{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,14]],"date-time":"2026-01-14T01:47:33Z","timestamp":1768355253408,"version":"3.49.0"},"reference-count":54,"publisher":"Association for Computing Machinery (ACM)","issue":"2","license":[{"start":{"date-parts":[[2020,1,10]],"date-time":"2020-01-10T00:00:00Z","timestamp":1578614400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["71571093"],"award-info":[{"award-number":["71571093"]}],"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":[[2020,4,30]]},"abstract":"<jats:p>As an e-commerce feature, the personalized recommendation is invariably highly-valued by both consumers and merchants. The e-tourism has become one of the hottest industries with the adoption of recommendation systems. Several lines of evidence have confirmed the travel-product recommendation is quite different from traditional recommendations. Travel products are usually browsed and purchased relatively infrequently compared with other traditional products (e.g., books and food), which gives rise to the extreme sparsity of travel data. Meanwhile, the choice of a suitable travel product is affected by an army of factors such as departure, destination, and financial and time budgets. To address these challenging problems, in this article, we propose a Probabilistic Matrix Factorization with Multi-Auxiliary Information (PMF-MAI) model in the context of the travel-product recommendation. In particular, PMF-MAI is able to fuse the probabilistic matrix factorization on the user-item interaction matrix with the linear regression on a suite of features constructed by the multiple auxiliary information. In order to fit the sparse data, PMF-MAI is built by a whole-data based learning approach that utilizes unobserved data to increase the coupling between probabilistic matrix factorization and linear regression. Extensive experiments are conducted on a real-world dataset provided by a large tourism e-commerce company. PMF-MAI shows an overwhelming superiority over all competitive baselines on the recommendation performance. Also, the importance of features is examined to reveal the crucial auxiliary information having a great impact on the adoption of travel products.<\/jats:p>","DOI":"10.1145\/3372118","type":"journal-article","created":{"date-parts":[[2020,2,24]],"date-time":"2020-02-24T18:22:16Z","timestamp":1582568536000},"page":"1-24","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":24,"title":["Travel Recommendation via Fusing Multi-Auxiliary Information into Matrix Factorization"],"prefix":"10.1145","volume":"11","author":[{"given":"Lei","family":"Chen","sequence":"first","affiliation":[{"name":"Nanjing University of Science and Technology, Nanjing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0591-1861","authenticated-orcid":false,"given":"Zhiang","family":"Wu","sequence":"additional","affiliation":[{"name":"Nanjing University of Finance and Economics, Nanjing, China"}]},{"given":"Jie","family":"Cao","sequence":"additional","affiliation":[{"name":"Nanjing University of Finance and Economics, Nanjing, China"}]},{"given":"Guixiang","family":"Zhu","sequence":"additional","affiliation":[{"name":"Nanjing University of Science and Technology, Nanjing, China"}]},{"given":"Yong","family":"Ge","sequence":"additional","affiliation":[{"name":"University of Arizona, Tucson, Arizona, USA"}]}],"member":"320","published-online":{"date-parts":[[2020,1,10]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/1557019.1557029"},{"key":"e_1_2_1_2_1","volume-title":"Journal of Machine Learning Research 13","author":"Chen Tianqi","year":"2012"},{"key":"e_1_2_1_3_1","volume-title":"Lyu","author":"Cheng Chen","year":"2012"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/2783258.2783346"},{"key":"e_1_2_1_5_1","volume-title":"Stork","author":"Duda Richard O.","year":"2012"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/2700495"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.5555\/2832415.2832536"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/2020408.2020568"},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/2559169"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/2020408.2020426"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.im.2016.04.003"},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2018.2831682"},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/2911451.2911489"},{"key":"e_1_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/2911451.2911489"},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2016.7498229"},{"key":"e_1_2_1_16_1","volume-title":"A user similarity-based top-n recommendation approach for mobile in-application advertising. Expert Systems with Applications","author":"Hu Jinlong","year":"2018"},{"key":"e_1_2_1_17_1","volume-title":"Smart tourism technologies in travel planning: The role