{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,13]],"date-time":"2025-11-13T12:34:30Z","timestamp":1763037270052,"version":"3.37.3"},"reference-count":37,"publisher":"Springer Science and Business Media LLC","issue":"12","license":[{"start":{"date-parts":[[2019,1,2]],"date-time":"2019-01-02T00:00:00Z","timestamp":1546387200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["617710686, 61671079, 61471063, 61372120, and 61421061"],"award-info":[{"award-number":["617710686, 61671079, 61471063, 61372120, and 61421061"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005089","name":"Beijing Municipal Natural Science Foundation","doi-asserted-by":"publisher","award":["4182041,4152039"],"award-info":[{"award-number":["4182041,4152039"]}],"id":[{"id":"10.13039\/501100005089","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Basic Research Program of China","doi-asserted-by":"crossref","award":["2013CB329102"],"award-info":[{"award-number":["2013CB329102"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"published-print":{"date-parts":[[2019,6]]},"DOI":"10.1007\/s11042-018-7019-9","type":"journal-article","created":{"date-parts":[[2019,1,2]],"date-time":"2019-01-02T17:31:49Z","timestamp":1546450309000},"page":"16923-16943","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Collaborative tensor\u2013topic factorization model for personalized activity recommendation"],"prefix":"10.1007","volume":"78","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0520-7807","authenticated-orcid":false,"given":"Tongcun","family":"Liu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianxin","family":"Liao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yulong","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jingyu","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qi","family":"Qi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,1,2]]},"reference":[{"key":"7019_CR1","doi-asserted-by":"publisher","unstructured":"Al-Ayyoub M, Alawneh E, Jararweh Y et al (2018) Collaboration networks of Arab biomedical researchers. Multimed Tools Appl. https:\/\/doi.org\/10.1007\/s11042-018-6557-5","DOI":"10.1007\/s11042-018-6557-5"},{"key":"7019_CR2","doi-asserted-by":"publisher","first-page":"4939","DOI":"10.1007\/s11042-016-4218-0","volume":"77","author":"M Al-Ayyoub","year":"2018","unstructured":"Al-Ayyoub M, AlZu\u2019bi S, Jararweh Y et al (2018) Accelerating 3D medical volume segmentation using GPUs. Multimed Tools Appl 77:4939\u20134958. https:\/\/doi.org\/10.1007\/s11042-016-4218-0","journal-title":"Multimed Tools Appl"},{"key":"7019_CR3","doi-asserted-by":"crossref","unstructured":"Bhargava P, Phan T, Zhou J, Lee J (2015) Who, What, When, and Where: Multi-Dimensional Collaborative Recommendations Using Tensor Factorization on Sparse User-Generated Data. In: Proceedings of the 24th International Conference on World Wide Web. International World Wide Web Conferences Steering Committee, Florence, Italy. 130\u2013140","DOI":"10.1145\/2736277.2741077"},{"key":"7019_CR4","doi-asserted-by":"publisher","first-page":"23435","DOI":"10.1007\/s11042-016-4114-7","volume":"76","author":"T-H Bui","year":"2017","unstructured":"Bui T-H, Park S-B (2017) Point of interest mining with proper semantic annotation. Multimed Tools Appl 76:23435\u201323457. https:\/\/doi.org\/10.1007\/s11042-016-4114-7","journal-title":"Multimed Tools Appl"},{"key":"7019_CR5","unstructured":"Feng S, Li X, Zeng Y, et al (2015) Personalized Ranking Metric Embedding for Next New POI Recommendation. In: Proceedings of the 24th International Joint Conference on Artificial Intelligence. AAAI Press, New York. 2069\u20132075"},{"key":"7019_CR6","doi-asserted-by":"crossref","unstructured":"Ference G, Ye M, Lee W-C (2013) Location recommendation for out-of-town users in location-based social networks. In: Proceedings of the 22nd ACM international conference on Conference on information & knowledge management - CIKM \u201813. ACM Press, San Francisco, California, USA. 721\u2013726","DOI":"10.1145\/2505515.2505637"},{"key":"7019_CR7","doi-asserted-by":"crossref","unstructured":"Gao H, Tang J, Hu X, Liu H (2013) Exploring temporal effects for location recommendation on location-based social networks. In: Proceedings of the 7th ACM conference on Recommender system. ACM Press, Hong Kong, China. 