{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T09:38:55Z","timestamp":1780393135212,"version":"3.54.1"},"publisher-location":"Cham","reference-count":17,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031434006","type":"print"},{"value":"9783031434013","type":"electronic"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"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":[[2023]]},"DOI":"10.1007\/978-3-031-43401-3_23","type":"book-chapter","created":{"date-parts":[[2023,9,4]],"date-time":"2023-09-04T19:03:00Z","timestamp":1693854180000},"page":"356-363","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Smart Meters and\u00a0Customer Consumption Behavior: An Exploratory Analysis Approach"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-8529-2338","authenticated-orcid":false,"given":"Ahmed Ala Eddine","family":"Benali","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1118-7109","authenticated-orcid":false,"given":"Massimo","family":"Cafaro","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6408-1335","authenticated-orcid":false,"given":"Italo","family":"Epicoco","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4201-1504","authenticated-orcid":false,"given":"Marco","family":"Pulimeno","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1369-9944","authenticated-orcid":false,"given":"Enrico Junior","family":"Schioppa","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3564-3834","authenticated-orcid":false,"given":"Jacopo","family":"Bonan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5069-4707","authenticated-orcid":false,"given":"Massimo","family":"Tavoni","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2023,9,5]]},"reference":[{"issue":"2","key":"23_CR1","doi-asserted-by":"publisher","first-page":"221","DOI":"10.1108\/K-09-2018-0506","volume":"50","author":"H Abbasimehr","year":"2021","unstructured":"Abbasimehr, H., Shabani, M.: A new methodology for customer behavior analysis using time series clustering: a case study on a bank\u2019s customers. Kybernetes 50(2), 221\u2013242 (2021)","journal-title":"Kybernetes"},{"issue":"22","key":"23_CR2","doi-asserted-by":"publisher","first-page":"4287","DOI":"10.3390\/en12224287","volume":"12","author":"M AbuBaker","year":"2019","unstructured":"AbuBaker, M.: Data mining applications in understanding electricity consumers\u2019 behavior: a case study of Tulkarm district, palestine. Energies 12(22), 4287 (2019)","journal-title":"Energies"},{"issue":"7","key":"23_CR3","doi-asserted-by":"publisher","first-page":"7543","DOI":"10.1007\/s12652-020-02455-4","volume":"12","author":"K Balachander","year":"2021","unstructured":"Balachander, K., Paulraj, D.: Retracted article: ann and fuzzy based household energy consumption prediction with high accuracy. J. Ambient. Intell. Humaniz. Comput. 12(7), 7543\u20137557 (2021)","journal-title":"J. Ambient. Intell. Humaniz. Comput."},{"key":"23_CR4","doi-asserted-by":"crossref","unstructured":"Deng, D.: Dbscan clustering algorithm based on density. In: 2020 7th International Forum on Electrical Engineering and Automation (IFEEA), pp. 949\u2013953. IEEE (2020)","DOI":"10.1109\/IFEEA51475.2020.00199"},{"key":"23_CR5","doi-asserted-by":"publisher","DOI":"10.1016\/j.enbuild.2021.111762","volume":"257","author":"N Iqbal","year":"2022","unstructured":"Iqbal, N., Kim, D.H., et al.: IoT task management mechanism based on predictive optimization for efficient energy consumption in smart residential buildings. Energy Build. 257, 111762 (2022)","journal-title":"Energy Build."},{"key":"23_CR6","doi-asserted-by":"crossref","unstructured":"Liu, J., et al.: Analysis of customers\u2019 electricity consumption behavior based on massive data. In: 2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD), pp. 1433\u20131438. IEEE (2016)","DOI":"10.1109\/FSKD.2016.7603388"},{"key":"23_CR7","doi-asserted-by":"publisher","DOI":"10.1016\/j.segan.2019.100212","volume":"18","author":"TA Nakabi","year":"2019","unstructured":"Nakabi, T.A., Toivanen, P.: An ANN-based model for learning individual customer behavior in response to electricity prices. Sustain. Energy Grids Networks 18, 100212 (2019)","journal-title":"Sustain. Energy Grids Networks"},{"key":"23_CR8","doi-asserted-by":"publisher","DOI":"10.1016\/j.compeleceng.2020.106902","volume":"89","author":"SV Oprea","year":"2021","unstructured":"Oprea, S.V., B\u00e2ra, A., Tudoric\u0103, B.G., C\u0103linoiu, M.I., Botezatu, M.A.: Insights into demand-side management with big data analytics in electricity consumers\u2019 behaviour. Comput. Electr. Eng. 89, 106902 (2021)","journal-title":"Comput. Electr. Eng."},{"key":"23_CR9","doi-asserted-by":"publisher","first-page":"9081","DOI":"10.1016\/j.egyr.2022.07.043","volume":"8","author":"KP Prakash","year":"2022","unstructured":"Prakash, K.P., et al.: A comprehensive analytical exploration and customer behaviour analysis of smart home energy consumption data with a practical case study. Energy Rep. 8, 9081\u20139093 (2022)","journal-title":"Energy Rep."