{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T11:37:19Z","timestamp":1775734639135,"version":"3.50.1"},"publisher-location":"Cham","reference-count":34,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031784644","type":"print"},{"value":"9783031784651","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,12,21]],"date-time":"2024-12-21T00:00:00Z","timestamp":1734739200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,12,21]],"date-time":"2024-12-21T00:00:00Z","timestamp":1734739200000},"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":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-3-031-78465-1_9","type":"book-chapter","created":{"date-parts":[[2024,12,20]],"date-time":"2024-12-20T02:23:14Z","timestamp":1734661394000},"page":"105-117","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Machine Learning-Based Exploration of Eye-Tracking Data to Predict Offer Selection"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2541-1909","authenticated-orcid":false,"given":"Mateusz","family":"Piwowarski","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4414-8547","authenticated-orcid":false,"given":"Pawe\u0142","family":"Ziemba","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0303-4073","authenticated-orcid":false,"given":"Jacek","family":"Cypryja\u0144ski","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,12,21]]},"reference":[{"key":"9_CR1","doi-asserted-by":"publisher","first-page":"280","DOI":"10.1086\/341577","volume":"29","author":"JA Bargh","year":"2002","unstructured":"Bargh, J.A.: Losing consciousness: automatic influences on consumer judgment, behavior, and motivation. J. Consum. Res. 29, 280\u2013285 (2002). https:\/\/doi.org\/10.1086\/341577","journal-title":"J. Consum. Res."},{"key":"9_CR2","first-page":"75","volume":"7","author":"M Koklic","year":"2009","unstructured":"Koklic, M., Vida, I.: A strategic household purchase: consumer house buying behavior. Manag. Global Trans. 7, 75\u201396 (2009)","journal-title":"Manag. Global Trans."},{"key":"9_CR3","first-page":"5","volume":"31","author":"B Bogdanowicz","year":"2017","unstructured":"Bogdanowicz, B., Cypryja\u0144ski, J.: Czynniki determinuj\u0105ce pozytywny odbi\u00f3r wizualizacji architektonicznych w opinii grafik\u00f3w. Architecturae et Artibus. 31, 5 (2017)","journal-title":"Architecturae et Artibus."},{"key":"9_CR4","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1167\/jov.22.11.9","volume":"22","author":"N Broers","year":"2022","unstructured":"Broers, N., Bainbridge, W.A., Michel, R., Balestrieri, E., Busch, N.A.: The extent and specificity of visual exploration determines the formation of recollected memories in complex scenes. J. Vis. 22, 9 (2022). https:\/\/doi.org\/10.1167\/jov.22.11.9","journal-title":"J. Vis."},{"key":"9_CR5","doi-asserted-by":"publisher","first-page":"1601","DOI":"10.3758\/s13423-021-01920-1","volume":"28","author":"A Mikhailova","year":"2021","unstructured":"Mikhailova, A., Raposo, A., Sala, S.D., Coco, M.I.: Eye-movements reveal semantic interference effects during the encoding of naturalistic scenes in long-term memory. Psychon. Bull. Rev. 28, 1601\u20131614 (2021). https:\/\/doi.org\/10.3758\/s13423-021-01920-1","journal-title":"Psychon. Bull. Rev."},{"key":"9_CR6","doi-asserted-by":"publisher","DOI":"10.1016\/j.dcn.2019.100710","volume":"40","author":"RS Hessels","year":"2019","unstructured":"Hessels, R.S., Hooge, I.T.C.: Eye-tracking in developmental cognitive neuroscience\u2014the good, the bad and the ugly. Dev. Cogn. Neurosci. 40, 100710 (2019). https:\/\/doi.org\/10.1016\/j.dcn.2019.100710","journal-title":"Dev. Cogn. Neurosci."},{"key":"9_CR7","doi-asserted-by":"publisher","unstructured":"Hu, T., Wang, X., Xu, H.: Eye-tracking in interpreting studies: a review of four decades of empirical studies. Front. Psychol. 