93\u2013100","DOI":"10.1145\/2507157.2507182"},{"key":"7019_CR8","doi-asserted-by":"crossref","unstructured":"Gao H, Tang J, Hu X, Liu H (2015) Content-Aware Point of Interest Recommendation on Location-Based Social Networks. In: Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence. Austin. 1721\u20131727","DOI":"10.1609\/aaai.v29i1.9462"},{"key":"7019_CR9","doi-asserted-by":"crossref","unstructured":"He J, Li X, Liao L (2017) Category-aware Next Point-of-Interest Recommendation via Listwise Bayesian Personalized Ranking. In: International Joint Conferences on Artificial Intelligence Organization. Melbourne. 1837\u20131843","DOI":"10.24963\/ijcai.2017\/255"},{"key":"7019_CR10","doi-asserted-by":"publisher","unstructured":"Jararweh Y, Al-Ayyoub M, Fakirah M et al (2017) Improving the performance of the needleman-wunsch algorithm using parallelization and vectorization techniques. Multimed Tools Appl. https:\/\/doi.org\/10.1007\/s11042-017-5092-0","DOI":"10.1007\/s11042-017-5092-0"},{"key":"7019_CR11","doi-asserted-by":"crossref","unstructured":"Karatzoglou A, Amatriain X, Baltrunas L, Oliver N (2010) Multiverse recommendation: n-dimensional tensor factorization for context-aware collaborative filtering. In: Proceedings of the fourth ACM conference on Recommender systems. ACM, Barcelona. 79\u201386","DOI":"10.1145\/1864708.1864727"},{"key":"7019_CR12","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3057283","volume":"35","author":"X Li","year":"2017","unstructured":"Li X, Jiang M, Hong H, Liao L (2017) A time-aware personalized point-of-interest recommendation via high-order tensor factorization. ACM Trans Inf Syst 35:1\u201323. https:\/\/doi.org\/10.1145\/3057283","journal-title":"ACM Trans Inf Syst"},{"key":"7019_CR13","doi-asserted-by":"crossref","first-page":"831","DOI":"10.1145\/2623330.2623638","volume-title":"Proceedings of the 20th ACM SIGKDD international conference on knowledge discovery and data mining","author":"D Lian","year":"2014","unstructured":"Lian D, Zhao C, Xie X et al (2014) GeoMF: joint geographical modeling and matrix factorization for point-of-interest recommendation. In: Proceedings of the 20th ACM SIGKDD international conference on knowledge discovery and data mining. ACM Press, New York, pp 831\u2013840"},{"key":"7019_CR14","doi-asserted-by":"publisher","first-page":"21980","DOI":"10.1109\/ACCESS.2018.2827422","volume":"6","author":"J Liao","year":"2018","unstructured":"Liao J, Liu T, Liu M et al (2018) Multi-context integrated deep neural network model for next location prediction. IEEE Access 6:21980\u201321990. https:\/\/doi.org\/10.1109\/ACCESS.2018.2827422","journal-title":"IEEE Access"},{"key":"7019_CR15","doi-asserted-by":"publisher","first-page":"396","DOI":"10.1137\/1.9781611972832.44","volume-title":"Proceedings of the 2013 SIAM international conference on data mining","author":"B Liu","year":"2013","unstructured":"Liu B, Xiong H (2013) Point-of-interest recommendation in location based social networks with topic and location awareness. In: Proceedings of the 2013 SIAM international conference on data mining. SIAM, Philadelphia, pp 396\u2013404"},{"key":"7019_CR16","doi-asserted-by":"publisher","first-page":"1167","DOI":"10.1109\/TKDE.2014.2362525","volume":"27","author":"B Liu","year":"2015","unstructured":"Liu B, Xiong H, Papadimitriou S et al (2015) A general geographical probabilistic factor model for point of interest recommendation. IEEE Trans Knowl Data Eng 27:1167\u20131179. https:\/\/doi.org\/10.1109\/TKDE.2014.2362525","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"7019_CR17","doi-asserted-by":"publisher","first-page":"108","DOI":"10.1016\/j.neucom.2015.08.096","volume":"181","author":"Y Liu","year":"2016","unstructured":"Liu Y, Nie L, Liu L, Rosenblum DS (2016) From action to activity: sensor-based activity recognition. Neurocomputing 181:108\u2013115. https:\/\/doi.org\/10.1016\/j.neucom.2015.08.096","journal-title":"Neurocomputing"},{"key":"7019_CR18","unstructured":"Liu Y, Nie L, Han L, et al (2016) Action2Activity: Recognizing Complex Activities from Sensor Data. In: Proceedings of the 24th International Conference on Artificial Intelligence. Buenos Aires, Argentina. 