},{"issue":"2","key":"23_CR10","doi-asserted-by":"publisher","first-page":"911","DOI":"10.1109\/TSG.2014.2364233","volume":"6","author":"FL Quilumba","year":"2014","unstructured":"Quilumba, F.L., Lee, W.J., Huang, H., Wang, D.Y., Szabados, R.L.: Using smart meter data to improve the accuracy of intraday load forecasting considering customer behavior similarities. IEEE Trans. Smart Grid 6(2), 911\u2013918 (2014)","journal-title":"IEEE Trans. Smart Grid"},{"key":"23_CR11","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/BFb0014140","volume-title":"Advances in Database Technology \u2014 EDBT \u201996","author":"R Srikant","year":"1996","unstructured":"Srikant, R., Agrawal, R.: Mining sequential patterns: generalizations and performance improvements. In: Apers, P., Bouzeghoub, M., Gardarin, G. (eds.) EDBT 1996. LNCS, vol. 1057, pp. 1\u201317. Springer, Heidelberg (1996). https:\/\/doi.org\/10.1007\/BFb0014140"},{"key":"23_CR12","doi-asserted-by":"publisher","first-page":"804","DOI":"10.1016\/j.energy.2016.04.065","volume":"107","author":"JL Viegas","year":"2016","unstructured":"Viegas, J.L., Vieira, S.M., Mel\u00edcio, R., Mendes, V., Sousa, J.M.: Classification of new electricity customers based on surveys and smart metering data. Energy 107, 804\u2013817 (2016)","journal-title":"Energy"},{"key":"23_CR13","doi-asserted-by":"crossref","unstructured":"Wang, H., Mahato, N.K., He, H., An, X., Chen, Z., Gong, G.: Research on electricity consumption behavior of users based on deep learning. In: 2020 IEEE\/IAS Industrial and Commercial Power System Asia (I &CPS Asia), pp. 1491\u20131497. IEEE (2020)","DOI":"10.1109\/ICPSAsia48933.2020.9208392"},{"issue":"3","key":"23_CR14","doi-asserted-by":"publisher","first-page":"2593","DOI":"10.1109\/TSG.2018.2805723","volume":"10","author":"Y Wang","year":"2018","unstructured":"Wang, Y., Chen, Q., Gan, D., Yang, J., Kirschen, D.S., Kang, C.: Deep learning-based socio-demographic information identification from smart meter data. IEEE Trans. Smart Grid 10(3), 2593\u20132602 (2018)","journal-title":"IEEE Trans. Smart Grid"},{"issue":"1","key":"23_CR15","doi-asserted-by":"publisher","first-page":"149","DOI":"10.1007\/s12273-020-0710-6","volume":"14","author":"J Xu","year":"2020","unstructured":"Xu, J., Kang, X., Chen, Z., Yan, D., Guo, S., Jin, Y., Hao, T., Jia, R.: Clustering-based probability distribution model for monthly residential building electricity consumption analysis. Building Simulation 14(1), 149\u2013164 (2020). https:\/\/doi.org\/10.1007\/s12273-020-0710-6","journal-title":"Building Simulation"},{"issue":"3","key":"23_CR16","doi-asserted-by":"publisher","first-page":"3374","DOI":"10.1109\/TSG.2018.2825335","volume":"10","author":"J Yang","year":"2018","unstructured":"Yang, J., Zhao, J., Wen, F., Dong, Z.: A model of customizing electricity retail prices based on load profile clustering analysis. IEEE Trans. Smart Grid 10(3), 3374\u20133386 (2018)","journal-title":"IEEE Trans. Smart Grid"},{"key":"23_CR17","doi-asserted-by":"publisher","first-page":"402","DOI":"10.1016\/j.apenergy.2017.10.014","volume":"208","author":"B Yildiz","year":"2017","unstructured":"Yildiz, B., Bilbao, J.I., Dore, J., Sproul, A.B.: Recent advances in the analysis of residential electricity consumption and applications of smart meter data. Appl. Energy 208, 402\u2013427 (2017)","journal-title":"Appl. Energy"}],"container-title":["Lecture Notes in Computer Science","Extended Reality"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-43401-3_23","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,29]],"date-time":"2024-01-29T19:06:17Z","timestamp":1706555177000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-43401-3_23"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031434006","9783031434013"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-43401-3_23","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"5 September 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"XR Salento","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Extended Reality","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Lecce","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6 September 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"9 September 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"avr2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.xrsalento.it\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"OCS - Unisalento Conferences","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"97","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":"60","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":"11","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":"62% - 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":"2","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":"3","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)"}}]}}