13 (2022). https:\/\/doi.org\/10.3389\/fpsyg.2022.872247","DOI":"10.3389\/fpsyg.2022.872247"},{"key":"9_CR8","doi-asserted-by":"publisher","first-page":"7168","DOI":"10.1523\/JNEUROSCI.1832-07.2007","volume":"27","author":"C Maioli","year":"2007","unstructured":"Maioli, C., Falciati, L., Gianesini, T.: Pursuit eye movements involve a covert motor plan for manual tracking. J. Neurosci. 27, 7168\u20137173 (2007). https:\/\/doi.org\/10.1523\/JNEUROSCI.1832-07.2007","journal-title":"J. Neurosci."},{"key":"9_CR9","doi-asserted-by":"publisher","first-page":"1457","DOI":"10.1016\/j.visres.2010.12.014","volume":"51","author":"E Kowler","year":"2011","unstructured":"Kowler, E.: Eye movements: the past 25 years. Vision. Res. 51, 1457\u20131483 (2011). https:\/\/doi.org\/10.1016\/j.visres.2010.12.014","journal-title":"Vision. Res."},{"key":"9_CR10","doi-asserted-by":"publisher","first-page":"515","DOI":"10.1080\/13467581.2023.2244566","volume":"23","author":"JY Kim","year":"2024","unstructured":"Kim, J.Y., Kim, M.J.: Identifying customer preferences through the eye-tracking in travel websites focusing on neuromarketing. J. Asian Architect. Build. Eng. 23, 515\u2013527 (2024). https:\/\/doi.org\/10.1080\/13467581.2023.2244566","journal-title":"J. Asian Architect. Build. Eng."},{"key":"9_CR11","doi-asserted-by":"publisher","first-page":"4180","DOI":"10.1016\/j.procs.2022.09.481","volume":"207","author":"P Wlek\u0142y","year":"2022","unstructured":"Wlek\u0142y, P., Piwowarski, M.: The usability of eye-tracking in the design of digital training materials. Procedia Comput. Sci. 207, 4180\u20134189 (2022). https:\/\/doi.org\/10.1016\/j.procs.2022.09.481","journal-title":"Procedia Comput. Sci."},{"key":"9_CR12","doi-asserted-by":"publisher","first-page":"230","DOI":"10.3109\/10673229.2010.496623","volume":"18","author":"CE Fisher","year":"2010","unstructured":"Fisher, C.E., Chin, L., Klitzman, R.: Defining neuromarketing: practices and professional challenges. Harv. Rev. Psychiatry 18, 230 (2010). https:\/\/doi.org\/10.3109\/10673229.2010.496623","journal-title":"Harv. Rev. Psychiatry"},{"key":"9_CR13","doi-asserted-by":"publisher","first-page":"293","DOI":"10.1007\/s11257-023-09373-y","volume":"34","author":"D Castilla","year":"2024","unstructured":"Castilla, D., et al.: Improving the understanding of web user behaviors through machine learning analysis of eye-tracking data. User Model. User-Adap. Inter. 34, 293\u2013322 (2024). https:\/\/doi.org\/10.1007\/s11257-023-09373-y","journal-title":"User Model. User-Adap. Inter."},{"key":"9_CR14","doi-asserted-by":"publisher","first-page":"713","DOI":"10.3390\/make5030038","volume":"5","author":"A Pina","year":"2023","unstructured":"Pina, A., Petersheim, C., Cherian, J., Lahey, J.N., Alexander, G., Hammond, T.: Using machine learning with eye-tracking data to predict if a recruiter will approve a resume. Mach. Learn. Knowl. Extr. 5, 713\u2013724 (2023). https:\/\/doi.org\/10.3390\/make5030038","journal-title":"Mach. Learn. Knowl. Extr."},{"key":"9_CR15","doi-asserted-by":"publisher","unstructured":"Lim, J.Z., Mountstephens, J., Teo, J.: Eye-tracking feature extraction for biometric machine learning. Front. Neurorobot. 15, (2022). https:\/\/doi.org\/10.3389\/fnbot.2021.796895","DOI":"10.3389\/fnbot.2021.796895"},{"key":"9_CR16","doi-asserted-by":"publisher","unstructured":"Nov\u00e1k, J.\u0160., Masner, J., Benda, P., \u0160imek, P., Merunka, V.: Eye tracking, usability, and user experience: a systematic review. Int. J. Hum. Comput. Interact. 40(17), 4484\u20134500 (2024).https:\/\/doi.org\/10.1080\/10447318.2023.2221600","DOI":"10.1080\/10447318.2023.2221600"},{"key":"9_CR17","doi-asserted-by":"publisher","first-page":"7","DOI":"10.1186\/s41235-019-0159-2","volume":"4","author":"TT Bruny\u00e9","year":"2019","unstructured":"Bruny\u00e9, T.T., Drew, T., Weaver, D.L., Elmore, J.G.: A review of eye-tracking for understanding and improving diagnostic interpretation. Cogn. Res. Princ. Implic. 4, 7 (2019). https:\/\/doi.org\/10.1186\/s41235-019-0159-2","journal-title":"Cogn. Res. Princ. Implic."