1617\u20131623"},{"key":"7019_CR19","doi-asserted-by":"crossref","unstructured":"Liu L, Cheng L, Liu Y, et al (2016) Recognizing Complex Activities by a Probabilistic Interval-Based Model. In: Thirtieth AAAI Conference on Artificial Intelligence. AAAI Press. 1266\u20131272","DOI":"10.1609\/aaai.v30i1.10155"},{"key":"7019_CR20","unstructured":"Mnih A, Salakhutdinov RR (2007) Probabilistic matrix factorization. In: Proceedings of the 20th International Conference on Neural Information Processing Systems. Vancouver. 1257\u20131264"},{"key":"7019_CR21","doi-asserted-by":"publisher","first-page":"38","DOI":"10.1016\/j.neucom.2017.02.005","volume":"241","author":"X Ren","year":"2017","unstructured":"Ren X, Song M, E H, Song J (2017) Context-aware probabilistic matrix factorization modeling for point-of-interest recommendation. Neurocomputing 241:38\u201355. https:\/\/doi.org\/10.1016\/j.neucom.2017.02.005","journal-title":"Neurocomputing"},{"key":"7019_CR22","doi-asserted-by":"crossref","unstructured":"Rendle S, Schmidt-Thieme L (2010) Pairwise interaction tensor factorization for personalized tag recommendation. In: Proceedings of the third ACM international conference on Web search and data mining. ACM Press, New York, p 81","DOI":"10.1145\/1718487.1718498"},{"key":"7019_CR23","doi-asserted-by":"crossref","unstructured":"Rendle S, Freudenthaler C, Schmidt-Thieme L (2010) Factorizing personalized markov chains for next-basket recommendation. In: Proceedings of the 19th International Conference on World Wide Web. ACM, Raleigh, North Carolina, USA. 811\u2013820","DOI":"10.1145\/1772690.1772773"},{"key":"7019_CR24","unstructured":"Wang WY, Cohen WW (2016) Learning First-Order Logic Embeddings via Matrix Factorization. In: Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence. New York. 2132\u20132138"},{"key":"7019_CR25","doi-asserted-by":"crossref","unstructured":"Wang Y, Zheng Y, Xue Y (2014) Travel time estimation of a path using sparse trajectories. In: Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining. ACM Press, New York. 25\u201334","DOI":"10.1145\/2623330.2623656"},{"key":"7019_CR26","doi-asserted-by":"crossref","unstructured":"Wang H, Wang N, Yeung D-Y (2015) Collaborative Deep Learning for Recommender Systems. In: Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM Press, Sydney. 1235\u20131244","DOI":"10.1145\/2783258.2783273"},{"key":"7019_CR27","doi-asserted-by":"crossref","unstructured":"Wang H, Fu Y, Wang Q, et al (2017) A Location-Sentiment-Aware Recommender System for Both Home-Town and Out-of-Town Users. In: Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM Press, Halifax. 1135\u20131143","DOI":"10.1145\/3097983.3098122"},{"key":"7019_CR28","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1137\/1.9781611972801.19","volume-title":"Proceedings of the 2010 SIAM international conference on data mining","author":"L Xiong","year":"2010","unstructured":"Xiong L, Chen X, Huang T-K et al (2010) Temporal collaborative filtering with Bayesian probabilistic tensor factorization. In: Parthasarathy S, Liu B, Goethals B et al (eds) Proceedings of the 2010 SIAM international conference on data mining. Society for Industrial and Applied Mathematics, Philadelphia, pp 211\u2013222"},{"key":"7019_CR29","doi-asserted-by":"crossref","unstructured":"Yan X, Guo J, Lan Y, Cheng X (2013) A biterm topic model for short texts. In: Proceedings of the 22nd international conference on World Wide Web. ACM, Rio de Janeiro. 