Lett."},{"issue":"1","key":"9321_CR62","doi-asserted-by":"publisher","first-page":"e12166","DOI":"10.1111\/exsy.12166","volume":"34","author":"CR de S\u00e1","year":"2017","unstructured":"de S\u00e1, C.R., Soares, C., Knobbe, A., Cortez, P.: Label ranking forests. Expert Syst. 34(1), e12166 (2017)","journal-title":"Expert Syst."},{"key":"9321_CR63","doi-asserted-by":"crossref","unstructured":"Salichs, M.A., Castro-Gonz\u00e1lez, \u00c1., Salichs, E., Fern\u00e1ndez-Rodicio, E., Maroto-G\u00f3mez, M., Gamboa-Montero, J.J., Marques-Villarroya, S., Castillo, J.C., Alonso-Mart\u00edn, F., Malfaz, M.: Mini: A new social robot for the elderly. Int. J. Soc. Robot. pp 1\u201319 (2020)","DOI":"10.1007\/s12369-020-00687-0"},{"issue":"2","key":"9321_CR64","doi-asserted-by":"publisher","first-page":"169","DOI":"10.1007\/s12369-020-00629-w","volume":"13","author":"S Schneider","year":"2021","unstructured":"Schneider, S., Kummert, F.: Comparing robot and human guided personalization: adaptive exercise robots are perceived as more competent and trustworthy. Int. J. Soc. Robot. 13(2), 169\u2013185 (2021)","journal-title":"Int. J. Soc. Robot."},{"issue":"5","key":"9321_CR65","doi-asserted-by":"publisher","first-page":"1763","DOI":"10.1213\/ANE.0000000000002864","volume":"126","author":"P Schober","year":"2018","unstructured":"Schober, P., Boer, C., Schwarte, L.A.: Correlation coefficients: appropriate use and interpretation. Anesthesia Analgesia 126(5), 1763\u20131768 (2018)","journal-title":"Anesthesia Analgesia"},{"key":"9321_CR66","doi-asserted-by":"crossref","unstructured":"Sch\u00fctze, H., Manning, C.D., Raghavan, P.: Introduction to information retrieval, vol\u00a039. Cambridge University Press Cambridge (2008)","DOI":"10.1017\/CBO9780511809071"},{"key":"9321_CR67","doi-asserted-by":"crossref","unstructured":"Spearman, C.: The proof and measurement of association between two things (1961)","DOI":"10.1037\/11491-005"},{"key":"9321_CR68","doi-asserted-by":"publisher","first-page":"179","DOI":"10.1201\/9781420089653.ch10","volume":"9","author":"D Steinberg","year":"2009","unstructured":"Steinberg, D., Colla, P.: Cart: classification and regression trees. Top Ten Algorithms Data Min. 9, 179 (2009)","journal-title":"Top Ten Algorithms Data Min."},{"issue":"4","key":"9321_CR69","doi-asserted-by":"publisher","first-page":"1502","DOI":"10.12928\/telkomnika.v14i4.3956","volume":"14","author":"I Syarif","year":"2016","unstructured":"Syarif, I., Prugel-Bennett, A., Wills, G.: Svm parameter optimization using grid search and genetic algorithm to improve classification performance. Telkomnika 14(4), 1502 (2016)","journal-title":"Telkomnika"},{"issue":"2","key":"9321_CR70","doi-asserted-by":"publisher","first-page":"169","DOI":"10.1007\/s11370-008-0017-4","volume":"1","author":"A Tapus","year":"2008","unstructured":"Tapus, A., \u0162\u0103pu\u015f, C., Matari\u0107, M.J.: User-robot personality matching and assistive robot behavior adaptation for post-stroke rehabilitation therapy. Intell. Service Robot. 1(2), 169 (2008)","journal-title":"Intell. Service Robot."},{"key":"9321_CR71","doi-asserted-by":"crossref","unstructured":"Tozadore, D.C., Valentini, J.P., Rodrigues, V.H., Vendrameto, F.M., Zavarizz, R.G., Romero, R.A.: Towards adaptation and personalization in task based on human-robot interaction. In: 2018 Latin American Robotic Symposium, 2018 Brazilian Symposium on robotics (SBR) and 2018 workshop on robotics in education (WRE), IEEE, pp 383\u2013389 (2018)","DOI":"10.1109\/LARS\/SBR\/WRE.2018.00075"},{"key":"9321_CR72","doi-asserted-by":"crossref","unstructured":"Vel\u00e1squez, J.D.: Cathexis\u2013a computational model for the generation of emotions and their influence in the behavior of autonomous agents. Ph.D. thesis, Massachusetts Institute of Technology (1996)","DOI":"10.1145\/267658.267808"},{"key":"9321_CR73","doi-asserted-by":"crossref","unstructured":"Vembu, S., G\u00e4rtner, T.: Label ranking algorithms: a survey. In: Preference Learning, Springer, pp 45\u201364 (2010)","DOI":"10.1007\/978-3-642-14125-6_3"},{"issue":"2","key":"9321_CR74","doi-asserted-by":"publisher","first-page":"102441","DOI":"10.1016\/j.ipm.2020.102441","volume":"58","author":"R Wang","year":"2021","unstructured":"Wang, R., Ridley, R., Qu, W., Dai, X., et al.: A novel reasoning mechanism for multi-label text classification. Info. Process. Manag. 58(2), 102441 (2021)","journal-title":"Info. Process. Manag."