},{"key":"9_CR18","doi-asserted-by":"publisher","unstructured":"Mahanama, B., et al.: Eye movement and pupil measures: a review. Front. Comput. Sci. 3 (2022). https:\/\/doi.org\/10.3389\/fcomp.2021.733531","DOI":"10.3389\/fcomp.2021.733531"},{"key":"9_CR19","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1016\/j.foodqual.2014.06.015","volume":"39","author":"LN van der Laan","year":"2015","unstructured":"van der Laan, L.N., Hooge, I.T.C., de Ridder, D.T.D., Viergever, M.A., Smeets, P.A.M.: Do you like what you see? The role of first fixation and total fixation duration in consumer choice. Food Qual. Prefer. 39, 46\u201355 (2015). https:\/\/doi.org\/10.1016\/j.foodqual.2014.06.015","journal-title":"Food Qual. Prefer."},{"key":"9_CR20","doi-asserted-by":"publisher","first-page":"229","DOI":"10.1016\/j.ergon.2015.12.001","volume":"53","author":"F Guo","year":"2016","unstructured":"Guo, F., Ding, Y., Liu, W., Liu, C., Zhang, X.: Can eye-tracking data be measured to assess product design?: Visual attention mechanism should be considered. Int. J. Ind. Ergon. 53, 229\u2013235 (2016). https:\/\/doi.org\/10.1016\/j.ergon.2015.12.001","journal-title":"Int. J. Ind. Ergon."},{"key":"9_CR21","doi-asserted-by":"publisher","first-page":"2191","DOI":"10.1001\/jama.2013.281053","volume":"310","author":"World Medical Association","year":"2013","unstructured":"World Medical Association: World medical association declaration of Helsinki: ethical principles for medical research involving human subjects. JAMA 310, 2191 (2013). https:\/\/doi.org\/10.1001\/jama.2013.281053","journal-title":"JAMA"},{"key":"9_CR22","doi-asserted-by":"publisher","first-page":"2099","DOI":"10.3390\/electronics10172099","volume":"10","author":"P Ziemba","year":"2021","unstructured":"Ziemba, P., Becker, J., Becker, A., Radomska-Zalas, A., Pawluk, M., Wierzba, D.: Credit decision support based on real set of cash loans using integrated machine learning algorithms. Electronics 10, 2099 (2021). https:\/\/doi.org\/10.3390\/electronics10172099","journal-title":"Electronics"},{"key":"9_CR23","doi-asserted-by":"publisher","unstructured":"Quinlan, J.R.: Improved use of continuous attributes in C4.5. J. Artif. Intell. Res 4, 77\u201390 (1996). https:\/\/doi.org\/10.1613\/jair.279","DOI":"10.1613\/jair.279"},{"key":"9_CR24","doi-asserted-by":"publisher","unstructured":"Kohavi, R.: The power of decision tables. In: Proceedings of the 8th European Conference on Machine Learning. Springer-Verlag, Berlin, Heidelberg, pp. 174\u2013189 (1995). https:\/\/doi.org\/10.1007\/3-540-59286-5_57","DOI":"10.1007\/3-540-59286-5_57"},{"key":"9_CR25","doi-asserted-by":"publisher","unstructured":"Park, Y.-S., Lek, S.: Chapter 7\u2014Artificial neural networks: multilayer perceptron for ecological modeling. In: J\u00f8rgensen, S.E. (ed.) Developments in Environmental Modelling. Elsevier, pp. 123\u2013140 (2016). https:\/\/doi.org\/10.1016\/B978-0-444-63623-2.00007-4","DOI":"10.1016\/B978-0-444-63623-2.00007-4"},{"key":"9_CR26","doi-asserted-by":"publisher","unstructured":"Yuk Carrie Lin, K.: Optimizing variable selection and neighbourhood size in the K-nearest neighbour algorithm. Comput. Ind. Eng. 191, 110142 (2024). https:\/\/doi.org\/10.1016\/j.cie.2024.110142","DOI":"10.1016\/j.cie.2024.110142"},{"key":"9_CR27","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2023.126874","volume":"562","author":"Q Wang","year":"2023","unstructured":"Wang, Q., et al.: A hybrid SVM and kernel function-based sparse representation classification for automated epilepsy detection in EEG signals. Neurocomputing 562, 126874 (2023). https:\/\/doi.org\/10.1016\/j.neucom.2023.126874","journal-title":"Neurocomputing"},{"key":"9_CR28","doi-asserted-by":"publisher","first-page":"357","DOI":"10.1016\/j.ejor.2023.06.036","volume":"312","author":"Y Chen","year":"2024","unstructured":"Chen, Y., Calabrese, R., Martin-Barragan, B.: Interpretable machine learning for imbalanced credit scoring datasets. Eur. J. Oper. Res. 312, 357\u2013372 (2024). https:\/\/doi.org\/10.1016\/j.ejor.2023.06.036","journal-title":"Eur. J. Oper. Res."