{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,12]],"date-time":"2025-08-12T21:36:30Z","timestamp":1755034590631,"version":"3.40.3"},"publisher-location":"Cham","reference-count":24,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030397692"},{"type":"electronic","value":"9783030397708"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"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":[[2020]]},"DOI":"10.1007\/978-3-030-39770-8_3","type":"book-chapter","created":{"date-parts":[[2020,1,26]],"date-time":"2020-01-26T20:03:21Z","timestamp":1580069001000},"page":"30-41","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Location Analysis Based Waiting Time Optimisation"],"prefix":"10.1007","author":[{"given":"Hami","family":"Aksu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wolfgang","family":"Dorner","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lihong","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,1,27]]},"reference":[{"issue":"2","key":"3_CR1","doi-asserted-by":"publisher","first-page":"144","DOI":"10.1108\/09564231211226097","volume":"23","author":"ACR van Riel","year":"2012","unstructured":"van Riel, A.C.R., Semeijn, J., Ribbink, D., Bomert Peters, Y.: Waiting for service at the checkout: negative emotional responses store image and overall satisfaction. J. Serv. Manag. 23(2), 144\u2013169 (2012)","journal-title":"J. Serv. Manag."},{"issue":"11","key":"3_CR2","first-page":"9","volume":"27","author":"J Peritz","year":"1993","unstructured":"Peritz, J.: Retailers who keep score know what their shoppers value. Mark. News 27(11), 9 (1993)","journal-title":"Mark. News"},{"key":"3_CR3","volume-title":"The Psychology of Waiting Lines","author":"DH Maister","year":"1984","unstructured":"Maister, D.H.: The Psychology of Waiting Lines. Harvard Business School, Boston (1984)"},{"issue":"5","key":"3_CR4","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1108\/08876049510100281","volume":"9","author":"G Tom","year":"1995","unstructured":"Tom, G., Lucey, S.: Waiting time delays and customer satisfaction in supermarkets. J. Serv. Market. 9(5), 20\u201329 (1995)","journal-title":"J. Serv. Market."},{"key":"3_CR5","unstructured":"Libelium.com: Libelium - Connecting Sensors to the Cloud (2019). http:\/\/www.libelium.com. Accessed 7 Sept 2019"},{"key":"3_CR6","unstructured":"Fox, D., et al.: Bayesian techniques for location estimation. In: Proceedings of the 2003 Workshop on Location-Aware Computing (2003)"},{"issue":"5","key":"3_CR7","doi-asserted-by":"publisher","first-page":"488","DOI":"10.1016\/j.robot.2010.01.009","volume":"58","author":"C Shi","year":"2010","unstructured":"Shi, C., Wang, Y., Yang, J.: Online topological map building and qualitative localization in large-scale environment. Rob. Auton. Syst. 58(5), 488\u2013496 (2010)","journal-title":"Rob. Auton. Syst."},{"key":"3_CR8","doi-asserted-by":"crossref","unstructured":"Furey, E., Curran, K., Mc Kevitt, P.: A Bayesian filter approach to modelling human movement patterns for first responders within indoor locations. In: Third International Conference on Intelligent Networking and Collaborative Systems (INCoS). IEEE (2011)","DOI":"10.1109\/INCoS.2011.14"},{"key":"3_CR9","unstructured":"Vintan, L., et al.: Person movement prediction using neural networks (2006)"},{"key":"3_CR10","unstructured":"Ashbrook, D., Starner, T.: Learning significant locations and predicting user movement with GPS. In: Proceedings of Sixth International Symposium on Wearable Computers (ISWC 2002). IEEE (2002)"},{"issue":"2","key":"3_CR11","doi-asserted-by":"publisher","first-page":"023026","DOI":"10.1117\/1.JEI.26.2.023026","volume":"26","author":"X Zhou","year":"2017","unstructured":"Zhou, X., et al.: Adaptive learning compressive tracking based on Markov location prediction. J. Electron. Imaging 26(2), 023026 (2017)","journal-title":"J. Electron. Imaging"},{"key":"3_CR12","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"884","DOI":"10.1007\/11840930_92","volume-title":"Artificial Neural Networks \u2013 ICANN 2006","author":"S-J Han","year":"2006","unstructured":"Han, S.-J., Cho, S.