{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,20]],"date-time":"2025-06-20T04:09:32Z","timestamp":1750392572787,"version":"3.41.0"},"publisher-location":"Singapore","reference-count":21,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819682942","type":"print"},{"value":"9789819682959","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"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\/978-981-96-8295-9_28","type":"book-chapter","created":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T17:47:09Z","timestamp":1750355229000},"page":"381-393","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["CANTER: A Novel Causal Model for\u00a0Tourism Demand Forecasting"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8392-0539","authenticated-orcid":false,"given":"Xin","family":"Han","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0363-1460","authenticated-orcid":false,"given":"Haiyang","family":"Xia","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4776-4932","authenticated-orcid":false,"given":"Ye","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1583-641X","authenticated-orcid":false,"given":"Gang","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7199-3757","authenticated-orcid":false,"given":"Rob","family":"Law","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,6,20]]},"reference":[{"issue":"2","key":"28_CR1","doi-asserted-by":"publisher","first-page":"149","DOI":"10.1002\/jtr.743","volume":"12","author":"OA Akinboade","year":"2010","unstructured":"Akinboade, O.A., Braimoh, L.A.: International tourism and economic development in South Africa: a granger causality test. Int. J. Tour. Res. 12(2), 149\u2013163 (2010). https:\/\/doi.org\/10.1002\/jtr.743","journal-title":"Int. J. Tour. Res."},{"key":"28_CR2","doi-asserted-by":"publisher","first-page":"767","DOI":"10.1613\/jair.1.13428","volume":"73","author":"CK Assaad","year":"2022","unstructured":"Assaad, C.K., Devijver, E., Gaussier, E.: Survey and evaluation of causal discovery methods for time series. J. Artif. Intell. Res. 73, 767\u2013819 (2022). https:\/\/doi.org\/10.1613\/jair.1.13428","journal-title":"J. Artif. Intell. Res."},{"key":"28_CR3","doi-asserted-by":"publisher","unstructured":"Assaf, A.G., Scuderi, R.: Tourism demand analysis: directions for future research. Tour. Econ., 13548166221130466 (2022). https:\/\/doi.org\/10.1177\/13548166221130466","DOI":"10.1177\/13548166221130466"},{"issue":"8","key":"28_CR4","doi-asserted-by":"publisher","first-page":"1719","DOI":"10.1177\/00472875211040569","volume":"61","author":"JW Bi","year":"2022","unstructured":"Bi, J.W., Li, C., Xu, H., Li, H.: Forecasting daily tourism demand for tourist attractions with big data: an ensemble deep learning method. J. Travel Res. 61(8), 1719\u20131737 (2022). https:\/\/doi.org\/10.1177\/00472875211040569","journal-title":"J. Travel Res."},{"key":"28_CR5","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.annals.2017.07.019","volume":"67","author":"Z Cao","year":"2017","unstructured":"Cao, Z., Li, G., Song, H.: Modelling the interdependence of tourism demand: the global vector autoregressive approach. Ann. Tour. Res. 67, 1\u201313 (2017). https:\/\/doi.org\/10.1016\/j.annals.2017.07.019","journal-title":"Ann. Tour. Res."},{"issue":"3","key":"28_CR6","doi-asserted-by":"publisher","DOI":"10.1016\/j.ipm.2024.103699","volume":"61","author":"J Chen","year":"2024","unstructured":"Chen, J., Ying, Z., Zhang, C., Balezentis, T.: Forecasting tourism demand with search engine data: a hybrid CNN-BiLSTM model based on Boruta feature selection. Inf. Process. Manag. 61(3), 103699 (2024). https:\/\/doi.org\/10.1016\/j.ipm.2024.103699","journal-title":"Inf. Process. Manag."},{"key":"28_CR7","doi-asserted-by":"publisher","first-page":"108","DOI":"10.1016\/j.tourman.2017.10.014","volume":"66","author":"T Dergiades","year":"2018","unstructured":"Dergiades, T., Mavragani, E., Pan, B.: Google trends and tourists\u2019 arrivals: emerging biases and proposed corrections. Tour. Manage. 66, 108\u2013120 (2018). https:\/\/doi.org\/10.1016\/j.tourman.2017.10.014","journal-title":"Tour. Manage."},{"issue":"1","key":"28_CR8","doi-asserted-by":"publisher","first-page":"134","DOI":"10.1198\/073500102753410444","volume":"20","author":"FX Diebold","year":"2002","unstructured":"Diebold, F.X., Mariano, R.S.: Comparing predictive accuracy. J. Bus. Econ. Stat. 20(1), 134\u2013144 (2002). https:\/\/doi.org\/10.1198\/073500102753410444","journal-title":"J. Bus. Econ. Stat."},{"key":"28_CR9","unstructured":"Entner, D., Hoyer, P.O.: On causal discovery from time series data using FCI. Probab. Graph. Models, 121\u2013128 (2010)"},{"issue":"5","key":"28_CR10","doi-asserted-by":"publisher","first-page":"499","DOI":"10.1016\/S0261-5177(02)00009-2","volume":"23","author":"C Goh","year":"2002","unstructured":"Goh, C., Law, R.: Modeling and forecasting tourism demand for arrivals with stochastic nonstationary seasonality and intervention. Tour. Manage. 23(5), 499\u2013510 (2002). https:\/\/doi.org\/10.1016\/S0261-5177(02)00009-2","journal-title":"Tour. Manage."