1445\u20131456","DOI":"10.1145\/2488388.2488514"},{"key":"7019_CR30","doi-asserted-by":"publisher","first-page":"129","DOI":"10.1109\/TSMC.2014.2327053","volume":"45","author":"D Yang","year":"2015","unstructured":"Yang D, Zhang D, Zheng VW, Zhiyong Y (2015) Modeling user activity preference by leveraging user spatial temporal characteristics in LBSNs. IEEE Trans Syst Man Cybern Syst 45:129\u2013142. https:\/\/doi.org\/10.1109\/TSMC.2014.2327053","journal-title":"IEEE Trans Syst Man Cybern Syst"},{"key":"7019_CR31","doi-asserted-by":"crossref","unstructured":"Ye J, Zhu Z, Cheng H (2013) What\u2019s Your Next Move: User Activity Prediction in Location-based Social Networks. In: Proceedings of the 2013 SIAM International Conference on Data Mining. pp 171\u2013179","DOI":"10.1137\/1.9781611972832.19"},{"key":"7019_CR32","doi-asserted-by":"publisher","first-page":"2537","DOI":"10.1109\/TKDE.2017.2741484","volume":"29","author":"H Yin","year":"2017","unstructured":"Yin H, Wang W, Wang H et al (2017) Spatial-aware hierarchical collaborative deep learning for POI recommendation. IEEE Trans Knowl Data Eng 29:2537\u20132551. https:\/\/doi.org\/10.1109\/TKDE.2017.2741484","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"7019_CR33","doi-asserted-by":"publisher","first-page":"195","DOI":"10.1016\/j.neucom.2017.02.067","volume":"242","author":"Y Ying","year":"2017","unstructured":"Ying Y, Chen L, Chen G (2017) A temporal-aware POI recommendation system using context-aware tensor decomposition and weighted HITS. Neurocomputing 242:195\u2013205. https:\/\/doi.org\/10.1016\/j.neucom.2017.02.067","journal-title":"Neurocomputing"},{"key":"7019_CR34","doi-asserted-by":"crossref","unstructured":"Zhang F, Yuan NJ, Lian D, et al (2016) Collaborative Knowledge Base Embedding for Recommender Systems. In: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM Press, San Francisco. 353\u2013362","DOI":"10.1145\/2939672.2939673"},{"key":"7019_CR35","doi-asserted-by":"crossref","unstructured":"Zheng VW, Zheng Y, Xie X, Yang Q (2010) Collaborative location and activity recommendations with GPS history data. In: Proceedings of the 19th international conference on World wide web. ACM Press, Raleigh. 1029","DOI":"10.1145\/1772690.1772795"},{"key":"7019_CR36","doi-asserted-by":"publisher","first-page":"276","DOI":"10.1016\/j.ins.2016.08.042","volume":"372","author":"X Zheng","year":"2016","unstructured":"Zheng X, Ding W, Lin Z, Chen C (2016) Topic tensor factorization for recommender system. Inf Sci 372:276\u2013293. https:\/\/doi.org\/10.1016\/j.ins.2016.08.042","journal-title":"Inf Sci"},{"key":"7019_CR37","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2532515","volume":"5","author":"H Zhu","year":"2014","unstructured":"Zhu H, Chen E, Xiong H et al (2014) Mining Mobile user preferences for personalized context-aware recommendation. ACM Trans Intell Syst Technol 5:1\u201327. https:\/\/doi.org\/10.1145\/2532515","journal-title":"ACM Trans Intell Syst Technol"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-018-7019-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11042-018-7019-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-018-7019-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,9,9]],"date-time":"2022-09-09T15:56:49Z","timestamp":1662739009000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11042-018-7019-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,1,2]]},"references-count":37,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2019,6]]}},"alternative-id":["7019"],"URL":"https:\/\/doi.org\/10.1007\/s11042-018-7019-9","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"type":"print","value":"1380-7501"},{"type":"electronic","value":"1573-7721"}],"subject":[],"published":{"date-parts":[[2019,1,2]]},"assertion":[{"value":"2 June 2018","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 November 2018","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 December 2018","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 January 2019","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}