-B.: Predicting user\u2019s movement with a combination of self-organizing map and Markov model. In: Kollias, S., Stafylopatis, A., Duch, W., Oja, E. (eds.) ICANN 2006. LNCS, vol. 4132, pp. 884\u2013893. Springer, Heidelberg (2006). https:\/\/doi.org\/10.1007\/11840930_92"},{"key":"3_CR13","unstructured":"Jiang, J., et al.: Predicting human mobility based on location data modeled by Markov chains. In: Fourth International Conference on Ubiquitous Positioning, Indoor Navigation and Location Based Services (UPINLBS) (2016)"},{"key":"3_CR14","unstructured":"Mantyjarvi, J., Himberg, J., Seppanen, T.: Recognizing human motion with multiple acceleration sensors. In: IEEE International Conference on Systems, Man, and Cybernetics. IEEE (2001)"},{"key":"3_CR15","doi-asserted-by":"crossref","unstructured":"Assam, R., Seidl, T.: Check-in location prediction using wavelets and conditional random fields. In: 2014 IEEE International Conference on Data Mining (2014)","DOI":"10.1109\/ICDM.2014.101"},{"key":"3_CR16","doi-asserted-by":"crossref","unstructured":"Al-Molegi, A., Jabreel, M., Ghaleb, B.: STF-RNN: space time features-based recurrent neural network for predicting people next location. In: IEEE Symposium Series on Computational Intelligence (SSCI) (2016)","DOI":"10.1109\/SSCI.2016.7849919"},{"issue":"2","key":"3_CR17","doi-asserted-by":"publisher","first-page":"201","DOI":"10.1016\/S0305-0548(02)00180-6","volume":"31","author":"O Berman","year":"2004","unstructured":"Berman, O., Larson, R.C.: A queueing control model for retail services having back room operations and cross-trained workers. Comput. Oper. Res. 31(2), 201\u2013222 (2004)","journal-title":"Comput. Oper. Res."},{"issue":"4","key":"3_CR18","doi-asserted-by":"publisher","first-page":"222","DOI":"10.1504\/IJSSC.2011.043503","volume":"1","author":"E Furey","year":"2011","unstructured":"Furey, E., Curran, K., Mc Kevitt, P.: Learning indoor movement habits for predictive control. Int. J. Space Based Situated Comput. 1(4), 222\u2013232 (2011)","journal-title":"Int. J. Space Based Situated Comput."},{"issue":"5","key":"3_CR19","doi-asserted-by":"publisher","first-page":"1116","DOI":"10.1287\/opre.32.5.1116","volume":"32","author":"F Lu","year":"1984","unstructured":"Lu, F., Serfozo, R.F.: M\/M\/1 queueing decision processes with monotone hysteretic optimal policies. Oper. Res. 32(5), 1116\u20131132 (1984)","journal-title":"Oper. Res."},{"issue":"1","key":"3_CR20","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1177\/0092070393211001","volume":"21","author":"VA Zeithaml","year":"1993","unstructured":"Zeithaml, V.A., Berry, L.L., Parasuraman, A.: The nature and determinants of customer expectations of service. J. Acad. Mark. Sci. 21(1), 1\u201312 (1993)","journal-title":"J. Acad. Mark. Sci."},{"key":"3_CR21","unstructured":"Liu, N., Lovell, B.C.: Gesture classification using hidden Markov models and Viterbi path counting. In: VIIth Digital Image Computing: Techniques and Applications (2003)"},{"issue":"5","key":"3_CR22","doi-asserted-by":"publisher","first-page":"1319","DOI":"10.1016\/j.ssci.2010.07.017","volume":"50","author":"C Shi","year":"2012","unstructured":"Shi, C., et al.: Modeling and safety strategy of passenger evacuation in a metro station in China. Saf. Sci. 50(5), 1319\u20131332 (2012)","journal-title":"Saf. Sci."},{"key":"3_CR23","unstructured":"Holliday, S.: Automatic self-optimizing queue management system. Google Patents (2010)"},{"key":"3_CR24","unstructured":"Frey, R.G., Nelson, J.D.: Checkout lane alert system and method for stores having express checkout lanes. Google Patents (1996)"}],"container-title":["Lecture Notes in Computer Science","Image and Video Technology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-39770-8_3","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,26]],"date-time":"2024-01-26T01:27:16Z","timestamp":1706232436000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-39770-8_3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030397692","9783030397708"],"references-count":24,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-39770-8_3","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"27 January 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PSIVT","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Pacific-Rim Symposium on Image and Video Technology","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Sydney, NSW","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Australia","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18 November 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 November 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"9","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"psivt2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.psivt.org\/psivt2019\/index.html","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"55","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"31","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"56% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"1.5","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}