},{"key":"28_CR11","doi-asserted-by":"publisher","first-page":"410","DOI":"10.1016\/j.annals.2019.01.014","volume":"75","author":"R Law","year":"2019","unstructured":"Law, R., Li, G., Fong, D., Han, X.: Tourism demand forecasting: a deep learning approach. Ann. Tour. Res. 75, 410\u2013423 (2019). https:\/\/doi.org\/10.1016\/j.annals.2019.01.014","journal-title":"Ann. Tour. Res."},{"key":"28_CR12","doi-asserted-by":"publisher","DOI":"10.1016\/j.annals.2022.103384","volume":"94","author":"C Li","year":"2022","unstructured":"Li, C., Zheng, W., Ge, P.: Tourism demand forecasting with spatiotemporal features. Ann. Tour. Res. 94, 103384 (2022). https:\/\/doi.org\/10.1016\/j.annals.2022.103384","journal-title":"Ann. Tour. Res."},{"key":"28_CR13","doi-asserted-by":"publisher","first-page":"248","DOI":"10.1016\/j.tourman.2017.01.008","volume":"61","author":"LF Martins","year":"2017","unstructured":"Martins, L.F., Gan, Y., Ferreira-Lopes, A.: An empirical analysis of the influence of macroeconomic determinants on world tourism demand. Tour. Manage. 61, 248\u2013260 (2017). https:\/\/doi.org\/10.1016\/j.tourman.2017.01.008","journal-title":"Tour. Manage."},{"issue":"12","key":"28_CR14","doi-asserted-by":"publisher","first-page":"3041","DOI":"10.1007\/s10115-021-01621-0","volume":"63","author":"R Moraffah","year":"2021","unstructured":"Moraffah, R., et al.: Causal inference for time series analysis: problems, methods and evaluation. Knowl. Inf. Syst. 63(12), 3041\u20133085 (2021). https:\/\/doi.org\/10.1007\/s10115-021-01621-0","journal-title":"Knowl. Inf. Syst."},{"issue":"3","key":"28_CR15","doi-asserted-by":"publisher","first-page":"357","DOI":"10.1080\/10548408.2016.1170651","volume":"34","author":"S Park","year":"2017","unstructured":"Park, S., Lee, J., Song, W.: Short-term forecasting of Japanese tourist inflow to South Korea using google trends data. J. Travel Tourism Market. 34(3), 357\u2013368 (2017). https:\/\/doi.org\/10.1080\/10548408.2016.1170651","journal-title":"J. Travel Tourism Market."},{"key":"28_CR16","doi-asserted-by":"crossref","unstructured":"Runge, J., Nowack, P., Kretschmer, M., Flaxman, S., Sejdinovic, D.: Detecting and quantifying causal associations in large nonlinear time series datasets. Sci. Adv. 5(11), eaau4996 (2019)","DOI":"10.1126\/sciadv.aau4996"},{"key":"28_CR17","doi-asserted-by":"publisher","DOI":"10.1016\/j.tourman.2022.104655","volume":"94","author":"H Song","year":"2023","unstructured":"Song, H., Qiu, R., Park, J.: Progress in tourism demand research: theory and empirics. Tour. Manage. 94, 104655 (2023). https:\/\/doi.org\/10.1016\/j.tourman.2022.104655","journal-title":"Tour. Manage."},{"key":"28_CR18","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.tourman.2018.07.010","volume":"70","author":"S Sun","year":"2019","unstructured":"Sun, S., Wei, Y., Tsui, K.L., Wang, S.: Forecasting tourist arrivals with machine learning and internet search index. Tour. Manage. 70, 1\u201310 (2019). https:\/\/doi.org\/10.1016\/j.tourman.2018.07.010","journal-title":"Tour. Manage."},{"key":"28_CR19","unstructured":"Togninalli, M., Ghisu, E., Llinares-L\u00f3pez, F., Rieck, B., Borgwardt, K.: Wasserstein Weisfeiler-Lehman graph kernels. In: Advances in Neural Information Processing Systems, vol. 32 (2019)"},{"issue":"4","key":"28_CR20","doi-asserted-by":"publisher","DOI":"10.1016\/j.ipm.2023.103399","volume":"60","author":"G Xue","year":"2023","unstructured":"Xue, G., Liu, S., Ren, L., Gong, D.: Forecasting hourly attraction tourist volume with search engine and social media data for decision support. Inf. Process. Manag. 60(4), 103399 (2023). https:\/\/doi.org\/10.1016\/j.ipm.2023.103399","journal-title":"Inf. Process. Manag."},{"issue":"5","key":"28_CR21","doi-asserted-by":"publisher","first-page":"981","DOI":"10.1177\/0047287520919522","volume":"60","author":"Y Zhang","year":"2021","unstructured":"Zhang, Y., Li, G., Muskat, B., Law, R.: Tourism demand forecasting: a decomposed deep learning approach. J. Travel Res. 60(5), 981\u2013997 (2021). https:\/\/doi.org\/10.1177\/0047287520919522","journal-title":"J. Travel Res."}],"container-title":["Lecture Notes in Computer Science","Data Science: Foundations and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-96-8295-9_28","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T17:47:10Z","timestamp":1750355230000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-96-8295-9_28"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9789819682942","9789819682959"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-981-96-8295-9_28","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"20 June 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PAKDD","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Pacific-Asia Conference on Knowledge Discovery and Data Mining","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":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 June 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 June 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"pakdd2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/pakdd2025.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}