},{"key":"9321_CR75","doi-asserted-by":"crossref","unstructured":"Weber, K., Ritschel, H., Aslan, I., Lingenfelser, F., Andr\u00e9, E.: How to shape the humor of a robot-social behavior adaptation based on reinforcement learning. In: Proceedings of the 20th ACM international conference on multimodal interaction, pp 154\u2013162 (2018)","DOI":"10.1145\/3242969.3242976"},{"key":"9321_CR76","doi-asserted-by":"crossref","unstructured":"Weiss, A., Bartneck, C.: Meta analysis of the usage of the godspeed questionnaire series. In: 2015 24th IEEE International symposium on robot and human interactive communication (RO-MAN), IEEE, pp 381\u2013388 (2015)","DOI":"10.1109\/ROMAN.2015.7333568"},{"key":"9321_CR77","doi-asserted-by":"crossref","unstructured":"Wen, S., Liu, W., Yang, Y., Zhou, P., Guo, Z., Yan, Z., Chen, Y., Huang, T.: Multilabel image classification via feature\/label co-projection. IEEE Transactions on Systems, Man, and Cybernetics: Systems (2020)","DOI":"10.1109\/TSMC.2020.2967071"},{"key":"9321_CR78","doi-asserted-by":"publisher","first-page":"50","DOI":"10.1016\/j.eswa.2019.06.022","volume":"136","author":"H Werbin-Ofir","year":"2019","unstructured":"Werbin-Ofir, H., Dery, L., Shmueli, E.: Beyond majority: Label ranking ensembles based on voting rules. Expert Syst. Appl. 136, 50\u201361 (2019)","journal-title":"Expert Syst. Appl."},{"key":"9321_CR79","unstructured":"Woodworth, B., Ferrari, F., Zosa, T.E., Riek, L.D.: Preference learning in assistive robotics: Observational repeated inverse reinforcement learning. In: Machine learning for healthcare conference, PMLR, pp 420\u2013439 (2018)"},{"issue":"2","key":"9321_CR80","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3379504","volume":"53","author":"J Wu","year":"2020","unstructured":"Wu, J., Sheng, V.S., Zhang, J., Li, H., Dadakova, T., Swisher, C.L., Cui, Z., Zhao, P.: Multi-label active learning algorithms for image classification: overview and future promise. ACM Comput. Surv. (CSUR) 53(2), 1\u201335 (2020)","journal-title":"ACM Comput. Surv. (CSUR)"},{"key":"9321_CR81","first-page":"5820","volume":"32","author":"R You","year":"2019","unstructured":"You, R., Zhang, Z., Wang, Z., Dai, S., Mamitsuka, H., Zhu, S.: Attentionxml: label tree-based attention-aware deep model for high-performance extreme multi-label text classification. Adv. Neural Info. Process. Syst. 32, 5820\u20135830 (2019)","journal-title":"Adv. Neural Info. Process. Syst."},{"key":"9321_CR82","unstructured":"Zheng, Z., Zha, H., Zhang, T., Chapelle, O., Chen, K., Sun, G.: A general boosting method and its application to learning ranking functions for web search. Adv. Neural Info. Process. Syst., pp 1697\u20131704 (2008)"},{"issue":"1","key":"9321_CR83","doi-asserted-by":"publisher","first-page":"e0245344","DOI":"10.1371\/journal.pone.0245344","volume":"16","author":"J Zhou","year":"2021","unstructured":"Zhou, J., Jiang, Y., Huang, B.: Source identification of infectious diseases in networks via label ranking. PloS one 16(1), e0245344 (2021)","journal-title":"PloS one"},{"key":"9321_CR84","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1016\/j.eswa.2018.06.036","volume":"112","author":"Y Zhou","year":"2018","unstructured":"Zhou, Y., Qiu, G.: Random forest for label ranking. Expert Syst. Appl. 112, 99\u2013109 (2018)","journal-title":"Expert Syst. Appl."},{"issue":"3","key":"9321_CR85","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1080\/00220973.1987.10806451","volume":"55","author":"DW Zimmerman","year":"1987","unstructured":"Zimmerman, D.W.: Comparative power of student t test and mann-whitney u test for unequal sample sizes and variances. J. Exp. Edu. 55(3), 171\u2013174 (1987)","journal-title":"J. Exp. Edu."}],"container-title":["User Modeling and User-Adapted Interaction"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11257-022-09321-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11257-022-09321-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11257-022-09321-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,4,28]],"date-time":"2023-04-28T17:07:03Z","timestamp":1682701623000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11257-022-09321-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,4,9]]},"references-count":85,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2023,4]]}},"alternative-id":["9321"],"URL":"https:\/\/doi.org\/10.1007\/s11257-022-09321-2","relation":{},"ISSN":["0924-1868","1573-1391"],"issn-type":[{"type":"print","value":"0924-1868"},{"type":"electronic","value":"1573-1391"}],"subject":[],"published":{"date-parts":[[2022,4,9]]},"assertion":[{"value":"29 December 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 March 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 April 2022","order":3,"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"}}]}}