{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T14:49:04Z","timestamp":1774450144430,"version":"3.50.1"},"reference-count":52,"publisher":"Association for Computing Machinery (ACM)","issue":"3","license":[{"start":{"date-parts":[[2017,12,19]],"date-time":"2017-12-19T00:00:00Z","timestamp":1513641600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"National Science Foundation of Tianjin","award":["14JCQNJC00600"],"award-info":[{"award-number":["14JCQNJC00600"]}]},{"DOI":"10.13039\/501100001809","name":"National Science Foundation of China","doi-asserted-by":"crossref","award":["U1633103"],"award-info":[{"award-number":["U1633103"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Intell. Syst. Technol."],"published-print":{"date-parts":[[2018,5,31]]},"abstract":"<jats:p>\n            Human mobility analysis is one of the most important research problems in the field of urban computing. Existing research mainly focuses on the intra-city ground travel behavior modeling, while the inter-city air travel behavior modeling has been largely ignored. Actually, the inter-city travel analysis can be of equivalent importance and complementary to the intra-city travel analysis. Understanding massive passenger-air-travel behavior delivers intelligence for airlines\u2019 precision marketing and related socioeconomic activities, such as airport planning, emergency management, local transportation planning, and tourism-related businesses. Moreover, it provides opportunities to study the characteristics of cities and the mutual relationships between them. However, modeling and predicting air traveler behavior is challenging due to the complex factors of the market situation and individual characteristics of customers (e.g., airlines\u2019 market share, customer membership, and travelers\u2019 intrinsic interests on destinations). To this end, in this article, we present a systematic study on the personalized air travel prediction problem, namely\n            <jats:italic>where<\/jats:italic>\n            a customer will fly to and\n            <jats:italic>which<\/jats:italic>\n            airline carrier to fly with, by leveraging real-world anonymized Passenger Name Record (PNR) data. Specifically, we first propose a relational travel topic model, which combines the merits of latent factor model with a neighborhood-based method, to uncover the personal travel preferences of aviation customers and the latent travel topics of air routes and airline carriers simultaneously. Then we present a multi-factor travel prediction framework, which fuses complex factors of the market situation and individual characteristics of customers, to predict airline customers\u2019 personalized travel demands. Experimental results on two real-world PNR datasets demonstrate the effectiveness of our approach on both travel topic discovery and customer travel prediction.\n          <\/jats:p>","DOI":"10.1145\/3078845","type":"journal-article","created":{"date-parts":[[2017,12,20]],"date-time":"2017-12-20T14:54:00Z","timestamp":1513781640000},"page":"1-26","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":11,"title":["Personalized Air Travel Prediction"],"prefix":"10.1145","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5544-8417","authenticated-orcid":false,"given":"Jie","family":"Liu","sequence":"first","affiliation":[{"name":"Nankai University, Tianjin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bin","family":"Liu","sequence":"additional","affiliation":[{"name":"IBM Thomas J. Watson Research Center, Yorktown Heights, NY"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanchi","family":"Liu","sequence":"additional","affiliation":[{"name":"Rutgers University, Newark, NJ"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huipeng","family":"Chen","sequence":"additional","affiliation":[{"name":"Nankai University, Tianjin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lina","family":"Feng","sequence":"additional","affiliation":[{"name":"Nankai University, Tianjin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hui","family":"Xiong","sequence":"additional","affiliation":[{"name":"Rutgers University, Newark, NJ"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yalou","family":"Huang","sequence":"additional","affiliation":[{"name":"Nankai University, Tianjin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2017,12,19]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939726"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939694"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10707-014-0220-8"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/2888402"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/2365952.2365997"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.5555\/944919.944937"},{"key":"e_1_2_1_7_1","volume-title":"Proceedings of the 12th International Conference on Artificial Intelligence and Statistics (AISTATS\u201909)","author":"Chang