},{"key":"9_CR29","doi-asserted-by":"publisher","first-page":"8580","DOI":"10.1016\/j.eswa.2011.01.061","volume":"38","author":"JP Hwang","year":"2011","unstructured":"Hwang, J.P., Park, S., Kim, E.: A new weighted approach to imbalanced data classification problem via support vector machine with quadratic cost function. Expert Syst. Appl. 38, 8580\u20138585 (2011). https:\/\/doi.org\/10.1016\/j.eswa.2011.01.061","journal-title":"Expert Syst. Appl."},{"key":"9_CR30","doi-asserted-by":"publisher","first-page":"48","DOI":"10.1016\/j.ecolmodel.2008.05.015","volume":"217","author":"EA Freeman","year":"2008","unstructured":"Freeman, E.A., Moisen, G.G.: A comparison of the performance of threshold criteria for binary classification in terms of predicted prevalence and kappa. Ecol. Model. 217, 48\u201358 (2008). https:\/\/doi.org\/10.1016\/j.ecolmodel.2008.05.015","journal-title":"Ecol. Model."},{"key":"9_CR31","doi-asserted-by":"publisher","first-page":"321","DOI":"10.1613\/jair.953","volume":"16","author":"NV Chawla","year":"2002","unstructured":"Chawla, N.V., Bowyer, K.W., Hall, L.O., Kegelmeyer, W.P.: SMOTE: synthetic minority over-sampling technique. J. Artif. Intell. Res. 16, 321\u2013357 (2002). https:\/\/doi.org\/10.1613\/jair.953","journal-title":"J. Artif. Intell. Res."},{"key":"9_CR32","doi-asserted-by":"publisher","unstructured":"Pushpalatha, K.R., Karegowda, A.G.: CFS based feature subset selection for enhancing classification of similar looking food grains\u2014a filter approach. In: 2017 2nd International Conference On Emerging Computation and Information Technologies (ICECIT), pp. 1\u20136 (2017). https:\/\/doi.org\/10.1109\/ICECIT.2017.8453403","DOI":"10.1109\/ICECIT.2017.8453403"},{"key":"9_CR33","doi-asserted-by":"publisher","DOI":"10.1016\/j.clet.2023.100664","volume":"15","author":"SM Malakouti","year":"2023","unstructured":"Malakouti, S.M., Menhaj, M.B., Suratgar, A.A.: The usage of 10-fold cross-validation and grid search to enhance ML methods performance in solar farm power generation prediction. Cleaner Eng. Technol. 15, 100664 (2023). https:\/\/doi.org\/10.1016\/j.clet.2023.100664","journal-title":"Cleaner Eng. Technol."},{"key":"9_CR34","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2024.111468","volume":"155","author":"S Szab\u00f3","year":"2024","unstructured":"Szab\u00f3, S., Holb, I.J., Abriha-Moln\u00e1r, V.\u00c9., Szatm\u00e1ri, G., Singh, S.K., Abriha, D.: Classification assessment tool: a program to measure the uncertainty of classification models in terms of class-level metrics. Appl. Soft Comput. 155, 111468 (2024). https:\/\/doi.org\/10.1016\/j.asoc.2024.111468","journal-title":"Appl. Soft Comput."}],"container-title":["Lecture Notes in Networks and Systems","Emerging Challenges in Intelligent Management Information Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-78465-1_9","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,20]],"date-time":"2024-12-20T03:11:34Z","timestamp":1734664294000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-78465-1_9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,21]]},"ISBN":["9783031784644","9783031784651"],"references-count":34,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-78465-1_9","relation":{},"ISSN":["2367-3370","2367-3389"],"issn-type":[{"value":"2367-3370","type":"print"},{"value":"2367-3389","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,12,21]]},"assertion":[{"value":"21 December 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECAI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"European Conference on Artificial Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Santiago de Compostela","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Spain","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18 October 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 October 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ecai2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}