of exploration and exploitation. Information and Management 54, 6","author":"Huang C. Derrick","year":"2017"},{"key":"e_1_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/TBDATA.2016.2541160"},{"key":"e_1_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSC.2015.2497241"},{"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":"10.1016\/j.tourman.2009.11.007"},{"key":"e_1_2_1_22_1","volume-title":"Proceedings of the 25th International Joint Conference on Artificial Intelligence. AAAI Press, 1683--1689","author":"Li Huayu","year":"2016"},{"key":"e_1_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/3136625"},{"key":"e_1_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/2623330.2623638"},{"key":"e_1_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/3077136.3080778"},{"key":"e_1_2_1_26_1","volume-title":"Proceedings of the 24th International Joint Conference on Artificial Intelligence","volume":"15","author":"Lim Kwan Hui","year":"2015"},{"key":"e_1_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2014.2362525"},{"key":"e_1_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/3078845"},{"key":"e_1_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2014.03.063"},{"key":"e_1_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2012.233"},{"key":"e_1_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2011.118"},{"key":"e_1_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10115-017-1091-8"},{"key":"e_1_2_1_33_1","volume-title":"Proceedings of the 23rd International Joint Conference on Artificial Intelligence. 1593--1599","author":"Park Sunho","year":"2013"},{"key":"e_1_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1145\/2987378"},{"key":"e_1_2_1_35_1","volume-title":"Proceedings of the 24th AAAI Conference on Artificial Intelligence.","author":"Porteous Ian","year":"2010"},{"key":"e_1_2_1_36_1","volume-title":"Proceedings of the 24th Annual Conference on Learning Theory. 615--634","author":"Rudin Cynthia","year":"2011"},{"key":"e_1_2_1_37_1","volume-title":"Proceedings of the 20th International Conference on Neural Information Processing Systems. Curran Associates Inc., 1257--1264","author":"Salakhutdinov Ruslan","year":"2007"},{"key":"e_1_2_1_38_1","first-page":"291","article-title":"Collaborative filtering recommender systems","volume":"22","author":"Schafer J. Ben","year":"2004","journal-title":"ACM Transactions on Information Systems"},{"key":"e_1_2_1_39_1","volume-title":"Proceedings of the 31st AAAI Conference on Artificial Intelligence. 1502--1508","author":"Sedhain Suvash","year":"2017"},{"key":"e_1_2_1_40_1","volume-title":"Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM, 650--658","author":"Ajit"},{"key":"e_1_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1145\/2542665"},{"key":"e_1_2_1_42_1","volume-title":"Proceedings of the 23rd International Joint Conference on Artificial Intelligence, IJCAI 2013","author":"Tang Jiliang","year":"2013"},{"key":"e_1_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1145\/2766462.2767716"},{"key":"e_1_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.1145\/3038912.3052568"},{"key":"e_1_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2017.04.014"},{"key":"e_1_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2017.2690421"},{"key":"e_1_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.2014.2327053"},{"key":"e_1_2_1_48_1","doi-asserted-by":"publisher","DOI":"10.5555\/3304222.3304315"},{"key":"e_1_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2015.2508816"},{"key":"e_1_2_1_50_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2016.2569096"},{"key":"e_1_2_1_51_1","doi-asserted-by":"publisher","DOI":"10.1145\/1772690.1772795"},{"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":"10.1007\/s11042-017-4406-6"},{"key":"e_1_2_1_54_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219826"}],"container-title":["ACM Transactions on Intelligent Systems and Technology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3372118","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3372118","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T23:45:06Z","timestamp":1750203906000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3372118"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,1,10]]},"references-count":54,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2020,4,30]]}},"alternative-id":["10.1145\/3372118"],"URL":"https:\/\/doi.org\/10.1145\/3372118","relation":{},"ISSN":["2157-6904","2157-6912"],"issn-type":[{"value":"2157-6904","type":"print"},{"value":"2157-6912","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,1,10]]},"assertion":[{"value":"2019-01-01","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2019-11-01","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2020-01-10","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}