Jonathan","year":"2009"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/BigDataService.2016.51"},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/956750.956767"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/2020408.2020568"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2011.18"},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/1835804.1835918"},{"key":"e_1_2_1_14_1","volume-title":"Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI\u201913)","author":"Groves William","year":"2013"},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2005.167"},{"key":"e_1_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/312624.312682"},{"key":"e_1_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/582415.582418"},{"key":"e_1_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1002\/for.2400"},{"key":"e_1_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/1401890.1401944"},{"key":"e_1_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/MC.2009.263"},{"key":"e_1_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/2030112.2030152"},{"key":"e_1_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/2020408.2020590"},{"key":"e_1_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/956750.956796"},{"key":"e_1_2_1_24_1","volume-title":"Algorithms for non-negative matrix factorization","author":"Lee Daniel D."},{"key":"e_1_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1287\/mnsc.2013.1860"},{"key":"e_1_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2012.233"},{"key":"e_1_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939773"},{"key":"e_1_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2014.138"},{"key":"e_1_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.5555\/1353862.1353922"},{"key":"e_1_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939789"},{"key":"e_1_2_1_31_1","volume-title":"Topic models conditioned on arbitrary features with dirichlet-multinomial regression. arXiv:1206.3278","author":"Mimno David","year":"2012"},{"key":"e_1_2_1_32_1","volume-title":"5th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD\u201901)","author":"Pritscher Lisa","year":"2001"},{"key":"e_1_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.5555\/1036843.1036902"},{"key":"e_1_2_1_34_1","first-page":"1","article-title":"Probabilistic matrix factorization","volume":"20","author":"Salakhutdinov Ruslan","year":"2011","journal-title":"NIPS"},{"key":"e_1_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1145\/2970819"},{"key":"e_1_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.3846\/16487788.2015.1054157"},{"key":"e_1_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.5555\/2627435.2670313"},{"key":"e_1_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1109\/DASC.2009.5347538"},{"key":"e_1_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.trb.2016.06.011"},{"key":"e_1_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.tra.2007.08.003"},{"key":"e_1_2_1_41_1","doi-asserted-by":"crossref","volume-title":"Forecasting a global air passenger demand network using weighted similarity-based algorithms","author":"Terekhov Ivan","DOI":"10.1007\/978-3-319-30569-1_26"},{"key":"e_1_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1145\/1390156.1390294"},{"key":"e_1_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1145\/2433396.2433444"},{"key":"e_1_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.1145\/2020408.2020480"},{"key":"e_1_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2016.2531661"},{"key":"e_1_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1145\/2623330.2623352"},{"key":"e_1_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.1145\/2663356"},{"key":"e_1_2_1_48_1","doi-asserted-by":"publisher","DOI":"10.1145\/2339530.2339561"},{"key":"e_1_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.1145\/1869790.1869807"},{"key":"e_1_2_1_50_1","doi-asserted-by":"publisher","DOI":"10.1145\/2030112.2030128"},{"key":"e_1_2_1_51_1","doi-asserted-by":"publisher","DOI":"10.1109\/TBDATA.2015.2465959"},{"key":"e_1_2_1_52_1","doi-asserted-by":"publisher","DOI":"10.1145\/2629592"},{"key":"e_1_2_1_53_1","doi-asserted-by":"publisher","DOI":"10.1145\/2684822.2685287"}],"container-title":["ACM Transactions on Intelligent Systems and Technology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3078845","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3078845","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T03:03:08Z","timestamp":1750215788000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3078845"}},"subtitle":["A Multi-factor Perspective"],"short-title":[],"issued":{"date-parts":[[2017,12,19]]},"references-count":52,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2018,5,31]]}},"alternative-id":["10.1145\/3078845"],"URL":"https:\/\/doi.org\/10.1145\/3078845","relation":{},"ISSN":["2157-6904","2157-6912"],"issn-type":[{"value":"2157-6904","type":"print"},{"value":"2157-6912","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,12,19]]},"assertion":[{"value":"2016-12-01","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2017-04-01","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2017-12-19","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}